Advancing biomarker discovery in pancreatic ductal adenocarcinoma: Traditional approaches and emerging technologies
Background: Pancreatic ductal adenocarcinoma (PDAC) is among the most aggressive solid malignancies, characterized by late-stage detection, rapid progression, and poor patient survival. Reliable biomarkers are urgently needed to improve early diagnosis, prognostic stratification, and therapeutic decision-making. Traditional approaches such as carbohydrate antigen 19-9 (CA19-9), carcinoembryonic antigen (CEA), and immunoassay-based methods have long supported clinical practice; however, their utility is limited by suboptimal sensitivity and specificity. Advances in molecular and analytical methodologies have broadened the biomarker landscape through next-generation sequencing, proteomics, metabolomics, and epigenetic profiling. Complementing these approaches, liquid biopsy platforms, including circulating tumor DNA, exosomes, and circulating tumor cells, as well as imaging-based radiomics and artificial intelligence-driven multi-omics integration, are enabling non-invasive, high-resolution biomarker discovery. Objective: This review aims to comprehensively synthesize both traditional approaches and the latest emerging technologies in PDAC biomarker discovery, emphasizing not only their underlying methodological principles but also their translational potential and the persistent challenges associated with clinical validation. Conclusion: By presenting a broad yet detailed methodological perspective, we trace the evolution of classical diagnostic and prognostic tools and examine how they are increasingly being integrated with innovative high-throughput and multi-omics platforms. Together, these advances underscore the pivotal role of biomarkers in enabling earlier detection, improving risk stratification, and driving the future of precision oncology.
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