Emerging biomarkers for pancreatic cancer: from early detection to personalized therapy

• Mohd Haris Jamal ^[1] ; Pratyush Porel ^[2] ; Khadga Raj Aran ^[2]
  1. [1] Department of Pharmacy Practice, ISF College of Pharmacy, Moga, Punjab, India
  2. [2] Department of Pharmacology, ISF College of Pharmacy, Moga, Punjab, India
• Localización: Clinical & translational oncology, ISSN 1699-048X, Vol. 27, Nº. 11, 2025, págs. 4071-4090
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • Pancreatic cancer (PC) remains one of the most lethal malignancies, primarily due to its poor prognosis and late diagnosis. Biomarkers are essential in enhancing diagnostic accuracy, prognostic assessments, and therapeutic strategies, thereby addressing these challenges. Conventional biomarkers, such as CA 19-9, are widely used for monitoring disease progression but have limitations in early detection and specificity, necessitating complementary markers like CEA and MUC1. Emerging genetic biomarkers, including KRAS mutations and TP53 alterations, offer critical insights into tumorigenesis and serve as valuable diagnostic, prognostic, and therapeutic targets. Epigenetic biomarkers, such as DNA methylation and histone modifications, provide additional molecular layers, with aberrant methylation patterns and dysregulated histone modifications influencing tumor aggressiveness and therapy resistance. RNA-based biomarkers, particularly microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), play pivotal roles in regulating tumor biology and offer significant diagnostic and therapeutic potential. Protein-based biomarkers, including glycoproteins and cytokines, alongside liquid biopsy components like circulating tumor DNA (ctDNA), exosomes, and circulating tumor cells (CTCs), facilitate real-time disease monitoring and early detection. Personalized therapy is increasingly guided by these biomarkers, which predict responses to chemotherapy and immunotherapy. Despite challenges in biomarker validation and clinical implementation, advancements in multi-omics, artificial intelligence, and collaborative research hold promise for improving patient outcomes and survival rates in PC.