Decoding Colon Cancer Heterogeneity Through Integrated miRNA–Gene Network Analysis
Year: 2025
Type: article
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.
Source: Mathematics
DOI: 10.3390/math13061020
Authors: Qingcai He, Zhilong Mi, Tianyue Liu, Taihang Huang, Mao Li, Binghui Guo, Zhiming Zheng
Institution: Beihang University
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,137
Award: G1230002412
OpenAlex ID: W4408691837
