what is lung cancer essay

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Introduction & Top Questions

Causes and symptoms

Types of lung cancer, small-cell lung cancer.

Non-small-cell lung cancer

Does smoking cause lung cancer?

What are the common symptoms of lung cancer.

lung cancer

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Table Of Contents

Between 80 to 90 percent of lung cancer cases are caused by smoking in countries with a prolonged history of tobacco smoking. Heavy smokers have a greater likelihood of developing the disease than light smokers. Also, people who started smoking at a young age are at greater risk. Passive inhalation of cigarette smoke has been linked to lung cancer in nonsmokers.

Lung cancer symptoms do not usually appear until the disease has reached an advanced stage. Common symptoms include shortness of breath, a persistent cough or wheeze, chest pain, bloody sputum, unexplained weight loss, and susceptibility to lower respiratory infections. Visible lumps, jaundice, or bone pain may occur in cases where cancer has spread beyond the lungs.

Are there different types of lung cancer?

There are two basic forms of lung cancer: small-cell lung cancer (SCLC), also called oat-cell carcinoma, and non-small-cell lung cancer (non-SCLC). SCLC accounts for 10 to 20 percent of all cases and is rarely found in people who have never smoked. The non-SCLCs are responsible for the remainder.

Can lung cancer be prevented?

The probability of developing lung cancer can be reduced by avoiding smoking. Smokers who quit also reduce their risk significantly. Testing for radon gas and avoiding exposure to coal products, asbestos, and other airborne carcinogens also lowers risk.

Recent News

lung cancer , disease characterized by uncontrolled growth of cells in the lungs . Lung cancer was first described by doctors in the mid-19th century. In the early 20th century it was considered relatively rare, but by the end of the century it was the leading cause of cancer-related death among men in more than 25 developed countries. In the 21st century lung cancer emerged as the leading cause of cancer deaths worldwide. By 2012 it had surpassed breast cancer as the leading cause of cancer death among women in developed countries. The rapid increase in the worldwide prevalence of lung cancer was attributed mostly to the increased use of cigarettes following World War I , though increases in environmental air pollution were suspected to have been a contributing factor as well.

Lung cancer occurs primarily in persons between the ages of 45 and 75 years. In countries with a prolonged history of tobacco smoking , between 80 and 90 percent of all cases are caused by smoking. Heavy smokers have a greater likelihood of developing the disease than do light smokers. The risk is also greater for those who started smoking at a young age.

Passive inhalation of cigarette smoke (sometimes called secondhand smoke ) is linked to lung cancer in nonsmokers. According to the American Cancer Society, about 3,400 deaths from lung cancer occur each year in nonsmokers in the United States . Other risk factors include exposure to radon gas and asbestos; smokers exposed to these substances run a greater risk of developing lung cancer than do nonsmokers. Uranium and pitchblende miners, chromium and nickel refiners, welders, and workers exposed to halogenated ethers also have an increased incidence , as do some workers in hydrocarbon-related processing, such as coal processors, tar refiners, and roofers. Lung cancer is rarely caused directly by inherited mutations.

Tumours can begin anywhere in the lung, but symptoms do not usually appear until the disease has reached an advanced stage or spread to another part of the body. The most common symptoms include shortness of breath, a persistent cough or wheeze, chest pain, bloody sputum, unexplained weight loss, and susceptibility to lower respiratory infections. In cases where the cancer has spread beyond the lungs, visible lumps, jaundice, or bone pain may occur.

A Yorkshire terrier dressed up as a veterinarian or doctor on a white background. (dogs)

Lung cancers are often discovered during examinations for other conditions. Cancer cells may be detected in sputum; a needle biopsy may be used to remove a sample of lung tissue for analysis; or the large airways of the lungs (bronchi) can viewed directly with a bronchoscope for signs of cancer. Noninvasive methods include X-rays, computerized axial tomography (CAT) scans, positron emission tomography (PET) scans, and magnetic resonance imaging (MRI). There are also several blood tests that may be used to detect proteins and other substances known to be associated with lung cancer. For example, abnormal fluctuations in the serum levels of parathormone or the presence in the blood of a protein called cytokeratin 19 fragment or of substances known as carcinogenic antigens may be indicative of malignant lung disease. Researchers are also developing blood tests to detect DNA shed by cells carrying genetic mutations associated with lung cancer; such tests raise the possibility of detecting lung tumours before they become malignant.

Most cases are usually diagnosed well after the disease has spread (metastasized) from its original site. For this reason, lung cancer has a poorer prognosis than many other cancers. Even when it is detected early, the five-year survival rate is about 50 percent.

Once diagnosed, the tumour’s type and degree of invasiveness are determined. There are two basic forms: small-cell lung cancer, which accounts for 10–20 percent of all cases, and non-small-cell lung cancer, which is responsible for the remainder.

Small-cell lung cancer (SCLC), also called oat-cell carcinoma , is rarely found in people who have never smoked. It is characterized by cells that are small and round, oval, or shaped like oat grains. SCLC is the most aggressive type of lung cancer; because it tends to spread quickly before symptoms become apparent, the survival rate is very low.

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Diseases & Conditions
Lung cancer

Lung cancer begins in the cells of the lungs.

Lung cancer is a kind of cancer that starts as a growth of cells in the lungs. The lungs are two spongy organs in the chest that control breathing.

Lung cancer is the leading cause of cancer deaths worldwide.

People who smoke have the greatest risk of lung cancer. The risk of lung cancer increases with the length of time and number of cigarettes smoked. Quitting smoking, even after smoking for many years, significantly lowers the chances of developing lung cancer. Lung cancer also can happen in people who have never smoked.

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Lung cancer typically doesn't cause symptoms early on. Symptoms of lung cancer usually happen when the disease is advanced.

Signs and symptoms of lung cancer that happen in and around the lungs may include:

A new cough that doesn't go away.
Chest pain.
Coughing up blood, even a small amount.
Hoarseness.
Shortness of breath.

Signs and symptoms that happen when lung cancer spreads to other parts of the body may include:

Losing weight without trying.
Loss of appetite.
Swelling in the face or neck.

When to see a doctor

Make an appointment with your doctor or other healthcare professional if you have any symptoms that worry you.

If you smoke and haven't been able to quit, make an appointment. Your healthcare professional can recommend strategies for quitting smoking. These may include counseling, medicines and nicotine replacement products.

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Lung cancer happens when cells in the lungs develop changes in their DNA. A cell's DNA holds the instructions that tell a cell what to do. In healthy cells, the DNA gives instructions to grow and multiply at a set rate. The instructions tell the cells to die at a set time. In cancer cells, the DNA changes give different instructions. The changes tell the cancer cells to make many more cells quickly. Cancer cells can keep living when healthy cells would die. This causes too many cells.

The cancer cells might form a mass called a tumor. The tumor can grow to invade and destroy healthy body tissue. In time, cancer cells can break away and spread to other parts of the body. When cancer spreads, it's called metastatic cancer.

Smoking causes most lung cancers. It can cause lung cancer in both people who smoke and in people exposed to secondhand smoke. But lung cancer also happens in people who never smoked or been exposed to secondhand smoke. In these people, there may be no clear cause of lung cancer.

How smoking causes lung cancer

Researchers believe smoking causes lung cancer by damaging the cells that line the lungs. Cigarette smoke is full of cancer-causing substances, called carcinogens. When you inhale cigarette smoke, the carcinogens cause changes in the lung tissue almost immediately.

At first your body may be able to repair this damage. But with each repeated exposure, healthy cells that line your lungs become more damaged. Over time, the damage causes cells to change and eventually cancer may develop.

Types of lung cancer

Lung cancer is divided into two major types based on the appearance of the cells under a microscope. Your healthcare professional makes treatment decisions based on which major type of lung cancer you have.

The two general types of lung cancer include:

Small cell lung cancer. Small cell lung cancer usually only happens in people who have smoked heavily for years. Small cell lung cancer is less common than non-small cell lung cancer.
Non-small cell lung cancer. Non-small cell lung cancer is a category that includes several types of lung cancers. Non-small cell lung cancers include squamous cell carcinoma, adenocarcinoma and large cell carcinoma.

Risk factors

A number of factors may increase the risk of lung cancer. Some risk factors can be controlled, for instance, by quitting smoking. Other factors can't be controlled, such as your family history.

Risk factors for lung cancer include:

Your risk of lung cancer increases with the number of cigarettes you smoke each day. Your risk also increases with the number of years you have smoked. Quitting at any age can significantly lower your risk of developing lung cancer.

Exposure to secondhand smoke

Even if you don't smoke, your risk of lung cancer increases if you're around people who are smoking. Breathing the smoke in the air from other people who are smoking is called secondhand smoke.

Previous radiation therapy

If you've had radiation therapy to the chest for another type of cancer, you may have an increased risk of developing lung cancer.

Exposure to radon gas

Radon is produced by the natural breakdown of uranium in soil, rock and water. Radon eventually becomes part of the air you breathe. Unsafe levels of radon can build up in any building, including homes.

Exposure to cancer-causing substances

Workplace exposure to cancer-causing substances, called carcinogens, can increase your risk of developing lung cancer. The risk may be higher if you smoke. Carcinogens linked to lung cancer risk include asbestos, arsenic, chromium and nickel.

Family history of lung cancer

People with a parent, sibling or child with lung cancer have an increased risk of the disease.

Complications

Lung cancer can cause complications, such as:

Shortness of breath

People with lung cancer can experience shortness of breath if cancer grows to block the major airways. Lung cancer also can cause fluid to collect around the lungs and heart. The fluid makes it harder for the affected lung to expand fully when you inhale.

Coughing up blood

Lung cancer can cause bleeding in the airway. This can cause you to cough up blood. Sometimes bleeding can become severe. Treatments are available to control bleeding.

Advanced lung cancer that spreads can cause pain. It may spread to the lining of a lung or to another area of the body, such as a bone. Tell your healthcare professional if you experience pain. Many treatments are available to control pain.

Fluid in the chest

Lung cancer can cause fluid to accumulate in the chest, called pleural effusion. The fluid collects in the space that surrounds the affected lung in the chest cavity, called the pleural space.

Pleural effusion can cause shortness of breath. Treatments are available to drain the fluid from your chest. Treatments can reduce the risk that pleural effusion will happen again.

Cancer that spreads to other parts of the body

Lung cancer often spreads to other parts of the body. Lung cancer may spread to the brain and the bones.

Cancer that spreads can cause pain, nausea, headaches or other symptoms depending on what organ is affected. Once lung cancer has spread beyond the lungs, it's generally not curable. Treatments are available to decrease symptoms and to help you live longer.

There's no sure way to prevent lung cancer, but you can reduce your risk if you:

Don't smoke

If you've never smoked, don't start. Talk to your children about not smoking so that they can understand how to avoid this major risk factor for lung cancer. Begin conversations about the dangers of smoking with your children early so that they know how to react to peer pressure.

Stop smoking

Stop smoking now. Quitting reduces your risk of lung cancer, even if you've smoked for years. Talk to your healthcare team about strategies and aids that can help you quit. Options include nicotine replacement products, medicines and support groups.

Avoid secondhand smoke

If you live or work with a person who smokes, urge them to quit. At the very least, ask them to smoke outside. Avoid areas where people smoke, such as bars. Seek out smoke-free options.

Test your home for radon

Have the radon levels in your home checked, especially if you live in an area where radon is known to be a problem. High radon levels can be fixed to make your home safer. Radon test kits are often sold at hardware stores and can be purchased online. For more information on radon testing, contact your local department of public health.

Avoid carcinogens at work

Take precautions to protect yourself from exposure to toxic chemicals at work. Follow your employer's precautions. For instance, if you're given a face mask for protection, always wear it. Ask your healthcare professional what more you can do to protect yourself at work. Your risk of lung damage from workplace carcinogens increases if you smoke.

Eat a diet full of fruits and vegetables

Choose a healthy diet with a variety of fruits and vegetables. Food sources of vitamins and nutrients are best. Avoid taking large doses of vitamins in pill form, as they may be harmful. For instance, researchers hoping to reduce the risk of lung cancer in people who smoked heavily gave them beta carotene supplements. Results showed the supplements increased the risk of cancer in people who smoke.

Exercise most days of the week

If you don't exercise regularly, start out slowly. Try to exercise most days of the week.

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Non-small cell lung cancer. National Comprehensive Cancer Network. https://www.nccn.org/guidelines/guidelines-detail?category=1&id=1450. Accessed Dec. 4, 2023.
Small cell lung cancer. National Comprehensive Cancer Network. https://www.nccn.org/guidelines/guidelines-detail?category=1&id=1462. Accessed Dec. 4, 2023.
Niederhuber JE, et al., eds. Cancer of the lung: Non-small cell lung cancer and small cell lung cancer. In: Abeloff's Clinical Oncology. 6th ed. Elsevier; 2020. https://www.clinicalkey.com. Accessed Dec. 4, 2023.
Non-small cell lung cancer treatment (PDQ) – Patient version. National Cancer Institute. https://www.cancer.gov/types/lung/patient/non-small-cell-lung-treatment-pdq. Accessed Dec. 4, 2023.
Small cell lung cancer treatment (PDQ) – Patient version. National Cancer Institute. https://www.cancer.gov/types/lung/patient/small-cell-lung-treatment-pdq. Accessed Dec. 4, 2023.
Lung cancer – non-small cell. Cancer.Net. https://www.cancer.net/cancer-types/lung-cancer/view-all. Accessed Dec. 4, 2023.
Lung cancer – small cell. Cancer.Net. https://www.cancer.net/cancer-types/33776/view-all. Accessed Dec. 4, 2023.
Detterbeck FC, et al. Executive Summary: Diagnosis and management of lung cancer, 3rd ed.: American College of Chest Physicians evidence-based clinical practice guidelines. Chest. 2013; doi:10.1378/chest.12-2377.
Palliative care. National Comprehensive Cancer Network. https://www.nccn.org/guidelines/guidelines-detail?category=3&id=1454. Accessed Dec. 4, 2023.
Lung cancer. World Health Organization. https://www.who.int/news-room/fact-sheets/detail/lung-cancer. Accessed Dec. 4, 2023.
Cairns LM. Managing breathlessness in patients with lung cancer. Nursing Standard. 2012; doi:10.7748/ns2012.11.27.13.44.c9450.
Warner KJ. Allscripts EPSi. Mayo Clinic. Jan. 13, 2020.
Brown AY. Allscripts EPSi. Mayo Clinic. July 30, 2019.
Searching for cancer centers. American College of Surgeons. https://www.facs.org/search/cancer-programs. Accessed Dec. 4, 2023.
Temel JS, et al. Early palliative care for patients with metastatic non-small-cell lung cancer. New England Journal of Medicine. 2010; doi:10.1056/NEJMoa1000678.
Dunning J, et al. Microlobectomy: A novel form of endoscopic lobectomy. Innovations. 2017; doi:10.1097/IMI.0000000000000394.
Leventakos K, et al. Advances in the treatment of non-small cell lung cancer: Focus on nivolumab, pembrolizumab and atezolizumab. BioDrugs. 2016; doi:10.1007/s40259-016-0187-0.
Dong H, et al. B7-H1, a third member of the B7 family, co-stimulates T-cell proliferation and interleukin-10 secretion. Nature Medicine. 1999;5:1365.
Aberle DR, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. New England Journal of Medicine. 2011; doi:10.1056/NEJMoa1102873.
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Lung cancer

Lung cancer is the leading cause of cancer-related deaths worldwide, accounting for the highest mortality rates among both men and women.
Smoking is the leading cause of lung cancer, responsible for approximately 85% of all cases.
Lung cancer is often diagnosed at advanced stages when treatment options are limited.
Screening high risk individuals has the potential to allow early detection and to dramatically improve survival rates.
Primary prevention (such as tobacco control measures and reducing exposure to environmental risk factors) can reduce the incidence of lung cancer and save lives.

Lung cancer is a type of cancer that starts when abnormal cells grow in an uncontrolled way in the lungs. It is a serious health issue that can cause severe harm and death.

Symptoms of lung cancer include a cough that does not go away, chest pain and shortness of breath.

It is important to seek medical care early to avoid serious health effects. Treatments depend on the person’s medical history and the stage of the disease.

The most common types of lung cancer are non-small cell carcinoma (NSCLC) and small cell carcinoma (SCLC). NSCLC is more common and grows slowly, while SCLC is less common but often grows quickly.

Lung cancer is a significant public health concern, causing a considerable number of deaths globally. GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer (IARC) show as lung cancer remains the leading cause of cancer death, with an estimated 1.8 million deaths (18%) in 2020.

Smoking tobacco (including cigarettes, cigars, and pipes) is the primary risk factor for lung cancer but it can also affect non-smokers. Other risk factors include exposure to secondhand smoke, occupational hazards (such as asbestos, radon and certain chemicals), air pollution, hereditary cancer syndromes, and previous chronic lung diseases.

Lung cancer can cause several symptoms that may indicate a problem in the lungs.

The most common symptoms include:

cough that does not go away
shortness of breath
coughing up blood (haemoptysis)
weight loss with no known cause
lung infections that keep coming back.

Early symptoms may be mild or dismissed as common respiratory issues, leading to delayed diagnosis.

Not smoking tobacco is the best way to prevent lung cancer.

Other risk factors to avoid include:

secondhand smoke
air pollution
workplace hazards like chemicals and asbestos.

Early treatment can prevent lung cancer from becoming worse and spreading to other parts of the body.

Prevention of lung cancer include primary and secondary prevention measures. Primary prevention aims to prevent the initial occurrence of a disease through risk reduction and promoting healthy behaviour. In public health, these preventive measures include smoking cessation, promoting smoke-free environments, implementing tobacco control policies, addressing occupational hazards, and reducing air pollution levels.

Secondary prevention for lung cancer involves screening methods that aim to detect the disease in its early stages, before symptoms become apparent and can be indicated for high-risk individuals. In this population, early detection can significantly increase the chances of successful treatment and improve outcomes. The primary screening method for lung cancer is low-dose computed tomography (LDCT).

Diagnostic methods for lung cancer include physical examination, imaging (such as chest X-rays, computed tomography scans, and magnetic resonance imaging), examination of the inside of the lung using a bronchoscopy, taking a sample of tissue (biopsy) for histopathology examination and definition of the specific subtype (NSCLC versus SCLC), and molecular testing to identify specific genetic mutations or biomarkers to guide the best treatment option.

Treatment and care

Treatments for lung cancer are based on the type of cancer, how much it has spread, and the person’s medical history. Early detection of lung cancer can lead to better treatments and outcomes.

Treatments include:

radiotherapy (radiation)
chemotherapy
targeted therapy
immunotherapy.

Surgery is often used in the early stages of lung cancer if the tumour has not spread to other areas of the body. Chemotherapy and radiation therapy can help shrink the tumour.

Doctors from several disciplines often work together to provide treatment and care of people with lung cancer.

Supportive care is important for people with lung cancer. It aims to manage symptoms, provide pain relief, and give emotional support. It can help to increase quality of life for people with lung cancer and their families.

Stages of care

a) Early stage disease : The primary treatment for early stage lung cancer (i.e. tumour limited to the lung, with no metastatic dissemination to distant organs or lymph nodes) is surgical removal of the tumour through procedures such as lobectomy, segmentectomy, or wedge resection. Neoadjuvant therapy (chemotherapy and/or radiation therapy before surgery) can help reduce tumour size, making it more manageable for surgical removal. Adjuvant treatment (chemotherapy and/or radiation therapy) is very often recommended after surgery to reduce the risk of cancer recurrence. In cases where surgery is not feasible, radiation therapy or stereotactic body radiation therapy (SBRT) may be used as the primary treatment. Targeted therapy and immunotherapy may also be considered based on specific tumour characteristics. Individualized treatment plans should be discussed with healthcare professionals.

b) Advanced disease: The treatment for metastatic stage lung cancer, where the cancer has spread to distant organs or lymph nodes, is based on various factors, including the patient's overall health, the extent and location of metastases, histology, genetic profile, and individual preferences. The primary goal is to prolong survival, alleviate symptoms, and improve quality of life. Systemic therapies, such as chemotherapy, targeted therapy, and immunotherapy, play a crucial role in the treatment of metastatic lung cancer.

Chemotherapy is often the first-line treatment for the majority of patients around the world and involves the use of drugs that circulate throughout the body to kill cancer cells. Combination chemotherapy regimens are commonly used, and the choice of drugs depends on factors such as the histological type of the cancer and the patient's general health conditions. Targeted therapy, designed to block the signalling pathways that drive the growth of cancer cells, is an important option for patients with specific genetic mutations or biomarkers identified in their tumour. Immunotherapy, specifically immune checkpoint inhibitors, has revolutionized the treatment of metastatic lung cancer. These drugs help to stimulate the immune system to recognize and attack cancer cells. Local treatments, such as radiation therapy and surgery, may be used to manage specific metastatic sites or alleviate symptoms caused by tumour growth.

Clinical Trials

Clinical trials offer opportunities to access novel treatments or experimental therapies for patients. Participation in clinical trials helps advance medical knowledge and potentially offers new treatment options.

WHO response

WHO recognizes the significant impact of lung cancer on global health and has implemented several initiatives to address the disease comprehensively. The WHO's response focuses on tobacco control, cancer prevention, early detection, and improving access to quality treatment and care. WHO supports countries in implementing evidence-based tobacco control policies, including increasing tobacco taxes, enforcing comprehensive bans on tobacco advertising, promotion, and sponsorship, and implementing strong graphic health warnings on tobacco products.

The Organization also promotes cancer prevention strategies by advocating for healthy lifestyles, including regular physical activity, a healthy diet, and minimizing exposure to environmental risk factors. Additionally, WHO supports early detection programs and encourages countries to implement screening measures for high-risk populations to detect lung cancer at earlier stages when treatment options are more effective. Last, WHO works towards ensuring access to quality treatment and care for lung cancer patients by providing technical guidance to member states, promoting equitable access to essential cancer medicines, and fostering international collaboration to share best practices and improve cancer care outcomes.

International Agency for Research on Cancer: Lung cancer

WHO's work on tobacco cessation

WHO's work on cancer

ESMO Clinical Practice Guidelines: Lung and Chest Tumours

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Lung cancer

Affiliations.

1 Peter MacCallum Cancer Centre, Melbourne, VIC, Australia; Sir Peter MacCallum Department of Oncology, University of Melbourne, VIC, Australia.
2 Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
3 Department of Medicine, Massachusetts General Hospital, Boston, MA, USA. Electronic address: [email protected].
PMID: 34273294
DOI: 10.1016/S0140-6736(21)00312-3

Lung cancer is one of the most frequently diagnosed cancers and the leading cause of cancer-related deaths worldwide with an estimated 2 million new cases and 1·76 million deaths per year. Substantial improvements in our understanding of disease biology, application of predictive biomarkers, and refinements in treatment have led to remarkable progress in the past two decades and transformed outcomes for many patients. This seminar provides an overview of advances in the screening, diagnosis, and treatment of non-small-cell lung cancer and small-cell lung cancer, with a particular focus on targeted therapies and immune checkpoint inhibitors.

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Conflict of interest statement

Declaration of interests BJS reports personal fees from Pfizer, Novartis, Roche/Genentech, AstraZeneca, Merck, Bristol Myers Squibb, Amgen, and Loxo Oncology outside the submitted work. JFG has served as a consultant or received honoraria from Bristol-Myers Squibb, Genentech, Ariad/Takeda, Loxo/Lilly, Blueprint, Oncorus, Regeneron, Gilead, Helsinn, EMD Serono, AstraZeneca, Pfizer, Incyte, Novartis, Merck, Agios, Amgen, and Array; has had research support from Novartis, Genentech/Roche, Ariad/Takeda, Bristol-Myers Squibb, Tesaro, Moderna, Blueprint, Jounce, Array Biopharma, Merck, Adaptimmune, and Alexo; and has an immediate family member who is an employee of Ironwood Pharmaceuticals. LVS reports grants and personal fees from AstraZeneca; grants from Novartis and Boehringer Ingelheim; grants and consulting fees from Genentech Blueprint and Merrimack Pharmaceuticals; and consulting fees from Janssen and grants from LOXO, all outside the submitted work. LVS has a patent about treatment of EGFR-mutant cancer pending. RSH reports honoraria from Novartis, Merck KGaA, Daichii Sankyo, Pfizer, Roche, Apollomics, Tarveda, and Boehringer Ingelheim; and grants from Novartis, Genentech Roche, Corvus, Incyte, Exelixis, Abbvie, Daichii Sankyo, Agios, Mirati, Turning Point, and Lilly when writing this Seminar. AAT declares no competing interests.

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Lung cancer: introduction, what is cancer.

Cancer may seem complex. But at its core, cancer is simple. Normal cells grow and die when your body needs them to. Cancer is what happens when certain cells grow even though your body doesn’t need them.

In many cases, these cancerous cells form a lump or mass called a tumor. Since cancerous cells don’t act like normal cells, tumors can prevent your body from working correctly. Given time, they can also spread, or metastasize, to other parts of the body.

Lung cancer is cancer that starts in the cells that make up the lungs. It isn’t cancer that spreads to the lungs from other parts of the body. This is key because treatment is based on the original site of the tumor. For example: If a tumor begins in the breast and spreads to the lungs, it would be treated as metastatic breast cancer—not lung cancer.

Understanding the lungs

The lungs are sponge-like organs in your chest. Their job is to bring oxygen into the body and to get rid of carbon dioxide. When you breathe air in, it goes into your lungs through your windpipe (trachea). The trachea divides into tubes called bronchi, which enter the lungs. These divide into smaller branches called bronchioles. At the end of the bronchioles are tiny air sacs called alveoli. The alveoli move oxygen from the air into your blood. They take carbon dioxide out of the blood. This leaves your body when you breathe out (exhale).

Your right lung is divided into 3 sections (lobes). Your left lung has 2 lobes.

Types of lung cancer

There are two main types of lung cancer: non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). Understanding the differences between these types may lessen anxiety about your diagnosis and treatment.

Non-small cell lung cancer

NSCLC accounts for 85% to 90% of lung cancer cases. There are 3 main subtypes. Each subtype is named for the type of cell it develops in:

Adenocarcinoma. This is the most common type of lung cancer—particularly among the minority of non-smokers who get the disease. It tends to appear on the outer edges of the lungs and grows more slowly than the other subtypes.

Squamous cell carcinoma (epidermoid carcinoma). This type of cancer develops more often in smokers or former smokers than lifetime nonsmokers. It tends to start in the center of the lungs near the bronchial tubes.

Large cell carcinoma. The least common NSCLC, large cell carcinoma can begin anywhere in the lung. It tends to grow more quickly than the other subtypes, which can make it harder to treat.

Despite minor differences, they are often treated the same way.

Small cell lung cancer

Only about 1 in 10 to 3 in 20 people diagnosed with lung cancer have small-cell lung cancer (also called oat cell cancer). It's also almost exclusively found in smokers. It tends to grow more quickly than NSCLC. It often spreads to other parts of the body at an earlier stage.

How lung cancer spreads

Lung cancer acts differently in different people. But when it spreads, it tends to go to the same places. First: lymph nodes in the center of the chest. It may also spread to lymph nodes in the lower neck.

Lymph nodes are small clusters of immune system cells.

During later stages, lung cancer may spread to more distant parts of the body, such as the liver, brain, or bones.

Talk with your healthcare provider

If you have questions about lung cancer, talk with your healthcare provider. They can help you understand more about this cancer.

Medical Reviewers:

Jessica Gotwals RN BSN MPH
Sabrina Felson MD
Todd Gersten MD
Ask a Medical Librarian Make an Appointment Physicians & Services Physicians who treat Lung Cancer

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Lung Cancer Symptoms

While lung cancer is the second most common cancer in the United States, it’s not often detected early.

Unlike some other cancers, lung cancer usually presents no noticeable symptoms until it’s in an advanced stage. When the tumor grows large enough to press against other organs, it causes pain and discomfort. Sometimes, though, earlier warning signs can be a signal to call the doctor.

Often, before patients receive a lung cancer diagnosis, they have been experiencing symptoms such as cough, shortness of breath, recurring respiratory infections or chest pain for a while. But since these symptoms have other, more common and less serious causes, the person may wait to see a doctor.

“While every cough or case of bronchitis isn’t a reason to believe you have lung cancer, if you are at high risk of developing lung cancer, paying attention to the early warning signs is critical,” says Russell Hales, a radiation oncologist and director of the Lung Cancer Program at the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins.

Respiratory symptoms of lung cancer include:

Chronic cough : People with lung cancer often have a cough that won’t go away. A cough that lasts for at least eight weeks is considered chronic.
Repeated respiratory infections : Lung tumors can block the airway, causing frequent infections such as bronchitis and pneumonia.
Coughing up blood : Even if it’s just a small amount, coughing up blood or bloody mucus is a reason to call your doctor.
Shortness of breath : Lung cancer can cause the airway passage to narrow, which leads to difficulty breathing.
Hoarseness : Chronic coughing or a tumor that interferes with the vocal cords can cause people with lung cancer to have a raspy voice.
Chest pain : Lung cancer pain is due to a tumor causing tightness in the chest or pressing on nerves. You may feel pain in your chest, especially when breathing deeply, coughing or laughing.

Generalized symptoms of lung cancer include:

Lumps in the neck or collarbone area
Weakness or numbness in the limbs
Swelling in the face, neck or arms

When to Talk to Your Doctor About Lung Cancer Screening

The best time to catch lung cancer is when it is not causing symptoms. Consequently, those at an increased risk of developing lung cancer should talk to their doctor about having routine screenings , Hales says. Screenings can offer hope for early detection, when treatment is most likely to result in cure.

People considered at high risk for developing lung cancer:

Have a history of heavy smoking (for example, smoking at least one pack a day for 30 years);
Are current smokers or former smokers who quit within the past 15 years; and
Are between the ages of 55 and 80.

Learn more about lung cancer risk factors .

If your doctor detects anything abnormal during a lung cancer screening, diagnostic tests such as imaging scans and biopsies (lung tissue sampling) are the next step.

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Peer review
Richard D Neal , professor of primary care oncology 1 ,
Fei Sun , clinical research fellow, honorary specialty registrar in clinical oncology 2 ,
Jon D Emery , Herman professor of primary care cancer research 3 ,
Matthew E Callister , consultant respiratory physician 2
1 Academic Unit of Primary Care, Leeds Institute of Health Sciences, University of Leeds, Leeds LS2 9NL, UK
2 Leeds Teaching Hospitals Trust, St James’s Hospital, Leeds LS9 7TF, UK
3 Centre for Cancer Research and Department of General Practice, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Victorian Comprehensive Cancer Centre, Victoria 3000, Australia
Correspondence to: R D Neal R.D.Neal{at}leeds.ac.uk

What you need to know

Most lung cancers present with non-specific symptoms; haemoptysis is a feature in only 20%

Consider a chest x ray for patients who have persistent symptoms or thrombocytosis, and repeat chest x ray or computed tomography (CT) if symptoms persist

Positron emission tomography-computed tomography (PET-CT) is used to identify distant metastases in those eligible for radical treatment after contrast-enhanced CT. If there is potential mediastinal node involvement, endobronchial ultrasound guided transbronchial needle aspiration is the optimal initial strategy for nodal sampling

Surgery remains the standard of care in early stage non-small cell lung cancer (NSCLC). Radical radiotherapy or stereotactic ablative radiotherapy (SABR) are alternatives. Options for locally advanced NSCLC include surgery with postoperative chemotherapy or chemoradiotherapy

Systemic therapy for metastatic NSCLC is now targeted primarily on tumour genetic mutations and biomarkers. Tyrosine-kinase inhibitor (TKIs) and immunotherapy are first line treatments for some patients with metastatic NSCLC. Combination chemotherapy is available for patients not eligible for TKIs or immunotherapy

Lung cancer is one of the commonest cancers worldwide. 1 Outcomes are among the poorest of all tumour types, with five year survival of 10-20%. 2 Survival is hugely influenced by stage at diagnosis, with five year survival varying from 92% to 0% for the earliest and latest stages respectively. 3 In this update we discuss contemporary therapeutic options, and approaches to increasing symptom awareness and early diagnosis. Low-dose computed tomography (CT) screening is beyond the scope of this review.

Sources and selection criteria

In addition to searching Clinical Evidence and the Cochrane Collaboration, we based this article on databases of references. We also examined the citation lists of included articles.

Who gets it?

Worldwide, about three quarters of lung cancers are attributable to smoking; others are caused by occupational workplace exposure, radon exposure, and air pollution. 4 It is more common in men, and incidence increases with age (fig 1). Recent …

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Advances in Lung Cancer Research

KRAS-driven cancer cells in a tumor sample from a lung cancer mouse model.

Lung cancer cells driven by the KRAS oncogene, which is highlighted in purple.

NCI-funded researchers are working to advance our understanding of how to prevent, detect, and treat lung cancer. In particular, scientists have made progress in identifying many different genetic alterations that can drive lung cancer growth.

This page highlights some of the latest research in non-small cell lung cancer (NSCLC), the most common form of lung cancer, including clinical advances that may soon translate into improved care, NCI-supported programs that are fueling progress, and research findings from recent studies.

Early Detection of Lung Cancer

A great deal of research has been conducted in ways to find lung cancer early. Several methods are currently being studied to see if they decrease the risk of dying from lung cancer.

The NCI-sponsored National Lung Screening Trial (NLST) showed that low-dose CT scans can be used to screen for lung cancer in people with a history of heavy smoking. Using this screening can decrease their risk of dying from lung cancer. Now researchers are looking for ways to refine CT screening to better predict whether cancer is present.

Markers in Blood and Sputum

Scientists are trying to develop or refine tests of sputum and blood that could be used to detect lung cancer early. Two active areas of research are:

Analyzing blood samples to learn whether finding tumor cells or molecular markers in the blood will help diagnose lung cancer early.
Examining sputum samples for the presence of abnormal cells or molecular markers that identify individuals who may need more follow-up.

Machine Learning

Machine learning is a method that allows computers to learn how to predict certain outcomes. In lung cancer, researchers are using computer algorithms to create computer-aided programs that are better able to identify cancer in CT scans than radiologists or pathologists. For example, in one artificial intelligence study , researchers trained a computer program to diagnose two types of lung cancer with 97% accuracy, as well as detect cancer-related genetic mutations.

Lung Cancer Treatment

Treatment options for lung cancer are surgery , radiation , chemotherapy , targeted therapy , immunotherapy , and combinations of these approaches. Researchers continue to look for new treatment options for all stages of lung cancer.

Treatments for early-stage lung cancer

Early-stage lung cancer can often be treated with surgery. Researchers are developing approaches to make surgery safer and more effective.

When lung cancer is found early, people usually have surgery to remove an entire section ( lobe ) of the lung that contains the tumor. However, a recent clinical trial showed that, for certain people with early-stage NSCLC, removing a piece of the affected lobe is as effective as surgery to remove the whole lobe .
The targeted therapy Osimertinib (Tagrisso ) was approved by the Food and Drug Administration (FDA) in 2021 to be given after surgery—that is, as adjuvant therapy —to people with early-stage NSCLC that has certain mutations in the EGFR gene.
Two immunotherapy drugs, atezolizumab (Tecentriq) and pembrolizumab (Keytruda) have been approved by the FDA to be used as adjuvant treatments after surgery and chemotherapy, for some patients with early-stage NSCLC.
The immunotherapy drug nivolumab (Opdivo) is approved to be used, together with chemotherapy, to treat patients with early-stage lung cancer before surgery (called neoadjuvant ). This approval, which came in 2022, was based on the results of the CheckMate 816 trial, which showed that patients at this stage who received neoadjuvant nivolumab plus chemotherapy lived longer than those who received chemotherapy alone .
In another trial (Keynote-671), patients with early-stage NSCLC who received pembrolizumab plus chemotherapy before surgery and pembrolizumab after surgery had better outcomes than those who received just neoadjuvant or just adjuvant treatment.

Treatments for advanced lung cancer

Newer therapies are available for people with advanced lung cancer. These primarily include immunotherapies and targeted therapies, which continue to show benefits as research evolves.

Immunotherapy

Immunotherapies work with the body's immune system to help fight cancer. They are a major focus in lung cancer treatment research today. Clinical trials are ongoing to look at new combinations of immunotherapies with or without chemotherapy to treat lung cancer.

Immune checkpoint inhibitor s are drugs that block an interaction between proteins on immune cells and cancer cells which, in turn, lowers the immune response to the cancer. Several immune checkpoint inhibitors have been approved for advanced lung cancer, including p embrolizumab (Keytruda) , a tezolizumab (Tecentriq) , c emiplimab (Libtayo) , d urvalumab (Imfinzi) , and n ivolumab (Opdivo) .

A key issue with immunotherapies is deciding which patients are most likely to benefit. There is some evidence that patients whose tumor cells have high levels of an immune checkpoint protein called PD-L1 may be more responsive to immune checkpoint inhibitors. Another marker for immunotherapy response is tumor mutational burden , or TMB, which refers to the amount of mutations in the DNA of the cancer cells. In some lung cancer trials, positive responses to immune checkpoint inhibitors have been linked with a high TMB. However, these markers cannot always predict a response and there is ongoing work to find better markers.

To learn more, see Immunotherapy to Treat Cancer .

Targeted Therapies

Targeted treatments identify and attack certain types of cancer cells with less harm to normal cells. In recent years, many targeted therapies have become available for advanced lung cancer and more are in development. Targeted treatments for lung cancer include the below.

Anaplastic lymphoma kinase (ALK) Inhibitors

ALK inhibitors target cancer-causing rearrangements in a protein called ALK. These drugs continue to be refined for the 5% of NSCLC patients who have an ALK gene alteration. Approved treatments include ceritinib (Zykadia) , alectinib (Alecensa) , brigatinib (Alunbrig) , and lorlatinib (Lorbrena) .

These ALK inhibitors are improvements from previous ones in their enhanced ability to cross the blood–brain barrier. This progress is critical because, in non-small cell lung cancer patients with ALK alterations, disease progression tends to occur in the brain. Based on clinical trial results, in 2024 the FDA approved alectinib as adjuvant therapy for people with ALK-positive NSCLC .

EGFR Inhibitors

Lung Cancer Trial of Osimertinib Draws Praise—and Some Criticism

The drug improved survival in a large clinical trial, but some question the trial’s design.

EGFR inhibitors block the activity of a protein called epidermal growth factor receptor (EGFR). Altered forms of EGFR are found at high levels in some lung cancers, causing them to grow rapidly. Osimertinib (Tagrisso) is the most effective and most widely used EGFR inhibitor. It is also used for adjuvant therapy after surgery for resectable NSCLC. Other drugs that target EGFR that are approved for treating NSCLC include afatinib (Gilotrif) , dacomitinib (Vizimpro) , erlotinib (Tarceva) , gefitinib (Iressa) . For people with Exon 20 mutations, amivantamab (Rybrevant) is an approved targeted therapy.

ROS1 Inhibitors

The ROS1 protein is involved in cell signaling and cell growth. A small percentage of people with NSCLC have rearranged forms of the ROS1 gene. Crizotinib (Xalkori) and entrectinib (Rozlytrek) are approved as treatments for patients with these alterations. In late 2023, the FDA approved repotrectinib (Augtyro) for advanced or metastatic NSCLC with ROS1 fusions as an initial treatment and as a second-line treatment in those who previously received a ROS1-targeted drug.

BRAF Inhibitors

The B-Raf protein is involved in sending signals in cells and cell growth. Certain changes in the B-Raf gene can increase the growth and spread of NSCLC cells.

The combination of the B-Raf-targeted drug dabrafenib (Tafinlar) and trametinib (Mekinist ), which targets a protein called MEK, has been approved as treatment for patients with NSCLC that has a specific mutation in the BRAF gene.

Encorafenib (Braftovi) combined with binimetinib (Mektovi) is approved for patients with metastatic NSCLC with a BRAF V600E mutation .

Other Inhibitors

Some NSCLCs have mutations in the genes NRTK-1 and NRTK-2 that can be treated with the targeted therapy larotrectinib (Vitrakvi). Those with certain mutations in the MET gene can be treated with tepotinib (Tepmetko) or capmatinib (Tabrecta) . And those with alterations in the RET gene are treated with selpercatinib (Retevmo) and pralsetinib (Gavreto) . A 2023 clinical trial showed that treatment with selpercatinib led to longer progression-free survival compared with people who received chemotherapy with or without pembrolizumab. Inhibitors of other targets that drive some lung cancers are being tested in clinical trials.

See a complete list of targeted therapies for lung cancer .

NCI-Supported Research Programs

Many NCI-funded researchers at the NIH campus, and across the United States and the world, are seeking ways to address lung cancer more effectively. Some research is basic, exploring questions as diverse as the biological underpinnings of cancer and the social factors that affect cancer risk. And some is more clinical, seeking to translate basic information into improved patient outcomes. The programs listed below are a small sampling of NCI’s research efforts in lung cancer.

Illustration of thousands of tiny people gathering into a shape that resembles a pair of lungs.

Pragmatica-Lung Study Enrolling Patients

The simplified trial may serve as a model for future cancer clinical trials.

The Pragmatica-Lung Study is a randomized trial that will compare the combination of the targeted therapy ramucirumab (Cyramza) and the immunotherapy pembrolizumab (Keytruda) with standard chemotherapy in people with advanced NSCLC whose disease has progressed after previous treatment with immunotherapy and chemotherapy. In addition to looking at an important clinical question, the trial will serve as a model for future trials because it is designed to remove many of the barriers that prevent people from joining clinical trials.
Begun in 2014, ALCHEMIST is a multicenter NCI trial for patients with early stage non-small cell lung cancer. It tests to see whether adding a targeted therapy after surgery, based on the genetics of a patient’s tumor, will improve survival.
The Lung MAP trial is an ongoing multicenter trial for patients with advanced non-small cell lung cancer who have not responded to earlier treatment. Patients are assigned to specific targeted therapies based on their tumor’s genetic makeup.
The Small Cell Lung Cancer Consortium was created to coordinate efforts and provide a network for investigators who focus on preclinical studies of small-cell lung cancer. The goal of the consortium is to accelerate progress on this disease through information exchange, data sharing and analysis, and face-to-face meetings.
NCI funds eight lung cancer Specialized Programs of Research Excellence (Lung SPOREs) . These programs are designed to quickly move basic scientific findings into clinical settings. Each SPORE has multiple lung cancer projects underway.

Clinical Trials

NCI funds and oversees both early- and late-phase clinical trials to develop new treatments and improve patient care. Trials are available for both non-small cell lung cancer treatment and small cell lung cancer treatment .

Lung Cancer Research Results

The following are some of our latest news articles on lung cancer research:

Durvalumab Extends Lives of People with Early-Stage Small Cell Lung Cancer
Alectinib Approved as an Adjuvant Treatment for Lung Cancer
Repotrectinib Expands Treatment Options for Lung Cancers with ROS1 Fusions
Tarlatamab Shows Promise for Some People with Small Cell Lung Cancer
Selpercatinib Slows Progression of RET-Positive Lung, Medullary Thyroid Cancers

View the full list of Lung Cancer Research Results and Study Updates .

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02 July 2024

Why cancer risk declines sharply in old age

Heidi Ledford

You can also search for this author in PubMed Google Scholar

A coloured scanning electron micrograph of an orange cancerous tumour filling an alveolus of a human lung in pink, blue and purple

A tumour (artificially coloured) fills the alveolus of a human lung. Some evidence suggests that risk of these cancers decreases with age. Credit: Moredun Animal Health Ltd/Science Photo Library

Becoming an octogenarian could have an unexpected benefit: a decrease in the risk of lung cancer , according to two studies in mice 1 , 2 .

The results, posted as preprints on the bioRxiv server, highlight specific genes that could contribute to the declining risk and reveal a surprising link between them and iron metabolism . The studies have not yet been peer reviewed.

The findings might seem counter-intuitive: cancer is a disease associated with ageing , and the likelihood of many cancer diagnoses peaks in a person’s 60s or 70s. But after that, rates of many of those cancers mysteriously decline.

“It’s an observation that we have made for decades,” says Ana Gomes, who studies ageing and cancer at the H. Lee Moffitt Cancer Center and Research Institute in Tampa, Florida, and who is not involved in the preprints. “But we have really not been able to explain why that is.”

Age accumulation

Cancer is caused by DNA mutations that accumulate over time . More years of life mean more opportunities to collect the constellation of mutations necessary to generate rogue cancer cells that grow uncontrollably. Immune responses that might once have been able to keep a tumour in check might also become more muted with age .

But the changes to the tissue that come with ageing can also discourage tumour growth by altering the environment in which cancer cells live. Older lungs, for example, tend to have more scar tissue than younger lungs do. Lung cells also become less capable of regeneration, and less resilient to the stresses of unregulated growth. “Structurally and functionally, what you have at an older age is a completely different environment than what you have at young age,” says Gomes.

New lung-cancer drugs extend survival times

To learn more about how ageing affects tumour growth, Emily Shuldiner, a cancer biologist at Stanford University in California, and her colleagues studied mice that have a cancer-causing mutation that the authors controlled with a genetic switch 1 . The team turned on these mutated genes in the lungs of young and old mice, and found that tumours were larger and more frequent in the younger mice than in the older mice.

The researchers also used CRISPR–Cas9 gene editing in mouse tumours to assess the effects of inactivating each of more than two dozen genes that normally suppress tumour growth. On average, turning off most of these genes increased the rate of tumour growth in mice of all ages, but there were more tumours, and they grew larger, in younger mice than in older mice. This suggests that a different process might be working to suppress cancer in older mice.

Iron grip on tumours

Another team led by Xueqian Zhuang, a cancer biologist at Memorial Sloan Kettering Cancer Center in New York City, found that ageing increases the production of a protein called NUPR1 — which affects iron metabolism — in mouse and human lung cells 2 . The cells then behaved as if they were iron deficient, limiting their capacity for the rapid growth that is a hallmark of cancer.

To follow up on this finding, the team used CRISPR—Cas9 gene editing to inactivate the Nupr 1 gene in older mice. Iron levels in their lungs rose, and the mice became more prone to tumours, like their younger counterparts.

The authors also found that people over the age of 80 have more NUPR1 in their lung tissue than do people under the age of 55, suggesting that the mechanism might be conserved between mice and humans.

The stress of cancer

The results nicely demonstrate that ageing can affect the fitness of lung cancer cells in ways that prevent tumours, says Gomes. But there could be important differences in how tumours are generated in humans and in these mice, she adds. In humans, cancer-causing mutations usually accumulate gradually, and the seeds of a cancer can be planted decades before a tumour is detectable. In the mice, however, tumours were initiated by suddenly switching on the cancer-causing gene when the mice were already old.

And results from lung cancer might not translate to cancers in other tissues, says Cecilia Radkiewicz, an oncologist and cancer epidemiologist at the Karolinska Institute in Stockholm. “It’s quite different between different cancer sites because there have different biological drivers,” she says.

Radkiewicz has found that, in many cancers, the apparent decline in incidence with old age could be an artefact. When she looked at how frequently tumours were found during autopsies, this decline often disappeared 3 . This suggests that the rates of various cancers often remain the same even during old age, she says, but the cancers are simply diagnosed or reported less often in people over the age of 75.

The pros and cons of screening

An exception, she adds was lung cancer: its incidence did actually decline in older people, even when accounting for autopsy data.

Overall, the findings highlight the importance of studying cancer in aged mice, says Zhuang. Such studies can be difficult, she says: it is expensive and time-consuming to rear mice into old age. But the results could illuminate new ways of treating cancer in old and young people, as well as highlight important targets for regenerative medicine .

“People often think ageing is just bad,” says Dmitri Petrov, an evolutionary biologist at Stanford University and an author on the preprint along with Zhuang. “But if this [work] is correct, then ageing has a beneficial role to play.”

doi: https://doi.org/10.1038/d41586-024-02107-z

Shuldiner, E. G. et al. Preprint at bioRxiv https://doi.org/10.1101/2024.05.28.596319 (2024).

Zhuang, X. et al . Preprint at bioRxiv https://doi.org/10.1101/2024.06.23.600305 (2024).

Radkiewicz, C., Krönmark, J. J., Adami, H-O. & Edgren, G. Cancer Epidemiol. Biomarkers Prev. 31 , 280–286 (2022).

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Honeybees Can Sniff Out Lung Cancer, Scientists Suggest

New research opens the door for doctors to one day use bees as a living diagnostic tool

Daily Correspondent

Honeybees are often hailed as heroes for pollinating crops that feed the world. But as it turns out, these buzzy insects might have another useful trick up their sleeves: sniffing out cancer.

Laboratory experiments suggest honeybees can identify lung cancer using their keen sense of smell, researchers report this month in the journal Biosensors and Bioelectronics .

Scientists have long known that animals can detect diseases through scents. Diabetic alert dogs can smell when their human’s blood sugar is too low or too high, and ants can be trained to smell cancer in urine , for example. Dogs can also learn to sniff out cancer from saliva samples.

For the new study, researchers were curious about the disease-detecting abilities of honeybees, which they say could serve as a more affordable and lower-maintenance alternative to cancer-sniffing dogs, reports CBS News ’ Kelly Vaughen.

The team held honeybees in place using wax and 3D-printed plastic harnesses, then attached electrodes to the part of their brains that processes odors. Then, they exposed the bees’ antennae to different aerosolized mixtures: one that mimicked the compounds found in the breath of a lung cancer patient, and another that represented the breath of a healthy person.

In response to the scents, the bees’ brains produced different electrical signals. Looking at these signals, researchers could distinguish between the two types of artificial breath at least 93 percent of the time.

The bees were able to tell the difference between the two types of synthetic breath, even at “very small concentrations,” says study co-author Debajit Saha , a biomedical engineer at Michigan State University, in a statement .

“Bees can differentiate between minute changes in the chemical concentrations of the breath mixture, which is in the parts per one billion range,” he adds.

The team also conducted a separate experiment to see if the bees could distinguish between two different types of cancer— small cell lung cancer , which is a rarer and fast-growing variety, and non-small cell lung cancer . The bees passed that test with flying colors, too.

“It doesn’t surprise me at all,” says Brian Peterson-Roest , co-founder and president of Bees in the D, a Detroit-based pollinator education and conservation nonprofit, to CBS News. He was not involved in the study.

In the future, the team hopes to run similar experiments using real breath exhaled by cancer patients.

But already, their findings could open the door for doctors to one day use honeybees as diagnostic tools. Lung cancer is the leading cause of cancer-related deaths around the world, responsible for an estimated 1.8 million deaths in 2022. Diagnosing lung cancer early can dramatically increase patients’ survival rates.

Though engineers are developing electronic devices that can “smell” the difference between chemical compounds, as of right now, the team says they’re still no substitute for mother nature.

“Biology has this ability to differentiate between very, very similar mixtures, which no other engineered sensors can do,” Saha tells Science News ’ Meghan Rosen.

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Sarah Kuta is a writer and editor based in Longmont, Colorado. She covers history, science, travel, food and beverage, sustainability, economics and other topics.

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Primary Care: Try These Steps to Boost Lung Cancer Screens

Ann Thomas, MD, MPH

June 27, 2024

A few years ago, Kim Lori Sandler, MD, realized many patients newly diagnosed with lung cancer had never been screened for the disease — they received CT scans only because they were symptomatic.

But Sandler, a radiologist at Vanderbilt University Medical Center in Nashville, Tennessee, could see in medical charts that most of these patients had been eligible for a screening before becoming symptomatic. And for women, most had received decades worth of mammograms. She saw an opportunity and launched a study to find out if an intervention would work.

Low-dose CT and mammography services often are available in the same imaging facility, so women who qualified for a lung cancer screening were offered the scan during their mammography visit. Monthly rates of lung scans in women rose by 50% at one facility and 36% at the other over a 3-year period.

"What we found is that women are really receptive, if you talk to them about it," Sandler said. "I don't think that lung cancer is thought of as a disease in women."

Although lung cancer is the leading cause of cancer deaths in the United States, a recent study in JAMA Internal Medicine found only 18% of eligible patients were screened in 2022, a far cry from the rates of 72% for colon cancer — which itself falls short of goals from US medical groups like the American Cancer Society (ACS). Among those eligible, rates of lung screenings were lowest among younger people without comorbid conditions, who did not have health insurance or a usual source of care, and those living in southern states and states that did not expand Medicaid as part of the Affordable Care Act.

But researchers and clinicians, from those working in an urban health center for the homeless to clinics in the poorest counties in the tobacco belt, have used strategies to raise their rates of screening for lung cancer.

Getting patients screened is lifesaving: 27% of people with lung cancer survive 5 years after diagnosis. But the survival rate rises to 63% when cases are diagnosed at an early stage.

Increasing Uptake

The formal recommendation to use low-dose chest CT to screen for lung cancer is only a decade old. The approach was first endorsed by the United States Preventive Services Taskforce (USPSTF) on the basis of an influential trial that found such testing was linked to a 20% reduction in mortality from the disease . Updated 2021 USPSTF guidelines call for annual screening of people aged 50-80 years who have a 20 pack-year history of smokin g and currently smoke or have quit within the past 15 years.

But implementing the recommendation is not always simple. Unlike a colorectal or breast cancer screening , which is recommended primarily on patient age, eligibility for a lung cancer screening requires calculating pack-years of smoking and for past smokers, knowledge of when they quit.

The structured fields in most electronic medical records (EMRs) inquire about current or past use of cigarettes and the number of daily packs smoked. But few EMRs can calculate when a patient starts smoking two cigarettes a day but then increases to a pack a day and cuts down again. EMRs also do not track when a patient has stopped smoking permanently. Individual clinicians or health systems must identify patients who are eligible for screening, but the lack of automated calculations makes that job more difficult.

Sandler and her colleagues turned to the informatics team at Vanderbilt to develop a natural language processing approach that extracts smoking data directly from clinician notes instead of using standard variables in their EMR.

The number of patients identified as needing a screening using the algorithm nearly doubled from baseline, from 5887 to 10,231 over a 3-year period, according to results from another study that Sandler published.

Although the algorithm may occasionally flag someone who does not need screening as eligible, "you can always have a conversation with the patient to determine if they actually meet eligibility criteria," Sandler said.

Patient Navigators to the Rescue?

About a decade ago, Travis Baggett, MD, MPH, an associate professor of internal medicine at Harvard Medical School, Boston, received pilot funding from the ACS to study cancer epidemiology among patients at Boston Health Care for the Homeless Program (BHCHP), which serves nearly 10,000 patients at a variety of Boston-area clinics each year.

"We found that both the incidence and mortality rates for lung cancer were more than twofold higher than in the general population," Baggett, who is also the director of research at BHCHP, said.

He also discovered that BHCHP patients were diagnosed at significantly later stages than people in the general population for malignancies like breast and colorectal cancer .

Screening for lung cancer was a new recommendation at the time. With additional funding from the ACS, he la unched a clinical trial in 2020 that randomized patients who were eligible for lung cancer screening to either work with a patient navigator or receive usual care.

The navigators eased the burden on primary care clinicians: They facilitated shared decision-making visits, helped participants make and attend appointments for low-dose CT, assisted with transportation, and arranged follow-up as needed.

The 3-year study found 43% of patients who received navigation services underwent screening for lung cancer compared with 9% in the usual care arm. Participants said the navigators played a critical role in educating them about the importance of screening, coordinating care, and providing emotional support.

"At the root of it all, it was quite clear that one thing that made the navigator successful was their interpersonal qualities and having someone that the patient could trust to help guide them through the process," Baggett said.

The navigator program, however, stopped when the funding for the study ended.

But another health system has implemented navigators in a sustainable way through a quality improvement project. Michael Gieske, MD, director of lung cancer screening at St. Elizabeth Healthcare in Edgewood, Kentucky, starts his Friday morning meeting with a multidisciplinary group, including a thoracic surgeon, radiologist, pulmonologist, and several screening nurse navigators. They review the week's chest CTs, with approximately one third from patients who underwent lung cancer screening.

Nurse navigators at St. Elizabeth Healthcare follow up with any patient whose scan is suspicious for lung cancer and guide them through the process of seeing specialists and obtaining additional testing.

"They essentially hold the patient's hand through this scary time in their life and make sure that everything flows smoothly and efficiently," Gieske, a family medicine physician, said.

St. Elizabeth's program also draws on several evidence-based strategies used for other cancer screening programs, such as patient and provider education and quarterly feedback to their 194 primary care clinicians on rates of lung cancer screening among their eligible patients.

Several requirements for reimbursement for a lung cancer screening from the US Centers for Medicare and Medicaid Services can also serve as barriers to getting patients screened : Clinicians must identify who is eligible, provide tobacco cessation counseling, and document the shared decision-making process.

To streamline the steps, St. Elizabeth's clinicians use an EMR smart set that reminds clinicians to verify smoking history and helps them document the required counseling.

Last year, 47% of eligible patients received their recommended screening, and Gieske said he expects even more improvement.

"We're on track this year to complete 60% uptake if things continue," he said, adding that 76% of the new cases of lung cancer are now diagnosed in stage I, with only 5% diagnosed in stage IV.

Gieske has shared his experience with many clinics in Appalachia, home to some of the highest rates of mortality from lung cancer in the country. A major part of his role with the Appalachian Community Cancer Alliance is helping educate primary care clinicians in the region about the importance of early detection of lung cancer.

"I think one of the most important things is just to convey a message of hope," he said. "We're trying to get the good word out there that if you screen individuals, you're going to catch it early, when you have an extremely high chance of curing the lung cancer."

Baggett reported support from grants from the ACS and the Massachusetts General Hospital Research Scholars Program. Bandi, Sandler, and Gieske reported no financial conflicts.

A former pediatrician and disease detective, Ann Thomas, MD, MPH, is a freelance science writer living in Portland, Oregon.

Send comments and news tips to [email protected] .

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Cancer Control
v.28; Jan-Dec 2021

Cancer Biology, Epidemiology, and Treatment in the 21st Century: Current Status and Future Challenges From a Biomedical Perspective

Patricia piña-sánchez.

1 Oncology Research Unit, Oncology Hospital, Mexican Institute of Social Security, Mexico

Antonieta Chávez-González

Martha ruiz-tachiquín, eduardo vadillo, alberto monroy-garcía, juan josé montesinos, rocío grajales.

2 Department of Medical Oncology, Oncology Hospital, Mexican Institute of Social Security, Mexico

Marcos Gutiérrez de la Barrera

3 Clinical Research Division, Oncology Hospital, Mexican Institute of Social Security, Mexico

Hector Mayani

Since the second half of the 20th century, our knowledge about the biology of cancer has made extraordinary progress. Today, we understand cancer at the genomic and epigenomic levels, and we have identified the cell that starts neoplastic transformation and characterized the mechanisms for the invasion of other tissues. This knowledge has allowed novel drugs to be designed that act on specific molecular targets, the immune system to be trained and manipulated to increase its efficiency, and ever more effective therapeutic strategies to be developed. Nevertheless, we are still far from winning the war against cancer, and thus biomedical research in oncology must continue to be a global priority. Likewise, there is a need to reduce unequal access to medical services and improve prevention programs, especially in countries with a low human development index.

Introduction

During the last one hundred years, our understanding of the biology of cancer increased in an extraordinary way. 1 - 4 Such a progress has been particularly prompted during the last few decades because of technological and conceptual progress in a variety of fields, including massive next-generation sequencing, inclusion of “omic” sciences, high-resolution microscopy, molecular immunology, flow cytometry, analysis and sequencing of individual cells, new cell culture techniques, and the development of animal models, among others. Nevertheless, there are many questions yet to be answered and many problems to be solved regarding this disease. As a consequence, oncological research must be considered imperative.

Currently, cancer is one of the illnesses that causes more deaths worldwide. 5 According to data reported in 2020 by the World Health Organization (WHO), cancer is the second cause of death throughout the world, with 10 million deaths. 6 Clearly, cancer is still a leading problem worldwide. With this in mind, the objective of this article is to present a multidisciplinary and comprehensive overview of the disease. We will begin by analyzing cancer as a process, focusing on the current state of our knowledge on 4 specific aspects of its biology. Then, we will look at cancer as a global health problem, considering some epidemiological aspects, and discussing treatment, with a special focus on novel therapies. Finally, we present our vision on some of the challenges and perspectives of cancer in the 21 st century.

The Biology of Cancer

Cancer is a disease that begins with genetic and epigenetic alterations occurring in specific cells, some of which can spread and migrate to other tissues. 4 Although the biological processes affected in carcinogenesis and the evolution of neoplasms are many and widely different, we will focus on 4 aspects that are particularly relevant in tumor biology: genomic and epigenomic alterations that lead to cell transformation, the cells where these changes occur, and the processes of invasion and metastasis that, to an important degree, determine tumor aggressiveness.

Cancer Genomics

The genomics of cancer can be defined as the study of the complete sequence of DNA and its expression in tumor cells. Evidently, this study only becomes meaningful when compared to normal cells. The sequencing of the human genome, completed in 2003, was not only groundbreaking with respect to the knowledge of our gene pool, but also changed the way we study cancer. In the post-genomic era, various worldwide endeavors, such as the Human Cancer Genome Project , the Cancer Genome ATLAS (TCGA), the International Cancer Genome Consortium, and the Pan-Cancer Analysis Working Group (PCAWG), have contributed to the characterization of thousands of primary tumors from different neoplasias, generating more than 2.5 petabytes (10 15 ) of genomic, epigenomic, and proteomic information. This has led to the building of databases and analytical tools that are available for the study of cancer from an “omic” perspective, 7 , 8 and it has helped to modify classification and treatment of various neoplasms.

Studies in the past decade, including the work by the PCAWG, have shown that cancer generally begins with a small number of driving mutations (4 or 5 mutations) in particular genes, including oncogenes and tumor-suppressor genes. Mutations in TP53, a tumor-suppressor gene, for example, are found in more than half of all cancer types as an early event, and they are a hallmark of precancerous lesions. 9 - 12 From that point on, the evolution of tumors may take decades, throughout which the mutational spectrum of tumor cells changes significantly. Mutational analysis of more than 19 000 exomes revealed a collection of genomic signatures, some associated with defects in the mechanism of DNA repair. These studies also revealed the importance of alterations in non-coding regions of DNA. Thus, for example, it has been observed that various pathways of cell proliferation and chromatin remodeling are altered by mutations in coding regions, while pathways, such as WNT and NOTCH, can be disrupted by coding and non-coding mutations. To the present date, 19 955 genes that codify for proteins and 25 511 genes for non-coding RNAs have been identified ( https://www.gencodegenes.org/human/stats.html ). Based on this genomic catalogue, the COSMIC (Catalogue Of Somatic Mutations In Cancer) repository, the most robust database to date, has registered 37 288 077 coding mutations, 19 396 fusions, 1 207 190 copy number variants, and 15 642 672 non-coding variants reported up to August 2020 (v92) ( https://cosmic-blog.sanger.ac.uk/cosmic-release-v92/ ).

The genomic approach has accelerated the development of new cancer drugs. Indeed, two of the most relevant initiatives in recent years are ATOM (Accelerating Therapeutics for Opportunities in Medicine), which groups industry, government and academia, with the objective of accelerating the identification of drugs, 13 and the Connectivity Map (CMAP), a collection of transcriptional data obtained from cell lines treated with drugs for the discovery of functional connections between genes, diseases, and drugs. The CMAP 1.0 covered 1300 small molecules and more than 6000 signatures; meanwhile, the CMAP 2.0 with L1000 assay profiled more than 1.3 million samples and approximately 400 000 signatures. 14

The genomic study of tumors has had 2 fundamental contributions. On the one hand, it has allowed the confirmation and expansion of the concept of intratumor heterogeneity 15 , 16 ; and on the other, it has given rise to new classification systems for cancer. Based on the molecular classification developed by expression profiles, together with mutational and epigenomic profiles, a variety of molecular signatures have been identified, leading to the production of various commercial multigene panels. In breast cancer, for example, different panels have been developed, such as Pam50/Prosigna , Blue Print , OncotypeDX , MammaPrint , Prosigna , Endopredict , Breast Cancer Index , Mammostrat, and IHC4 . 17

Currently, the genomic/molecular study of cancer is more closely integrated with clinical practice, from the classification of neoplasms, as in tumors of the nervous system, 18 to its use in prediction, as in breast cancer. 17 Improvement in molecular methods and techniques has allowed the use of smaller amounts of biological material, as well as paraffin-embedded samples for genomic studies, both of which provide a wealth of information. 19 In addition, non-invasive methods, such as liquid biopsies, represent a great opportunity not only for the diagnosis of cancer, but also for follow-up, especially for unresectable tumors. 20

Research for the production of genomic information on cancer is presently dominated by several consortia, which has allowed the generation of a great quantity of data. However, most of these consortia and studies are performed in countries with a high human development index (HDI), and countries with a low HDI are not well represented in these large genomic studies. This is why initiatives such as Human Heredity and Health in Africa (H3Africa) for genomic research in Africa are essential. 21 Generation of new information and technological developments, such as third-generation sequencing, will undoubtedly continue to move forward in a multidisciplinary and complex systems context. However, the existing disparities in access to genomic tools for diagnosis, prognosis, and treatment of cancer will continue to be a pressing challenge at regional and social levels.

Cancer Epigenetics

Epigenetics studies the molecular mechanisms that produce hereditable changes in gene expression, without causing alterations in the DNA sequence. Epigenetic events are of 3 types: methylation of DNA and RNA, histone modification (acetylation, methylation, and phosphorylation), and the expression of non-coding RNA. Epigenetic aberrations can drive carcinogenesis when they alter chromosome conformation and the access to transcriptional machinery and to various regulatory elements (promoters, enhancers, and anchors for interaction with chromatin, for example). These changes may activate oncogenesis and silence tumor-suppressor mechanisms when they modulate coding and non-coding sequences (such as micro-RNAs and long-RNAs). This can then lead to uncontrolled growth, as well as the invasion and metastasis of cancer cells.

While genetic mutations are stable and irreversible, epigenetic alterations are dynamic and reversible; that is, there are several epigenomes, determined by space and time, which cause heterogeneity of the “epigenetic status” of tumors during their development and make them susceptible to environmental stimuli or chemotherapeutic treatment. 22 Epigenomic variability creates differences between cells, and this creates the need to analyze cells at the individual level. In the past, epigenetic analyses measured “average states” of cell populations. These studies revealed general mechanisms, such as the role of epigenetic marks on active or repressed transcriptional states, and established maps of epigenetic composition in a variety of cell types in normal and cancerous tissue. However, these approaches are difficult to use to examine events occurring in heterogeneous cell populations or in uncommon cell types. This has led to the development of new techniques that permit marking of a sequence on the epigenome and improvement in the recovery yield of epigenetic material from individual cells. This has helped to determine changes in DNA, RNA, and histones, chromatin accessibility, and chromosome conformation in a variety of neoplasms. 23 , 24

In cancer, DNA hypomethylation occurs on a global scale, while hypermethylation occurs in specific genomic loci, associated with abnormal nucleosome positioning and chromatin modifications. This information has allowed epigenomic profiles to be established in different types of neoplasms. In turn, these profiles have served as the basis to identify new neoplasm subgroups. For example, in triple negative breast cancer (TNBC), 25 and in hepatocellular carcinoma, 26 DNA methylation profiles have helped to the identification of distinct subgroups with clinical relevance. Epigenetic approaches have also helped to the development of prognostic tests to assess the sensitivity of cancer cells to specific drugs. 27

Epigenetic traits could be used to characterize intratumoral heterogeneity and determine the relevance of such a heterogeneity in clonal evolution and sensitivity to drugs. However, it is clear that heterogeneity is not only determined by genetic and epigenetic diversity resulting from clonal evolution of tumor cells, but also by the various cell populations that form the tumor microenvironment (TME). 28 Consequently, the epigenome of cancer cells is continually remodeled throughout tumorigenesis, during resistance to the activity of drugs, and in metastasis. 29 This makes therapeutic action based on epigenomic profiles difficult, although significant advances in this area have been reported. 30

During carcinogenesis and tumor progression, epigenetic modifications are categorized by their mechanisms of regulation ( Figure 1A ) and the various levels of structural complexity ( Figure 1B ). In addition, the epigenome can be modified by environmental stimuli, stochastic events, and genetic variations that impact the phenotype ( Figure 1C ). 31 , 32 The molecules that take part in these mechanisms/events/variations are therapeutic targets of interest with potential impact on clinical practice. There are studies on a wide variety of epidrugs, either alone or in combination, which improve antitumor efficacy. 33 However, the problems with these drugs must not be underestimated. For a considerable number of epigenetic compounds still being under study, the main challenge is to translate in vitro efficacy of nanomolar (nM) concentrations into well-tolerated and efficient clinical use. 34 The mechanisms of action of epidrugs may not be sufficiently controlled and could lead to diversion of the therapeutic target. 35 It is known that certain epidrugs, such as valproic acid, produce unwanted epigenetic changes 36 ; thus the need for a well-established safety profile before these drugs can be used in clinical therapy. Finally, resistance to certain epidrugs is another relevant problem. 37 , 38

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Epigenetics of cancer. (A) Molecular mechanisms. (B) Structural hierarchy of epigenomics. (C) Factors affecting the epigenome. Modified from Refs. 31 and 32 .

As we learn about the epigenome of specific cell populations in cancer patients, a door opens to the evaluation of sensitivity tests and the search for new molecular markers for detection, prognosis, follow-up, and/or response to treatment at various levels of molecular regulation. Likewise, the horizon expands for therapeutic alternatives in oncology with the use of epidrugs, such as pharmacoepigenomic modulators for genes and key pathways, including methylation of promoters and regulation of micro-RNAs involved in chemoresponse and immune response in cancer. 39 There is no doubt that integrated approaches identifying stable pharmagenomic and epigenomic patterns and their relation with expression profiles and genetic functions will be more and more valuable in our fight against cancer.

Cancer Stem Cells

Tumors consist of different populations of neoplastic cells and a variety of elements that form part of the TME, including stromal cells and molecules of the extracellular matrix. 40 Such intratumoral heterogeneity becomes even more complex during clonal variation of transformed cells, as well as influence the elements of the TME have on these cells throughout specific times and places. 41 To explain the origin of cancer cell heterogeneity, 2 models have been put forward. The first proposes that mutations occur at random during development of the tumor in individual neoplastic cells, and this promotes the production of various tumor populations, which acquire specific growth and survival traits that lead them to evolve according to intratumor mechanisms of natural selection. 42 The second model proposes that each tumor begins as a single cell that possess 2 functional properties: it can self-renew and it can produce several types of terminal cells. As these 2 properties are characteristics of somatic stem cells, 43 the cells have been called cancer stem cells (CSCs). 44 According to this model, tumors must have a hierarchical organization, where self-renewing stem cells produce highly proliferating progenitor cells, unable to self-renew but with a high proliferation potential. The latter, in turn, give rise to terminal cells. 45 Current evidence indicates that both models may coexist in tumor progression. In agreement with this idea, new subclones could be produced as a result of a lack of genetic stability and mutational changes, in addition to the heterogeneity derived from the initial CSC and its descendants. Thus, in each tumor, a set of neoplastic cells with different genetic and epigenetic traits may be found, which would provide different phenotypic properties. 46

The CSC concept was originally presented in a model of acute myeloid leukemia. 47 The presence of CSCs was later proved in chronic myeloid leukemia, breast cancer, tumors of the central nervous system, lung cancer, colon cancer, liver cancer, prostate cancer, pancreatic cancer, melanoma, and cancer of the head and neck, amongst others. In all of these cases, detection of CSCs was based on separation of several cell populations according to expression of specific surface markers, such as CD133, CD44, CD24, CD117, and CD15. 48 It is noteworthy that in some solid tumors, and even in some hematopoietic ones, a combination of specific markers that allow the isolation of CSCs has not been found. Interestingly, in such tumors, a high percentage of cells with the capacity to start secondary tumors has been observed; thus, the terms Tumor Initiating Cells (TIC) or Leukemia Initiating Cells (LIC) have been adopted. 46

A relevant aspect of the biology of CSCs is that, just like normal stem cells, they can self-renew. Such self-renewal guarantees the maintenance or expansion of the tumor stem cell population. Another trait CSCs share with normal stem cells is their quiescence, first described in chronic myeloid leukemia. 49 The persistence of quiescent CSCs in solid tumors has been recently described in colorectal cancer, where quiescent clones can become dominant after therapy with oxaliplatin. 50 In non-hierarchical tumors, such as melanoma, the existence of slow-cycling cells that are resistant to antimitogenic agents has also been proved. 51 Such experimental evidence supports the idea that quiescent CSCs or TICs are responsible for both tumor resistance to antineoplastic drugs and clinical relapse after initial therapeutic success.

In addition to quiescence, CSCs use other mechanisms to resist the action of chemotherapeutic drugs. One of these is their increased numbers: upon diagnosis, a high number of CSCs are observed in most analyzed tumors, making treatment unable to destroy all of them. On the other hand, CSCs have a high number of molecular pumps that expulse drugs, as well as high numbers of antiapoptotic molecules. In addition, they have very efficient mechanisms to repair DNA damage. In general, these cells show changes in a variety of signaling pathways involved in proliferation, survival, differentiation, and self-renewal. It is worth highlighting that in recent years, many of these pathways have become potential therapeutic targets in the elimination of CSCs. 52 Another aspect that is highly relevant in understanding the biological behavior of CSCs is that they require a specific site for their development within the tissue where they are found that can provide whatever is needed for their survival and growth. These sites, known as niches, are made of various cells, both tumor and non-tumor, as well as a variety of non-cellular elements (extracellular matrix [ECM], soluble cytokines, ion concentration gradients, etc.), capable of regulating the physiology of CSCs in order to promote their expansion, the invasion of adjacent tissues, and metastasis. 53

It is important to consider that although a large number of surface markers have been identified that allow us to enrich and prospectively follow tumor stem cell populations, to this day there is no combination of markers that allows us to find these populations in all tumors, and it is yet unclear if all tumors present them. In this regard, it is necessary to develop new purification strategies based on the gene expression profiles of these cells, so that tumor heterogeneity is taken into account, as it is evident that a tumor can include multiple clones of CSCs that, in spite of being functional, are genetically different, and that these clones can vary throughout space (occupying different microenvironments and niches) and time (during the progression of a range of tumor stages). Such strategies, in addition to new in vitro and in vivo assays, will allow the development of new and improved CSC elimination strategies. This will certainly have an impact on the development of more efficient therapeutic alternatives.

Invasion and Metastasis

Nearly 90% of the mortality associated with cancer is related to metastasis. 54 This consists of a cascade of events ( Figure 2 ) that begins with the local invasion of a tumor into surrounding tissues, followed by intravasation of tumor cells into the blood stream or lymphatic circulation. Extravasation of neoplastic cells in areas distant from the primary tumor then leads to the formation of one or more micrometastatic lesions which subsequently proliferate to form clinically detectable lesions. 4 The cells that are able to produce metastasis must acquire migratory characteristics, which occur by a process known as epithelial–mesenchymal transition (EMT), that is, the partial loss of epithelial characteristics and the acquirement of mesenchymal traits. 55

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Invasion and metastasis cascade. Invasion and metastasis can occur early or late during tumor progression. In either case, invasion to adjacent tissues is driven by stem-like cells (cancer stem cells) that acquire the epithelial–mesenchymal transition (EMT) (1). Once they reach sites adjacent to blood vessels, tumor cells (individually or in clusters) enter the blood (2). Tumor cells in circulation can adhere to endothelium and extravasation takes place (3). Other mechanisms alternative to extravasation can exist, such as angiopelosis, in which clusters of tumor cells are internalized by the endothelium. Furthermore, at certain sites, tumor cells can obstruct microvasculature and initiate a metastatic lesion right there. Sometimes, a tumor cells that has just exit circulation goes into an MET in order to become quiescent (4). Inflammatory signals can activate quiescent metastatic cells that will proliferate and generate a clinically detectable lesion (5).

Although several of the factors involved in this process are currently known, many issues are still unsolved. For instance, it has not yet been possible to monitor in vivo the specific moment when it occurs 54 ; the microenvironmental factors of the primary tumor that promote such a transition are not known with precision; and the exact moment during tumor evolution in which one cell or a cluster of cells begin to migrate to distant areas, is also unknown. The wide range of possibilities offered by intra- and inter-tumoral heterogeneity 56 stands in the way of suggesting a generalized strategy that could resolve this complication.

It was previously believed that metastasis was only produced in late stages of tumor progression; however, recent studies indicate that EMT and metastasis can occur during the early course of the disease. In pancreatic cancer, for example, cells going through EMT are able to colonize and form metastatic lesions in the liver in the first stages of the disease. 52 , 57 Metastatic cell clusters circulating in peripheral blood (PB) are prone to generate a metastatic site, compared to individual tumor cells. 58 , 59 In this regard, novel strategies, such as the use of micro-RNAs, are being assessed in order to diminish induction of EMT. 60 It must be mentioned, however, that the metastatic process seems to be even more complex, with alternative pathways that do not involve EMT. 61 , 62

A crucial stage in the process of metastasis is the intravasation of tumor cells (alone or in clusters) towards the blood stream and/or lymphatic circulation. 63 These mechanisms are also under intensive research because blocking them could allow the control of spreading of the primary tumor. In PB or lymphatic circulation, tumor cells travel to distant parts for the potential formation of a metastatic lesion. During their journey, these cells must stand the pressure of blood flow and escape interaction with natural killer (NK) cells . 64 To avoid them, tumor cells often cover themselves with thrombocytes and also produce factors such as VEGF, angiopoietin-2, angiopoietin-4, and CCL2 that are involved in the induction of vascular permeability. 54 , 65 Neutrophils also contribute to lung metastasis in the bloodstream by secreting IL-1β and metalloproteases to facilitate extravasation of tumor cells. 64

The next step in the process of metastasis is extravasation, for which tumor cells, alone or in clusters, can use various mechanisms, including a recently described process known as angiopellosis that involves restructuring the endothelial barrier to internalize one or several cells into a tissue. 66 The study of leukocyte extravasation has contributed to a more detailed knowledge of this process, in such a way that some of the proposed strategies to avoid extravasation include the use of integrin inhibitors, molecules that are vital for rolling, adhesion, and extravasation of tumor cells. 67 , 68 Another strategy that has therapeutic potential is the use of antibodies that strengthen vascular integrity to obstruct transendothelial migration of tumor cells and aid in their destruction in PB. 69

Following extravasation, tumor cells can return to an epithelial phenotype, a process known as mesenchymal–epithelial transition and may remain inactive for several years. They do this by competing for specialized niches, like those in the bone marrow, brain, and intestinal mucosa, which provide signals through the Notch and Wnt pathways. 70 Through the action of the Wnt pathway, tumor cells enter a slow state of the cell cycle and induce the expression of molecules that inhibit the cytotoxic function of NK cells. 71 The extravasated tumor cell that is in a quiescent state must comply with 2 traits typical of stem cells: they must have the capacity to self-renew and to generate all of the cells that form the secondary tumor.

There are still several questions regarding the metastatic process. One of the persisting debates at present is if EMT is essential for metastasis or if it plays a more important role in chemoresistance. 61 , 62 It is equally important to know if there is a pattern in each tumor for the production of cells with the capacity to carry out EMT. In order to control metastasis, it is fundamental to know what triggers acquisition of the migratory phenotype and the intrinsic factors determining this transition. Furthermore, it is essential to know if mutations associated with the primary tumor or the variety of epigenetic changes are involved in this process. 55 It is clear that metastatic cells have affinity for certain tissues, depending on the nature of the primary tumor (seed and soil hypothesis). This may be caused by factors such as the location and the direction of the bloodstream or lymphatic fluid, but also by conditioning of premetastatic niches at a distance (due to the large number of soluble factors secreted by the tumor and the recruitment of cells of the immune system to those sites). 72 We have yet to identify and characterize all of the elements that participate in this process. Deciphering them will be of upmost importance from a therapeutic point of view.

Epidemiology of Cancer

Cancer is the second cause of death worldwide; today one of every 6 deaths is due to a type of cancer. According to the International Agency for Research on Cancer (IARC), in 2020 there were approximately 19.3 million new cases of cancer, and 10 million deaths by this disease, 6 while 23.8 million cases and 13.0 million deaths are projected to occur by 2030. 73 In this regard, it is clear the increasing role that environmental factors—including environmental pollutants and processed food—play as cancer inducers and promoters. 74 The types of cancer that produce the greatest numbers of cases and deaths worldwide are indicated in Table 1 . 6

Total Numbers of Cancer Cases and Deaths Worldwide in 2020 by Cancer Type (According to the Global Cancer Observatory, IARC).

	Cases
Both sexes	Women	Men
Breast (2.26 million)	Breast (2.26 million)	Lung (1.43 million)
Lung (2.20 million)	Colorectal (865 000)	Prostate (1.41 million)
Colorectal (1.93 million)	Lung (770 000)	Colorectal (1.06 million)
Prostate (1.41 million)	Cervical (604 000)	Stomach (719 000)
Stomach (1.08 million)	Thyroid (448 000)	Liver (632 000)

	Deaths
Both sexes	Women	Men
Lung (1.79 million)	Breast (684 000)	Lung (1.18 million)
Colorectal (935 000)	Lung (607 000)	Liver (577 000)
Liver (830 000)	Colorectal (419 000)	Colorectal (515 000)
Stomach (768 000)	Cervical (341 000)	Stomach (502 000)
Breast (684 000)	Stomach (266 000)	Prostate (375 000)

Data presented on this table were obtained from Ref. 6.

As shown in Figure 3 , lung, breast, prostate, and colorectal cancer are the most common throughout the world, and they are mostly concentrated in countries of high to very high human development index (HDI). Although breast, prostate, and colorectal cancer have a high incidence, the number of deaths they cause is proportionally low, mostly reflecting the great progress made in their control. However, these data also reveal the types of cancer that require further effort in prevention, precise early detection avoiding overdiagnosis, and efficient treatment. This is the case of liver, lung, esophageal, and pancreatic cancer, where the difference between the number of cases and deaths is smaller ( Figure 3B ). Social and economic transition in several countries has had an impact on reducing the incidence of neoplasms associated with infection and simultaneously produced an increase in the types related to reproductive, dietary, and hormonal factors. 75

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Incidence and mortality for some types of cancer in the world. (A) Estimated number of cases and deaths in 2020 for the most frequent cancer types worldwide. (B) Incidence and mortality rates, normalized according to age, for the most frequent cancer types in countries with very high/& high (VH&H; blue) and/low and middle (L&M; red) Human Development Index (HDI). Data include both genders and all ages. Data according to https://gco.iarc.fr/today , as of June 10, 2021.

In the past 3 decades, cancer mortality rates have fallen in high HDI countries, with the exception of pancreatic cancer, and lung cancer in women. Nevertheless, changes in the incidence of cancer do not show the same consistency, possibly due to variables such as the possibility of early detection, exposure to risk factors, or genetic predisposition. 76 , 77 Countries such as Australia, Canada, Denmark, Ireland, New Zealand, Norway, and the United Kingdom have reported a reduction in incidence and mortality in cancer of the stomach, colon, lung, and ovary, as well as an increase in survival. 78 Changes in modifiable risk factors, such as the use of tobacco, have played an important role in prevention. In this respect, it has been estimated that decline in tobacco use can explain between 35% and 45% of the reduction in cancer mortality rates, 79 while the fall in incidence and mortality due to stomach cancer can be attributed partly to the control of Helicobacter pylori infection. 80 Another key factor in the fall of mortality rates in developed countries has been an increase in early detection as a result of screening programs, as in breast and prostate cancer, which have had their mortality rates decreased dramatically in spite of an increase in their incidence. 76

Another important improvement observed in recent decades is the increase in survival rates, particularly in high HDI countries. In the USA, for example, survival rates for patients with prostate cancer at 5 years after initial diagnosis was 28% during 1947–1951; 69% during 1975–1977, and 100% during 2003–2009. Something similar occurred with breast cancer, with a 5-year survival rate of 54% in 1947–1951, 75% in 1975–1977, and 90% in 2003–2009. 81 In the CONCORD 3 version, age-standardize 5-year survival for patients with breast cancer in the USA during 2010–2014 was 90%, and 97% for prostate cancer patients. 82 Importantly, even among high HDI countries, significant differences have been identified in survival rates, being stage of disease at diagnosis, time for access to effective treatment, and comorbidities, the main factors influencing survival in these nations. 78 Unfortunately, survival rates in low HDI countries are significantly lower due to several factors, including lack of information, deficient screening and early detection programs, limited access to treatment, and suboptimal cancer registration. 82 It should be noted that in countries with low to middle HDI, neoplasms with the greatest incidence are those affecting women (breast and cervical cancer), which reflects not only a problem with access to health services, but also a serious inequality issue that involves social, cultural, and even religious obstacles. 83

Up to 42% of incident cases and 47% of deaths by cancer in the USA are due to potentially modifiable risk factors such as use of tobacco, physical activity, diet, and infection. 84 It has been calculated that 2.4 million deaths by cancer, mostly of the lung, can be attributed to tobacco. 73 In 2020, the incidence rate of lung cancer in Western Africa was 2.2, whereas in Polynesia and Eastern Asia was 37.3 and 34.4, respectively. 6 In contrast, the global burden of cancer associated with infection was 15.4%, but in Sub-Saharan Africa it was 30%. 85 Likewise, the incidence of cervical cancer in Eastern Africa was 40.1, in contrast with the USA and Canada that have a rate of 6.2. This makes it clear that one of the challenges we face is the reduction of the risk factors that are potentially modifiable and associated with specific types of cancer.

Improvement of survival rates and its disparities worldwide are also important challenges. Five-year survival for breast cancer—diagnosed during 2010-2014— in the USA, for example, was 90%, whereas in countries like South Africa it was 40%. 82 Childhood leukemia in the USA and several European countries shows a 5-year survival of 90%, while in Latin-American countries it is 50–76%. 86 Interestingly, there are neoplasms, such as pancreatic cancer, for which there has been no significant increase in survival, which remains low (5–15%) both in developed and developing countries. 82

Although data reported on global incidence and mortality gives a general overview on the epidemiology of cancer, it is important to note that there are great differences in coverage of cancer registries worldwide. To date, only 1 out of every 3 countries reports high quality data on the incidence of cancer. 87 For the past 50 years, the IARC has supported population-based cancer registries; however, more than one-third of the countries belonging to the WHO, mainly countries of low and middle income (LMIC), have no data on more than half of the 18 indicators of sustainable development goals. 88 High quality cancer registries only cover 4% of the population in Africa, 8% in Asia, and 7% in Latin America, contrasting with 83% in the USA and Canada, and 33% in Europe. 89 In response to this situation, the Global Initiative for Cancer Registry Development was created in 2012 to generate improved infrastructure to permit greater coverage and better quality registries, especially in countries with low and middle HDI. 88 It is expected that initiatives of this sort in the coming years will allow more and better information to guide strategies for the control of cancer worldwide, especially in developing regions. This will enable survival to be measured over longer periods of time (10, 15, or 20 years), as an effective measure in the control of cancer. The WHO has established as a target for 2025 to reduce deaths by cancer and other non-transmissible diseases by 25% in the population between the ages of 30–69; such an effort requires not only effective prevention measures to reduce incidence, but also more efficient health systems to diminish mortality and increase survival. At the moment, it is an even greater challenge because of the effects of the COVID-19 pandemic which has negatively impacted cancer prevention and health services. 90

Oncologic Treatments

A general perspective.

At the beginning of the 20th century, cancer treatment, specifically treatment of solid tumors, was based fundamentally on surgical resection of tumors, which together with other methods for local control, such as cauterization, had been used since ancient times. 91 At that time, there was an ongoing burst of clinical observations along with interventions sustained on fundamental knowledge about physics, chemistry, and biology. In the final years of the 19 th century and the first half of the 20th, these technological developments gave rise to radiotherapy, hormone therapy, and chemotherapy. 92 - 94 Simultaneously, immunotherapy was also developed, although usually on a smaller scale, in light of the overwhelming progress of chemotherapy and radiotherapy. 95

Thus began the development and expansion of disciplines based on these approaches (surgery, radiotherapy, chemotherapy, hormone therapy, and immunotherapy), with their application evolving ever more rapidly up to their current uses. Today, there is a wide range of therapeutic tools for the care of cancer patients. These include elements that emerged empirically, arising from observations of their effects in various medical fields, as well as drugs that were designed to block processes and pathways that form part of the physiopathology of one or more neoplasms according to knowledge of specific molecular alterations. A classic example of the first sort of tool is mustard gas, originally used as a weapon in war, 96 but when applied for medical purposes, marked the beginning of the use of chemicals in the treatment of malignant neoplasms, that is, chemotherapy. 94 A clear example of the second case is imatinib, designed specifically to selectively inhibit a molecular alteration in chronic myeloid leukemia: the Bcr-Abl oncoprotein. 97

It is on this foundation that today the 5 areas mentioned previously coexist and complement one another. The general framework that motivates this amalgam and guides its development is precision medicine, founded on the interaction of basic and clinical science. In the forecasts for development in each of these fields, surgery is expected to continue to be the fundamental approach for primary tumors in the foreseeable future, as well as when neoplastic disease in the patient is limited, or can be limited by applying systemic or regional elements, before and/or after surgical resection, and it can be reasonably anticipated for the patient to have a significant period free from disease or even to be cured. With regards to technology, intensive exploration of robotic surgery is contemplated. 98

The technological possibilities for radiotherapy have progressed in such a way that it is now possible to radiate neoplastic tissue with an extraordinary level of precision, and therefore avoid damage to healthy tissue. 99 This allows administration of large doses of ionizing radiation in one or a few fractions, what is known as “radiosurgery.” The greatest challenges to the efficacy of this approach are related to radio-resistance in certain neoplasms. Most efforts regarding research in this field are concentrated on understanding the underlying biological mechanisms of the phenomenon and their potential control through radiosensitizers. 100

“Traditional” chemotherapy, based on the use of compounds obtained from plants and other natural products, acting in a non-specific manner on both neoplastic and healthy tissues with a high proliferation rate, continues to prevail. 101 The family of chemotherapeutic drugs currently includes alkylating agents, antimetabolites, anti-topoisomerase agents, and anti-microtubules. Within the pharmacologic perspective, the objective is to attain a high concentration or activity of such molecules in specific tissues while avoiding their accumulation in others, in order to achieve an increase in effectiveness and a reduction in toxicity. This has been possible with the use of viral vectors, for example, that are able to limit their replication in neoplastic tissues, and activate prodrugs of normally nonspecific agents, like cyclophosphamide, exclusively in those specific areas. 102 More broadly, chemotherapy also includes a subgroup of substances, known as molecular targeted therapy, that affect processes in a more direct and specific manner, which will be mentioned later.

There is no doubt that immunotherapy—to be explored next—is one of the therapeutic fields where development has been greatest in recent decades and one that has produced enormous expectation in cancer treatment. 103 Likewise, cell therapy, based on the use of immune cells or stem cells, has come to complement the oncologic therapeutic arsenal. 43 Each and every one of the therapeutic fields that have arisen in oncology to this day continue to prevail and evolve. Interestingly, the foreseeable future for the development of cancer treatment contemplates these approaches in a joint and complementary manner, within the general framework of precision medicine, 104 and sustained by knowledge of the biological mechanisms involved in the appearance and progression of neoplasms. 105 , 106

Immunotherapy

Stimulating the immune system to treat cancer patients has been a historical objective in the field of oncology. Since the early work of William Coley 107 to the achievements reached at the end of the 20 th century, scientific findings and technological developments paved the way to searching for new immunotherapeutic strategies. Recombinant DNA technology allowed the synthesis of cytokines, such as interferon-alpha (IFN-α) and interleukin 2 (IL-2), which were authorized by the US Food and Drug Administration (FDA) for the treatment of hairy cell leukemia in 1986, 108 as well as kidney cancer and metastatic melanoma in 1992 and 1998, respectively. 109

The first therapeutic vaccine against cancer, based on the use of autologous dendritic cells (DCs), was approved by the FDA against prostate cancer in 2010. However, progress in the field of immunotherapy against cancer was stalled in the first decade of the present century, mostly due to failure of several vaccines in clinical trials. In many cases, application of these vaccines was detained by the complexity and cost involved in their production. Nevertheless, with the coming of the concept of immune checkpoint control, and the demonstration of the relevance of molecules such as cytotoxic T-lymphocyte antigen 4 (CTLA-4), and programmed cell death molecule-1 (PD-1), immunotherapy against cancer recovered its global relevance. In 2011, the monoclonal antibody (mAb) ipilimumab, specific to the CTLA-4 molecule, was the first checkpoint inhibitor (CPI) approved for the treatment of advanced melanoma. 110 Later, inhibitory mAbs for PD-1, or for the PD-1 ligand (PD-L1), 111 as well as the production of T cells with chimeric receptors for antigen recognition (CAR-T), 112 which have been approved to treat various types of cancer, including melanoma, non-small cell lung cancer (NSCLC), head and neck cancer, bladder cancer, renal cell carcinoma (RCC), and hepatocellular carcinoma, among others, have changed the paradigm of cancer treatment.

In spite of the current use of anti-CTLA-4 and anti-PD-L1 mAbs, only a subgroup of patients has responded favorably to these CPIs, and the number of patients achieving clinical benefit is still small. It has been estimated that more than 70% of patients with solid tumors do not respond to CPI immunotherapy because either they show primary resistance, or after responding favorably, develop resistance to treatment. 113 In this regard, it is important to mention that in recent years very important steps have been taken to identify the intrinsic and extrinsic mechanisms that mediate resistance to CPI immunotherapy. 114 Intrinsic mechanisms include changes in the antitumor immune response pathways, such as faulty processing and presentation of antigens by APCs, activation of T cells for tumor cell destruction, and changes in tumor cells that lead to an immunosuppressive TME. Extrinsic factors include the presence of immunosuppressive cells in the local TME, such as regulatory T cells, myeloid-derived suppressor cells (MDSC), mesenchymal stem/stromal cells (MSCs), and type 2 macrophages (M2), in addition to immunosuppressive cytokines.

On the other hand, classification of solid tumors as “hot,” “cold,” or “excluded,” depending on T cell infiltrates and the contact of such infiltrates with tumor cells, as well as those that present high tumor mutation burden (TMB), have redirected immunotherapy towards 3 main strategies 115 ( Table 2 ): (1) Making T-cell antitumor response more effective, using checkpoint inhibitors complementary to anti-CTLA-4 and anti-PD-L1, such as LAG3, Tim-3, and TIGT, as well as using CAR-T cells against tumor antigens. (2) Activating tumor-associated myeloid cells including monocytes, granulocytes, macrophages, and DC lineages, found at several frequencies within human solid tumors. (3) Regulating the biochemical pathways in TME that produce high concentrations of immunosuppressive molecules, such as kynurenine, a product of tryptophan metabolism, through the activity of indoleamine 2,3 dioxygenase; or adenosine, a product of ATP hydrolysis by the activity of the enzyme 5’nucleotidase (CD73). 116

Current Strategies to Stimulate the Immune Response for Antitumor Immunotherapy.

Strategies	T cells	Myeloid cells	TME
Lymph node	Anti-CTLA4	TNF-α
To improve tumor antigen presentation by APCs	Anti-CD137	IFN-α
To optimize effector T-cell activation	Anti-OX40	IL-1
	Anti-CD27/CD70	GM-CSF
	HVEM	CD40L/CD40
	GITR	CDN
	L-2	ATP
	IL-12	HMGB1
		TLR
		STING
		RIG-1/MDA-5
Blood vessel	CX3CL1
To improve T-cell traffic to tumors	CXCL9
To favor T-cell infiltration into tumors	CXCL10
Transference of T cells bearing antigen-specific receptor	CCL5
	LFA1/ICAM1
	Selectins
	CAR-T cell
	TCR-T cell
Tumor	Anti-PD-L1	Anti-CSF1/CSF1R	Anti-VEGF
To improve tumor antigen uptake by APCs	Anti-CTLA-4	Anti-CCR2	Inhibitors of IDO anti-CD73
To improve recognition and killing of tumor cells by T cells	Anti-LAG-3	PI3Kγ	ARs antagonists
	Anti-TIM-3
	Anti-TIGIT
	TNFR-agonists
	IL-2
	IL-10

Abbreviations: TME, tumor microenvironment; IL, interleukin; TNF, Tumor Necrosis Factor; TNFR, TNF-receptor; CD137, receptor–co-stimulator of the TNFR family; OX40, member number 4 of the TNFR superfamily; CD27/CD70, member of the TNFR superfamily; CD40/CD40L, antigen-presenting cells (APC) co-stimulator and its ligand; GM-CSF, granulocyte-macrophage colony-stimulating factor; IFN, interferon; STING, IFN genes-stimulator; RIG-I, retinoic acid inducible gene-I; MDA5, melanoma differentiation-associated protein 5; CDN, cyclic dinucleotide; ATP, adenosine triphosphate; HMGB1, high mobility group B1 protein; TLR, Toll-like receptor; HVEM, Herpes virus entry mediator; GITR, glucocorticoid-induced TNFR family-related gene; CTLA4, cytotoxic T lymphocyte antigen 4; PD-L1, programmed death ligand-1; TIGIT, T-cell immunoreceptor with immunoglobulin and tyrosine-based inhibition motives; CSF1/CSF1R, colony-stimulating factor-1 and its receptor; CCR2, Type 2 chemokine receptor; PI3Kγ, Phosphoinositide 3-Kinase γ; CXCL/CCL, chemokine ligands; LFA1, lymphocyte function-associated antigen 1; ICAM1, intercellular adhesion molecule 1; VEGF, vascular endothelial growth factor; IDO, indolamine 2,3-dioxigenase; TGF, transforming growth factor; LAG-3, lymphocyte-activation gene 3 protein; TIM-3, T-cell immunoglobulin and mucin-domain containing-3; CD73, 5´nucleotidase; ARs, adenosine receptors; Selectins, cell adhesion molecules; CAR-T, chimeric antigen receptor T cell; TCR-T, T-cell receptor engineered T cell.

Apart from the problems associated with its efficacy (only a small group of patients respond to it), immunotherapy faces several challenges related to its safety. In other words, immunotherapy can induce adverse events in patients, such as autoimmunity, where healthy tissues are attacked, or cytokine release syndrome and vascular leak syndrome, as observed with the use of IL-2, both of which lead to serious hypotension, fever, renal failure, and other adverse events that are potentially lethal. The main challenges to be faced by immunotherapy in the future will require the combined efforts of basic and clinical scientists, with the objective of accelerating the understanding of the complex interactions between cancer and the immune system, and improve treatment options for patients. Better comprehension of immune phenotypes in tumors, beyond the state of PD-L1 and TME, will be relevant to increase immunotherapy efficacy. In this context, the identification of precise tumor antigenicity biomarkers by means of new technologies, such as complete genome sequencing, single cell sequencing, and epigenetic analysis to identify sites or subclones typical in drug resistance, as well as activation, traffic and infiltration of effector cells of the immune response, and regulation of TME mechanisms, may help define patient populations that are good candidates for specific therapies and therapeutic combinations. 117 , 118 Likewise, the use of agents that can induce specific activation and modulation of the response of T cells in tumor tissue, will help improve efficacy and safety profiles that can lead to better clinical results.

Molecular Targeted Therapy

For over 30 years, and based on the progress in our knowledge of tumor biology and its mechanisms, there has been a search for therapeutic alternatives that would allow spread and growth of tumors to be slowed down by blocking specific molecules. This approach is known as molecular targeted therapy. 119 Among the elements generally used as molecular targets there are transcription factors, cytokines, membrane receptors, molecules involved in a variety of signaling pathways, apoptosis modulators, promoters of angiogenesis, and cell cycle regulators. 120

Imatinib, a tyrosine kinase inhibitor for the treatment of chronic myeloid leukemia, became the first targeted therapy in the final years of the 1990s. 97 From then on, new drugs have been developed by design, and today more than 60 targeted therapies have been approved by the FDA for the treatment of a variety of cancers ( Table 3 ). 121 This has had a significant impact on progression-free survival and global survival in neoplasms such as non-small cell lung cancer, breast cancer, renal cancer, and melanoma.

FDA Approved Molecular Targeted Therapies for the Treatment of Solid Tumors.

Drug	Therapeutic target	Indications	Biomarkers
Abemaciclib	CDK4/6 inhibitor	Breast cancer	ER+/PR+
Abiraterone	Anti-androgen	Prostate cancer	AR+
Afatinib	TKI anti-ErbB, EGFR (ErbB1), HER2 (ErbB2), ErbB3, ErbB4	NSCLC	EGFR mutated
			Deletion of exon 19
			Substitution in exon 21 (L858R)
Aflibercept	Anti-VEGF fusion protein	Colorectal cancer
Alectinib	Anti-ALK TKI	NSCLC	ALK+
Alpelisib	PI3K inhibitor	Breast cancer	PI3K mutated
Apalutamide	Anti-androgen	Prostate cancer	AR+
Atezolizumab	Anti-PD-L1 mAb	Breast cancer	PD-L1
		Hepatocellular carcinoma
		NSCLC
		Bladder cancer
Avapritinib	Kinase inhibitor	GIST	PDGFRA mutated in exon 18 (D842V)
Avelumab	Anti-PD-L1 mAb	Renal cancer	PD-L1
		Bladder cancer
		Neuroendocrine tumors
Axitinib	Anti-VEGF TKI	Renal cancer
Bevacizumab	Anti-VEGF mAb	CNS tumors
		Ovarian cancer
		Cervical cancer
		Colorectal cancer
		Hepatocellular carcinoma
		NSCLC
		Renal cancer
Brigatinib	Anti-ALK TKI	NSCLC	ALK+
Cabozantinib	TKR inhibitor: anti-MET, anti-VEGF, anti-RET, ROS1, MER, KIT	Renal cancer
		Hepatocellular carcinoma
		Thyroid cancer
Ceritinib	Anti-ALK TKI	NSCLC	ALK+
Cetuximab	Anti-EGFR mAb	Colorectal cancer	KRAS
		Head and Neck cancer	EGFR+
Crizotinib	Anti-ALK TKI	NSCLC	ALK+, ROS1+
Dabrafenib	BRAF inhibitor	NSCLC	BRAF-V600E, V600K
		Thyroid cancer
		Melanoma
Dacomitinib	Anti-EGFR TKI	NSCLC	EGFR+
Darolutamide	Anti-androgen	Prostate cancer	AR+
Durvalumab	Anti-PD-L1 mAb	NSCLC	PD-L1
		Bladder cancer
Encorafenib	BRAF inhibitor	Colorectal cancer	BRAF-V600E
		Melanoma
Entrectinib	Anti-ROS1 TKI	NSCLC	ROS1+
Enzalutamide	Anti-androgen	Prostate cancer	AR+
Erdafitinib	Anti-FGFR-1 TKI	Bladder cancer
Erlotinib	Anti-EGFR TKI	NSCLC	EGFR mutated
		Pancreatic caner	Deletion of exon 19
			Substitution in exon 21 (L858R)
Everolimus	mTOR inhibitor	CNS tumors
		Pancreatic cancer
		Breast cancer
		Renal cancer
Fulvestrant	ER antagonist	Breast cancer	ER+/PR+
Gefitinib	Anti-EGFR TKI	NSCLC	EGFR mutated
			Deletion of exon 19
			Substitution in exon 21 (L858R)
Imatinib	Anti-KIT TKI	GIST	KIT+
		Dermatofibroma protuberans
Ipilimumab	Anti-CTLA-4 mAb	Colorectal cancer
		Hepatocellular carcinoma
		NSCLC
		Melanoma
		Renal cancer
Lapatinib	TKI: anti-EGFR, anti-HER2	Breast cancer	ERBB2 over-expression or amplification
Lenvatinib	TKR: anti-VEGF, VEGFR1 (FLT1), VEGFR2 (KDR) y VEGFR3 (FLT4); (FGF) FGFR1, 2, 3 y 4, PDGF, PDGFRA, KIT, RET	Endometrial cancer
		Hepatocellular carcinoma
		Renal cancer
		Thyroid cancer
Lorlatinib	TKI: anti-ALK, anti-ROS2	NSCLC	ALK+, ROS1+
Necitumumab	Anti-EGFR mAb	NSCLC	EGFR+
Neratinib	Anti-HER2 TKI
Anti-EGFR	Breast cancer	ERBB2 over-expression or amplification
Niraparib	PARP inhibitor	Ovarian cancer	BRCA1/2 mutations
		Fallopian tube cancer	Homologous recombination deficiency
		Peritoneal cancer
Nivolumab	Anti-PD-1 mAb	Colorectal cancer	PD-1
		Esophageal cancer
		Hepatocellular carcinoma
		NSCLC
		Melanoma
		Renal cancer
		Bladder cancer
		Head and Neck cancer
Olparib	PARP inhibitor	Breast cancer	BRCA1/2 mutations
		Ovarian cancer
		Pancreatic cancer
		Prostate cancer
Osimertinib	Anti-EGFR TKI	NSCLC	EGFR-T790M
Palbociclib	CDK4/6 inhibitor	Breast cancer	RE+/RP+
Pantitumumab	Anti-EGFR mAb	Colorectal cancer	KRAS
			EGFR+
Pazopanib	TKI: Anti-VEGF, anti-PDGFR, anti-FGFR, anti-cKIT	Renal cancer
		Soft tissues sarcoma
Pembrolizumab	PD-1 inhibitor	Cervical cancer	PD-1
		Endometrial cancer
		Esophageal cancer
		Gastric cancer
		Hepatocellular carcinoma
		NSCLC
		Bladder cancer
		Head and Neck cancer
Pertuzumab	Anti-HER2 mAb	Breast cancer	ERBB2 over-expression or amplification
Ramucirumab	Anti-VEGF mAb	Colorectal cancer
		Esophageal cancer
		Gastric cancer
		Hepatocellular carcinoma
		NSCLC
Regorafenib	Anti-cKIT TKI	Colorectal cancer	KIT+
		Hepatocellular carcinoma
		GIST
Ribociclib	CDK4/6 inhibitor	Breast cancer	ER+/PR+
Ripretinib	TKI: anti-KIT, anti-PDGFR	GIST	KIT+
Rucaparib	PARP inhibitor	Prostate cancer	BRCA1/2 mutations
		Ovarian cancer
		Fallopian tube cancer
		Peritoneal cancer
Sacituzumab-Govitecan	Conjugated Ab anti-trop-2	Breast cancer	RE- RP- HER2-
Selpercatinib	Kinase inhibitor	NSCLC	RET+
		Thyroid cancer
Sorafenib	Multi-kinase inhibitor: anti-PDGFR, VEGFR, cKIT, TKR	Renal cancer
		Hepatocellular carcinoma
		Thyroid cancer
Sunitinib	Multi-kinase inhibitor: anti-PDGFR, VEGFR, cKIT, TKR	Renal cancer
		Pancreatic cancer
		GIST
Tamoxifeno	SERM	Breast cancer	ER+/PR+
Talazoparib	PARP inhibitor	Breast cancer	BRCA1/2 mutations
Temsirolimus	mTOR inhibitor	Renal cancer
Trametinib	BRAF inhibitor	NSCLC	BRAF-V600E, V600K
		Thyroid cancer
		Melanoma
Trastuzumab	Anti-HER2 mAb	Gastric cancer	ERBB2 over-expression of amplification
		Gastro-esophageal junction cancer
		Breast cancer
Trastuzumab-Deruxtecan	Anti-HER2 conjugated Ab	Breast cancer	ERBB2 over-expression of amplification
Trastuzumab-Emtansine	Anti-HER2 conjugated Ab	Breast cancer	ERBB2 over-expression of amplification
Tucatinib	Anti-HER2 TKI	Breast cancer	ERBB2 over-expression of amplification
Vandetanib	TKI: anti-VEGF, anti-EGFR	Thyroid cancer	EGFR+
Vemurafenib	BRAF inhibitor	Melanoma	BRAF-V600E

Abbreviations: mAb, monoclonal antibody; ALK, anaplastic lymphoma kinase; CDK, cyclin-dependent kinase; CTLA-4, cytotoxic lymphocyte antigen-4; EGFR, epidermal growth factor receptor; FGFR, fibroblast growth factor receptor; GIST, gastrointestinal stroma tumor; mTOR, target of rapamycine in mammal cells; NSCLC, non-small cell lung carcinoma; PARP, poli (ADP-ribose) polimerase; PD-1, programmed death protein-1; PDGFR, platelet-derived growth factor receptor; PD-L1, programmed death ligand-1; ER, estrogen receptor; PR, progesterone receptor; TKR, tyrosine kinase receptors; SERM, selective estrogen receptor modulator; TKI, tyrosine kinase inhibitor; VEGFR, vascular endothelial growth factor receptor. Modified from Ref. [ 127 ].

Most drugs classified as targeted therapies form part of 2 large groups: small molecules and mAbs. The former are defined as compounds of low molecular weight (<900 Daltons) that act upon entering the cell. 120 Targets of these compounds are cell cycle regulatory proteins, proapoptotic proteins, or DNA repair proteins. These drugs are indicated based on histological diagnosis, as well as molecular tests. In this group there are multi-kinase inhibitors (RTKs) and tyrosine kinase inhibitors (TKIs), like sunitinib, sorafenib, and imatinib; cyclin-dependent kinase (CDK) inhibitors, such as palbociclib, ribociclib and abemaciclib; poli (ADP-ribose) polimerase inhibitors (PARPs), like olaparib and talazoparib; and selective small-molecule inhibitors, like ALK and ROS1. 122

As for mAbs, they are protein molecules that act on membrane receptors or extracellular proteins by interrupting the interaction between ligands and receptors, in such a way that they reduce cell replication and induce cytostasis. Among the most widely used mAbs in oncology we have: trastuzumab, a drug directed against the receptor for human epidermal growth factor-2 (HER2), which is overexpressed in a subgroup of patients with breast and gastric cancer; and bevacizumab, that blocks vascular endothelial growth factor and is used in patients with colorectal cancer, cervical cancer, and ovarian cancer. Other mAbs approved by the FDA include pembolizumab, atezolizumab, nivolumab, avelumab, ipilimumab, durvalumab, and cemiplimab. These drugs require expression of response biomarkers, such as PD-1 and PD-L1, and must also have several resistance biomarkers, such as the expression of EGFR, the loss of PTEN, and alterations in beta-catenin. 123

Because cancer is such a diverse disease, it is fundamental to have precise diagnostic methods that allow us to identify the most adequate therapy. Currently, basic immunohistochemistry is complemented with neoplastic molecular profiles to determine a more accurate diagnosis, and it is probable that in the near future cancer treatments will be based exclusively on molecular profiles. In this regard, it is worth mentioning that the use of targeted therapy depends on the existence of specific biomarkers that indicate if the patient will be susceptible to the effects of the drug or not. Thus, the importance of underlining that not all patients are susceptible to receive targeted therapy. In certain neoplasms, therapeutic targets are expressed in less than 5% of the diagnosed population, hindering a more extended use of certain drugs.

The identification of biomarkers and the use of new generation sequencing on tumor cells has shown predictive and prognostic relevance. Likewise, mutation analysis has allowed monitoring of tumor clone evolution, providing information on changes in canonic gene sequences, such as TP53, GATA3, PIK3CA, AKT1, and ERBB2; infrequent somatic mutations developed after primary treatments, like SWI-SNF and JAK2-STAT3; or acquired drug resistance mutations such as ESR1. 124 The study of mutations is vital; in fact, many of them already have specific therapeutic indications, which have helped select adequate treatments. 125

There is no doubt that molecular targeted therapy is one of the main pillars of precision medicine. However, it faces significant problems that often hinder obtaining better results. Among these, there is intratumor heterogeneity and differences between the primary tumor and metastatic sites, as well as intrinsic and acquired resistance to these therapies, the mechanisms of which include the presence of heterogeneous subclones, DNA hypermethylation, histone acetylation, and interruption of mRNA degradation and translation processes. 126 Nonetheless, beyond the obstacles facing molecular targeted therapy from a biological and methodological point of view, in the real world, access to genomic testing and specific drugs continues to be an enormous limitation, in such a way that strategies must be designed in the future for precision medicine to be possible on a global scale.

Cell Therapy

Another improvement in cancer treatment is the use of cell therapy, that is, the use of specific cells as therapeutic agents. This clinical procedure has 2 modalities: the first consists of replacing and regenerating functional cells in a specific tissue by means of stem/progenitor cells of a certain kind, 43 while the second uses immune cells as effectors to eliminate malignant cells. 127

Regarding the first type, we must emphasize the development of cell therapy based on hematopoietic stem and progenitor cells. 128 For over 50 years, hematopoietic cell transplants have been used to treat a variety of hematologic neoplasms (different forms of leukemia and lymphoma). Today, it is one of the most successful examples of cell therapy, including innovative modalities, such as haploidentical transplants, 129 as well as application of stem cells expanded ex vivo . 130 There are also therapies that have used immature cells that form part of the TME, such as MSCs. The replication potential and cytokine secretion capacity of these cells make them an excellent option for this type of treatment. 131 Neural stem cells can also be manipulated to produce and secrete apoptotic factors, and when these cells are incorporated into primary neural tumors, they cause a certain degree of regression. They can even be transfected with genes that encode for oncolytic enzymes capable of inducing regression of glioblastomas. 132

With respect to cell therapy using immune cells, several research groups have manipulated cells associated with tumors to make them effector cells and thus improve the efficacy and specificity of the antitumor treatment. PB leckocytes cultured in the presence of IL-2 to obtain activated lymphocytes, in combination with IL-2 administration, have been used in antitumor clinical protocols. Similarly, infiltrating lymphocytes from tumors with antitumor activity have been used and can be expanded ex vivo with IL-2. These lymphocyte populations have been used in immunomodulatory therapies in melanoma, and pancreatic and kidney tumors, producing a favorable response in treated patients. 133 NK cells and macrophages have also been used in immunotherapy, although with limited results. 134 , 135

One of the cell therapies with better projection today is the use of CAR-T cells. This strategy combines 2 forms of advanced therapy: cell therapy and gene therapy. It involves the extraction of T cells from the cancer patient, which are genetically modified in vitro to express cell surface receptors that will recognize antigens on the surface of tumor cells. The modified T cells are then reintroduced in the patient to aid in an exacerbated immune response that leads to eradication of the tumor cells ( Figure 4 ). Therapy with CAR-T cells has been used successfully in the treatment of some types of leukemia, lymphoma, and myeloma, producing complete responses in patients. 136

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CAR-T cell therapy. (A) T lymphocytes obtained from cancer patients are genetically manipulated to produce CAR-T cells that recognize tumor cells in a very specific manner. (B) Interaction between CAR molecule and tumor antigen. CAR molecule is a receptor that results from the fusion between single-chain variable fragments (scFv) from a monoclonal antibody and one or more intracellular signaling domains from the T-cell receptor. CD3ζ, CD28 and 4-1BB correspond to signaling domains on the CAR molecule.

Undoubtedly, CAR-T cell therapy has been truly efficient in the treatment of various types of neoplasms. However, this therapeutic strategy can also have serious side effects, such as release of cytokines into the bloodstream, which can cause different symptoms, from high fever to multiorgan failure, and even neurotoxicity, leading to cerebral edema in many cases. 137 Adequate control of these side effects is an important medical challenge. Several research groups are trying to improve CAR-T cell therapy through various approaches, including production of CAR-T cells directed against a wider variety of tumor cell-specific antigens that are able to attack different types of tumors, and the identification of more efficient types of T lymphocytes. Furthermore, producing CAR-T cells from a single donor that may be used in the treatment of several patients would reduce the cost of this sort of personalized cell therapy. 136

Achieving wider use of cell therapy in oncologic diseases is an important challenge that requires solving various issues. 138 One is intratumor cell heterogeneity, including malignant subclones and the various components of the TME, which results in a wide profile of membrane protein expression that complicates finding an ideal tumor antigen that allows specific identification (and elimination) of malignant cells. Likewise, structural organization of the TME challenges the use of cell therapy, as administration of cell vehicles capable of recognizing malignant cells might not be able to infiltrate the tumor. This results from low expression of chemokines in tumors and the presence of a dense fibrotic matrix that compacts the inner tumor mass and avoids antitumor cells from infiltrating and finding malignant target cells.

Further Challenges in the 21st Century

Beyond the challenges regarding oncologic biomedical research, the 21 st century is facing important issues that must be solved as soon as possible if we truly wish to gain significant ground in our fight against cancer. Three of the most important have to do with prevention, early diagnosis, and access to oncologic medication and treatment.

Prevention and Early Diagnosis

Prevention is the most cost-effective strategy in the long term, both in low and high HDI nations. Data from countries like the USA indicate that between 40-50% of all types of cancer are preventable through potentially modifiable factors (primary prevention), such as use of tobacco and alcohol, diet, physical activity, exposure to ionizing radiation, as well as prevention of infection through access to vaccination, and by reducing exposure to environmental pollutants, such as pesticides, diesel exhaust particles, solvents, etc. 74 , 84 Screening, on the other hand, has shown great effectiveness as secondary prevention. Once population-based screening programs are implemented, there is generally an initial increase in incidence; however, in the long term, a significant reduction occurs not only in incidence rates, but also in mortality rates due to detection of early lesions and timely and adequate treatment.

A good example is colon cancer. There are several options for colon cancer screening, such as detection of fecal occult blood, fecal immunohistochemistry, flexible sigmoidoscopy, and colonoscopy, 139 , 140 which identify precursor lesions (polyp adenomas) and allow their removal. Such screening has allowed us to observe 3 patterns of incidence and mortality for colon cancer between the years 2000 and 2010: on one hand, an increase in incidence and mortality in countries with low to middle HDI, mainly countries in Asia, South America, and Eastern Europe; on the other hand, an increase in incidence and a fall in mortality in countries with very high HDI, such as Canada, the United Kingdom, Denmark, and Singapore; and finally a fall in incidence and mortality in countries like the USA, Japan, and France. The situation in South America and Asia seems to reflect limitations in medical infrastructure and a lack of access to early detection, 141 while the patterns observed in developed countries reveal the success, even if it may be partial, of that which can be achieved by well-structured prevention programs.

Another example of success, but also of strong contrast, is cervical cancer. The discovery of the human papilloma virus (HPV) as the causal agent of cervical cancer brought about the development of vaccines and tests to detect oncogenic genotypes, which modified screening recommendations and guidelines, and allowed several developed countries to include the HPV vaccine in their national vaccination programs. Nevertheless, the outlook is quite different in other areas of the world. Eighty percent of the deaths by cervical cancer reported in 2018 occurred in low-income nations. This reveals the urgency of guaranteeing access to primary and secondary prevention (vaccination and screening, respectively) in these countries, or else it will continue to be a serious public health problem in spite of its preventability.

Screening programs for other neoplasms, such as breast, prostate, lung, and thyroid cancer have shown outlooks that differ from those just described, because, among other reasons, these neoplasms are highly diverse both biologically and clinically. Another relevant issue is the overdiagnosis of these neoplasms, that is, the diagnosis of disease that would not cause symptoms or death in the patient. 142 It has been calculated that 25% of breast cancer (determined by mammogram), 50–60% of prostate cancer (determined by PSA), and 13–25% of lung cancer (determined by CT) are overdiagnosed. 142 Thus, it is necessary to improve the sensitivity and specificity of screening tests. In this respect, knowledge provided by the biology of cancer and “omic” sciences offers a great opportunity to improve screening and prevention strategies. All of the above shows that prevention and early diagnosis are the foundations in the fight against cancer, and it is essential to continue to implement broader screening programs and better detection methods.

Global Equity in Oncologic Treatment

Progress in cancer treatment has considerably increased the number of cancer survivors. Nevertheless, this tendency is evident only in countries with a very solid economy. Indeed, during the past 30 years, cancer mortality rates have increased 30% worldwide. 143 Global studies indicate that close to 70% of cancer deaths in the world occur in nations of low to middle income. But even in high-income countries, there are sectors of society that are more vulnerable and have less access to cancer treatments. 144 Cancer continues to be a disease of great social inequality.

In Europe, the differences in access to cancer treatment are highly marked. These treatments are more accessible in Western Europe than in its Eastern counterpart. 145 Furthermore, highly noticeable differences between high-income countries have been detected in the cost of cancer drugs. 146 It is interesting to note that in many of these cases, treatment is too costly and the clinical benefit only marginal. Thus, the importance of these problems being approached by competent national, regional, and global authorities, because if these new drugs and therapeutic programs are not accessible to the majority, progress in biomedical, clinical and epidemiological research will have a limited impact in our fight against cancer. We must not forget that health is a universal right, from which low HDI countries must not be excluded, nor vulnerable populations in nations with high HDI. The participation of a well-informed society will also be fundamental to achieve a global impact, as today we must fight not only against the disease, but also against movements and ideas (such as the anti-vaccine movement and the so-called miracle therapies) that can block the medical battle against cancer.

Final Comments

From the second half of the 20th century to the present day, progress in our knowledge about the origin and development of cancer has been extraordinary. We now understand cancer in detail in genomic, molecular, cellular, and physiological terms, and this knowledge has had a significant impact in the clinic. There is no doubt that a patient who is diagnosed today with a type of cancer has a better prospect than a patient diagnosed 20 or 50 years ago. However, we are still far from winning the war against cancer. The challenges are still numerous. For this reason, oncologic biomedical research must be a worldwide priority. Likewise, one of the fundamental challenges for the coming decades must be to reduce unequal access to health services in areas of low- to middle income, and in populations that are especially vulnerable, as well as continue improving prevention programs, including public health programs to reduce exposure to environmental chemicals and improve diet and physical activity in the general population. 74 , 84 Fostering research and incorporation of new technological resources, particularly in less privileged nations, will play a key role in our global fight against cancer.

Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.

Hector Mayani https://orcid.org/0000-0002-2483-3782

Open access
Published: 29 June 2024

Blood-based molecular and cellular biomarkers of early response to neoadjuvant PD-1 blockade in patients with non-small cell lung cancer

Xi Zhang 1 , 2 ,
Rui Chen 1 ,
Zirong Huo 1 ,
Wenqing Li 1 ,
Mengju Jiang 1 ,
Guodong Su 1 ,
Yuru Liu 1 ,
Wuhao Huang 3 ,
Yuyan Xiong 1 , 2 &
Shengguang Wang 3

Cancer Cell International volume 24 , Article number: 225 ( 2024 ) Cite this article

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Despite the improved survival observed in PD-1/PD-L1 blockade therapy, a substantial proportion of cancer patients, including those with non-small cell lung cancer (NSCLC), still lack a response.

Transcriptomic profiling was conducted on a discovery cohort comprising 100 whole blood samples, as collected multiple times from 48 healthy controls (including 43 published data) and 31 NSCLC patients that under treatment with a combination of anti-PD-1 Tislelizumab and chemotherapy. Differentially expressed genes (DEGs), simulated immune cell subsets, and germline DNA mutational markers were identified from patients achieved a pathological complete response during the early treatment cycles. The predictive values of mutational markers were further validated in an independent immunotherapy cohort of 1661 subjects, and then confirmed in genetically matched lung cancer cell lines by a co-culturing model.

The gene expression of hundreds of DEGs (FDR p < 0.05, fold change < -2 or > 2) distinguished responders from healthy controls, indicating the potential to stratify patients utilizing early on-treatment features from blood. PD-1-mediated cell abundance changes in memory CD4 + and regulatory T cell subset were more significant or exclusively observed in responders. A panel of top-ranked genetic alterations showed significant associations with improved survival ( p < 0.05) and heightened responsiveness to anti-PD-1 treatment in patient cohort and co-cultured cell lines.

This study discovered and validated peripheral blood-based biomarkers with evident predictive efficacy for early therapy response and patient stratification before treatment for neoadjuvant PD-1 blockade in NSCLC patients.

Introduction

In the past decade, given the significant benefits achieved by immune checkpoint inhibitors (ICIs) in cancer, immunotherapy has emerged as a “common denominator” [ 1 ]. It has been demonstrated that combining anti-programmed death-1 (anti-PD-1) agents with chemotherapy can restore anti-tumor activities in multiple immune cell subsets, leading to increased overall survival [ 2 ]. Despite these impressive successes, the clinical benefit of this treatment remains limited to a small subset of patients [ 3 ]. Advanced NSCLC has been one of the first pioneers in becoming a common therapeutic focus for therapies targeting programmed death-1 (PD-1) or its ligand programmed death-ligand 1 (PD-L1) [ 4 , 5 ]. The combination of anti-PD-1 therapy with chemotherapy has shown more encouraging results in the upfront treatment of NSCLC [ 6 ], although the overall response rate remains low. Taking the anti-PD-1 antibody Pembrolizumab as an example, the objective response rate for the unselected NSCLC population was only 19%, and the median overall survival was 12 months [ 7 ].

Numerous clinical studies have suggested that the detection of PD-L1 expression or tumor mutation burden (TMB) should serve as a companion diagnostic (CDx) assay for individuals newly diagnosed with NSCLC. [ 8 , 9 , 10 ]. Indeed, a few drug-specific companion diagnostic (CDx) tests have been approved to guide individualized anti-PD-1 treatment strategies for NSCLC patients [ 11 , 12 ]. A recent guideline was just published by The American Society of Clinical Oncology (ASCO) that recommends patients across many cancer types should take germline genetic test [ 13 ]. Various molecular or cellular biomarkers with predictive efficacy for immune checkpoint inhibitors (ICIs) response have been suggested, encompassing gene expression biomarkers [ 14 ], tumor-infiltrating CD8-T cells [ 15 ], local or peripheral immune cell clusters [ 16 , 17 ] and mutational DNA markers [ 18 ]. Pioneering studies in recent times put forth this hypothesis that the response of modern combination therapy is likely modulated by an intricate tumor ecosystem comprising diverse biological parameters which should be integrated in the development of predictive models for therapy response [ 19 , 20 ].

In this study, a comprehensive analysis workflow was formulated to identify gene expression change, immune cell subset and germline mutation biomarkers that can predicting response of synergistic effect of immunotherapy and chemotherapy through transcriptomic analysis of a discovery cohort, followed by validation in a larger and independent cohort. By utilizing widely acknowledged computational tools and in vitro cell culture models, these markers also underwent extensive validations by published datasets, clinical evidences and genetically matched lung cancer cell lines. This collective approach enabled the identification of novel blood-derived biomarkers with the potential to guide combined therapy for NSCLC patients.

Responder DEGs represent potential biomarkers from pre-therapy blood samples

As described in Method (Fig. 1 ), a discovery cohort was recruited to collect blood samples from NSCLC patients what were under treatment of anti-PD-1 plus chemotherapy. We firstly identified 876 significant DEGs (FDR p < 0.05 and fold change > 2 or < -2) from unpaired and paired comparisons between on- vs. pre-treatment blood samples (Fig. 2 A, Table S1 , Fig. S1 B). On top of the shared DEGs ( n = 834), a larger number of DEGs were exclusively identified from responders ( n = 1464, defined in Table S1 ) comparing to those only seen in non-responders ( n = 191) (Fig. 2 B, Figs. S1 B & S1 C). High or middle ranked DEGs were re-tested by Quantitative real-time PCR (qRT-PCR), showing consistent expression changes comparing to RNA sequencing (RNAseq) (Fig. 2 C). In an independent tissue microarray database (GENT2), most of the representative genes (7/8) displayed consistent alteration ( p < 0.01), comparing the differences from tumor to normal lung tissue versus the early on-treatment changes in blood samples (Fig. 2 D). This result suggests an interesting agreement of between therapy-induced DEGs in blood and tumor-specific genes in tissue, which is further supported by results from another large lung cancer database (LCE) with meta-analysis across multiple independent cohorts (Fig. S2 ).

Workflow diagram of the study to identify blood-based signatures. The discovery cohort comprises a total of 100 blood samples collected from 79 subjects, including 43 subjects’ data obtained from publicly available database (GEO). NSCLC, non-small cell lung cancer; vs., versus; DEGs, differently expressed genes

Identification and validation of transcriptomic signatures altered during neoadjuvant anti-PD-1 treatment. A & B ) Venn diagrams and volcano plots of DEGs identified in overall comparisons (A) of on- versus pre-treatment blood samples and in individual comparisons between responder and non-responder subgroups (B) . Shared DEGs (Common) identified from unpaired (upper) and pairwise (lower) comparisons and DEGs only seen (Unique) in pairwise comparison are color-coded and plotted (A) . Common DEGs seen in responder (upper) and non-responder (lower) subgroups and Unique DEGs from non-responders are color-coded and plotted (B) . Expression changes of eight genes as annotated in volcano plots were confirmed by qRT-PCR. C ) Relative mRNA expressions of 8 Common DEGs validated by qRT-PCR and compared to RNAseq results. The mean fold changes identified from both methods are provided after binary logarithmic conversion (Log 2 (mean fold change)). HBG1 and HGB2 were detected by same primer set. D ) Relative mRNA expression changes in 8 Common DEGs in normal and lung cancer tissues (GENT2 database). vs., versus; DEGs, differently expressed genes; Res, responders; Non-res, non-responders; *, p < 0.05; **, p < 0.01; ***, p < 0.001

Next we sought to test our hypothesis that the responder-specific DEGs may serve as gene expression biomarkers to predict early therapy response. We started by investigating DEGs changed between on-and pre-treatment samples. Firstly our blood-derived DEGs were compared with two published tissue-derived transcriptional signatures that either correlates with PD-L1 expression [ 21 ] or responds to anti-PD-1 therapy in cancer [ 14 ]. It was observed the responder-specific DEGs (Unique DEGs) or the DEGs shared (Common DEGs) align better with the published signatures as compared to the non-responder-specific DEGs (Fig. 3 A). However, the Unique DEGs among responders (Fig. S3 A), non-responses and the Common DEGs (not shown) both prove ineffective in distinguishing between responder and non-responder samples, irrespective of their pre- or on-treatment conditions. Subsequently, we examined an additional set of DEGs that resulted from comparing patients’ pre-treatment samples with those of healthy individuals (healthy controls, HCs). A total of 784 and 589 significant Unique DEGs were generated in responders’ and non-responders’ blood, respectively (Fig. 3 B & S3 B, Table S1 ). It is noteworthy that the newly identified DEGs successfully distinguishes responders from non-responders, only using the pre-therapy blood samples (Fig. 3 C and D). Correspondingly, we examined the DEGs that resulted from comparing patients’ on-treatment samples with those of healthy individuals (healthy controls, HCs). A total of 889 and 482 significant Unique DEGs were generated in on-treatment responders’ and non-responders’ blood, respectively (Figs. S3 E & S3 F, Table S1 ).

Characterization of pre-treatment blood biomarkers for patient stratification. (A) Venn diagrams showing the overlap between blood-derived DEG subgroups with published tissue-based molecular signatures, including the top-ranked cancer transcriptional signatures related with PD-L1 expression (blue box) and the gene expression signatures responding to anti-PD-1 therapy in melanoma (green box). (B) Venn diagrams and volcano plots of DEGs identified in comparing pre-treatment blood samples of responder and non-responder to healthy control (HC), respectively. Shared DEGs (Common) identified from both comparisons and DEGs only seen (Unique) in responders versus HCs are color-coded and plotted. (C) The hierarchical clustering of all pre-treatment samples according to the expression profiles of responder-specific Unique DEGs as identified comparing cancer versus healthy control (5 HC) samples. The heatmap visualized the relative expression level of each DEG. Sample status (healthy control, responder etc.) are color-coded and annotated. (D) The hierarchical clustering of all pre-treatment samples according to the expression profiles of non-responder-specific Unique DEGs as identified comparing cancer versus healthy control (48 HC) samples. The heatmap visualized the relative expression level of each DEG. Sample status (healthy control, responder etc.) are color-coded and annotated. vs., versus; DEGs, differently expressed genes; Res, responders; Non-res, non-responders; HC, healthy control

Regulatory T cells form distinct cellular signatures in responders during the treatment

By employing the responder and non-responder unique DEGs identified above, a majority of pathway regulations were uncovered in all patients subsequent to administration of anti-PD-1 treatment (Fig. 4 A, Figs. S4 & S5 ). On the contrary, crucial PD-1 signaling pathways were only significantly regulated in responders, including signaling of PD-1, CD3, TCR, CD28, IL-1 and IFN-γ (Fig. 4 B and C). Consistent with this observation, gene set enrichment analysis (GSEA) suggested substantial alterations in immune cell subsets, including a decrease in monocytes and an increase in CD4 + T lymphocytes (Fig. 5 A and B, Figs. S6 & S7 ). The immune cell abundance dynamics was further elucidated by in silico leukocyte deconvolution approach adopted from our previous work (AImmune) [ 22 , 23 , 24 ] and a classic machine learning tool CIBERSORTx [ 25 ]. These computing tools not only validated the changes in monocytes and resting memory CD4 + T cells but also unveiled an elevation in regulatory T cells, specifically observed in responders (Fig. 5 C and D, Figs. S8 & S9 ).

Characterization of pathways and GOs hat specifically regulated in responders. A ) Venn diagram visualization of the significant KEGG pathways, Reactome pathways and gene ontology (GO) items regulated after treatment. The counts of terms regulated in responders, non-responders and both are provided respectively. B & C ) Bubble plots of the top 20 pathways regulated in responders (B) and non-responders (C) . Bubble with bigger size stands for smaller p value and higher significance. The star denotes immune-related pathways. Names of unique terms are colored in red (responders), blue (non-responders) or grey (shared). Res, responders; Non-res, non-responders

Identification of gene sets and immune cell subsets responding to the treatment. A & B ) Bubble plots of the top 20 gene sets downregulated (A) and upregulated (B) in responders. Names of unique terms are colored in red (responders) while the shared terms are annotated in grey text. Bubble with bigger size stands for higher k/K value ratio and larger fraction of gene was matched with a certain reference gene set. The star denotes immune-related gene sets. C & D ) Cell abundance scores as computed by AImmune (C) and CIBERSORTx (D) across responder and non-responder samples. Dot plots and box plots show individual values and average value of the scores. Connecting lines indicate the pairwise relationship between pre- and on-treatment samples. Res, responders; Non-res, non-responders; HC, healthy control; Pre, pre-treatment; On, on-treatment; *, p < 0.05; **, p < 0.01. All p values were calculated for pairwise comparisons

DNA mutations observed in responders are positively associated with enhanced survival

The Cancer-Related Analysis of Variants Toolkit (CRAVAT) was employed in our discovery cohort to identify cancer-associated germline mutations that predict clinical benefit for anti-PD-1 treatment (Fig. S10 ). The top-ranked mutated genes (gene-level FDR p values < 0.05) were identified from responders, non-responders and healthy controls (Fig. 6 A) and the top 10 genes from responders or non-responders are listed (Fig. 6 B). The scores computed and ranked by CHASM (cancer driver classifier) and VEST (pathogenicity classifier) are all close to 1, suggesting confident classification of these germline variants as cancer-related mutations (Fig. 6 B) [ 26 , 27 ]. Three mutational markers (TNFAIP3, BRCA1, ASXL1) of non-responders were found to be shared with the DNA markers from patients with progressive disease in an independent cervical cancer cohort (GEO repository: GSE205247) (Fig. S11 A). It is noteworthy that these three shared genes are ranked prominently as the top 1st, 3rd, and 4th mutations in the discovery cohort (bold in Fig. 6 B).

Identification and validation of DNA mutational markers in bloodstream. (A) Venn diagram showing cancer-related germline mutations as identified and ranked from discover cohort. (B) Top 10 mutated genes exclusively identified from responders and non-responders as ranked by CHASM and VEST scores. Mutations called in an independent cohort of with cervical cancer (Figure S11 A) are indicated in bold. (C) Validation of the high-ranked mutations in an independent pan-cancer cohort (“tmb_mskcc_2018” cohort, n = 1661). Pan-cancer patients were stratified into 9 subgroups by the 8 mutational markers and their overall survivals were plotted by Kaplan-Meier curves. (D) Patients were stratified into 3 subgroups according to 2 mutational marker sets (4 for responders and 4 for non-responders) and their TMB scores were plotted. (E) Patients were stratified into 2 subgroups according to 1 mutational marker set (responder set). The Kaplan Meier overall survival curves of responder and unaltered subgroups as defined by mutational marker sets. Curves were generated for all immunotherapy patients (upper) and patients only received anti-PD(L)1 therapy (lower). P value was generated from by Log-Rank test which compares the survival distributions in individual groups as annotated. Res, responders; Non-res, non-responders; **, p < 0.01

In a considerably larger validation cohort (“tmb_mskcc_2018”) comprising 1661 pan-cancer patients [ 28 ], 8 out of the top 20 ranked gene mutations from the discovery cohort were detected in patients who all underwent PD-1 or cytotoxic T lymphocyte antigen 4 (CTLA-4) blockade treatment (Fig. 6 C, upper). The Kaplan-Meier curves depicts a significantly difference of overall survival ( p < 0.01) across 9 patient groups as defined by 8 mutational markers. Patients with no mutations show an overall median survival of 16 months, whereas those with non-responder mutations exhibit shorter median survivals (10–15 months), and patients with responder mutations demonstrate much longer median survivals (23–41 months), if available (Fig. 6 C, lower). Subsequently, the patients were categorized into three subgroups using combined DNA mutations identified from responders (PTCH1, DNMT3A, PTPRS, JAK2) and non-responders (TNFAIP3, BRCA1, ASXL1, GATA2) as markers. TMB as the recognized favorable biomarker for clinical response to anti-PD(L)1 therapies, was observed to be highest in the responder subgroup (138 patients) and lowest in the unaltered patient subgroup (1307 patients) (Fig. 6 D). As expected, the mean survival of the responder subgroup showed an extension compared to the unaltered patient subgroup seen in all patients (41 vs. 17 months) and only PD(L)1 blockade-treated patients (31 vs. 14 months) (Fig. 6 E). The Cox regression results indicate hazard ratios of 0.559 (95% confidence interval: 0.425 to 0.735) for the responders in overall patient group and 0.579 (95% confidence interval: 0.425 to 0.789) in the PD(L)1 blockade only group. There was no significant difference observed when comparing the non-responder subgroup with the unaltered patient subgroup (Fig. S11 ).

DNA mutational markers are validated in cancer cell lines co-cultured with immune cells

The co-culture system involving activated immune cells and cancer cells is commonly utilized to acquire in-depth knowledge of immune-tumor interactions [ 29 ]. Here Jurkat CD4+-T-cell line was activated before co-culturing with lung cancer cell lines to assess their responsiveness to anti-PD-1 treatments (Fig. 7 A). HARA-B and A549 cell lines, representing the molecular profiles of responder and non-responder respectively as identified earlier (Fig. 7 B, left), were characterized before being studied pairwise in the co-culture model (Fig. 7 B, right). HARA-B exhibited a similar (if not lower) PD‑L1 expression compared to A549 (Fig. 7 C), aligning with their comparable immunosuppressive effects on IFN-γ production (Fig. 7 D). The suppressed immune response was subsequently restored by the anti-PD-1 antibody Tislelizumab, as observed exclusively in HARA-B cells (responder) in contrast to the paired A549 cells (non-responder) (Fig. 7 D). Indeed, transcriptomic proofing of treated versus untreated cell lines established that HARA-B cell but not A549 is highly sensitive to PD-1 inhibition. This is supported by the identification of a significantly larger number of DEGs in HARA-B ( n = 3623) compared to A549 cells (Fig. 7 E, Figs. S12 A, Table S3 ). It is further proved by KEGG pathway analysis which revealed that cancer-driving signaling and PD-L1 signaling in HARA-B are prominently impaired, as marked by the down-regulated DEGs in the top-ranked pathways (Fig. 7 F, Fig. S12 B, Table S4 ). Based on these cell line data, it is likely that lung cancer cells carrying responder mutations would exhibit a more favorable response to treatment with PD-1 inhibitors.

Evaluation of immunotherapy responsiveness of lung cancer cell lines carrying mutational markers. (A) Workflow diagram illustrating the co-culture model consisting of Jurkat cells and lung cancer tumor cells, which received anti-PD-1 treatment. (B) The genetic profiles of A549 and HARA-B cell line as obtained from the DepMap database ( https://depmap.org/portal/ ) and confirmed by genotyping (PTPRS gene). (C) mRNA levels of PD-L1 in cell lines were assessed by qRT-PCR (left) and obtained from the Human Protein Atlas database ( https://www.proteinatlas.org/ ) (right). (D) IFN-γ concentration in the supernatant of co-cultured cell lines was assessed by ELISA. (E) Venn diagrams and volcano plots of DEGs identified by comparing treated cells versus untreated cells. Shared DEGs (Common) identified from both cell lines and DEGs only seen (Unique) in HARA-B cell lines are color-coded and plotted. (F) Bubble plots of the top 15 downregulated KEGG pathways regulated in HARA-B cells. Bubble with bigger size stands for smaller p value and higher significance. DEGs, differently expressed genes; vs., versus. *, p < 0.05; **, p < 0.01. All p values were calculated for pairwise comparisons

The overarching hypothesis of this study is that blood-based signatures identified from early responders to tislelizumab plus chemotherapy would offer prognostic values. To clarify, three comparison strategies were employed to identify blood-derived biomarkers: (1) DEGs identified by comparing pre-treatment responders vs. pre-treatment non-responders were used to stratify responder patients before treatment (Fig. 3 C and D); (2) DEGs identified by comparing changes from pre-treatment to on-treatment in responders vs. non-responders were utilized to characterize responsiveness-related pathways (Fig. 4 B, pink) and immune cell subsets (Fig. 5 ), which are different from intervention-related pathways (Fig. 4 B and C, gray) etc.; (3) DNA mutations identified in responders and non-responders (irrespective of pre-treatment or on-treatment status) indicate mutation markers for stratifying responder patients. Our findings offer new evidences suggesting gene expression signatures, peripheral immune cell clusters, and DNA mutational determinants that profiled through a blood draw may predict clinical efficacy either before the combined therapy or during the early treatment cycles.

The initiation of this study identified a set of Common DEGs that exhibited changes during early treatment. The significance of this findings lies in the fact that these DEGs were, on one hand, triggered by early therapy in blood samples, as confirmed by both RNAseq and qRT-PCR; on the other hand, their expression levels also changed consistently in tissue when comparing tumor to normal samples. One of the validated DEGs (HBG1) that was up-regulated in treated patients here, showed a continuous increase in advanced NSCLC patients during the 2nd to the 5th cycles of treatment [ 30 ]. Other validated DEG genes includes a hematopoietic transcription regulator (GATA2) [ 31 ], a metabolism mediator (ANKRD22) [ 32 , 33 ], and a transcription factor involved in differentiation control (LHX4) [ 34 ]. This is consistent with the current understanding that immunological and metabolism mechanisms are enriched in patients received treatments [ 35 ]. The DEGs from early responders exhibited overlap with two sets of published signature genes identified from cancer tissue. One set is the top 100 (out of the total 1788) transcriptional correlates of PD-L1 expression [ 21 ] and the other set consists of 100 immune-positive genes utilized for predicting melanoma patient response [ 14 ]. In comparison to the first set of DEGs requiring blood samples from on-treatment patients, a second set of DEGs was identified from pre-therapy samples (responders vs. healthy controls) and exhibited promising biomarker features, offering better distinction of early responders from other subjects. Notably, the top-ranked genes in this list (Fig. 3 B) are either previously reported as prognostic biomarkers (PSMD9 and APH1A) for other cancer indication (cervical cancer and HCC) [ 36 , 37 ], or are known a vesicular trafficking modulator (TRAPPC4) that regulates the intracellular trafficking of PD-L1 and antitumor immunity [ 38 ]. Collectively, the predictive values of these newly identified markers are novel when obtained from the bloodstream of lung cancer patients during the early stages of treatment. Prior to this study, their significance had only been reported in other cancer indications or as therapeutic targets rather than as biomarkers.

PD-1 blockade therapy is known to crosstalk with T cell activation, differentiation, and other immune cell activities. There is a growing body of evidence confirming that the efficacy of chemotherapies also depends on activating antitumor immune responses. It is logical for us to observe PD-1 signaling and PD-1-regulated signaling cascades (such as CD3, TCR, CD28, IL-1 and IFN-γ) enriched only in responders. Our GSEA and immune cell abundance analysis provided additional insights into the orchestration of immune clusters, aligning with published findings. Firstly, it was expected that we found monocyte-to-DC differentiation to be significantly higher at the early stage of therapy for NSCLC patients, given this differentiation is known to attenuate CD8 + T cell response and predict clinical outcomes of patients with other cancers [ 39 , 40 , 41 ]. Secondly, our observation of enriched peripheral CD4 + T cell subset in responders is consistent with a recent study that characterized NSCLC patients who received anti-PD-1 therapy [ 42 ]. The uniqueness of our study lies in the approach, as RNAseq requires a minimal blood specimen compared to the flow cytometry as employed in by the existing study. At last, our method also revealed a significant elevation of regulatory T cell (Treg cell) in circulating blood of responders. This supports the prevailing understanding that PD-1 blockade facilitates the proliferation of highly suppressive PD-1 + Treg cells [ 43 ]. Given the complex and sometimes conflicting conclusions in this field, the prognostic value of peripheral immune cell subsets in anti-PD-1 therapy needs to be addressed through further fine-tuned studies.

Emerging studies as well as a recent ASCO guideline provide evidence-based recommendations that pathogenic germline variants can predict patient outcomes [ 13 , 44 , 45 ]. The present study has identified 4 cancer driver genes (PTCH1, DNMT3A, PTPRS, JAK2) that rank highest in responders and are linked to enhanced survival in the validation cohort, either as individual markers or as part of a grouped marker panel. Individual diver gene mutations were previously identified from tumor tissue demonstrated to promote (such as KRAS [ 46 ], TP53 [ 47 ], PTCH1 [ 48 ]) or weaken (such as JAK1/2 [ 49 ], EGFR [ 50 ], PTEN [ 51 ]) the response to immune checkpoint inhibitor therapy in cancer patients. The driver role of somatic mutation is consistent across cancer indications. An typical example is TNFAIP3 mutation indicates low responses to PD-1 inhibitor in NSCLC and cervical cancer patients as showed in the present study, which is also supported by a study on melanoma [ 52 ]. Another example is that the association of PTCH1 mutation with improved outcome of PD-1 blockade was seen in both colorectal cancer [ 48 ] and NSCLC (the present study). Improved responsiveness is also observed in human squamous cell lung carcinoma HARA-B, which harbors mutations in two marker genes, compared to the genetically matched control cell line A549. This occurs after coculturing with CD4 + Jurkat cell line and both undergoing treatment with PD-1 blockade. Patients with these mutational markers exhibit a higher tumor mutational burden (TMB), a well-established marker correlated with improved survival in NSCLC patients treated with PD-1 plus CTLA-4 blockade [ 53 , 54 ]. While the prognostic values of these (or similar) genes with somatic mutations have been highlighted recently [ 48 , 55 , 56 , 57 ], our study stands out as a unique research endeavor identifying germline mutations to be cancer-related and associated with increased susceptibility. Collectively, our results offer robust evidence affirming the predictive significance of these DNA mutational markers, even though they are detected in peripheral blood rather than tumor tissue.

While our study offers crucial insights into the biomarker features in bloodstream and the molecular mechanism of resistance in PD-1 blockade therapy plus chemotherapy, the discovery dataset is derived from a small cohort. Therefore, we aimed to validate our observations using large independent cohorts of pan-cancers that received similar treatments, as well as in genetically matched cell lines. It is important to note that the cell abundance analysis tool AImmune employed here is still in its early development stage in-house. Despite undergoing robust testing and validation in our published studies [ 22 , 23 , 24 ], the current version is limited to cover up to 10 major immune cell subsets from peripheral blood. Rare cell populations or the small-scale dynamics of immune cells might be neglected. For instance, changes in composition of PD-L1 + or CD14 macrophages and CD62L low CD4 + T cells, as detected by flow cytometry, were emphasized in PD-1 blockade responders [ 58 , 59 , 60 ]. These cell subsets would need to be evaluated once a more finely tuned computational tool is available.

Study cohorts and overall workflow

This study constructed a discovery cohort and collected a total of 100 whole blood samples (or data) from 5 healthy controls, in combination with another 43 published healthy blood samples (RNAseq data from Gene Expression Omnibus (GEO): GSE152641, GSE160351, GSE166253, GSE206263) [ 61 , 62 , 63 ] (Figs S3 C, S3 D), and 31 EGFR wild-type NSCLC patients visited Tianjin Cancer Hospital from 2020 to 2022 (Fig. 1 ; Table 1 ). All patients were ineligible for EGFR-targeted therapies (due to genotyping result) and thus underwent treatment by anti-PD-1 monoclonal antibody Tislelizumab [ 64 , 65 ], in combination with standard chemotherapy. Early on-treatment clinical benefit was observed in 10 out of 31 patients, indicating a positive response. Among these responders, 7 had valid pre-treatment samples, while 8 had valid on-treatment samples. The majority of enrolled patients were male (87.1%), over 60 years old (64.5%), ever-smokers (80.6%), and diagnosed with lung squamous cell carcinoma (SqCC) (83.9%) (Table 1 ). The protocol was approved by the local Ethics Committee and the Institutional Review Board of Norwest University (approval number: 200,402,001) and all subjects provided written informed consent.

Whole blood samples were collected twice: the first one up to one month before the initiation of therapy (pre-treatment), and the second one before completion of 2 to 4 cycles (on-treatment). Patients achieved pathological complete response (pCR) during this period were categorized as “responders” and those did not achieve pCR were labelled as “non-responders”. Specimens that failed during sampling process or did not meet RNAseq QC were excluded, resulting a total of 57 cancer and 5 healthy donor (healthy control) samples sequenced in the discovery cohort. The candidate molecular biomarkers were identified through RNAseq, validated by RT-PCR and then compared to known immunotherapy signatures from published clinical studies [ 14 , 21 ] as well as lung cancer tissue datasets (GENT2: https://gent2.appex.kr ; LCE: https://lce.biohpc.swmed.edu ) (Fig. S1 A). Pathways and cellular biomarkers were investigated via KOBAS-i portal ( http://kobas.cbi.pku.edu.cn/ ) [ 66 ] and computational tools (AImmune; CIBERSORTx: https://cibersortx.stanford.edu ). Cancer-associated germline mutations were called by CRAVAT ( https://www.cravat.us/CRAVAT ).

The findings of mutational markers were compared with an independent study (GEO: GSE205247) and then rigorously assessed in an independent validation cohort (tmb_mskcc_2018 from cBioPortal) [ 28 , 67 ] (Fig. S1 A). Finally, we tested the responsiveness of paired lung cancer cell lines that harboring mutational markers or wildtype genotypes after co-cultured with T lymphocyte cell line and treated by anti-PD-1 antibody.

RNAseq, and qRT-PCR

PBMCs of 5 healthy control donors or cultured cell lines in 2 or 3 replicates were isolated from whole blood or cell pellets were collected at the desired end point of co-culture models. One PBMC samples was collected and sequenced for each patient at single or multiple timepoints (pre- or/and on-treatment). The total RNA was isolated using Trizol (Invitrogen, Carlsbad, CA, USA) and the purity and concentration were verified using a NanoDrop ND-1000 instrument (ThermoFisher Scientific, Waltham, MA, USA). The integrity of the RNA was assessed by a 2100 Bioanalyzer gel image analysis system (Agilent, Santa Clara, CA, USA) before transcriptomic analysis (RNAseq) and (or) Quantitative real-time PCR (qRT-PCR).

Qualified RNA samples were then enriched and synthesized into two strand cDNA for library preparation. RNAseq libraries were constructed using the TruSeq RNA Sample Prep Kit (Illumina, San Diego, CA, USA). The libraries from qualified RNA samples were sequenced in the 150 nt paired-end mode on an Illumina NovaSeq 6000 platform at Novogene Bioinformatic Technology (Tianjin, China). After quality filtering (FastQC, quality value > 5), over 30 billion clean reads were obtained in each library and then used for down-stream analysis. PCR primers were designed for selected genes as obtained by differential gene analysis (Table S2 ). Real-time quantitative PCR was performed in real-time PCR systems (Bio-Rad, Hercules, CA, USA). The relative expression levels were calculated by the 2 −ΔΔCt method. Two or three replicates were measured for each sample.

Cell culture and co-culture model

Lung cancer cell lines (A549 and HARA-B) and Jurkat T (Jurkat) cell lines were purchased from Procell Life Science & Technology (Wuhan, Hubei, China). A549 cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM, Procell, Wuhan, Hubei, China). HARA-B and Jurkat cells were cultured in RPMI-1640 (Procell, Wuhan, Hubei, China). In both media, 10% fetal bovine serum (FBS, Bioind, Israel) and 1% penicillin/streptomycin (Procell, Wuhan, Hubei, China) were added. The above cells were grown in a humidified 5% CO 2 incubator at 37 °C.

The workflow of co-culture model is illustrated in Fig. 7 A. Briefly, A549 and HARA-B cells were seeded onto 6-well plate at 1 × 10 5 per ml and cultured in their respective required media (as described above). The Jurkat cells were pre-activated with 3 µg ml − 1 anti-CD3 (BioGems, Westlake Village, CA, USA), 2 µg ml − 1 soluble anti-CD28 (BioGems, Westlake Village, CA, USA) and IL-2 (25 ng ml − 1 , Peprotech, Cranbury, NJ, USA) for 48 h. Briefly, we first diluted anti-CD3 in PBS and incubated overnight at 4 °C. After discarding the PBS, use fresh 1640 medium (including anti-CD28 and IL-2) to culture Jurkat cells in a 37 °C incubator for 48 h. Jurkat was then mixed with A549 and HARA-B cells at a density of 1 × 10 6 per ml (the ratio of Jurkat cells to tumor cells is 10:1) and maintained in fresh RPMI-1640 medium containing 10% FBS, and all cells were treated with or without 50 µg ml − 1 anti-PD-1 antibody Tislelizumab (MCE, Monmouth Junction, NJ, USA) for 24 h.

Enzyme-linked immunosorbent assay (ELISA) for detection of IFN-γ

Interferon-γ (IFN-γ) level in supernatants of the co-culture model was measured using Human IFN-γ Enzyme-linked immunosorbent assay kit (MLBIO, Shanghai, China) according to the manufacturer’s protocol. Optical density was measured at 450 nm, and the IFN-γ level was calculated from a standard curve prepared using the recombinant protein provided in the kit.

DNA was extracted from lung cancer cells using Genomic DNA Extraction Kit (Tiangen, Beijing, China) followed by a standard PCR amplification with GoTaq Green master mix (Promega, Madison, WI, USA). Amplified DNA was separated and visualized by agarose gels (2%). The DNA bands were imaged using an automatic digital gel image analysis system (Tanon-1600, Shanghai, China).

Computational analysis to quantify immune cell abundance

A novel in silico leukocyte deconvolution method, named AImmune, is a computational approach developed by integrating our established immune cell profiling [30] with published single cell RNAseq data obtained from NSCLC blood samples (1071 qualified cells from one patient, GSE127471) and healthy blood samples (8369 and 7687 cells from two donors, 10X Genomics). Briefly, with the additional marker genes included, more than 30 candidate marker genes for each cell subsets in peripheral immune cell subsets (CD4-T cells, CD8-T cells, B cells, Monocytes, DCs, NK cells and NKT cells) were selected based on their expression patterns across immune cell subsets [ 68 ]. The pairwise similarity statistic of all cell subsets was computed (data not shown) between all pairs of the candidate marker genes within the normalized RNAseq profiles (FPKM) from whole blood samples. Using the criteria (average Pearson correlation factor > 0.60, p < 0.01), 10–20 selected marker genes were identified as our final marker genes. The raw cell abundance score was calculated as the sum of the simple averages of the marker genes’ log2 expression, which allows comparison of cell composition across subject groups. This approach also tested a novel deconvolution model (unpublished) built by DNN (deep neural networks) algorithms and then trained by pseudo-bulk samples obtained by randomly subsampling of published single-cell RNA sequencing (scRNAseq) data [ 69 ]. Machine learning-based feature extraction (marker gene selection) was integrated for model optimization. Most of the computational analysis procedure was coded by common Python packages; scRNAseq data was processed by R package scanpy; machine learning model was developed and tested with Python library Tensorflow. All computational analysis were performed and visualized using R version 3.6.1 or Python version 3.7.9.

Bioinformatics and variant calling

All raw RNAseq reads were filtered by R package trim_fastq to remove adapters, rRNA and low-quality reads. The QC criteria included: removing bases below Phred quality 20, containing over two “N”, or shorter than 75. The output reads were then indexed by aligner STAR and mapped to reference genome by BAM. Normalized read counts were generated and compared between groups to generate DEGs using R package DESeq2. Another R package countToFPKM was employed to produce FPKM for AImmune analysis. Genes in PBMC samples that displayed at least two-fold difference in gene expression between comparison groups (fold change > 2 or < -2, FDR p < 0.05) were considered significant differentially expressed genes (DEGs) and carried forward in the analysis. DEGs in lung cancer cell lines were identified by lower threshold (fold change > 1.2 or < -1.2, FDR p < 0.05) to maximin DEG count as illustrated in a volcano plot. Hierarchical clustering was performed to show the gene expression patterns and similarities among samples. Pathway and gene ontology (GO) enrichment analysis was carried out via an integrated platform KOBAS 3.0 [35]. GSEA analysis was carried out by searching the established MSigDB gene-set collections (C7). CIBERSORTx analysis was performed following the instruction from the portal ( https://cibersortx.stanford.edu ). Differences of mRNA levels and cell abundance scores were evaluated using independent t -tests or paired t -tests if pairwise samples were given.

Variant calling was performed using the HaplotypeCaller that plug-in in the Genome Analysis Toolkit v4.0 (GATK). First, RNA reads were aligned to the reference genome using the STAR aligner, then the MarkDuplicates was used to clean up data. The gatk BaseRecalibrator and gatk ApplyBQSR were used to adjust the mass fraction of original bases, detect the system errors in mass fraction, and reduce the false positives. We used only variants marked with PASS in the VCF file and filtered the variant calls with the VariantFiltration tool. The Cancer-Related Analysis of Variants Toolkit (CRAVAT) is a well-recognized informatics toolkit used in this study for variant calling from VCF files [ 70 , 71 ]. This tool covers multi-level mutational analysis functions including mutation mapping and quality control, impact prediction and extensive annotation. Two Random Forest filters were employed in CRAVAT for predicting mutation impact, namely Cancer-Specific High-Throughput Annotation of Somatic Mutations (CHASM) and Variant Effect Scoring Tool (VEST). CHASM is a classifier that classifies if a mutation is an oncogenic driver while VEST rates if a mutation is pathogenic or benign.

A p -value of < 0.05, < 0.01, and < 0.001 was considered statistically significant, annotated by *, **, and ***, respectively. Kaplan-Meier analysis was utilized to estimate the survival curve of cancer patients and to calculate the incidence of each mutation subgroup over time. Additionally, a Cox regression model was conducted to quantitatively measure the hazard ratio of each subgroup. Bioinformatics and statistics analyses were performed and visualized using R version 3.6.1 or Python version 3.7.9.

Data availability

Raw and processed files for RNA sequences (FASTQ format) supporting the findings of this study have been deposited in the National Center for Biotechnology Information Gene Expression Omnibus (NCBI-GEO) under accession number GSE225620.

Abbreviations

Companion diagnostic

Cancer-Related Analysis of Variants Toolkit

Cancer-Specific High-Throughput Annotation of Somatic Mutations

Cytotoxic T lymphocyte antigen 4

Differentially expressed genes

Dulbecco’s modified Eagle’s medium

Deep neural networks

Enzyme-linked immunosorbent assay

Gene ontology

Genome Analysis Toolkit v4.0

Gene set enrichment analysis

Immune checkpoint inhibitors

Interferon-γ

Non-small cell lung cancer

Programmed Death 1

Programmed Death-Ligand 1

Pathological complete response

Quantitative real-time PCR

RNA sequencing

seqsingle-cell RNA sequencing

Lung squamous cell carcinoma

Regulatory T cell

Tumor mutation burden

Variant Effect Scoring Tool

Topalian SL, Taube JM, Pardoll DM. Neoadjuvant checkpoint blockade for cancer immunotherapy. Science. 2020;367(6477).

Murciano-Goroff YR, Warner AB, Wolchok JD. The future of cancer immunotherapy: microenvironment-targeting combinations. Cell Res. 2020;30(6):507–19.

Article PubMed PubMed Central Google Scholar

Havel JJ, Chowell D, Chan TA. The evolving landscape of biomarkers for checkpoint inhibitor immunotherapy. Nat Rev Cancer. 2019;19(3):133–50.

Article CAS PubMed PubMed Central Google Scholar

De Giglio A, Di Federico A, Nuvola G, Deiana C, Gelsomino F. The Landscape of Immunotherapy in Advanced NSCLC: driving beyond PD-1/PD-L1 inhibitors (CTLA-4, LAG3, IDO, OX40, TIGIT, vaccines). Curr Oncol Rep. 2021;23(11):126.

Sgambato A, Casaluce F, Sacco PC, Palazzolo G, Maione P, Rossi A, et al. Anti PD-1 and PDL-1 immunotherapy in the treatment of Advanced non- small cell Lung Cancer (NSCLC): a review on Toxicity Profile and its management. Curr Drug Saf. 2016;11(1):62–8.

Article CAS PubMed Google Scholar

Mathew M, Enzler T, Shu CA, Rizvi NA. Combining chemotherapy with PD-1 blockade in NSCLC. Pharmacol Ther. 2018;186:130–7.

Peters S, Kerr KM, Stahel R. PD-1 blockade in advanced NSCLC: a focus on pembrolizumab. Cancer Treat Rev. 2018;62:39–49.

Roach C, Zhang N, Corigliano E, Jansson M, Toland G, Ponto G, et al. Development of a Companion Diagnostic PD-L1 immunohistochemistry assay for Pembrolizumab Therapy in Non-small-cell Lung Cancer. Appl Immunohistochem Mol Morphology: AIMM. 2016;24(6):392–7.

Article CAS Google Scholar

Hansen AR, Siu LL. PD-L1 testing in Cancer: challenges in Companion Diagnostic Development. JAMA Oncol. 2016;2(1):15–6.

Article PubMed Google Scholar

Marabelle A, Fakih M, Lopez J, Shah M, Shapira-Frommer R, Nakagawa K, et al. Association of tumour mutational burden with outcomes in patients with advanced solid tumours treated with pembrolizumab: prospective biomarker analysis of the multicohort, open-label, phase 2 KEYNOTE-158 study. Lancet Oncol. 2020;21(10):1353–65.

Maule JG, Clinton LK, Graf RP, Xiao J, Oxnard GR, Ross JS et al. Comparison of PD-L1 tumor cell expression with 22C3, 28 – 8, and SP142 IHC assays across multiple tumor types. J Immunother Cancer. 2022;10(10).

Batenchuk C, Albitar M, Zerba K, Sudarsanam S, Chizhevsky V, Jin C, et al. A real-world, comparative study of FDA-approved diagnostic assays PD-L1 IHC 28 – 8 and 22C3 in lung cancer and other malignancies. J Clin Pathol. 2018;71(12):1078–83.

Tung N, Ricker C, Messersmith H, Balmana J, Domchek S, Stoffel EM et al. Selection of Germline Genetic Testing panels in patients with Cancer: ASCO Guideline. J Clin Oncology: Official J Am Soc Clin Oncol. 2024:JCO2400662.

Wu CC, Wang YA, Livingston JA, Zhang J, Futreal PA. Prediction of biomarkers and therapeutic combinations for anti-PD-1 immunotherapy using the global gene network association. Nat Commun. 2022;13(1):42.

Kim KH, Kim HK, Kim HD, Kim CG, Lee H, Han JW, et al. PD-1 blockade-unresponsive human tumor-infiltrating CD8(+) T cells are marked by loss of CD28 expression and rescued by IL-15. Cell Mol Immunol. 2021;18(2):385–97.

Araujo BLV, Hansen M, Spanggaard I, Rohrberg K, Reker Hadrup S, Lassen U, et al. Immune Cell profiling of peripheral blood as signature for response during checkpoint inhibition Across Cancer types. Front Oncol. 2021;11:558248.

Article Google Scholar

Frigola J, Navarro A, Carbonell C, Callejo A, Iranzo P, Cedres S, et al. Molecular profiling of long-term responders to immune checkpoint inhibitors in advanced non-small cell lung cancer. Mol Oncol. 2021;15(4):887–900.

Pagadala M, Sears TJ, Wu VH, Perez-Guijarro E, Kim H, Castro A, et al. Germline modifiers of the tumor immune microenvironment implicate drivers of cancer risk and immunotherapy response. Nat Commun. 2023;14(1):2744.

Sammut SJ, Crispin-Ortuzar M, Chin SF, Provenzano E, Bardwell HA, Ma W, et al. Multi-omic machine learning predictor of breast cancer therapy response. Nature. 2022;601(7894):623–9.

Santhanam B, Oikonomou P, Tavazoie S. Systematic assessment of prognostic molecular features across cancers. Cell Genomics. 2023;3(3):100262.

Banchereau R, Leng N, Zill O, Sokol E, Liu G, Pavlick D, et al. Molecular determinants of response to PD-L1 blockade across tumor types. Nat Commun. 2021;12(1):3969.

Zhang X, Pan A, Jia S, Ideozu JE, Woods K, Murkowski K, et al. Cystic fibrosis plasma blunts the Immune response to bacterial infection. Am J Respir Cell Mol Biol. 2019;61(3):301–11.

Zhang X, Moore CM, Harmacek LD, Domenico J, Rangaraj VR, Ideozu JE et al. CFTR-mediated monocyte/macrophage dysfunction revealed by cystic fibrosis proband-parent comparisons. JCI Insight. 2022;7(6).

Han RH, Zhang XT. AImmune: a new blood-based machine learning approach to improving immune profiling analysis on COVID-19 patients. medRxiv. 2021:2021.11.26.21266883.

Newman AM, Steen CB, Liu CL, Gentles AJ, Chaudhuri AA, Scherer F, et al. Determining cell type abundance and expression from bulk tissues with digital cytometry. Nat Biotechnol. 2019;37(7):773–82.

Liu M, Liu X, Suo P, Gong Y, Qu B, Peng X, et al. The contribution of hereditary cancer-related germline mutations to lung cancer susceptibility. Translational lung cancer Res. 2020;9(3):646–58.

Qing T, Mohsen H, Marczyk M, Ye Y, O’Meara T, Zhao H, et al. Germline variant burden in cancer genes correlates with age at diagnosis and somatic mutation burden. Nat Commun. 2020;11(1):2438.

Samstein RM, Lee CH, Shoushtari AN, Hellmann MD, Shen R, Janjigian YY, et al. Tumor mutational load predicts survival after immunotherapy across multiple cancer types. Nat Genet. 2019;51(2):202–6.

Zheng Y, Fang YC, Li J. PD-L1 expression levels on tumor cells affect their immunosuppressive activity. Oncol Lett. 2019;18(5):5399–407.

CAS PubMed PubMed Central Google Scholar

Wu J, Cheung YH, Huang W, Yin C, Fallon JT, Dimitrova N, et al. Gene expression profiles of peripheral blood mononuclear cells from patients with advanced non-small cell lung cancer treated with anti-PD-1 monoclonal antibodies. J Clin Oncol. 2019;37(15suppl):e14107–e.

Castano J, Aranda S, Bueno C, Calero-Nieto FJ, Mejia-Ramirez E, Mosquera JL, et al. GATA2 promotes hematopoietic development and represses Cardiac differentiation of human mesoderm. Stem cell Rep. 2019;13(3):515–29.

Pan T, Liu J, Xu S, Yu Q, Wang H, Sun H, et al. ANKRD22, a novel tumor microenvironment-induced mitochondrial protein promotes metabolic reprogramming of colorectal cancer cells. Theranostics. 2020;10(2):516–36.

Qiu Y, Yang S, Pan T, Yu L, Liu J, Zhu Y, et al. ANKRD22 is involved in the progression of prostate cancer. Oncol Lett. 2019;18(4):4106–13.

Dong X, Yang H, Zhou X, Xie X, Yu D, Guo L, et al. LIM-Homeodomain transcription factor LHX4 is required for the differentiation of Retinal Rod Bipolar cells and OFF-Cone bipolar subtypes. Cell Rep. 2020;32(11):108144.

Kumar A, Chamoto K. Immune metabolism in PD-1 blockade-based cancer immunotherapy. Int Immunol. 2021;33(1):17–26.

Koster F, Sauer L, Hoellen F, Ribbat-Idel J, Brautigam K, Rody A, et al. PSMD9 expression correlates with recurrence after radiotherapy in patients with cervical cancer. Oncol Lett. 2020;20(1):581–8.

Wu P, Shi J, Wang Z, Sun W, Zhang H. Evaluate the immune-related eRNA models and signature score to predict the response to immunotherapy in thyroid carcinoma. Cancer Cell Int. 2022;22(1):307.

Ren Y, Qian Y, Ai L, Xie Y, Gao Y, Zhuang Z, et al. TRAPPC4 regulates the intracellular trafficking of PD-L1 and antitumor immunity. Nat Commun. 2021;12(1):5405.

Schetters STT, Rodriguez E, Kruijssen LJW, Crommentuijn MHW, Boon L, Van den Bossche J et al. Monocyte-derived APCs are central to the response of PD1 checkpoint blockade and provide a therapeutic target for combination therapy. J Immunother Cancer. 2020;8(2).

Mayoux M, Roller A, Pulko V, Sammicheli S, Chen S, Sum E et al. Dendritic cells dictate responses to PD-L1 blockade cancer immunotherapy. Sci Transl Med. 2020;12(534).

Peng Q, Qiu X, Zhang Z, Zhang S, Zhang Y, Liang Y, et al. PD-L1 on dendritic cells attenuates T cell activation and regulates response to immune checkpoint blockade. Nat Commun. 2020;11(1):4835.

Lao J, Xu H, Liang Z, Luo C, Shu L, Xie Y, et al. Peripheral changes in T cells predict efficacy of anti-PD-1 immunotherapy in non-small cell lung cancer. Immunobiology. 2023;228(3):152391.

Zhulai G, Oleinik E. Targeting regulatory T cells in anti-PD-1/PD-L1 cancer immunotherapy. Scand J Immunol. 2022;95(3):e13129.

Aoude LG, Bonazzi VF, Brosda S, Patel K, Koufariotis LT, Oey H, et al. Pathogenic germline variants are associated with poor survival in stage III/IV melanoma patients. Sci Rep. 2020;10(1):17687.

Mavaddat N, Dorling L, Carvalho S, Allen J, Gonzalez-Neira A, Keeman R, et al. Pathology of tumors Associated with pathogenic germline variants in 9 breast Cancer susceptibility genes. JAMA Oncol. 2022;8(3):e216744.

Landre T, Justeau G, Assie JB, Chouahnia K, Davoine C, Taleb C, et al. Anti-PD-(L)1 for KRAS-mutant advanced non-small-cell lung cancers: a meta-analysis of randomized-controlled trials. Cancer Immunol Immunotherapy: CII. 2022;71(3):719–26.

Sun H, Liu SY, Zhou JY, Xu JT, Zhang HK, Yan HH, et al. Specific TP53 subtype as biomarker for immune checkpoint inhibitors in lung adenocarcinoma. EBioMedicine. 2020;60:102990.

Wang Y, Chen H, Jiao X, Wu L, Yang Y, Zhang J, et al. PTCH1 mutation promotes antitumor immunity and the response to immune checkpoint inhibitors in colorectal cancer patients. Cancer Immunol Immunotherapy: CII. 2022;71(1):111–20.

Zaretsky JM, Garcia-Diaz A, Shin DS, Escuin-Ordinas H, Hugo W, Hu-Lieskovan S, et al. Mutations Associated with Acquired Resistance to PD-1 blockade in Melanoma. N Engl J Med. 2016;375(9):819–29.

Masuda K, Horinouchi H, Tanaka M, Higashiyama R, Shinno Y, Sato J, et al. Efficacy of anti-PD-1 antibodies in NSCLC patients with an EGFR mutation and high PD-L1 expression. J Cancer Res Clin Oncol. 2021;147(1):245–51.

Teng J, Zhou K, Lv D, Wu C, Feng H. Case Report: PTEN Mutation Induced by anti-PD-1 therapy in Stage IV Lung Adenocarcinoma. Front Pharmacol. 2022;13:714408.

Guo W, Ma J, Guo S, Wang H, Wang S, Shi Q et al. A20 regulates the therapeutic effect of anti-PD-1 immunotherapy in melanoma. J Immunother Cancer. 2020;8(2).

Ricciuti B, Wang X, Alessi JV, Rizvi H, Mahadevan NR, Li YY, et al. Association of High Tumor Mutation Burden in Non-small Cell Lung Cancers with increased Immune Infiltration and Improved Clinical outcomes of PD-L1 Blockade Across PD-L1 expression levels. JAMA Oncol. 2022;8(8):1160–8.

Hellmann MD, Nathanson T, Rizvi H, Creelan BC, Sanchez-Vega F, Ahuja A, et al. Genomic features of response to Combination Immunotherapy in patients with Advanced Non-small-cell Lung Cancer. Cancer Cell. 2018;33(5):843–52. e4.

Wang X, Wu B, Yan Z, Wang G, Chen S, Zeng J, et al. Association of PTPRD/PTPRT Mutation with Better Clinical outcomes in NSCLC patients treated with Immune Checkpoint blockades. Front Oncol. 2021;11:650122.

Zhang W, Shi F, Kong Y, Li Y, Sheng C, Wang S, et al. Association of PTPRT mutations with immune checkpoint inhibitors response and outcome in melanoma and non-small cell lung cancer. Cancer Med. 2022;11(3):676–91.

Hundal J, Lopetegui-Lia N, Vredenburgh J, Discovery. Significance, and utility of JAK2 mutation in squamous cell carcinoma of the lung. Cureus. 2022;14(6):e25913.

PubMed PubMed Central Google Scholar

Kagamu H, Kitano S, Yamaguchi O, Yoshimura K, Horimoto K, Kitazawa M, et al. CD4(+) T-cell immunity in the peripheral blood correlates with response to Anti-PD-1 therapy. Cancer Immunol Res. 2020;8(3):334–44.

Zuazo M, Arasanz H, Bocanegra A, Fernandez G, Chocarro L, Vera R, et al. Systemic CD4 immunity as a key contributor to PD-L1/PD-1 Blockade Immunotherapy Efficacy. Front Immunol. 2020;11:586907.

Kamada T, Togashi Y, Tay C, Ha D, Sasaki A, Nakamura Y, et al. PD-1(+) regulatory T cells amplified by PD-1 blockade promote hyperprogression of cancer. Proc Natl Acad Sci USA. 2019;116(20):9999–10008.

Aguilar D, Bosacoma A, Blanco I, Tura-Ceide O, Serrano-Mollar A, Barbera JA et al. Differences and similarities between the lung transcriptomic profiles of COVID-19, COPD, and IPF patients: a Meta-analysis study of Pathophysiological Signaling pathways. Life (Basel). 2022;12(6).

Doni A, Parente R, Laface I, Magrini E, Cunha C, Colombo FS, et al. Serum amyloid P component is an essential element of resistance against Aspergillus Fumigatus. Nat Commun. 2021;12(1):3739.

Giroux NS, Ding S, McClain MT, Burke TW, Petzold E, Chung HA, et al. Differential chromatin accessibility in peripheral blood mononuclear cells underlies COVID-19 disease severity prior to seroconversion. Sci Rep. 2022;12(1):11714.

Liu SY, Wu YL. Tislelizumab: an investigational anti-PD-1 antibody for the treatment of advanced non-small cell lung cancer (NSCLC). Expert Opin Investig Drugs. 2020;29(12):1355–64.

Desai J, Deva S, Lee JS, Lin CC, Yen CJ, Chao Y et al. Phase IA/IB study of single-agent tislelizumab, an investigational anti-PD-1 antibody, in solid tumors. J Immunother Cancer. 2020;8(1).

Bu D, Luo H, Huo P, Wang Z, Zhang S, He Z, et al. KOBAS-i: intelligent prioritization and exploratory visualization of biological functions for gene enrichment analysis. Nucleic Acids Res. 2021;49(W1):W317–25.

Liu X, Zhang X, Liu C, Mu W, Peng J, Song K. Immune and inflammation: related factor alterations as biomarkers for predicting prognosis and responsiveness to PD-1 monoclonal antibodies in cervical cancer. Discover Oncol. 2022;13(1):96.

Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015;12(5):453–7.

Menden K, Marouf M, Oller S, Dalmia A, Magruder DS, Kloiber K, et al. Deep learning-based cell composition analysis from tissue expression profiles. Sci Adv. 2020;6(30):eaba2619.

Masica DL, Douville C, Tokheim C, Bhattacharya R, Kim R, Moad K, et al. CRAVAT 4: Cancer-Related Analysis of Variants Toolkit. Cancer Res. 2017;77(21):e35–8.

Douville C, Carter H, Kim R, Niknafs N, Diekhans M, Stenson PD, et al. CRAVAT: cancer-related analysis of variants toolkit. Bioinformatics. 2013;29(5):647–8.

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Acknowledgements

We thank all patients and donors who donated blood samples for this study.

This work was supported by National Natural Science Foundation of China (81672627 and 82071863).

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School of Life Science, Northwest University, Xi’an, Shaanxi, 710069, China

Xi Zhang, Rui Chen, Zirong Huo, Wenqing Li, Mengju Jiang, Guodong Su, Yuru Liu, Yu Cai & Yuyan Xiong

Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Medicine, Northwest University, 710069, Shaanxi, Xi’an, China

Xi Zhang & Yuyan Xiong

Department of Lung Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Tianjin Lung Cancer Center, Tianjin, 300060, China

Wuhao Huang & Shengguang Wang

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XZ designed the workflow, drafted and finalized the manuscript, and supervised all aspects of the study. RC built the data-analysis pipeline. ZH and WL processed samples, performed experiments, analyzed and illustrated the data, and prepared the manuscript. YC reviewed the manuscript and provided advice. MJ performed AImmune analysis. GS, YL and WH aided in sample collecting and processing. YX aided in experiment design, supervised experiment, and reviewed the manuscript. SW recruited patients, collected clinical information, supervised all clinical data analysis, and reviewed the manuscript.

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Correspondence to Xi Zhang or Shengguang Wang .

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The protocol was approved by the local Ethics Committee and the Institutional Review Board of Norwest University (approval number: 200402001) and all subjects provided written informed consent.

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The authors declare no competing interests.

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12935_2024_3412_MOESM1_ESM.tif

Supplementary Material 1: figure S1 (A) Summary of validation cohorts, validation methods and additional datasets used in this study. (B) Venn diagrams and volcano plots of DEGs identified in overall comparisons (left) of on- versus pre-treatment blood samples and in individual comparisons (right) between responder and non-responder subgroups. Shared DEGs (Common) identified from unpaired (upper) and pairwise (lower) comparisons and DEGs only seen (Unique) in unpaired comparison are color-coded and plotted (left). Common DEGs seen in responder (upper) and non-responder (lower) subgroups and Unique DEGs in responders are color-coded and plotted (right). Expression changes of eight genes as annotated in volcano plots were confirmed by qRT-PCR. (C) Venn diagram showing the overlap of DEGs across each comparison pairs: overall comparison (Common genes), responder and non-responder subgroups. vs., versus; DEGs, differently expressed genes; Res, responders; Non-res, non-responders.

12935_2024_3412_MOESM2_ESM.tif

Supplementary Material 2: figure S2 Forest plots showing the standardized mean of gene expression difference between normal and tumor tissue as estimated from multiple studies (collected from LCE database). The leftmost column shows the included studies by the first author’s name and publication year and followed by the cohort size. The circles lined up in each column represent the effect estimates from individual studies and the very bottom circles show the pooled result for each gene as annotated. The size of each circle indicates the cohort size of individual study. The horizontal lines through the boxes illustrate the length of the 95% confidence interval in both positive and negative sides. Random-effects model was utilized to evaluate the overall effect as described by z-score and p value. v, versus; N, normal lung tissue; T, lung cancer tissue.

12935_2024_3412_MOESM3_ESM.tif

Supplementary Material 3: figure S3 (A) The hierarchical clustering of all study samples according to the profiles of responder-specific Unique DEGs identified comparing on- versus pre-treatment blood samples. The heatmap visualized the relative expression level of each DEG. Sample status (healthy control, responder etc.) are color-coded and annotated. (B) Venn diagrams and volcano plots of DEGs identified in comparing pre-treatment blood samples of responder and non-responder to healthy control (HC), respectively. Shared DEGs (Common) identified from both comparisons and DEGs only seen (Unique) in non-responders versus HCs are color-coded and plotted. (C) Principal Component Analysis (PCA) plots of healthy control samples grouped by its source (43 new from GSE datasets and 5 original donors). The left panel shows raw RNAseq data before batch effect correction while the right panel shows pre-processed data after batch effect correction. (D) PCA plots of all sample groups reported in this study. (E) Venn diagrams and volcano plots of DEGs identified in comparing on-treatment blood samples of responder and non-responder to healthy control (HC), respectively. Shared DEGs (Common) identified from both comparisons and DEGs only seen (Unique) in responders versus HCs are color-coded and plotted. (F) Venn diagrams and volcano plots of DEGs identified in comparing on-treatment blood samples of responder and non-responder to healthy control (HC), respectively. Shared DEGs (Common) identified from both comparisons and DEGs only seen (Unique) in non-responders versus HCs are color-coded and plotted. vs., versus; DEGs, differently expressed genes; Res, responders; Non-res, non-responders; HCs, healthy controls.

12935_2024_3412_MOESM4_ESM.tif

Supplementary Material 4: figure S4 Bubble plots of the top 30 KEGG pathways regulated in responders (A) and non-responders (B). Bubble with bigger size stands for smaller p value and higher significance. Res, responders; Non-res, non-responders.

12935_2024_3412_MOESM5_ESM.tif

Supplementary Material 5: figure S5 Bubble plots of the top 20 unique GO items regulated in responders (A) and non-responders (B). Bubble with bigger size stands for smaller p value and higher significance. Res, responders; Non-res, non-responders.

12935_2024_3412_MOESM6_ESM.tif

Supplementary Material 6: figure S6 Venn diagram of the top 50 gene sets downregulated (upper) or upregulated (lower) identified in comparison of on- versus pre-treatment samples. The number of unique gene sets are colored in red (responders) or blue (non-responders) while the shared gene sets are annotated in grey text. DEGs, differently expressed genes; Res, responders; Non-res, non-responders.

12935_2024_3412_MOESM7_ESM.tif

Supplementary Material 7: figure S7 Bubble plots of top 20 gene sets downregulated (A) and upregulated (B) in non-responders. Bubble with bigger size stands for higher k/K value ratio and larger fraction of gene was matched with a certain reference gene set.

12935_2024_3412_MOESM8_ESM.tif

Supplementary Material 8: figure S8 Immune cell abundance scores computed by AImmune. (A) Dot plot showing AImmune cell abundance scores of 10 immune cell subsets across five study groups as color-coded and annotated. (B) Immune cell subsets with AImmune scores that are significantly ( p < 0.05) different across on- vs. pre-treatment samples. Pre_NS, pre-treatment samples from non-responders; On_NS, on-treatment samples from non-responders; Pre_RS, pre-treatment samples from responders; On_RS, on-treatment from responders; HCs, healthy controls; CD4, CD4 + T cells; CD8, CD8 + T cells; B, B cells; NK, natural killer cells; NKT, natural killer T cells; DC, dendritic cells; DC_ac, activated dendritic cells; Macro, macrophages; Macro_ac, activated macrophages; Mon, monocytes. All p values were calculated via pairwise comparisons.

12935_2024_3412_MOESM9_ESM.tif

Supplementary Material 9: figure S9 Immune cell fractions estimated by CIBERSORTx. (A) Stacked bar plot showing individual fractions of 22 immune cell subsets in five study groups color-coded and annotated. The different conditions are shown in different colors. (B) Immune cell subsets with CIBERSORTx fractions that are significantly ( p < 0.05) different across on- vs. pre-treatment samples. Pre_NS, pre-treatment samples from non-responders; On_NS, on-treatment samples from non-responders; Pre_RS, pre-treatment samples from responders; On_RS, on-treatment samples from responders; HCs, healthy controls. All p values were calculated via pairwise comparisons.

12935_2024_3412_MOESM10_ESM.tif

Supplementary Material 10: figure S10 Pie charts showing distribution and counts of the reported mutations grouped by sequence ontology as identified in responders (A) and non-responders (B).

12935_2024_3412_MOESM11_ESM.tif

Supplementary Material 11: figure S11 A) Venn diagram comparing the mutated genes identified from the non-responders in discovery cohort versus the mutated genes from non-responder patients (those with progressive disease) of an independent cohort with cervical cancer patients (published dataset). All shared genes are top-ranked in discover cohort (bold and blue in Fig. 6 B). B & C) Patients were stratified into 2 subgroups according to 1 mutational marker set (non-responder set). The Kaplan Meier overall survival curves of non-responder and unaltered subgroups. The Cox regression results indicate hazard ratios of 1.438 (95% confidence interval: 1.092 to 1.896) for non-responders in the overall patient group and 1.496 (95% confidence interval: 1.091 to 2.051) in the PD(L)1 blockade only group. Curves were generated for all immunotherapy patients (B) and patients received anti-PD(L)1 therapy only (C). Non-res, non-responders.

12935_2024_3412_MOESM12_ESM.tif

Supplementary Material 12: figure S12 (A) Venn diagrams and volcano plots of DEGs identified by comparing treated cells versus untreated cells. Shared DEGs (Common) identified from both cell lines and DEGs only seen (Unique) in A549 cell lines are color-coded and plotted. (B) Venn diagram visualization of the significant KEGG pathways, Reactome pathways and gene ontology (GO) items identified by comparing treated cells with untreated cells. The numbers of terms exclusively regulated in HARA-B cells, A549 cells and the shared terms are provided respectively.

12935_2024_3412_MOESM13_ESM.xls

Supplementary Material 13: Table S1 DEG lists identified from NSCLC patients. Table S1a List of DEGs identified in unpaired comparison (all subjects), n = 927. Table S1b List of DEGs identified in paired comparison (all subjects), n = 1211. Table S1c List of DEGs identified in responders, n = 2298. Table S1d List of DEGs identified in non-responders, n = 1025. Table S1e List of DEGs (pre-treatment vs. healthy control) exclusively identified in responders, n = 784. Table S1f List of DEGs (pre-treatment vs. healthy control) exclusively identified in non-responders, n = 589. Table S1g List of DEGs (on-treatment vs. healthy control) exclusively identified in responders, n = 889. Table S1h List of DEGs (on-treatment vs. healthy control) exclusively identified in non-responders, n = 482.

Supplementary Material 14: Table S2 List of PCR primers used in this study.

12935_2024_3412_moesm15_esm.xls.

Supplementary Material 15: Table S3 DEG lists identified from co-cultured lung cancer cell lines. Table S3a List of DEGs identified in HARA-B cells, n = 4792. Table S3b List of DEGs identified in A549 cells, n = 1494.

12935_2024_3412_MOESM16_ESM.xls

Supplementary Material 16: Table S4 KEGG pathways identified from co-cultured lung cancer cell lines. Table S4a Downregulated KEGG pathways identified in HARA-B cells ( p < 0.05), n = 50. Table S4b Upregulated KEGG pathways identified in HARA-B cells ( p < 0.05), n = 90. Table S4c Downregulated KEGG pathways identified in A549 cells ( p < 0.05), n = 4. Table S4d Upregulated KEGG pathways identified in A549 cells ( p < 0.05), n = 0.

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Zhang, X., Chen, R., Huo, Z. et al. Blood-based molecular and cellular biomarkers of early response to neoadjuvant PD-1 blockade in patients with non-small cell lung cancer. Cancer Cell Int 24 , 225 (2024). https://doi.org/10.1186/s12935-024-03412-3

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Efficacy and Safety of thermal ablation for Patients With stage I non-small cell lung cancer.

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Published in Academic Radiology 1 June 2024

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Synchronous percutaneous core-needle biopsy and microwave ablation for stage i non-small cell lung cancer in patients with idiopathic pulmonary fibrosis: initial experience, radiofrequency ablation for stage <iib non‐small cell lung cancer: opportunities, challenges, and the road ahead, stereotactic body radiation therapy and thermal ablation for treatment of nsclc: a systematic literature review and meta-analysis., microwave ablation for inoperable stage i non-small cell lung cancer in patients aged ≥ 70 years: a prospective, single-center study., novel image-guided flexible-probe transbronchial microwave ablation for stage 1 lung cancer, the safety and feasibility of three-dimensional visualization planning system for ct-guided microwave ablation of stage i nsclc (diameter ≤2.5 cm): a pilot study, microwave ablation via a flexible catheter for the treatment of nonsurgical peripheral lung cancer: a pilot study, survival outcomes of radiofrequency ablation compared with surgery in patients with early-stage primary non-small-cell lung cancer: a meta-analysis., computed tomography-guided percutaneous radiofrequency ablation in older adults with early-stage peripheral lung cancer: a retrospective cohort study, imaging following thermal ablation of early lung cancers: expected post-treatment findings and tumour recurrence., related papers.

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Vapers May Be Less Likely to Undergo Lung Cancer Screening

— "former smokers who use e-cigarettes remain at increased risk of lung cancer," researchers say.

by Elizabeth Short , Staff Writer, MedPage Today July 2, 2024

A close up photo of a man smoking an ecigarette.

E-cigarette use among individuals eligible for lung cancer screening was independently associated with a reduced likelihood of screening, a cross-sectional study of U.S. adults revealed.

Compared with those who never used e-cigarettes, current vapers had a lower odds of ever undergoing lung cancer screening (OR 0.79, 95% CI 0.62-1.00) and of being up to date on screening (OR 0.67, 95% CI 0.51-0.88), reported researchers led by Qian Wang, MD, MPH, of Case Western Reserve University in Cleveland.

The associations were more apparent for former (rather than current) smokers of traditional cigarettes. For individuals who previously smoked, those who used e-cigarettes appeared less likely to have undergone lung cancer screening (OR 0.73, 95% CI 0.52-1.04) and had a 46% lower chance of being up to date on screening (OR 0.54, 95% CI 0.37-0.80) compared with those who never used e-cigarettes.

No associations were seen between past e-cigarette use and lung cancer screening use, according to the findings in JAMA Network Open .

"Former smokers who use e-cigarettes remain at increased risk of lung cancer and should be targeted by interventions to improve adherence to LCS [lung cancer screening]," Wang and co-authors concluded.

E-cigarettes are increasingly being used as cessation aids for smokers seeking to quit traditional cigarettes, the research team explained in their introduction, but there have been growing concerns about the potential for lung cancer risk with long-term use, among other concerns .

"Emerging research suggests that e-cigarettes contain definite and probable carcinogens and cause similar cancer-associated gene deregulations as combustible tobacco," wrote Wang and co-authors. "However, it has been shown that two-thirds of individuals currently using e-cigarettes consider e-cigarettes to be less harmful than combustible cigarettes. Thus, individuals who use e-cigarettes may have lower awareness of lung cancer risks."

Their study included more than 20,000 individuals who met the current criteria for lung cancer screening set by the U.S. Preventive Services Task Force (USPSTF). The task force first recommended screening via low-dose CT in 2013, but broadened its criteria for eligibility in 2021.

"I would not see this as 'Well, you shouldn't be smoking an e-cigarette,'" said Nancy Rigotti, MD, of Massachusetts General Hospital in Boston, of the findings from Wang's group. "If you're smoking an e-cigarette and you used to smoke, you still need lung cancer screening."

"It's a reminder for us that we need to make sure that everybody who has recently or are currently smoking cigarettes and fits the eligibility criteria for lung cancer screening gets lung cancer screening," said Rigotti, who was not involved in the study.

Current USPSTF guidelines recommend annual screening via low-dose CT for adults ages 50 to 80 years who have at least a 20 pack-year smoking history and who either currently smoke or have quit in the past 15 years.

But in clinical practice, uptake of the screening recommendations has been " woefully low ," noted Ashley Prosper, MD, of the University of California Los Angeles, who also was not involved in the study.

In the current sample, just 27% of the individuals had undergone lung cancer screening.

"Barriers to lung cancer screening adherence are myriad," Prosper told MedPage Today via email. These include "factors such as participant characteristics (insurance status, income, race, education), healthcare provider factors (whether or not a recommendation for lung screening is made by a provider to an eligible patient), and a number of psychological variables that are unique to lung screening as compared to other cancer screenings -- such as the fear of discovering a lung cancer and stigma associated with smoking."

Wang and colleagues' study included 22,713 individuals from within the 2022 Behavioral Risk Factor Surveillance System who met current USPSTF guidelines for lung cancer screening.

Median age was 62 years and 56% were men. Most were white (77%), while 9% were Black, 7% were Hispanic, and 7% were of another race. Individuals had a median 39 pack-year history of cigarette smoking: a majority still smoked (59%) while the rest were former smokers (41%; median 6 years since quitting).

With regard to e-cigarette use, a majority (55%) had never used them, while 35% were former users and 9% were current users. The vast majority (81%) of the sample had had a routine checkup in the prior year, and nearly two-thirds said they were in good general health.

Overall, 5,885 individuals had undergone screening, with 3,472 (14.6%) up to date on screening and 2,513 (11.4%) no longer up to date.

People who underwent screening tended to be older (64 vs 61 years for those never screened); have lower income, poorer health, more comorbidities, and a greater smoking history (43 vs 38 pack-years); and they were more likely to have attempted quitting in the prior year (18% vs 14%) and live in the Northeast. Individuals in the screening group were also more likely to have reported never using e-cigarettes (57% vs 55%) and were less likely to be uninsured (2% vs 7%).

Study limitations cited by Wang and colleagues included the cross-sectional design, use of self-reported screening and smoking information, and the fact that the study could not account for switching between traditional cigarettes and e-cigarettes and the impact of that on screening uptake.

Elizabeth Short is a staff writer for MedPage Today. She often covers pulmonology and allergy & immunology. Follow

Disclosures

Wang reported no disclosures. Co-authors reported relationships with Regeneron, Mirati, AstraZeneca, Amgen, Sanofi, Pharmaceutical Product Development, and Axella.

Prosper is a member of the American College of Radiology's Lung CT Screening Reporting & Data System (Lung-RADS), is co-director of UCLA's Lung Screening Program, and reported a relationship with the National Institutes of Health.

Rigotti reported a relationship with Achieve Life Sciences.

Primary Source

JAMA Network Open

Source Reference: Wang Q, et al "E-cigarette use and lung cancer screening uptake" JAMA Netw Open 2024; DOI: 10.1001/jamanetworkopen.2024.19648.

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Jafari-Kashi, A.; Rafiee-Pour, H.-A.; Shabani-Nooshabadi, M. A New Strategy to Design Label-Free Electrochemical Biosensor for Ultrasensitive Diagnosis of CYFRA 21–1 as a Biomarker for Detection of Non-Small Cell Lung Cancer. Chemosphere 2022 , 301 , 134636. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Meng, F.; Yu, W.; Chen, C.; Guo, S.; Tian, X.; Miao, Y.; Ma, L.; Zhang, X.; Yu, Y.; Huang, L.; et al. A Versatile Electrochemical Biosensor for the Detection of Circulating MicroRNA toward Non-Small Cell Lung Cancer Diagnosis. Small 2022 , 18 , 2200784. [ Google Scholar ] [ CrossRef ]
Ahmad, A.; Imran, M.; Ahsan, H. Biomarkers as Biomedical Bioindicators: Approaches and Techniques for the Detection, Analysis, and Validation of Novel Biomarkers of Diseases. Pharmaceutics 2023 , 15 , 1630. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Han, K.; Liu, H.; Cui, J.; Liu, Y.; Pan, P. Recent Strategies for Electrochemical Sensing Detection of miRNAs in Lung Cancer. Anal. Biochem. 2023 , 661 , 114986. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Taniguchi, H.; Sen, T.; Rudin, C.M. Targeted Therapies and Biomarkers in Small Cell Lung Cancer. Front. Oncol. 2020 , 10 , 741. [ Google Scholar ] [ CrossRef ] [ PubMed ]
de Jong, C.; Deneer, V.H.M.; Kelder, J.C.; Ruven, H.; Egberts, T.C.G.; Herder, G.J.M. Association between Serum Biomarkers CEA and LDH and Response in Advanced Non-Small Cell Lung Cancer Patients Treated with Platinum-Based Chemotherapy. Thorac. Cancer 2020 , 11 , 1790–1800. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Du, J.; Li, Y.; Wang, L.; Zhou, Y.; Shen, Y.; Xu, F.; Chen, Y. Selective Application of Neuroendocrine Markers in the Diagnosis and Treatment of Small Cell Lung Cancer. Clin. Chim. Acta 2020 , 509 , 295–303. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Huang, Z.; Yan, Y.; Wang, T.; Wang, Z.; Cai, J.; Cao, X.; Yang, C.; Zhang, F.; Wu, G.; Shen, B. Identification of ENO1 as a Prognostic Biomarker and Molecular Target among ENOs in Bladder Cancer. J. Transl. Med. 2022 , 20 , 315. [ Google Scholar ] [ CrossRef ]
Chen, J.M.; Chiu, S.; Chen, K.; Huang, Y.J.; Liao, Y.A.; Yu, C.R. Enolase 1 Differentially Contributes to Cell Transformation in Lung Cancer but Not in Esophageal Cancer. Oncol. Lett. 2020 , 19 , 3189–3196. [ Google Scholar ] [ CrossRef ]
Liao, C.; Xiao, S.; Wang, X. Bench-to-Bedside: Translational Development Landscape of Biotechnology in Healthcare. Health Sci. Rev. 2023 , 7 , 100097. [ Google Scholar ] [ CrossRef ]
Mani, V.; Beduk, T.; Khushaim, W.; Ceylan, A.E.; Timur, S.; Wolfbeis, O.S.; Salama, K.N. Electrochemical Sensors Targeting Salivary Biomarkers: A Comprehensive Review. TrAC Trends Anal. Chem. 2021 , 135 , 116164. [ Google Scholar ] [ CrossRef ]
Hashem, A.; Hossain, M.A.M.; Marlinda, A.R.; Mamun, M.A.; Sagadevan, S.; Shahnavaz, Z.; Simarani, K.; Johan, M.R. Nucleic Acid-Based Electrochemical Biosensors for Rapid Clinical Diagnosis: Advances, Challenges, and Opportunities. Crit. Rev. Clin. Lab. Sci. 2022 , 59 , 156–177. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Sande, M.G.; Rodrigues, J.L.; Ferreira, D.; Silva, C.J.; Rodrigues, L.R. Novel Biorecognition Elements against Pathogens in the Design of State-of-the-Art Diagnostics. Biosensors 2021 , 11 , 418. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Hashem, A.; Hossain, M.A.M.; Marlinda, A.R.; Mamun, M.A.; Simarani, K.; Johan, M.R. Nanomaterials Based Electrochemical Nucleic Acid Biosensors for Environmental Monitoring: A Review. Appl. Surf. Sci. Adv. 2021 , 4 , 100064. [ Google Scholar ] [ CrossRef ]
Brito-Rocha, T.; Constâncio, V.; Henrique, R.; Jerónimo, C. Shifting the Cancer Screening Paradigm: The Rising Potential of Blood-Based Multi-Cancer Early Detection Tests. Cells 2023 , 12 , 935. [ Google Scholar ] [ CrossRef ]
Thenrajan, T.; Alwarappan, S.; Wilson, J. Molecular Diagnosis and Cancer Prognosis—A Concise Review. Diagnostics 2023 , 13 , 766. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Voitechovič, E.; Pauliukaite, R. Electrochemical Multisensor Systems and Arrays in the Era of Artificial Intelligence. Curr. Opin. Electrochem. 2023 , 42 , 101411. [ Google Scholar ] [ CrossRef ]
Singh, D. Nanotechnology-Based Assays for the Detection of Cancer through Sputum. Curr. Anal. Chem. 2023 , 19 , 633–641. [ Google Scholar ] [ CrossRef ]
Bakker, E.; Telting-Diaz, M. Electrochemical Sensors. Anal. Chem. 2002 , 74 , 2781–2800. [ Google Scholar ] [ CrossRef ]
Fan, X.; Deng, D.; Chen, Z.; Qi, J.; Li, Y.; Han, B.; Huan, K.; Luo, L. A Sensitive Amperometric Immunosensor for the Detection of Carcinoembryonic Antigen Using ZnMn 2 O 4 @reduced Graphene Oxide Composites as Signal Amplifier. Sens. Actuators B Chem. 2021 , 339 , 129852. [ Google Scholar ] [ CrossRef ]
Cao, L.; Zhang, W.; Lu, S.; Guo, C.; Wang, P.; Zhang, D.; Ma, W. A Label-Free Electrochemical Immunosensor for CEA Detection on a Novel Signal Amplification Platform of Cu 2 S/Pd/CuO Nanocomposites. Front. Bioeng. Biotechnol. 2021 , 9 , 767717. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Li, Y.; Yang, W.-K.; Fan, M.-Q.; Liu, A. A Sensitive Label-Free Amperometric CEA Immunosensor Based on Graphene-Nafion Nanocomposite Film as an Enhanced Sensing Platform. Anal. Sci. 2011 , 27 , 727–731. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Fu, X.; Wang, J.; Li, N.; Wang, L.; Pu, L. Label-Free Electrochemical Immunoassay of Carcinoembryonic Antigen in Human Serum Using Magnetic Nanorods as Sensing Probes. Microchim. Acta 2009 , 165 , 437–442. [ Google Scholar ] [ CrossRef ]
Hong, Z.; Chen, G.; Yu, S.; Huang, R.; Fan, C. A Potentiometric Aptasensor for Carcinoembryonic Antigen (CEA) on Graphene Oxide Nanosheets Using Catalytic Recycling of DNase I with Signal Amplification. Anal. Methods 2018 , 10 , 5364–5371. [ Google Scholar ] [ CrossRef ]
Taheri, N.; Khoshsafar, H.; Ghanei, M.; Ghazvini, A.; Bagheri, H. Dual-Template Rectangular Nanotube Molecularly Imprinted Polypyrrole for Label-Free Impedimetric Sensing of AFP and CEA as Lung Cancer Biomarkers. Talanta 2022 , 239 , 123146. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Filik, H.; Avan, A.A. Nanostructures for Nonlabeled and Labeled Electrochemical Immunosensors: Simultaneous Electrochemical Detection of Cancer Markers: A Review. Talanta 2019 , 205 , 120153. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Yáñez-Sedeño, P.; Campuzano, S.; Pingarrón, J.M. Multiplexed Electrochemical Immunosensors for Clinical Biomarkers. Sensors 2017 , 17 , 965. [ Google Scholar ] [ CrossRef ]
Han, J. Preparation of a Highly Sensitive Graphene-Based Sensor to Investigate the Effect of Exercise on Electrolytes in Sweat in Hot and Humid Environment. Carbon Lett. 2023 , 33 , 1959–1966. [ Google Scholar ] [ CrossRef ]
Li, Z.; Liu, H. Study on Electrochemical Properties of Lead Calcium Tin Anode for Hydrometallurgy. Alex. Eng. J. 2023 , 82 , 389–395. [ Google Scholar ] [ CrossRef ]
Khanmohammadi, A.; Aghaie, A.; Vahedi, E.; Qazvini, A.; Ghanei, M.; Afkhami, A.; Hajian, A.; Bagheri, H. Electrochemical Biosensors for the Detection of Lung Cancer Biomarkers: A Review. Talanta 2020 , 206 , 120251. [ Google Scholar ] [ CrossRef ]
Vijayan, V.M.; Jothi, L.; Arunagirinathan, R.S.; Nageswaran, G. Recent Advances in the Electrochemical Sensing of Lung Cancer Biomarkers. Biosens. Bioelectron. X 2022 , 12 , 100235. [ Google Scholar ] [ CrossRef ]
Wei, Z.; Zhang, J.; Zhang, A.; Wang, Y.; Cai, X. Electrochemical Detecting Lung Cancer-Associated Antigen Based on Graphene-Gold Nanocomposite. Molecules 2017 , 22 , 392. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Wang, Y.; Luo, J.; Liu, J.; Sun, S.; Xiong, Y.; Ma, Y.; Yan, S.; Yang, Y.; Yin, H.; Cai, X. Label-Free Microfluidic Paper-Based Electrochemical Aptasensor for Ultrasensitive and Simultaneous Multiplexed Detection of Cancer Biomarkers. Biosens. Bioelectron. 2019 , 136 , 84–90. [ Google Scholar ] [ CrossRef ]
Mo, X.; Wang, Y.; Xiao, Q.; Zhou, X.; Li, H. Conjugated Polymer Sensitized Hyperbranched Titanium Dioxide Based Photoelectrochemical Biosensor for Detecting AFP in Serum. Surf. Interfaces 2021 , 24 , 101103. [ Google Scholar ] [ CrossRef ]
Dang, W.; Sun, Y.; Jiao, H.; Xu, L.; Lin, M. AuNPs-NH 2 /Cu-MOF Modified Glassy Carbon Electrode as Enzyme-Free Electrochemical Sensor Detecting H 2 O 2 . J. Electroanal. Chem. 2020 , 856 , 113592. [ Google Scholar ] [ CrossRef ]
Lahcen, A.A.; Rauf, S.; Beduk, T.; Durmus, C.; Aljedaibi, A.; Timur, S.; Alshareef, H.N.; Amine, A.; Wolfbeis, O.S.; Salama, K.N. Electrochemical Sensors and Biosensors Using Laser-Derived Graphene: A Comprehensive Review. Biosens. Bioelectron. 2020 , 168 , 112565. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Anzar, N.; Hasan, R.; Tyagi, M.; Yadav, N.; Narang, J. Carbon Nanotube—A Review on Synthesis, Properties and Plethora of Applications in the Field of Biomedical Science. Sens. Int. 2020 , 1 , 100003. [ Google Scholar ] [ CrossRef ]
Feng, T.; Wang, Y.; Qiao, X. Recent Advances of Carbon Nanotubes-Based Electrochemical Immunosensors for the Detection of Protein Cancer Biomarkers. Electroanalysis 2017 , 29 , 662–675. [ Google Scholar ] [ CrossRef ]
Guo, J.; Han, X.; Wang, J.; Zhao, J.; Guo, Z.; Zhang, Y. Horseradish Peroxidase Functionalized Gold Nanorods as a Label for Sensitive Electrochemical Detection of Alpha-Fetoprotein Antigen. Anal. Biochem. 2015 , 491 , 58–64. [ Google Scholar ] [ CrossRef ]
Lai, W.; Tang, D.; Que, X.; Zhuang, J.; Fu, L.; Chen, G. Enzyme-Catalyzed Silver Deposition on Irregular-Shaped Gold Nanoparticles for Electrochemical Immunoassay of Alpha-Fetoprotein. Anal. Chim. Acta 2012 , 755 , 62–68. [ Google Scholar ] [ CrossRef ]
Niu, C.; Lin, X.; Jiang, X.; Guo, F.; Liu, J.; Liu, X.; Huang, H.; Huang, Y. An Electrochemical Aptasensor for Highly Sensitive Detection of CEA Based on Exonuclease III and Hybrid Chain Reaction Dual Signal Amplification. Bioelectrochemistry 2022 , 143 , 107986. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Jie, G.; Ge, J.; Gao, X.; Li, C. Amplified Electrochemiluminescence Detection of CEA Based on Magnetic Fe 3 O 4 @Au Nanoparticles-Assembled Ru@SiO 2 Nanocomposites Combined with Multiple Cycling Amplification Strategy. Biosens. Bioelectron. 2018 , 118 , 115–121. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Zhai, X.-J.; Wang, Q.-L.; Cui, H.-F.; Song, X.; Lv, Q.-Y.; Guo, Y. A DNAzyme-Catalyzed Label-Free Aptasensor Based on Multifunctional Dendrimer-like DNA Assembly for Sensitive Detection of Carcinoembryonic Antigen. Biosens. Bioelectron. 2021 , 194 , 113618. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Figueroa-Miranda, G.; Wu, C.; Zhang, Y.; Nörbel, L.; Lo, Y.; Tanner, J.A.; Elling, L.; Offenhäusser, A.; Mayer, D. Polyethylene Glycol-Mediated Blocking and Monolayer Morphology of an Electrochemical Aptasensor for Malaria Biomarker Detection in Human Serum. Bioelectrochemistry 2020 , 136 , 107589. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Lichtenberg, J.Y.; Ling, Y.; Kim, S. Non-Specific Adsorption Reduction Methods in Biosensing. Sensors 2019 , 19 , 2488. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Xu, Z.; Han, R.; Liu, N.; Gao, F.; Luo, X. Electrochemical Biosensors for the Detection of Carcinoembryonic Antigen with Low Fouling and High Sensitivity Based on Copolymerized Polydopamine and Zwitterionic Polymer. Sens. Actuators B Chem. 2020 , 319 , 128253. [ Google Scholar ] [ CrossRef ]
Yang, X.; Chen, P.; Zhang, X.; Zhou, H.; Song, Z.; Yang, W.; Luo, X. An Electrochemical Biosensor for HER2 Detection in Complex Biological Media Based on Two Antifouling Materials of Designed Recognizing Peptide and PEG. Anal. Chim. Acta 2023 , 1252 , 341075. [ Google Scholar ] [ CrossRef ]
Asadian, E.; Ghalkhani, M.; Shahrokhian, S. Electrochemical Sensing Based on Carbon Nanoparticles: A Review. Sens. Actuators B Chem. 2019 , 293 , 183–209. [ Google Scholar ] [ CrossRef ]
Yang, C.; Denno, M.E.; Pyakurel, P.; Venton, B.J. Recent Trends in Carbon Nanomaterial-Based Electrochemical Sensors for Biomolecules: A Review. Anal. Chim. Acta 2015 , 887 , 17–37. [ Google Scholar ] [ CrossRef ]
Tiwari, J.N.; Vij, V.; Kemp, K.C.; Kim, K.S. Engineered Carbon-Nanomaterial-Based Electrochemical Sensors for Biomolecules. ACS Nano 2016 , 10 , 46–80. [ Google Scholar ] [ CrossRef ]
Bagyalakshmi, S.; Sivakami, A.; Pal, K.; Sarankumar, R.; Mahendran, C. Manufacturing of Electrochemical Sensors via Carbon Nanomaterials Novel Applications: A Systematic Review. J. Nanoparticle Res. 2022 , 24 , 201. [ Google Scholar ] [ CrossRef ]
Power, A.C.; Gorey, B.; Chandra, S.; Chapman, J. Carbon Nanomaterials and Their Application to Electrochemical Sensors: A Review. Nanotechnol. Rev. 2018 , 7 , 19–41. [ Google Scholar ] [ CrossRef ]
Jothi, L.; Jaganathan, S.K.; Nageswaran, G. An Electrodeposited Au Nanoparticle/Porous Graphene Nanoribbon Composite for Electrochemical Detection of Alpha-Fetoprotein. Mater. Chem. Phys. 2020 , 242 , 122514. [ Google Scholar ] [ CrossRef ]
Li, J.; Zhao, L.; Wang, W.; Liu, Y.; Yang, H.; Kong, J.; Si, F. Polymer-Functionalized Carbon Nanotubes Prepared via Ring-Opening Polymerization for Electrochemical Detection of Carcinoembryonic Antigen. Sens. Actuators B Chem. 2021 , 328 , 129031. [ Google Scholar ] [ CrossRef ]
Lorencova, L.; Bertok, T.; Dosekova, E.; Holazova, A.; Paprckova, D.; Vikartovska, A.; Sasinkova, V.; Filip, J.; Kasak, P.; Jerigova, M. Electrochemical Performance of Ti 3 C 2 Tx MXene in Aqueous Media: Towards Ultrasensitive H 2 O 2 Sensing. Electrochim. Acta 2017 , 235 , 471–479. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Wu, Q.; Li, N.; Wang, Y.; Xu, Y.; Wu, J.; Jia, G.; Ji, F.; Fang, X.; Chen, F.; Cui, X. Ultrasensitive and Selective Determination of Carcinoembryonic Antigen Using Multifunctional Ultrathin Amino-Functionalized Ti 3 C 2 -MXene Nanosheets. Anal. Chem. 2020 , 92 , 3354–3360. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Yun, Q.; Li, L.; Hu, Z.; Lu, Q.; Chen, B.; Zhang, H. Layered Transition Metal Dichalcogenide-Based Nanomaterials for Electrochemical Energy Storage. Adv. Mater. 2020 , 32 , 1903826. [ Google Scholar ] [ CrossRef ]
Wang, Y.-H.; Huang, K.-J.; Wu, X. Recent Advances in Transition-Metal Dichalcogenides Based Electrochemical Biosensors: A Review. Biosens. Bioelectron. 2017 , 97 , 305–316. [ Google Scholar ] [ CrossRef ]
Hou, X.; Li, Y.; Cheng, L.; Feng, X.; Zhang, H.; Han, S. Cobalt-Molybdenum Disulfide Supported on Nitrogen-Doped Graphene towards an Efficient Hydrogen Evolution Reaction. Int. J. Hydrogen Energy 2019 , 44 , 11664–11674. [ Google Scholar ] [ CrossRef ]
Hu, T.; Zhang, M.; Wang, Z.; Chen, K.; Li, X.; Ni, Z. Layer-by-Layer Self-Assembly of MoS 2 /PDDA Hybrid Film in Microfluidic Chips for Ultrasensitive Electrochemical Immunosensing of Alpha-Fetoprotein. Microchem. J. 2020 , 158 , 105209. [ Google Scholar ] [ CrossRef ]
Wang, L.; Xiong, Q.; Xiao, F.; Duan, H. 2D Nanomaterials Based Electrochemical Biosensors for Cancer Diagnosis. Biosens. Bioelectron. 2017 , 89 , 136–151. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Wang, F.; Hu, S. Electrochemical Sensors Based on Metal and Semiconductor Nanoparticles. Microchim. Acta 2009 , 165 , 1–22. [ Google Scholar ] [ CrossRef ]
Islam, T.; Hasan, M.M.; Awal, A.; Nurunnabi, M.; Ahammad, A.J.S. Metal Nanoparticles for Electrochemical Sensing: Progress and Challenges in the Clinical Transition of Point-of-Care Testing. Molecules 2020 , 25 , 5787. [ Google Scholar ] [ CrossRef ] [ PubMed ]
George, J.M.; Antony, A.; Mathew, B. Metal Oxide Nanoparticles in Electrochemical Sensing and Biosensing: A Review. Microchim. Acta 2018 , 185 , 358. [ Google Scholar ] [ CrossRef ] [ PubMed ]
John, A.; Benny, L.; Cherian, A.R.; Narahari, S.Y.; Varghese, A.; Hegde, G. Electrochemical Sensors Using Conducting Polymer/Noble Metal Nanoparticle Nanocomposites for the Detection of Various Analytes: A Review. J. Nanostruct. Chem. 2021 , 11 , 1–31. [ Google Scholar ] [ CrossRef ]
Raghav, R.; Srivastava, S. Immobilization Strategy for Enhancing Sensitivity of Immunosensors: L-Asparagine–AuNPs as a Promising Alternative of EDC–NHS Activated Citrate–AuNPs for Antibody Immobilization. Biosens. Bioelectron. 2016 , 78 , 396–403. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Li, Y.; Chen, Y.; Deng, D.; Luo, L.; He, H.; Wang, Z. Water-Dispersible Graphene/Amphiphilic Pyrene Derivative Nanocomposite: High AuNPs Loading Capacity for CEA Electrochemical Immunosensing. Sens. Actuators B Chem. 2017 , 248 , 966–972. [ Google Scholar ] [ CrossRef ]
Zhao, J.; Guo, Z.; Feng, D.; Guo, J.; Wang, J.; Zhang, Y. Simultaneous Electrochemical Immunosensing of Alpha-Fetoprotein and Prostate Specific Antigen Using a Glassy Carbon Electrode Modified with Gold Nanoparticle-Coated Silica Nanospheres and Decorated with Azure A or Ferrocenecarboxylic Acid. Microchim. Acta 2015 , 182 , 2435–2442. [ Google Scholar ] [ CrossRef ]
Su, B.; Tang, D.; Li, Q.; Tang, J.; Chen, G. Gold–Silver–Graphene Hybrid Nanosheets-Based Sensors for Sensitive Amperometric Immunoassay of Alpha-Fetoprotein Using Nanogold-Enclosed Titania Nanoparticles as Labels. Anal. Chim. Acta 2011 , 692 , 116–124. [ Google Scholar ] [ CrossRef ]
Akbari Nakhjavani, S.; Afsharan, H.; Khalilzadeh, B.; Ghahremani, M.H.; Carrara, S.; Omidi, Y. Gold and Silver Bio/Nano-Hybrids-Based Electrochemical Immunosensor for Ultrasensitive Detection of Carcinoembryonic Antigen. Biosens. Bioelectron. 2019 , 141 , 111439. [ Google Scholar ] [ CrossRef ]
Shi, B.-J.; Shang, L.; Zhang, W.; Jia, L.-P.; Ma, R.-N.; Xue, Q.-W.; Wang, H.-S. Electrochemical Stripping Chemiluminescent Sensor Based on Copper Nanoclusters for Detection of Carcinoembryonic Antigen. Sens. Actuators B Chem. 2021 , 344 , 130291. [ Google Scholar ] [ CrossRef ]
Wang, X.; Liao, X.; Mei, L.; Zhang, M.; Chen, S.; Qiao, X.; Hong, C. An Immunosensor Using Functionalized Cu 2 O/Pt NPs as the Signal Probe for Rapid and Highly Sensitive CEA Detection with Colorimetry and Electrochemistry Dual Modes. Sens. Actuators B Chem. 2021 , 341 , 130032. [ Google Scholar ] [ CrossRef ]
Song, D.; Zheng, J.; Myung, N.V.; Xu, J.; Zhang, M. Sandwich-Type Electrochemical Immunosensor for CEA Detection Using Magnetic Hollow Ni/C@SiO 2 Nanomatrix and Boronic Acid Functionalized CPS@PANI@Au Probe. Talanta 2021 , 225 , 122006. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Zhao, Z.; Wang, P.; Tang, F.; Wang, Y.; Wang, S.; Liu, Q.; Li, Y. Electrochemical Immunosensor Based on Multi-Order Rubik’s Cube-Type Platinum Nickel Nanocubes and Au NPs/cPDA NTs for Detection of CEA. Bioelectrochemistry 2023 , 149 , 108325. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Krishnan, S.; He, X.; Zhao, F.; Zhang, Y.; Liu, S.; Xing, R. Dual Labeled Mesoporous Silica Nanospheres Based Electrochemical Immunosensor for Ultrasensitive Detection of Carcinoembryonic Antigen. Anal. Chim. Acta 2020 , 1133 , 119–127. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Wang, W.; Cui, M.; Song, Z.; Luo, X. An Antifouling Electrochemical Immunosensor for Carcinoembryonic Antigen Based on Hyaluronic Acid Doped Conducting Polymer PEDOT. RSC Adv. 2016 , 6 , 88411–88416. [ Google Scholar ] [ CrossRef ]
Martínez-Rojas, F.; Castañeda, E.; Armijo, F. Conducting Polymer Applied in a Label-Free Electrochemical Immunosensor for the Detection Prostate-Specific Antigen Using Its Redox Response as an Analytical Signal. J. Electroanal. Chem. 2021 , 880 , 114877. [ Google Scholar ] [ CrossRef ]
Lakard, B. Electrochemical Biosensors Based on Conducting Polymers: A Review. Appl. Sci. 2020 , 10 , 6614. [ Google Scholar ] [ CrossRef ]
Sun, X.; Hui, N.; Luo, X. Reagentless and Label-Free Voltammetric Immunosensor for Carcinoembryonic Antigen Based on Polyaniline Nanowires Grown on Porous Conducting Polymer Composite. Microchim. Acta 2017 , 184 , 889–896. [ Google Scholar ] [ CrossRef ]
Song, J.; Teng, H.; Xu, Z.; Liu, N.; Xu, L.; Liu, L.; Gao, F.; Luo, X. Free-Standing Electrochemical Biosensor for Carcinoembryonic Antigen Detection Based on Highly Stable and Flexible Conducting Polypyrrole Nanocomposite. Microchim. Acta 2021 , 188 , 217. [ Google Scholar ] [ CrossRef ]
Wang, J.; Hua, X.; Jin, B. Ultrasensitive Detection of Carcinoembryonic Antigen by Chitosan/Polythiophene/CdTe Electrochemical Biosensor. ACS Omega 2022 , 7 , 45361–45370. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Grunnet, M.; Sorensen, J.B. Carcinoembryonic Antigen (CEA) as Tumor Marker in Lung Cancer. Lung Cancer 2012 , 76 , 138–143. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Harmsma, M.; Schutte, B.; Ramaekers, F.C.S. Serum Markers in Small Cell Lung Cancer: Opportunities for Improvement. Biochim. Biophys. Acta (BBA)-Rev. Cancer 2013 , 1836 , 255–272. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Yan, M.; Fu, L.; Feng, H.; Namadchian, M. Application of Ag nanoparticles decorated on graphene nanosheets for electrochemical sensing of CEA as an important cancer biomarker. Environ. Res. 2023 , 239 , 117363. [ Google Scholar ] [ CrossRef ]
Feng, D.; Chen, L.; Zhang, K.; Zhu, S.; Ying, M.; Jiang, P.; Fu, M.; Wei, Y.; Li, L. Highly Sensitive Immunosensing of Carcinoembryonic Antigen Based on Gold Nanoparticles Dotted PB@PANI Core-Shell Nanocubes as a Signal Probe. J. Anal. Methods Chem. 2023 , 2023 , e7009624. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Ji, Y.; Guo, J.; Ye, B.; Peng, G.; Zhang, C.; Zou, L. An Ultrasensitive Carcinoembryonic Antigen Electrochemical Aptasensor Based on 3D DNA Nanoprobe and Exo III. Biosens. Bioelectron. 2022 , 196 , 113741. [ Google Scholar ] [ CrossRef ]
Yang, H.; Xu, Y.; Hou, Q.; Xu, Q.; Ding, C. Magnetic Antifouling Material Based Ratiometric Electrochemical Biosensor for the Accurate Detection of CEA in Clinical Serum. Biosens. Bioelectron. 2022 , 208 , 114216. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Shamsazar, A.; Soheili-Moghaddam, M.; Asadi, A. A Novel Electrochemical Immunosensor Based on MWCNT/CuO Nanocomposite for Effectively Detection of Carcinoembryonic Antigen (CEA). Microchem. J. 2024 , 196 , 109643. [ Google Scholar ] [ CrossRef ]
Chakraborty, B.; Das, A.; Mandal, N.; Samanta, N.; Das, N.; Chaudhuri, C.R. Label Free, Electric Field Mediated Ultrasensitive Electrochemical Point-of-Care Device for CEA Detection. Sci. Rep. 2021 , 11 , 2962. [ Google Scholar ] [ CrossRef ]
Zhang, K.; Pei, M.; Cheng, Y.; Zhang, Z.; Niu, C.; Liu, X.; Liu, J.; Guo, F.; Huang, H.; Lin, X. A Novel Electrochemical Aptamer Biosensor Based on Tetrahedral DNA Nanostructures and Catalytic Hairpin Assembly for CEA Detection. J. Electroanal. Chem. 2021 , 898 , 115635. [ Google Scholar ] [ CrossRef ]
Zhang, J.; Yang, L.; Pei, J.; Tian, Y.; Liu, J. A Reagentless Electrochemical Immunosensor for Sensitive Detection of Carcinoembryonic Antigen Based on the Interface with Redox Probe-Modified Electron Transfer Wires and Effectively Immobilized Antibody. Front. Chem. 2022 , 10 , 939736. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Liao, X.; Wang, X.; Zhang, M.; Mei, L.; Chen, S.; Qi, Y.; Hong, C. An Immunosensor Based on an Electrochemical-Chemical-Chemical Advanced Redox Cycle Amplification Strategy for the Ultrasensitive Determination of CEA. Anal. Chim. Acta 2021 , 1170 , 338647. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Zhang, M.; Mei, L.; Zhang, L.; Wang, X.; Liao, X.; Qiao, X.; Hong, C. Ti3C2 MXene Anchors CuAu-LDH Multifunctional Two-Dimensional Nanomaterials for Dual-Mode Detection of CEA in Electrochemical Immunosensors. Bioelectrochemistry 2021 , 142 , 107943. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Liao, X.; Wang, X.; Ma, C.; Zhang, L.; Zhao, C.; Chen, S.; Li, K.; Zhang, M.; Mei, L.; Qi, Y.; et al. Enzyme-Free Sandwich-Type Electrochemical Immunosensor for CEA Detection Based on the Cooperation of an Ag/g-C 3 N 4 -Modified Electrode and Au@SiO 2 /Cu 2 O with Core-Shell Structure. Bioelectrochemistry 2021 , 142 , 107931. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Jozghorbani, M.; Fathi, M.; Kazemi, S.H.; Alinejadian, N. Determination of Carcinoembryonic Antigen as a Tumor Marker Using a Novel Graphene-Based Label-Free Electrochemical Immunosensor. Anal. Biochem. 2021 , 613 , 114017. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Yang, G.; Xiao, Z.; Tang, C.; Deng, Y.; Huang, H.; He, Z. Recent Advances in Biosensor for Detection of Lung Cancer Biomarkers. Biosens. Bioelectron. 2019 , 141 , 111416. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Ma, E.; Wang, P.; Yang, Q.; Yu, H.; Pei, F.; Zheng, Y.; Liu, Q.; Dong, Y.; Li, Y. Electrochemical Immunosensors for Sensitive Detection of Neuron-Specific Enolase Based on Small-Size Trimetallic Au@Pd^Pt Nanocubes Functionalized on Ultrathin MnO 2 Nanosheets as Signal Labels. ACS Biomater. Sci. Eng. 2020 , 6 , 1418–1427. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Wang, H.; Han, H.; Ma, Z. Conductive Hydrogel Composed of 1,3,5-Benzenetricarboxylic Acid and Fe 3+ Used as Enhanced Electrochemical Immunosensing Substrate for Tumor Biomarker. Bioelectrochemistry 2017 , 114 , 48–53. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Lv, C.-L.; Tang, C.; Zhou, H.; Wang, A.-J.; Feng, J.-J.; Cheang, T.Y. Self-Supported PtPdMnCoFe High-Entropy Alloy with Nanochain-like Internetworks for Ultrasensitive Electrochemical Immunoassay of Biomarker. Sens. Actuators B Chem. 2024 , 401 , 135041. [ Google Scholar ] [ CrossRef ]
Aydın, E.B.; Aydın, M.; Sezgintürk, M.K. Selective and Ultrasensitive Electrochemical Immunosensing of NSE Cancer Biomarker in Human Serum Using Epoxy-Substituted Poly(Pyrrole) Polymer Modified Disposable ITO Electrode. Sens. Actuators B Chem. 2020 , 306 , 127613. [ Google Scholar ] [ CrossRef ]
Yu, X.; Li, X.; Zhang, S.; Jia, Y.; Xu, Z.; Li, X.; Chen, Z.; Li, Y. Ultrasensitive Electrochemical Detection of Neuron-Specific Enolase Based on Spiny Core-Shell Au/CuxO@CeO 2 Nanocubes. Bioelectrochemistry 2021 , 138 , 107693. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Acero Sánchez, J.L.; Fragoso, A.; Joda, H.; Suárez, G.; McNeil, C.J.; O’Sullivan, C.K. Site-Directed Introduction of Disulfide Groups on Antibodies for Highly Sensitive Immunosensors. Anal. Bioanal. Chem. 2016 , 408 , 5337–5346. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Fang, Y.; Li, Y.; Zhang, M.; Cui, B.; Hu, Q.; Wang, L. A Novel Electrochemical Strategy Based on Porous 3D Graphene-Starch Architecture and Silver Deposition for Ultrasensitive Detection of Neuron-Specific Enolase. Analyst 2019 , 144 , 2186–2194. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Zhang, C.; Ma, Z. PtCu Nanoprobe-Initiated Cascade Reaction Modulated Iodide-Responsive Sensing Interface for Improved Electrochemical Immunosensor of Neuron-Specific Enolase. Biosens. Bioelectron. 2019 , 143 , 111612. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Tang, C.; Wang, P.; Zhou, K.; Ren, J.; Wang, S.; Tang, F.; Li, Y.; Liu, Q.; Xue, L. Electrochemical Immunosensor Based on Hollow Porous Pt Skin AgPt Alloy/NGR as a Dual Signal Amplification Strategy for Sensitive Detection of Neuron-Specific Enolase. Biosens. Bioelectron. 2022 , 197 , 113779. [ Google Scholar ] [ CrossRef ]
Huang, X.; Miao, J.; Fang, J.; Xu, X.; Wei, Q.; Cao, W. Ratiometric Electrochemical Immunosensor Based on L-Cysteine Grafted Ferrocene for Detection of Neuron Specific Enolase. Talanta 2022 , 239 , 123075. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Karaman, C.; Bölükbaşı, Ö.S.; Yola, B.B.; Karaman, O.; Atar, N.; Yola, M.L. Electrochemical Neuron-Specific Enolase (NSE) Immunosensor Based on CoFe 2 O 4 @Ag Nanocomposite and AuNPs@MoS 2 /rGO. Anal. Chim. Acta 2022 , 1200 , 339609. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Fan, D.; Luo, J.; Gong, Z.; Wang, H.; Ma, H.; Wu, D.; Wei, Q.; Ju, H. Polyacrylic Acid/Polyethylene Glycol Hybrid Antifouling Interface for Photoelectrochemical Immunosensing of NSE Based on ZnO/CdSe. Anal. Chim. Acta 2023 , 1254 , 341085. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Yang, T.; Yu, R.; Yan, Y.; Zeng, H.; Luo, S.; Liu, N.; Morrin, A.; Luo, X.; Li, W. A Review of Ratiometric Electrochemical Sensors: From Design Schemes to Future Prospects. Sens. Actuators B Chem. 2018 , 274 , 501–516. [ Google Scholar ] [ CrossRef ]
Zhou, J.; Zhang, C.; Chen, Y.; Wang, Z.; Lan, L.; Wang, Y.; Han, B.; Pan, M.; Jiao, J.; Chen, Q. A Simple Immunosensor for Alpha-Fetoprotein Determination Based on Gold Nanoparticles-Dextran-Reduced Graphene Oxide. J. Electroanal. Chem. 2019 , 833 , 126–132. [ Google Scholar ] [ CrossRef ]
Wang, Y.; Qu, Y.; Ye, X.; Wu, K.; Li, C. Fabrication of an Electrochemical Immunosensor for α-Fetoprotein Based on a Poly-L-Lysine-Single-Walled Carbon Nanotubes/Prussian Blue Composite Film Interface. J. Solid State Electrochem. 2016 , 20 , 2217–2222. [ Google Scholar ] [ CrossRef ]
Lin, J.; Zhao, Y.; Wei, Z.; Wang, W. Chemiluminescence Immunoassay Based on Dual Signal Amplification Strategy of Au/Mesoporous Silica and Multienzyme Functionalized Mesoporous Silica. Mater. Sci. Eng. B 2011 , 176 , 1474–1478. [ Google Scholar ] [ CrossRef ]
Grubisha, D.S.; Lipert, R.J.; Park, H.-Y.; Driskell, J.; Porter, M.D. Femtomolar Detection of Prostate-Specific Antigen: An Immunoassay Based on Surface-Enhanced Raman Scattering and Immunogold Labels. Anal. Chem. 2003 , 75 , 5936–5943. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Fang, X.; Liu, J.; Wang, J.; Zhao, H.; Ren, H.; Li, Z. Dual Signal Amplification Strategy of Au Nanopaticles/ZnO Nanorods Hybridized Reduced Graphene Nanosheet and Multienzyme Functionalized Au@ZnO Composites for Ultrasensitive Electrochemical Detection of Tumor Biomarker. Biosens. Bioelectron. 2017 , 97 , 218–225. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Xiao, H.; Wei, S.; Gu, M.; Chen, Z.; Cao, L. A Sandwich-Type Electrochemical Immunosensor Using rGO-TEPA-Thi-Au as Sensitive Platform and CMK-3@AuPtNPs as Signal Probe for AFP Detection. Microchem. J. 2021 , 170 , 106641. [ Google Scholar ] [ CrossRef ]
Sun, D.; Li, H.; Li, M.; Li, C.; Qian, L.; Yang, B. Electrochemical Immunosensors with AuPt-Vertical Graphene/Glassy Carbon Electrode for Alpha-Fetoprotein Detection Based on Label-Free and Sandwich-Type Strategies. Biosens. Bioelectron. 2019 , 132 , 68–75. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Rong, S.; Zou, L.; Li, Y.; Guan, Y.; Guan, H.; Zhang, Z.; Zhang, Y.; Gao, H.; Yu, H.; Zhao, F.; et al. An Ultrasensitive Disposable Sandwich-Configuration Electrochemical Immunosensor Based on OMC@AuNPs Composites and AuPt-MB for Alpha-Fetoprotein Detection. Bioelectrochemistry 2021 , 141 , 107846. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Bölükbaşi, Ö.S.; Yola, B.B.; Karaman, C.; Atar, N.; Yola, M.L. Electrochemical α-Fetoprotein Immunosensor Based on Fe 3 O 4 NPs@covalent Organic Framework Decorated Gold Nanoparticles and Magnetic Nanoparticles Including SiO 2 @TiO 2 . Microchim. Acta 2022 , 189 , 242. [ Google Scholar ] [ CrossRef ]
Li, W.; Chen, M.; Liang, J.; Lu, C.; Zhang, M.; Hu, F.; Zhou, Z.; Li, G. Electrochemical Aptasensor for Analyzing Alpha-Fetoprotein Using RGO–CS–Fc Nanocomposites Integrated with Gold–Platinum Nanoparticles. Anal. Methods 2020 , 12 , 4956–4966. [ Google Scholar ] [ CrossRef ]
Wei, T.; Zhang, W.; Tan, Q.; Cui, X.; Dai, Z. Electrochemical Assay of the Alpha Fetoprotein-L3 Isoform Ratio to Improve the Diagnostic Accuracy of Hepatocellular Carcinoma. Anal. Chem. 2018 , 90 , 13051–13058. [ Google Scholar ] [ CrossRef ]
Sampurno, F.H.H.; Pratiwi, S.D.; Putra, N.P.P. Correlation Between CEA Serum Level on NSCLC Patients with EGFR Mutation from Tissue and Plasma Sample. J. Respirologi Indones. 2022 , 42 , 97–106. [ Google Scholar ] [ CrossRef ]
Recek, N.; Jaganjac, M.; Kolar, M.; Milkovic, L.; Mozetič, M.; Stana-Kleinschek, K.; Vesel, A. Protein Adsorption on Various Plasma-Treated Polyethylene Terephthalate Substrates. Molecules 2013 , 18 , 12441–12463. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Choi, Y.; Tran, H.-V.; Lee, T.R. Self-Assembled Monolayer Coatings on Gold and Silica Surfaces for Antifouling Applications: A Review. Coatings 2022 , 12 , 1462. [ Google Scholar ] [ CrossRef ]
Wang, J.; Hui, N. Zwitterionic Poly(Carboxybetaine) Functionalized Conducting Polymer Polyaniline Nanowires for the Electrochemical Detection of Carcinoembryonic Antigen in Undiluted Blood Serum. Bioelectrochemistry 2019 , 125 , 90–96. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Ding, M.; Zha, L.; Wang, H.; Liu, J.; Chen, P.; Zhao, Y.; Jiang, L.; Li, Y.; Ouyang, R.; Miao, Y. A Frogspawn-like Ag@C Core–Shell Structure for an Ultrasensitive Label-Free Electrochemical Immunosensing of Carcinoembryonic Antigen in Blood Plasma. RSC Adv. 2021 , 11 , 16339–16350. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Wu, Y.; Xue, P.; Hui, K.M.; Kang, Y. A Paper-Based Microfluidic Electrochemical Immunodevice Integrated with Amplification-by-Polymerization for the Ultrasensitive Multiplexed Detection of Cancer Biomarkers. Biosens. Bioelectron. 2014 , 52 , 180–187. [ Google Scholar ] [ CrossRef ]
Yuan, Y.; Liu, B.; Wang, T.; Li, N.; Zhang, Z.; Zhang, H. Electrochemical Microfluidic Paper-Based Analytical Devices for Tumor Marker Detection. TrAC Trends Anal. Chem. 2022 , 157 , 116816. [ Google Scholar ] [ CrossRef ]
Zhou, C.; Cui, K.; Liu, Y.; Hao, S.; Zhang, L.; Ge, S.; Yu, J. Ultrasensitive Microfluidic Paper-Based Electrochemical/Visual Analytical Device via Signal Amplification of Pd@Hollow Zn/Co Core–Shell ZIF67/ZIF8 Nanoparticles for Prostate-Specific Antigen Detection. Anal. Chem. 2021 , 93 , 5459–5467. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Pavithra, M.; Muruganand, S.; Parthiban, C. Development of Novel Paper Based Electrochemical Immunosensor with Self-Made Gold Nanoparticle Ink and Quinone Derivate for Highly Sensitive Carcinoembryonic Antigen. Sens. Actuators B Chem. 2018 , 257 , 496–503. [ Google Scholar ] [ CrossRef ]
Cao, L.; Fang, C.; Zeng, R.; Zhao, X.; Zhao, F.; Jiang, Y.; Chen, Z. A Disposable Paper-Based Microfluidic Immunosensor Based on Reduced Graphene Oxide-Tetraethylene Pentamine/Au Nanocomposite Decorated Carbon Screen-Printed Electrodes. Sens. Actuators B Chem. 2017 , 252 , 44–54. [ Google Scholar ] [ CrossRef ]
Yun, J.W.; Lee, S.; Kim, H.M.; Chun, S.; Engleman, E.G.; Kim, H.C.; Kang, E.-S. A Novel Type of Blood Biomarker: Distinct Changes of Cytokine-Induced Stat Phosphorylation in Blood t Cells between Colorectal Cancer Patients and Healthy Individuals. Cancers 2019 , 11 , 1157. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Wang, N.; Zhao, X.; Chen, H.; Bai, L.; Xu, H.; Wang, W.; Yang, H.; Wei, D.; Yang, L. Fabrication of Novel Electrochemical Immunosensor by Mussel-Inspired Chemistry and Surface-Initiated PET-ATRP for the Simultaneous Detection of CEA and AFP. React. Funct. Polym. 2020 , 154 , 104632. [ Google Scholar ] [ CrossRef ]
Yang, H.; Bao, J.; Huo, D.; Zeng, Y.; Wang, X.; Samalo, M.; Zhao, J.; Zhang, S.; Shen, C.; Hou, C. Au Doped Poly-Thionine and Poly-m-Cresol Purple: Synthesis and Their Application in Simultaneously Electrochemical Detection of Two Lung Cancer Markers CEA and CYFRA21-1. Talanta 2021 , 224 , 121816. [ Google Scholar ] [ CrossRef ] [ PubMed ]
Dhanapala, L.; Krause, C.E.; Jones, A.L.; Rusling, J.F. Printed Electrodes in Microfluidic Arrays for Cancer Biomarker Protein Detection. Biosensors 2020 , 10 , 115. [ Google Scholar ] [ CrossRef ]
Dhanapala, L.; Jones, A.L.; Czarnecki, P.; Rusling, J.F. Sub-Zeptomole Detection of Biomarker Proteins Using a Microfluidic Immunoarray with Nanostructured Sensors. Anal. Chem. 2020 , 92 , 8021–8025. [ Google Scholar ] [ CrossRef ]

Sensing Strategy	Technology	Linear Detection Range	Limit of Detection	Real Sample	Ref.
Self-assembled, label-free 3D DNA nanoprobe and exonuclease III-assisted signal amplification	DPV	10 fg/mL to 50 ng/mL	4.88 fg/mL	Serum	[ ]
Ratiometric electrochemical detection using an aptamer and an internal standard	DPV	1 pg/mL to 1 μg/mL	0.62 pg/mL	Serum	[ ]
Sandwich-type assay using primary anti-CEA antibody immobilized on MWCNT/CuO nanocomposite-modified electrode, CEA antigen, and secondary anti-CEA antibody conjugated to Fe O nanoparticles	DPV	0.005 ng/mL to 4 ng/mL	1.9 pg/mL	Serum	[ ]
Sensing strategy exonuclease III and hybrid chain reaction dual signal amplification	I-T	10 pg/mL to 100 ng/mL	0.84 pg/mL	Serum	[ ]
Label-free, electric field-mediated electrochemical detection using a graphene–ZnO nanorod heterostructure	EIS	0.001 pg/mL to 10 pg/mL	1 fg/mL	-	[ ]
Electrochemical aptamer biosensor based on tetrahedral DNA nanostructures and catalytic hairpin assembly	DPV	1 pg/mL to 30,000 pg/mL	0.04567 pg/mL	Serum	[ ]
Electrochemical immunosensor based on redox probe-modified electron transfer wires and an immobilized antibody	DPV	10 pg/mL to 100 ng/mL	0.6 pg/mL	Serum	[ ]
Electrochemical immunosensor with RCA	DPV	0.01 pg/mL to 80 ng/mL	0.0037 pg/mL	Serum	[ ]
Sandwich-type electrochemical immunosensor using magnetic hollow Ni/C@SiO2 nanomatrix and a boronic acid-functionalized CPS@PANI@Au probe	DPV	0.006–12.00 ng/mL	1.56 pg/mL	Serum	[ ]
Electrochemical immunosensor using Ti C MXene-anchored CuAu-LDH as signal enhancer	I-T/DPV	0.0001–80 ng/mL	33.6 fg/mL	Serum	[ ]
Enzyme-free sandwich-type electrochemical immunosensor using a Ag/g-C N -modified electrode and a Au@SiO /Cu O signal probe	I-T	0.01 pg/mL to 80 ng/mL	0.0038 pg/mL	Serum	[ ]
Label-free electrochemical immunosensor based on graphene oxide	EIS	0.1 to 5 ng/mL	0.05 ng/mL	Serum	[ ]

Sensing Strategy	Technology	Linear Detection Range	Limit of Detection	Real Sample	Ref.
Label-free electrochemical immunosensor using PtPdMnCoFe HEAINN as signal amplifier	DPV	0.1 pg/mL to 200 ng/mL	0.0036 pg/mL	Serum	[ ]
Label-free electrochemical impedimetric immunosensor using an epoxy-substituted polypyrrole (P(Pyr-Epx)) polymer-modified disposable ITO electrode	EIS	0.02 pg/mL to 7.5 pg/mL	6.1 fg/mL	Serum	[ ]
Label-free electrochemical immunoassay based on anti-NSE antibodies immobilized on a AuNP-modified conductive hydrogel film	DPV	1 pg/mL to 200 ng/mL	0.26 pg/mL	-	[ ]
Sandwich-type electrochemical immunosensor using Au/Cu x O@CeO as label material and AuPt NSNs as substrate	I-T	50 fg/mL to 100 ng/mL	31.3 fg/mL	Serum	[ ]
Sandwich immunoassay using anti-NSE21 antibody modified with disulfide groups via carbohydrate residues as the capture antibody and anti-NSE17-HRP conjugate as the reporter antibody	DPV	0–25 ng/mL	4.6 ng/mL	-	[ ]
A 3D graphene–starch-modified immunoelectrode to capture antigens, AuNP-loaded antibody tags to catalyze silver deposition, and direct detection of AgNPs using stripping voltammetry for signal amplification	LSV	0.02 pg/mL to 35 ng/mL	0.008 pg/mL	Serum	[ ]
PtCu nanoprobe-initiated cascade reaction and iodide-responsive sensing interface	SWV	0.0001 to 100 ng/mL	52.14 fg/mL	Serum	[ ]
Sandwich-type electrochemical immunosensor using HP-AgPt/NGR as a dual signal amplification label and PPy-PEDOT-Au as the substrate	I-T	50 fg/mL to 100 ng/mL	18.5 fg/mL	Serum	[ ]
Ratiometric electrochemical immunosensor based on Cu-MOF-Au as the electrode sensing surface and Fc-L-Cys as the label of Ab2	DPV	1 pg/mL to 1 μg/mL	0.011 pg/mL	Serum	[ ]
An electrochemical NSE immunosensor using a AuNPs@MoS /rGO platform and a CoFe O @Ag label for signal amplification	DPV	0.01 to 1.00 pg/mL	3.00 fg/mL	Serum	[ ]
PEC immunosensing using ZnO/CdSe and an antifouling interface	DPV	0.10 pg/mL–100 ng/mL	34 fg/mL	Serum	[ ]

Sensing Strategy	Technology	Linear Detection Range	Limit of Detection	Real Sample	Ref.
Electrochemical immunosensor based on a AuNP–dextran–rGO nanocomposite	DPV	0.01–20 ng/mL	0.05 pg/mL	Serum	[ ]
Electrochemical immunosensing using an anti-alpha fetoprotein antibody labeled with horseradish peroxidase immobilized on poly-L-lysine-functionalized SWCNT/PB composite film	DPV	0.05–10.0 ng/mL 10.0–50.0 ng/mL	0.011 ng/mL	Serum	[ ]
Chemiluminescent immunoassay based on dual signal amplification using HRP and an HRP-labeled antibody co-immobilized on mesoporous silica nanoparticles	ECL	0.01 to 0.5 ng/mL 0.5 to 100 ng/mL	0.005 ng/mL	Serum	[ ]
Sandwich-type electrochemical immunosensor using a signal amplification strategy	DPV	0.02–10,000 pg/mL 10,000–100,000 pg/mL	0.01 pg/mL	Serum	[ ]
Sandwich-type electrochemical immunosensor using rGO-TEPA-Thi-Au as a sensitive platform and CMK-3@AuPtNPs as a signal probe	I-T	0.005 to 100 ng/mL	0.0022 ng/mL	Serum	[ ]
Monitoring the electrochemical response current of AuPt-vertical graphene/GCE for the oxidation of the methyl orange redox probe	DPV	1 fg/mL to 100 ng/mL	0.7 fg/mL	Serum	[ ]
Ordered mesoporous carbon (OMC) doped with AuNPs as a substrate to immobilize AFP antibodies, along with AuPt-MB nanorods as signal probes to bind secondary AFP antibodies and amplify detection	DPV	10 fg/mL to 100 ng/mL	3.33 fg/mL	Serum	[ ]
Electrochemical immunosensor based on Fe O NPs@COF-decorated gold nanoparticles and magnetic nanoparticles including SiO @TiO	DPV	0.01 pg/mL to 1 pg/mL	3.30 fg/mL	Serum	[ ]
Label-free electrochemical aptasensing using rGO–chitosan–Fc nanocomposites and Au-Pt NPs	DPV	0.001 to 10.0 mg/mL	0.3013 ng/mL	Serum	[ ]

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Zheng, R.; Wu, A.; Li, J.; Tang, Z.; Zhang, J.; Zhang, M.; Wei, Z. Progress and Outlook on Electrochemical Sensing of Lung Cancer Biomarkers. Molecules 2024 , 29 , 3156. https://doi.org/10.3390/molecules29133156

Zheng R, Wu A, Li J, Tang Z, Zhang J, Zhang M, Wei Z. Progress and Outlook on Electrochemical Sensing of Lung Cancer Biomarkers. Molecules . 2024; 29(13):3156. https://doi.org/10.3390/molecules29133156

Zheng, Rui, Aochun Wu, Jiyue Li, Zhengfang Tang, Junping Zhang, Mingli Zhang, and Zheng Wei. 2024. "Progress and Outlook on Electrochemical Sensing of Lung Cancer Biomarkers" Molecules 29, no. 13: 3156. https://doi.org/10.3390/molecules29133156

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Introduction
Conclusions
Article Information

A, Incidence of lung cancer in survivors of head and neck cancer randomized to low-dose computed tomography (CT) chest vs chest radiography. B, Overall survival in survivors of head and neck cancer randomized to low-dose CT chest vs chest radiography. HR indicates hazard ratio.

Trial Protocol

eFigure. Flow Diagram of Cohort Selection

Data Sharing Statement

Most Survivors of Head and Neck Cancer Should Be Offered Lung Cancer Screening JAMA Otolaryngology–Head & Neck Surgery Invited Commentary December 1, 2021 Sean T. Massa, MD, MSCI; James A. Gallogly, MD; Ronald J. Walker, MD

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Cramer JD , Grauer J , Sukari A , Nagasaka M. Incidence of Second Primary Lung Cancer After Low-Dose Computed Tomography vs Chest Radiography Screening in Survivors of Head and Neck Cancer : A Secondary Analysis of a Randomized Clinical Trial . JAMA Otolaryngol Head Neck Surg. 2021;147(12):1071–1078. doi:10.1001/jamaoto.2021.2776

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Incidence of Second Primary Lung Cancer After Low-Dose Computed Tomography vs Chest Radiography Screening in Survivors of Head and Neck Cancer : A Secondary Analysis of a Randomized Clinical Trial

1 Department of Otolaryngology–Head and Neck Surgery, Wayne State University School of Medicine, Karmanos Cancer Institute, Detroit, Michigan
2 Karmanos Cancer Institute, Department of Oncology, Wayne State University School of Medicine, Detroit, Michigan
3 Division of Hematology and Oncology, University of California Irvine School of Medicine, Orange
4 Division of Neurology, Department of Internal Medicine, St Marianna University School of Medicine, Kawasaki, Kanagawa, Japan
Invited Commentary Most Survivors of Head and Neck Cancer Should Be Offered Lung Cancer Screening Sean T. Massa, MD, MSCI; James A. Gallogly, MD; Ronald J. Walker, MD JAMA Otolaryngology–Head & Neck Surgery

Question What is the role of lung cancer screening in survivors of head and neck cancer?

Findings In this ad hoc secondary analysis of a large randomized clinical trial, 171 head and neck cancer survivors with a long smoking history were identified. These individuals had 2.5 times the rate of lung cancer as those without prior head and neck cancer.

Meaning These results support annual low-dose computed tomography chest screening for lung cancer in head and neck cancer survivors who have a significant smoking history and are fit to undergo curative treatment.

Importance In head and neck cancer survivors, lung cancer screening may aid in detecting a second primary lung cancer or metastatic head and neck cancer earlier in the course of disease, which may improve treatment outcomes. However, no randomized data exist to assess the value of lung cancer screening in this population.

Objective To evaluate the incidence of second primary lung cancer in survivors of head and neck cancer survivors with screening low-dose computed tomography (CT) vs chest radiography (CXR).

Design, Setting and Participants For this ad hoc secondary analysis of a randomized clinical trial, head and neck cancer survivors were identified from the National Lung Screening Trial, which enrolled participants from August 2002 to April 2004. This randomized clinical trial compared screening using low-dose CT chest vs CXR in patients aged 55 to 74 years with at least a 30 pack-year history of cigarette smoking and who were current smokers or had quit within the past 15 years and who were at high risk for lung cancer. The incidences of second primary lung cancer and second primary head and neck cancer were compared with screening using low-dose CT vs CXR. Data were analyzed from December 1, 2020, to June 30, 2021.

Interventions Screening low-dose CT of the chest vs CXR.

Main Outcomes and Measures The primary outcome was the incidence of a second primary lung cancer.

Results Among 53 452 enrolled participants, we identified 171 survivors of head and neck cancer, of whom 82 were screened with low-dose CT of the chest and 89 with CXR. Participants’ mean (SD) age was 61 (5) years, and 132 were men (77.2%). The incidence of lung cancer was higher among head and neck cancer survivors compared with participants without head and neck cancer (2080 per 100 000 person-years [2.1%] vs 609 per 100 000 person-years [0.6%]; adjusted rate ratio, 2.54; 95% CI, 1.63-3.95). In head and neck cancer survivors, the incidence of second primary lung cancer was 2610 cases per 100 000 person-years in the low-dose CT group vs 1594 cases per 100 000 person-years in the CXR group (rate ratio, 1.55; 95% CI, 0.59-3.63). In head and neck cancer survivors, overall survival was 7.07 years with low-dose CT vs 6.66 years with CXR (log-rank P = .48).

Conclusions and Relevance The results of this ad hoc secondary analysis of a randomized clinical trial suggest that head and neck cancer survivors are at especially high risk for a second primary lung cancer. These findings underscore the importance of low-dose CT screening in head and neck cancer survivors with significant cigarette smoking history who are fit to undergo treatment with curative intent.

Imaging after cancer treatment is used to identify residual cancer, recurrent initial cancer, and/or screen for second primary cancers at an earlier stage to hopefully provide curative treatment and improve subsequent outcomes. Among survivors of head and neck cancer (HNC), to our knowledge, no randomized data exist to help guide surveillance imaging beyond 6 months after treatment, and approaches to posttreatment imaging surveillance for HNC vary widely. As a result, the National Comprehensive Cancer Network Guidelines and American Society of Clinical Oncology HNC Survivorship Care Guideline do not recommend routine surveillance imaging for HNC beyond 6 months after treatment unless there are concerning signs or symptoms, 1 , 2 whereas the American College of Radiology Neck Imaging Reporting and Data Systems white paper recommends surveillance imaging for the first 2 years after treatment. 3

Survivors of HNC are at high risk of second primary cancers such as lung cancer, as 70% to 80% of HNC is associated with prior tobacco use. 4 - 6 Current US Preventive Services Task Force (USPSTF) guidelines recommend low-dose computed tomography (CT) lung cancer screening annually for those aged 50 to 79 years with 20 pack-years or more, regardless of prior cancer status. 7 However, USPSTF guidelines do not mention HNC as a risk factor for lung cancer. 7 Furthermore, adherence to lung cancer screening recommendations is low, with only 14% of eligible individuals completing recommended screening. 8

To examine the effects of lung cancer screening in survivors of HNC, we performed an ad hoc secondary analysis of a randomized clinical trial of lung cancer screening. Our primary goals were to (1) compare the rate of abnormal imaging findings in survivors of HNC vs participants without prior HNC, (2) compare the incidence of a secondary primary lung cancer (SPLC) in survivors of HNC vs participants without prior HNC, and (3) examine the benefits of low-dose CT vs chest radiography (CXR) lung cancer screening in survivors of HNC.

For this ad hoc secondary analysis of a randomized clinical trial, we used data from the National Lung Screening Trial (NLST), the details of which have been previously published. 9 Briefly, this trial randomized participants at high risk for lung cancer in a 1:1 ratio to screening low-dose CT of the chest vs CXR for lung cancer detection conducted at 33 medical centers in the US. This trial enrolled individuals aged 55 to 74 years with at least a 30 pack-year history of cigarette smoking and who were current smokers or had quit within the past 15 years. Participants underwent 3 screening examinations (times T0, T1, and T2) starting soon after randomization at 1-year intervals. Participants were randomized using a centralized system stratified by age, sex, and screening center. Enrollment took place from August 2002 through April 2004. Importantly for this subgroup analysis, participants were excluded from the NLST if they had a previous cancer diagnosis in the past 5 years. The NLST was funded by the National Cancer Institute. The trial protocol is available at the ClinicalTrials.gov website 10 and in Supplement 1 . The NLST was approved by the institutional review board at each participating institution, and this secondary analysis of trial data was approved by the Wayne State University institutional review board. Written informed consent was obtained from all participants. Our study followed the Consolidated Standards of Reporting Trials ( CONSORT ) reporting guideline.

We identified a subset of participants in the NLST who were diagnosed with HNC before randomization (eFigure in Supplement 2 ). Race was self-reported by participants during study eligibility screening as required by the funding agency. We defined HNC survivors as any NLST participant who reported a history of oral cavity, pharynx, larynx, and/or nasal and sinus cancer. We made 2 sets of comparisons. First, we compared HNC survivors with participants without prior HNC to examine the incidence of abnormal imaging findings and examine the incidence of lung cancer. Second, in HNC survivors who were randomly assigned to low-dose CT chest vs CXR screening, we compared the incidence of SPLC and overall survival.

Our primary outcome was the incidence of SPLC in HNC survivors after randomization to either low-dose CT of the chest or CXR. Our secondary outcomes were the incidence of a second primary HNC (SPHNC), combined SPHNC or SPLC, and overall survival in HNC survivors. Additional secondary outcomes included the incidence of abnormal imaging findings suggestive of lung cancer and the incidence of lung cancer when comparing HNC survivors and participants without prior HNC history.

We used unadjusted statistical models for comparisons in the group of HNC survivors randomized to either low-dose CT or CXR using the intention-to-screen principle. The primary outcome was a comparison of the incidence of SPLC after randomization to either low-dose CT or CXR. Event rates for the primary outcome were defined as in the primary analysis of the NLST based on the ratio of events to the person-years at risk for the event. 11 We calculated CIs for the incidence of SPLC and used a log-rank test to compare survival of participants with prior HNC randomized to low-dose CT or CXR. For comparisons between HNC survivors and participants without prior HNC, there was a potential for confounding. Thus, we used a Cox proportional hazards model to test the relationship between prior HNC and development of lung cancer over time after adjusting for age, sex, race, and smoking pack-years. We performed statistical analyses using SPSS, version 26 (IBM Corp). Data were analyzed from December 1, 2020, to June 30, 2021.

Among the cohort of 53 452 participants in the NLST, we identified 171 HNC survivors who were enrolled a median of 9 years (range, 1-54 years) after HNC diagnosis. Of those survivors, 132 (77.2%) were men and 39 (22.8%) were women; 7 (4.1%) were Black; 154 (90.1%) were White; and 9 (5.6%) were of other race or ethnicity, including American Indian or Alaska Native, Asian, Native Hawaiian or Other Pacific Islander, multiple races, or unknown. Median follow-up after enrollment and randomization was 6.7 years (range, 0-8.2 years). Compared with all other patients, HNC survivors were more likely to be male (77.2% vs 58.9%; difference, 18.3%; 95% CI, 11.6-24.2) and had a more extensive cigarette smoking history (59 median pack-years [IQR, 44-80 pack-years] vs 48 median pack-years [IQR, 39-66 pack-years]; difference, 11 pack-years; 95% CI, 10-12 pack-years) ( Table 1 ).

Among the 171 HNC survivors, 82 were screened with low-dose CT of the chest, and 89 were screened with CXR. At least 1 screening examination was suspicious for lung cancer in 35 participants (42.7%) in the low-dose CT group and 24 participants (27.0%) in the CXR group ( Table 2 ). Survivors of HNC in the low-dose CT group were also more likely to have significant abnormalities identified at first screening that were not suspicious for lung cancer (15 participants [18.3%] vs 2 participants [2.2%]). Invasive procedures were performed in 8 HNC survivors (9.8%) in the low-dose CT group vs 2 (2.2%) in the CXR group. In the original NLST, lung cancer screening resulted in false-positive rates of 26.3% at baseline, 27.2% at year 1, and 15.9% at year 2.

We then compared the incidence of lung cancer in survivors of HNC and other forms of cancer vs participants with no prior cancer. After adjustment for age, sex, race, and pack-years of cigarette smoking, the incidence of lung cancer was highest in HNC survivors when compared against participants with history of a non-HNC or no prior cancer (2080 per 100 000 person-years [2.1%] vs 609 per 100 000 person-years [0.6%]; adjusted rate ratio, 2.54; 95% CI, 1.63-3.95) ( Table 3 ).

We next compared results in the subgroup of 171 HNC survivors who were randomized to either low-dose CT of the chest or CXR. In our primary analysis, the incidence of SPLC was 2610 cases per 100 000 person-years (12 cancers) in the low-dose CT group, compared with 1594 cases per 100 000 person-years in the CXR group (8 cancers, rate ratio, 1.55; 95% CI, 0.59-3.63). The incidence of either SPHNC or SPLC was 3659 cases per 100 000 person-years in the low-dose CT group, whereas there were no additional HNC diagnoses made after randomization in the CXR group, which had a total incidence of 1594 cases per 100 000 person-years (adjusted rate ratio, 1.95; 95% CI, 0.83-4.61). Notably, HNC survivors who were diagnosed with lung cancer after randomization were more likely to have squamous cell carcinoma histology (9 of 19 [47.4%] vs 447 of 2003 [22.3%]; difference, 25.1%; 95% CI, 4.9%-46.1%) ( Table 4 ). In the low-dose CT group and CXR group, 7 of 11 (63.6%) and 4 of 8 (50.0%) participants were diagnosed with stage I SPLC, whereas 1 of 11 (9.1%) and 2 of 8 (25.0%), respectively, were diagnosed with stage IV. There was a 20% reduction in overall survival among HNC survivors who were randomized to CXR as compared with participants randomized to low-dose CT (hazard ratio, 0.79; 95% CI, 0.42-1.52) ( Figure ). In HNC survivors, overall survival was 7.07 years with low-dose CT vs 6.66 years with CXR (log-rank P = .48). The wide CI associated with the hazard ratio prevents making definitive conclusions regarding the effect of low-dose CT vs CXR.

In this secondary analysis of the NLST examining HNC survivors, we identified 3 principal findings. First, we demonstrated that HNC survivors were more likely to have abnormal screening results. Second, in the setting of a randomized clinical trial, we confirmed that HNC is an especially high-risk feature for development of secondary lung cancer. Importantly, the risk of developing SPLC persists for many years after treatment for HNC. Third, in a cohort of 171 HNC survivors, we identified a potential benefit of lung cancer screening with low-dose CT of the chest vs CXR. Together, these results underscore the importance of low-dose CT screening in HNC survivors.

Pulmonary nodules are frequently detected on CT in HNC survivors. Previous retrospective single institutional studies have reported an 11% to 52% rate of pulmonary nodules in patients with HNC. 6 , 12 However, these reports were single-arm analyses of HNC survivors, and it is difficult to compare the results to those of people with other forms of cancer. We found that HNC survivors in the NLST were more likely to have significant abnormalities identified with screening, and 42.7% had at least 1 low-dose CT screening test suspicious for lung cancer. Furthermore, 9.8% of HNC survivors who were screened with low-dose CT of the chest underwent an invasive procedure related to screening. This finding suggests that individuals with a history of HNC may be more likely to experience the risks associated with screening, including subsequent invasive procedures.

Previous retrospective research has demonstrated that HNC survivors have a widely varying risk of developing SPLC, ranging from 0.6% to 8.0%. 13 , 14 An analysis of a Taiwanese national cancer database found that 5.7% of 63 720 HNC survivors developed a second primary cancer, although in that series, only 0.6% of patients developed SPLC. 14 In contrast, an analysis of the Surveillance Epidemiology and End Results database found that 8.0% of HNC survivors developed SPLC an average of 6.7 years after treatment, most frequently after supraglottic or hypopharyngeal cancer. 13 Another study 15 found that the risk of SPLC was higher after HNC than after other cancers. That study compared HNC survivors in the Surveillance Epidemiology and End Results database with the control group of the NLST and estimated that cancers of the larynx, oropharynx, hypopharynx, and tonsils were among the highest demonstrated cumulative incidence of SPLC. 15 However, the wide range in incidence of SPLC leaves some doubt as to the true incidence. In this prospective cohort enrolled in a randomized trial a median of 9 years after HNC, we confirm that HNC survivors are at high risk for developing SPLC. We found that 2.1% of participants with prior HNC will develop lung cancer per year of follow-up (2080 per 100 000-person-years), well above the incidence seen for survivors of other forms of cancer.

We observed that HNC survivors had a nonsignificant trend for increased detection of SPLC and improved overall survival with low-dose CT of the chest. The wide CIs, presumably due to the small sample size and number of outcome events, prevent definitive conclusions. A larger sample of HNC survivors and outcome events will provide a more precise estimate of the true effect of low-dose CT lung screening when compared with CXR. Importantly, results from the well-powered full sample of 53 452 participants showed a significant 6.7% improvement in overall survival and 20% improvement in lung cancer mortality with low-dose CT chest screening. 9 The incidence of lung cancer in HNC survivors was 2.5 times higher than that in the overall trial, suggesting that low-dose CT screening was more effective at diagnosing SPLC than CXR; this effect may be even greater in HNC survivors.

The differences in incidence of SPHNC (6 cases of SPHNC in the low-dose CT group vs 0 cases in the CXR group) further hint that low-dose CT screening may also lead to detection of SPHNC. The mechanisms are likely multifactorial and not fully discernible from the present data. We hypothesize that low-dose CT chest screening may detect some findings in the lower cervical lymph nodes, larynx, and hypopharynx that may lead to a diagnosis of SPHNC. Furthermore, many patients who undergo low-dose CT chest screening require positron emission tomography (PET)/CT to investigate suspicious lesions; these images include the entire head and neck, which may lead to the diagnosis of SPHNC. Thus, we hypothesize that in addition to screening for SPLC, low-dose CT chest screening may contribute to the diagnosis of SPHNC.

The frequency of surveillance imaging of the neck after HNC is controversial, with differing opinions and guideline recommendations. The National Comprehensive Cancer Network and the American Society of Clinical Oncology HNC Survivorship Care Guidelines do not recommend routine surveillance imaging for HNC beyond 6 months after treatment unless there are concerning signs or symptoms. 1 , 2 In contrast, the American College of Radiology Neck Imaging Reporting and Data Systems white paper recommends that HNC patients undergo a PET/CT screening 3 months after treatment, followed by a contrast-enhanced CT of the neck and chest or PET/CT 6 months later. If contrast-enhanced CT is negative, the American College of Radiology white paper recommends another contrast-enhanced CT scan of the neck and chest 12 months later. 3 Our study does not examine surveillance neck imaging but does provide some perspective on the risks and benefits of chest imaging after HNC.

Survivors of HNC are at high risk of second primary cancers such as lung cancer. The National Comprehensive Cancer Network guidelines recommend annual low-dose CT chest screening for individuals aged 50 years or older with at least a 20 pack-year smoking history and importantly include prior HNC as a high-risk feature. 16 Similarly, recently updated USPSTF guidelines recommend annual low-dose CT chest screening for those aged 50 to 80 years with at least a 20 pack-year smoking history who currently smoke or have quit within the past 15 years. 7 These guidelines have decreased the number of pack-years necessary to warrant screening from the 30 pack-years or more used in the NLST to 20 pack-years or more based on modeling data showing likely benefit in this group. 17 Significantly, USPSTF guidelines do not mention prior HNC as a risk factor for lung cancer. However, USPSTF guidelines do state that screening should stop if a patient has not smoked in 15 years or if they develop a health problem that substantially limits life expectancy or the ability to undergo curative lung treatment. Based on the data presented here and in the other reports of the NLST, 9 , 18 we would advocate that HNC survivors aged 50 years or older with a 20 pack-year or more smoking history who are fit enough to undergo curative lung cancer treatment should undergo annual low-dose CT screening for lung cancer.

Although this conclusion is not practice-changing, it does emphasize the importance of adhering to lung cancer screening recommendations in HNC survivors. Adherence to USPSTF lung cancer screening guidelines is estimated to be only 14% nationally. 8 Lung cancer screening rates are even lower in current smokers, non-White individuals, and those with less education. 8 , 19 Our results show that HNC survivors are at especially high risk for SPLC and may warrant special consideration to boost adherence. Given the especially high rates of SPLC in HNC survivors, we believe that all lung cancer screening guidelines, including those by the USPSTF, should include prior HNC as a high-risk feature for the development of lung cancer. We would recommend incorporating lung cancer screening into standard HNC survivorship and recommend integration of quality metrics to optimize adherence in this population. However, implementing routine lung cancer screening into HNC survivorship will require a concerted approach, as clinicians who treat patients with HNC have raised concerns about incorporating lung cancer screening into cancer clinics related to workflow, shared decision-making, and competing priorities. 20

There are several limitations to consider when interpreting our results. First, the NLST was not specifically designed to address our study question, and the data collected were not optimized for our study question. Prior HNC was self-reported, and no data on the stage or treatment for HNC were collected. In addition, we were unable to identify or differentiate human papillomavirus–related cancers, which are associated with different smoking rates. Second, the group of HNC survivors was small, and our results may reflect imprecision in effect size estimates, which prevents definitive conclusions. Third, participants with previous cancers diagnosed within 5 years were excluded from the NLST. If prior HNC within 5 years was not an exclusion criterion, the incidence of both SPHNC and SPLC would have been even higher. 21 However, owing to the mortality risk in HNC survivors within 5 years of treatment, the benefits of SPLC diagnosis may be decreased owing to competing risks of mortality. 22 Fourth, the results presented were limited to the results of screening, the incidence of SPLC and SPHNC, and overall survival. Additional oncologic and quality-of-life outcomes may help to better define the risks and benefits of low-dose CT screening. Fifth, differentiating pulmonary head and neck squamous cell carcinoma metastases from squamous cell SPLC relies on clinical impression, radiologic imaging, and histology. However, in cases with squamous cell histology, it is not always possible to determine definitively whether this finding represents a second primary or pulmonary metastases; this uncertainty may explain some of the differences in observed rates. Nonetheless, we believe that this secondary analysis of a randomized clinical trial provides important insight into the risk of SPLC among HNC survivors.

In this secondary analysis of a randomized clinical trial, we evaluated HNC survivors enrolled in the NLST and found a 2.5 times greater rate of lung cancer compared with patients with no previous cancer. Adherence to lung cancer screening recommendations in the real world is low, and our results underscore the importance of lung cancer screening in HNC survivors. In total, these results support routine annual low-dose CT chest screening for lung cancer in HNC survivors with prior significant tobacco use who are fit enough to undergo treatment with curative intent.

Accepted for Publication: August 29, 2021.

Published Online: October 28, 2021. doi:10.1001/jamaoto.2021.2776

Corresponding Author: John D. Cramer, MD, Department of Otolaryngology–Head and Neck Surgery, Wayne State University, 4201 St Antoine, UHC 5E, Detroit, MI 48201 ( [email protected] ).

Author Contributions: Dr Cramer had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Cramer, Sukari.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Cramer, Grauer, Sukari.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Cramer, Grauer.

Administrative, technical, or material support: Cramer, Grauer.

Supervision: Sukari, Nagasaka.

Conflict of Interest Disclosures: Dr Nagasaka reported receiving personal fees from AstraZeneca, Caris Life Sciences, Daiichi-Sankyo, Takeda, Novartis, EMD Serono, Blueprint Medicines, Janssen, Pfizer, Lilly, and Genentech and nonfinancial support from AnHeart outside the submitted work. No other disclosures were reported.

Data Sharing Statement: See Supplement 3 .

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