Advances in lung cancer screening and risk stratification

Despite substantial changes in lung cancer epidemiology and significant advances in prevention and treatment, lung cancer remains the leading cause of cancer-related mortality worldwide (1). Smoking is the principal risk factor across all geographic regions. However, there is increasing recognition that additional factors contribute to lung cancer initiation and progression. These persistent disease burdens continue to drive investigations into novel pathogenic mechanisms and therapeutic strategies, including studies of the tumor microenvironment, immunotherapy approaches, chronic infections and inflammation. Based on the morphological and molecular characteristics of lung tumors, approximately 85% of lung cancers are classified as non-small cell lung cancer and the remaining 15% as small cell lung cancer. The major non-small cell lung cancer histologic subtypes are lung adenocarcinoma and lung squamous cell carcinoma, with increasing efforts directed at developing tools to better stratify these tumors.

Although therapeutic advances coupled with modest improvements in 5-year survival after a lung cancer diagnosis highlight medical progress, challenges remain due to delayed diagnoses, persistent disparities, suboptimal screening, and lack of minimally invasive tools for risk stratification. To address many of these limitations, a multi-center biospecimen and imaging resource was established by Dennison et al. (2) as an international collaboration of eight centers in the US, one in France, and one in Spain to prospectively recruit eligible lung cancer screening (LCS) participants into a 5-year longitudinal cohort study. Low-dose computed tomography (LDCT) LCS was first introduced by the United States Prevention Services Task Force in 2013 and revised in 2021 to expand eligibility criteria from 55 to 50 years of age and to reduce cigarette use requirements from 30 to 20 pack-years.

The Lung Cancer, Early Detection, Assessment of Risk, and Prevention (LEAP) study created a longitudinal cohort for future use by investigators worldwide interested in identifying promising cancer biomarkers. The study enrolled individuals at elevated risk of developing lung cancer based on National Comprehensive Cancer Network guidelines and recruited a total of 2,841 participants at baseline, 2,097 at year 1, and 1,779 at year 2. The design included a 2-year active screening phase with annual LDCT scanning, blood specimen collection, and optimal pulmonary testing for risk profiling at baseline (initial visit, year 1 and year 2). This was followed by a 3-year follow-up phase for a total follow-up duration of 5 years from baseline.

The study cohort was divided into two groups: the first included individuals who met the original National Lung Screening Trial (NLST) inclusion criteria of age (≥55 years old), pack-years of cigarette use (≥30) and time since quitting (>15), whereas the second had broader criteria including a lower age limit (≥50 years old), lower pack-years of cigarette use (≥20) and a least one additional risk factor such as contact with cancer causing agents, personal cancer history, significant family history of cancer, or history of chronic lung diseases such as chronic obstructive pulmonary disease or pulmonary fibrosis. Exclusion criteria included prior history of lung cancer, prior cancer treated within the past 5 years (except nonmelanoma skin cancer), prior removal of any portion of the lung, oxygen therapy, symptoms suggestive of lung cancer, or life expectancy less than 5 years. Helical scans followed the protocols established in the NLST study, while pulmonary nodule evaluation used the Lung Reporting and Data System (Lung-Rads) version 1.0 (2014). The study confirmed the clinical utility of LDCT screening and created a resource of specimens for future use in biomarker discovery efforts. A major strength of the study was the integration of pre-diagnostic biospecimens from individuals at risk of lung malignancy with a longitudinal database that includes clinical data, LDCT findings, and matched blood specimens. Another strength was the ability to compare original NLST recommendations with more recently revised recommendations, including younger individuals with lower cigarette exposures.

Not surprisingly, the characteristics of participants in the LEAP study differed between the United States and Europe, including body mass index and certain comorbidities. The LEAP study also included a higher proportion of current smokers and a greater prevalence of comorbidities. The participation of Black and Asian individuals in the United States was higher than the NLST cohort, although racial-, ethnic-, or sex-specific outcomes were not reported. Site differences likely reflect cohort-specific factors and possibly technical differences in data capture and lung volume measurements. As expected, lung cancer was associated with reduced lung function and increased airway obstruction. Most lung cancer cases were adenocarcinomas detected at early stages following positive screening, although tumors at sites other than the lung were also observed.

The LEAP study excluded individuals at risk who were ineligible for LCS based on clinical guidelines at the time of testing, including never-smokers with genetic predisposition, light smokers, passive smokers, environmentally/occupationally exposed individuals, and patients with chronic lung diseases such as chronic infections, chronic obstructive pulmonary disease, or idiopathic pulmonary fibrosis. These limitations aside, efforts to establish the LEAP collaborative network can bring innovative perspectives, improve recruitment diversity, and help to balance research risks. International collaborations have been highly successful in addressing the more pressing challenges of our time, as demonstrated by initiatives such as the COVAX initiative to accelerate the development and equitable access to COVID-19 vaccines (3), and the Global Fund to Fight AIDS, Tuberculosis and Malaria, a partnership between governments, civilian society, and the private sector to combat these diseases on a global scale (4). However, centralized coordination is essential to minimize variation in study designs and execution and to reduce the biases introduced by cultural or regional differences.

LCS has clear benefits, as evidenced by the shift toward stage I non-small cell lung cancer diagnoses and improved survival following the introduction of screening (5). Its value proposition rests on the facilitated access to biospecimens collected following specified guidelines from individuals at heightened risk of lung malignancies. Adoption of screening recommendations has been limited by high rates of false positive findings, leading to unnecessary procedures, overdiagnosis, limited access in underserved areas, increased radiation exposure, and psychological stress. Despite these challenges, large-scale trials have demonstrated reduced lung cancer mortality and earlier detection to make curative surgery a feasible option (6,7). Therefore, coordinated efforts, such as those proposed in the LEAP study for lung cancer risk stratification and lung nodule risk assessment, are needed to overcome these limitations.

The potential clinical utility of biomarkers to improve the effectiveness of LCS using high-quality specimen biorepositories is widely recognized. Biomarker studies have proven invaluable for improving early cancer detection and refining risk stratification. Importantly, the application of biomarker technologies to a well-curated set of samples enables delivery of personalized, precision-based healthcare for patients at risk or those diagnosed with lung malignancy. Blood-derived biomarkers include circulating tumor cells (8), cell-free DNA (9), cell-free RNA (10), circulating proteins (11), circulating autoantibodies (12), circulating microRNAs (13), and exosome-derived analytes (14). Breath-derived biomarkers include measurement of volatile organic compounds, such as aldehydes, hydrocarbons, ketones, and carboxylic acids, reflecting altered cancer cell metabolism (15). Technologies such as secondary electrospray ionization-high resolution mass spectrometry can detect cancer-specific signatures in breath (16). It should be noted, however, that challenges remain in translating circulating and breath-based biomarkers into routine clinical screening due to lack of standardization in sample collection, differences in analytical sensitivity, insufficient understanding of confounding variables, and existing barriers to regulatory/commercialization. It is also worth noting that biorepositories typically store limited biological material, restricting repeat testing and precluding analysis of long-term storage impacts on analyte stability. These limitations must be considered in designing prioritization schemes for the allocation and distribution of samples.

Emerging approaches like radiomics, artificial intelligence (AI), and multi-omics are also transforming LCS. Their combined utilization has facilitated the integration of higher-resolution metadata into lung cancer risk assessment. Analysis of large datasets in combination with deep learning models can help identify patterns and signals that would otherwise be missed using conventional approaches. For example, radiomics translates medical images into high-dimensional data to evaluate shape, texture, and intensity; AI automates analysis of complex, large datasets and minimizes the risk of false positives and false negatives; while multi-omics generates signatures that can create a molecular patient phenotype. Clearly, integration of these technologies can lead to a more precise stratification of patient risk, the development of predictive models of disease trajectory and clinical outcomes, and the implementation of targeted medical interventions.

Precision oncology focuses on the individualization of cancer diagnosis and treatment and the development of actionable modalities for risk stratification. Breaking barriers to collaboration and development of minimally invasive approaches for diagnosis and risk stratification are essential to accelerate the translation of scientific discovery into improved clinical care. Biomarker studies support precision medicine by guiding diagnosis, prognosis, therapy selection, clinical trial recruitment, response monitoring, toxicity reduction, and target identification. Standardization of LDCT acquisition protocols is necessary because scanner variability can affect radiation speed and dose and image interpretation. As noted by Dennison et al. (2), ongoing biomarker studies, such as the 4-protein panel (4MP), measuring pro-surfactant protein B, CA-125, carcinoembryonic antigen, and cytokeratin-19 fragment, may improve lung cancer risk stratification and nodule malignancy risk assessment. Future studies should consider demographic variables such as age, sex, race, and integrate biomarker measurements with pre- and post-LDCT risk assessment, radiomics-based evaluation, exposome data, and pan-cancer screening strategies. As noted above, further improvements in the sensitivity and specificity of LDCT screening can be realized by taking advantage of AI and deep learning and measurements of tumor volume. The standardization of lung nodule review programs can also be beneficial to ensure consistency and efficiency of patient evaluation protocols. Clinicians, scientists and policy makers should collaboratively address the benefits and risks of LDCT screening to establish specific approaches for biomarker implementation.

Resources such as those generated by the LEAP study provide valuable biospecimens for longitudinal evaluation of disease endpoints and biomarker discovery. However, concerted measures are required to ensure standardization and integrity of samples, including the implementation of a Quality Management System that properly defines standard operating procedures, preserves the quality of samples prior, during and after collection, and across their lifecycle. These safeguards must be supported by an efficient Laboratory Information Management System as well as data governance- and regulatory compliance policies that ensure optimal metadata assembly, curation and use. Lastly, alignment with the recommendations published by the International Society for Biological and Environmental Repositories is highly desirable.

In summary, the LEAP study provides a unique resource integrating longitudinal biospecimens, standardized LDCT imaging, and clinical follow-up to support biomarker validation for early lung cancer detection. Most insurance plans and Medicare cover LDCT screening for individuals aged 50–77 years with a 20-pack-year smoking history. As noted earlier, reluctance to participate may stem from concerns over false positives and imprecise risk estimations of malignancy—limitations potentially mitigated by the advancement of validated biomarkers. Stigma and limited access to LCS may also significantly contribute to patient reluctance. Screening should be accompanied by smoking-cessation counseling and education on harmful environmental exposures that exacerbate risks of malignancy. The thoracic field of study currently lacks validated, minimally invasive tools for early diagnosis and risk stratification. Future efforts should expand infrastructure enabling access to pre-diagnostic samples, nested case–control and longitudinal analyses, and risk-adapted screening intervals that include lower-risk populations.

Acknowledgments

None.

Footnote

Provenance and Peer Review: This article was commissioned by the editorial office, Annals of Cancer Epidemiology. The article has undergone external peer review.

Peer Review File: Available at https://ace.amegroups.com/article/view/10.21037/ace-2026-1-0016/prf

Funding: None.

Conflicts of Interest: The author has completed the ICMJE uniform disclosure form (available at https://ace.amegroups.com/article/view/10.21037/ace-2026-1-0016/coif). The author has no conflicts of interest to declare.

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