Clinica chimica acta; international journal of clinical chemistry · 2025
Non-nucleic acid biomarkers in early detection of lung cancer.
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Saravanan Suresh, Baskar Ravikumar, Devendiran Vishwar, Palaniappan Natarajan Alangudi, Wahab Mugip Rahaman Abdul, Manivannan S, Rab Safia Obaidur, Saeed Mohd, Palaniyandi Thirunavukkarasu
Аннотация
Lung cancer remains a leading cause of cancer mortality worldwide, largely due to its asymptomatic onset, histological heterogeneity, and frequent late-stage diagnosis. Conventional diagnostic approaches such as imaging and biopsies, although essential, are invasive, costly, and limited in detecting early-stage disease. These challenges have accelerated research into non-invasive biomarkers derived from body fluids. A structured literature search was performed in PubMed, Scopus, Web of Science, and ScienceDirect for studies published between 2010 and 2025. Peer-reviewed original research and review articles evaluating the clinical or translational role of non-nucleic acid biomarkers in early lung cancer detection were included, while non-English publications, case reports, and non-cancer studies were excluded. Among these, non-nucleic acid biomarkers including proteins, extracellular vesicles (EVs), circulating tumour cells (CTCs), and metabolic signatures are emerging as promising diagnostic tools. Protein markers such as CEA, CYFRA 21-1, and NSE demonstrate clinically relevant sensitivity and specificity. EVs provide a stable reservoir of tumour-derived molecules that reflect the tumour microenvironment. CTCs offer real-time insights into tumour progression and metastasis, while metabolomic profiling using LC-MS and NMR identifies distinct metabolic fingerprints linked to lung cancer pathogenesis. This review critically assesses recent advances, applicability, and technological platforms for detecting non-nucleic acid biomarkers, and compares them not only with nucleic acid-based biomarkers but also with conventional diagnostic methods such as imaging and tissue biopsies. Integrating these biomarkers into clinical workflows may complement existing tools, enhance early diagnostic accuracy, and ultimately improve survival outcomes in lung cancer patients.