Screening of Core Genes for Gastric Cancer Promoting M2 Macrophage Polarization by Weighted Gene Co-expression Network Analysis

Author(s): Zidong Zhao, Dandan Zhao, Yu Tan, Satoshi Endo, Yanwen Liu

Objective: M2 macrophages promote gastric cancer (GC) progression via chemokine secretion, inflammation suppression, and angiogenesis/lymphangiogenesis. To address low GC survival and the need for prognostic predictors/therapeutic targets, this study used WGCNA to screen core genes driving M2 polarization in GC, build a prognostic model, and explore drug sensitivity. 

Methods: 381 STAD samples were obtained from TCGA. CIBERSORT calculated immune cell infiltration for grouping; Kaplan-Meier analysis assessed prognosis. WGCNA constructed co-expression modules to screen key modules and core genes. GO/KEGG enrichment analyses were performed. Cox regression built and validated a risk model; a nomogram was developed with clinical data. Cell Miner analyzed drug sensitivity.

Results: High M2 infiltration correlated with poorer prognosis. WGCNA generated 18 modules, identifying the turquoise module and 160 core genes. Enrichment analyses clarified their functional pathways. A validated 3-gene (BCHE, CHRDL1, CNTN1) risk model and a nomogram were established. High-risk patients showed higher sensitivity to 8 drugs.

Conclusion: M2 infiltration is a poor prognostic marker for GC. The 3-gene model and BCHE (as a drug marker) contribute to GC prognosis prediction and precision therapy.