ArticleBMC cancer2025
Senescence-driven molecular subtyping in pancreatic cancer: a multi-omics framework for precision medicine.
Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundPancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy with a five-year survival rate below 15%, largely due to tumor heterogeneity and limited therapeutic options. While senescence-related genes (SRGs) are implicated in cancer progression, their pancreas-specific roles in PDAC subtyping and treatment remain unexplored.
methodsWe integrated multi-omics data (RNA-seq, ATAC-seq, and whole-genome sequencing) from 402 pancreas-specific SRGs to classify PDAC subtypes through unsupervised clustering. Independent validation cohorts (TCGA-PAAD, n = 183; patient-derived organoids, n = 40) and drug sensitivity screens were used to define subtype-specific therapeutic vulnerabilities. A machine learning-based random forest model identified key SRG biomarkers for clinical stratification.
resultsThree distinct PDAC subtypes were identified: Cluster 1, characterized by extensive immune infiltration; Cluster 2, mixed features with moderate prognosis; and Cluster 3, defined by significant metabolic reprogramming. Drug screens revealed Cluster 3 as uniquely sensitive to Metformin and Trametinib, suggesting combinatory therapy potential. A 20-gene random forest classifier achieved high accuracy in subtype prediction (AUC = 0.96).
conclusionThis study establishes the first pancreas-specific SRG-driven classification of PDAC, resolving prior inconsistencies in Metformin trial outcomes. Our framework enables risk stratification and subtype-guided therapy, with immediate clinical implications: Metabolic-targeting agents (Metformin) may benefit the high-risk Cluster 3, while immunotherapy could be prioritized for Cluster 1.
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