Prediction of prognosis, immunogenicity and efficacy of immunotherapy based on cholesterol metabolism in gastric cancer.

BACKGROUND

Cholesterol metabolism plays a crucial role in tumor progression and immune response modulation. However, the precise connection between cholesterol metabolism-related genes (CMRGs) and their implications for clinical prognosis, the tumor microenvironment (TME), and the outcomes of immunotherapy in gastric cancer remains to be fully elucidated.

METHODS

Transcriptome data and related clinical information from 675 gastric cancer patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A total of 50 cholesterol metabolism-related genes (CMRGs) were identified from the Kyoto Encyclopedia of Genes and Genomes (KEGG, hsa04979). Consensus clustering analysis was used to classify patients into distinct molecular subgroups, while principal component analysis (PCA) was applied to develop a prognostic scoring system for predicting survival and immunotherapy response. The scoring system was validated using three independent cohorts of gastric cancer patients.

RESULTS

Based on 49 CMRGs, 675 gastric cancer patients were categorized into three distinct subgroups with varying prognoses, tumor microenvironment features, and clinical characteristics. Further differential gene analysis and consensus clustering identified two additional subgroups. The prognostic scoring system developed through PCA demonstrated that the high-score subgroup had significantly improved survival, higher tumor mutational burden (TMB), and microsatellite instability (MSI), as well as a greater number of mutated genes, indicating greater sensitivity to immunotherapy. This system was validated in a real-world cohort undergoing immunotherapy. Additionally, the correlation between GPC3 expression and cholesterol levels was confirmed, highlighting GPC3's potential biological role.

CONCLUSION

This study highlights the importance of CMRGs in gastric cancer, deepens our understanding of the tumor immune microenvironment, and guides individualized immunotherapy.