An integrative analysis of UFMylation-related genes reveals a prognostic signature and identifies GDF7 as a novel therapeutic target in gastric cancer.

BACKGROUND: Recent studies have shown that UFMylation plays an important role in cancer, but its specific function in gastric cancer (GC) remains to be fully elucidated. This study aimed to develop a prognostic signature based on UFMylation-related genes (URGs) for survival prediction in GC. MATERIALS AND METHODS: We screened for differentially expressed genes (DEGs) between GC and normal control samples using The Cancer Genome Atlas (TCGA) database. Based on eight core URGs, unsupervised consensus clustering (CC) was utilized to classify GC samples into distinct molecular subtypes. Key co-expression modules and functional pathways were identified via Weighted Gene Co-expression Network Analysis (WGCNA) and enrichment analyses. A prognostic model was then constructed by Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis, followed by independent validation in the GSE84437 dataset. The biological effects of growth differentiation factor 7 (GDF7) on GC progression were evaluated through both in vitro and in vivo experiments. RESULTS: A prognostic risk model was successfully constructed using 13 signature genes: PGR, BVES, CAVIN2, CDH6, COL10A1, GDF7, WDR17, MMP16, NSG2, NPTX1, ZNF662, APOD, and LBH. Using this model, patients were stratified into high- and low-risk groups. The model displayed robust predictive performance and was identified as an independent prognostic factor. Immune infiltration analysis revealed significantly altered immune cell distributions between the two risk groups, and drug sensitivity assessments identified potential therapeutic agents tailored to each group. Functional experiments confirmed GDF7 acts as a critical regulator of the proliferation, invasion, and migration of GC cells. CONCLUSION: A novel GC prognostic model was created, and GDF7 was determined as a potential therapeutic target. This study offers insights into the GC molecular mechanism and contributes to the formulation of personalized treatment strategies.