Speaker's Highlight

• Don Sin University of British Columbia, St. Paul Hospital (Canada)
  Kenneth R. Chapman Toronto General Hospital Research Institute (Canada)
• Parameswaran Nair McMaster University (Canada)
  Carolyn Calfee UCSF (U.S.A.)
• Gregory P. Downey University of Colorado School of Medicine (U.S.A.)
  David A. Schwartz University of Colorado School of Medicine (U.S.A.)
• Neil Schluger Tuberculosis Control Branch, California Department of Public Health (U.S.A.)
  Nick Kim Critical Care & Sleep Medicine, University of California San Diego (U.S.A.)
• Nicola Hananiah Baylor College of Medicine (U.S.A.)
  Jae-Joon Yim Seoul National University College of Medicine (Republic of Korea)
• Koichiro Asano Tokai University School of Medicine (Japan)
  Diahn-Warng Perng Taipei Veterans General Hospital (Taiwan)
• Konstantinos Kostikas University of Ioannina (Greece)
  Karin Klooster University Medical Center Groningen (Kingdom of the Netherlands)

• Emerging Biomarkers for Early Lung Cancer Detection

  Lung cancer remains one of the leading causes of cancer-related mortality because many tumors are discovered after symptoms appear or disease has already spread. Low-dose computed tomography (LDCT) screening can identify suspicious pulmonary nodules earlier, yet its use is limited by false-positive findings, incidental abnormalities, cost, and unequal access. Biomarker research is therefore focused on finding signals that reveal malignant change before it becomes clinically obvious.

  Emerging biomarkers may support risk assessment, improve nodule evaluation, and help clinicians decide which patients need closer surveillance or invasive testing. These signals can be detected in blood, breath, sputum, or tissue, and may include genetic alterations, epigenetic changes, proteins, metabolites, and immune responses.

  For respiratory specialists, thoracic oncologists, radiologists, laboratory scientists, and public health teams, the central issue is not simply whether a biomarker can distinguish cancer from non-cancer. It must also perform reliably in people with smoking-related lung disease, chronic inflammation, infection, emphysema, and other conditions that can produce similar biological signals.

  Why earlier detection remains difficult

  Early-stage lung cancer may cause few or no symptoms. A persistent cough, breathlessness, fatigue, or chest discomfort can be attributed to chronic obstructive pulmonary disease, asthma, infection, or the long-term effects of smoking. As a result, some patients reach specialist care only after the disease has become more advanced.

  LDCT has demonstrated value in high-risk populations, particularly people with substantial tobacco exposure. However, a scan identifies an anatomical change rather than proving malignancy. Small nodules may remain indeterminate, and repeated imaging can increase anxiety and healthcare utilization. Biomarkers could add a biological layer to imaging, helping distinguish harmless lesions from tumors that require rapid action.

  Signals found in blood and other body fluids

  Circulating tumor DNA (ctDNA) is released into the bloodstream by cancer cells. It may carry tumor-specific mutations, copy-number changes, or methylation patterns. Because early tumors often shed very small amounts of DNA, highly sensitive sequencing and carefully selected marker panels are essential. Fragmentomics, which examines the size and distribution of cell-free DNA fragments, is another developing approach.

  Circulating tumor cells, microRNAs, long non-coding RNAs, and extracellular vesicles are also being studied. MicroRNAs can influence gene expression and may show distinctive patterns in lung adenocarcinoma, squamous cell carcinoma, and other subtypes. Extracellular vesicles protect molecular cargo as it travels through the body, potentially making them useful carriers of cancer-related information.

  Protein biomarkers remain attractive because laboratory immunoassays are familiar and relatively scalable. Candidate proteins include tumor-associated antigens, inflammatory mediators, and combinations of markers rather than one isolated molecule. Sputum and exhaled breath may offer additional information, especially when tumor cells or volatile organic compounds are present close to the respiratory tract.

  Comparing promising biomarker approaches

  No single platform currently provides a complete solution for population-wide early detection. Performance varies according to cancer stage, histological subtype, smoking history, sample quality, and the prevalence of disease in the tested population.

  Biomarker approach	Sample source	Potential value	Main limitation
  Circulating tumor DNA	Blood plasma	Detects mutations, methylation, and fragment patterns	Very low signal in small or early tumors
  MicroRNA signatures	Blood, sputum, tissue	May reflect tumor biology and subtype	Results can vary between platforms and cohorts
  Protein panels	Blood	Compatible with established laboratory workflows	Inflammation and comorbidities may reduce specificity
  Volatile organic compounds	Exhaled breath	Non-invasive and repeatable	Requires standardization of collection and analysis
  Circulating tumor cells	Blood	May provide cellular and genomic information	Rare cells are technically difficult to isolate
  Radiomic and AI-derived features	CT images	Adds quantitative information to nodule assessment	Requires external validation and consistent imaging protocols

  Combining biomarkers with imaging

  The most practical near-term role for biomarkers may be to complement LDCT rather than replace it. A combined model could incorporate age, tobacco exposure, occupational risks, family history, lung function, CT nodule characteristics, and molecular signals. This approach may improve risk stratification for nodules that are too small or atypical for a confident radiological diagnosis.

  Artificial intelligence can assist by extracting features from CT scans that are difficult to identify through visual assessment alone. When imaging analytics are integrated with blood-based or breath-based biomarkers, the resulting model may capture both tumor appearance and tumor biology. Such systems must be trained on diverse populations to avoid underperforming in people from different ethnic groups, healthcare settings, or smoking histories.

  Clinical usefulness depends on the consequence of a test result. A highly sensitive test with many false positives could lead to unnecessary biopsies, while a highly specific test that misses early tumors would offer limited screening value. The best models will need transparent thresholds and clear pathways for repeat testing, diagnostic imaging, biopsy, or referral.

  From promising research to clinical practice

  Many biomarker studies are retrospective, single-center, or based on samples collected after diagnosis. These designs can overestimate accuracy because cases and controls are easier to distinguish than patients encountered in everyday clinics. Prospective validation is needed in asymptomatic, high-risk populations before a test can guide screening decisions.

  Researchers must also address pre-analytical and analytical variation. Blood collection tubes, processing time, storage temperature, sequencing platforms, and laboratory thresholds can all influence results. Standardized protocols and quality assurance are particularly important for multi-center studies and international collaborations such as those shared through respiratory medicine congresses connected with APSR and KATRD.

  Cost-effectiveness, accessibility, informed consent, and data protection are equally important. A sophisticated assay will have limited public health value if it is available only in major academic hospitals. Implementation studies should examine how results affect referral times, patient anxiety, invasive procedures, treatment eligibility, and long-term mortality.

  Priorities for clinicians and researchers

  Effective development of early detection tools requires a coordinated clinical and scientific strategy.

  • Validate candidate biomarkers prospectively in people undergoing risk-based LDCT screening.
  • Use multimodal models that combine molecular, imaging, clinical, and exposure-related data.
  • Report sensitivity, specificity, predictive values, stage distribution, and false-positive rates transparently.
  • Standardize sample collection, laboratory processing, assay design, and data interpretation.
  • Include diverse populations and evaluate affordability, workflow integration, and patient outcomes.

  The next step in respiratory cancer care

  Emerging molecular and physiological signals could make lung cancer detection more precise, particularly when paired with carefully targeted imaging. Their greatest value may come from helping clinicians identify biologically significant disease while reducing unnecessary investigations for benign nodules.

  Progress will depend on rigorous prospective trials, reproducible laboratory methods, multidisciplinary collaboration, and responsible integration into screening pathways. Explore the latest respiratory medicine research, congress sessions, and expert perspectives through APSR 2022 to follow how biomarker science is moving toward earlier, more personalized lung cancer care.

  Richard Russell Nuffield Department of Clinical Medicine, University of Oxford (United Kingdom)
• Mona Bafadhel King’s College London (United Kingdom)
  David Jackson Guy’s and St Thomas’ Hospital, King’s College London (United Kingdom)
• James Chalmers University of Dundee (United Kingdom)
  David Price University of Aberdeen (United Kingdom)