Abstract
BACKGROUND: Lung cancer is a leading cause of cancer mortality, largely due to late-stage diagnosis. Biomarker detection is critical for early screening, molecular subtyping, and personalized therapy. This review summarizes the categories of lung cancer biomarkers, evaluates recent advances in detection technologies, and assesses their clinical potential and associated challenges. METHODS: Biomarkers were systematically categorized into three categories: molecular (DNA, RNA, proteins), epigenetic (e.g., DNA methylation), and liquid biopsy-based (e.g., ctDNA, CTCs, exosomes). Detection platforms were analyzed, including gene-based techniques (PCR, NGS, FISH), protein-based methods (IHC, ELISA, MS), liquid biopsy workflows, and emerging biosensors. The principles, applications, and limitations of each technology were critically examined. RESULTS: Biomarkers and detection technologies serve complementary roles. Tissue-based assays (e.g., IHC, PCR) remain foundational for molecular profiling. Liquid biopsies (e.g., NGS, dPCR) enable non-invasive monitoring of therapy and resistance analysis. Novel biosensors provide ultra-high sensitivity (fg/mL to aM level) for early detection. Challenges include low abundance of early-stage biomarkers, lack of standardization, tumor heterogeneity, and clinical translation hurdles. CONCLUSIONS: The field is moving towards multi-omics integration, ultra-sensitive detection, and standardization. Combining multiple biomarkers, utilizing complementary technologies, and facilitating the clinical adoption of innovative platforms are essential for enhancing early diagnosis and enabling precision oncology in lung cancer.