Functional Enrichment, Drug Prediction, and Molecular Docking to Identify Fibroblast-Related Biomarkers for Gastric Cancer via High-Dimensional Weighted Gene Co-Expression Network Analysis.

INTRODUCTION

Cancer-associated fibroblasts (CAFs) can promote gastric cancer (GC) progression through regulating the tumor microenvironment (TME). This study explored cell-to-fibroblast communication based on the single-cell data of GC, identified CAF-related genes linked to GC using high-dimensional weighted gene co-expression network analysis (hdWGCNA), and conducted functional mining, drug prediction, and molecular docking for these genes.

MATERIALS AND

METHODS

Single-cell data were preprocessed using the Seurat package. The communication network between cell subpopulations and fibroblasts was analyzed using CellChat. Key hub genes were initially identified through hdWGCNA, while differentially expressed genes (DEGs) between cancer and control groups were obtained using DESeq2. Subsequently, the overlapping genes between the hub genes and DEGs were subjected to LASSO regression (via the glmnet package) and SVM-RFE (implemented in e1071 package) to select biomarkers for GC. Immune cell infiltration was assessed using the CIBERSORT package, and functional enrichment analysis was performed on the background gene set by GSEA_4.2.2 software. Finally, drugs targeting the biomarkers were predicted by employing the DSigDB database.

RESULTS

Single-cell analysis identified eight major cell subpopulations, with fibroblasts distinctly marked by DCN and LUM expression. Cell communication analysis revealed that HLA-ECD94: NKG2A and HLA-E-KLRC1 were the main interactions through which other cell clusters exerted influence on fibroblasts. COL1A1 and SERPINH1 were identified as CAF-related biomarkers that promoted GC progression through macrophage-mediated immune infiltration. High co-expression of the two genes was significantly enriched in epithelial-mesenchymal transition (EMT).

DISCUSSION: COL1A1 and SERPINH1 may promote GC progression via regulating EMT and forming an immunosuppressive microenvironment through ECM remodeling and macrophage polarization. Additionally, chitosamine was screened as a potential COL1A1-targeting drug for GC treatment.

CONCLUSION

These findings have deepened our current understanding of CAF-mediated mechanisms in GC, contributing to the development of precision diagnostics and therapeutics in GC.