Decoding Colon Cancer Heterogeneity Through Integrated miRNA–Gene Network Analysis

Abstract

Colon adenocarcinoma (COAD) demonstrates significant clinical heterogeneity across disease stages, gender, and age groups, posing challenges for unified therapeutic strategies. This study establishes a multi-dimensional stratification framework through integrative analysis of miRNA–gene co-expression networks, employing the MRNETB algorithm coupled with Markov flow entropy (MFE) centrality quantification. Analysis of TCGA-COAD cohorts revealed stage-dependent regulatory patterns centered on CDX2-hsa-miR-22-3p-MUC13 interactions, with progressive dysregulation mirroring tumor progression. Gender-specific molecular landscapes have emerged, characterized by predominant SLC26A3 expression in males and GPA33 enrichment in females, suggesting divergent pathogenic mechanisms between genders. Striking age-related disparities were observed, where early-onset cases exhibited molecular signatures distinct from conventional COAD, highlighted by marked XIST expression variations. Drug-target network analysis identified actionable candidates including CEACAM5-directed therapies and differentiation-modulating agents. Our findings underscore the critical need for heterogeneity-aware clinical decision-making, providing a roadmap for stratified intervention paradigms in precision oncology.