Background
The role of cholesterol metabolism in gastric cancer (GC) and its implications for tumor characteristics and immunotherapy response remain poorly understood. In this study, our
Conclusion
Our results highlight the effectiveness of cholesterol metabolism patterns as biomarkers for predicting the prognosis and immunotherapy response in GC. The expression of cholesterol metabolism genes and the assessment of cholesterol metabolism patterns have the potential to predict the outcome of immunotherapy and guide treatment strategies.
Methods
We conducted a comprehensive analysis of cholesterol metabolism genes (CMGs) using transcriptomic data from TCGA and GEO. Based on 23 representative CMGs, we classified GC into metabolic subtypes. We evaluated clinical features and immune cell infiltration between these subtypes. Additionally, we identified a CMG signature and assessed its clinical relevance in GC. We retrospectively enrolled thirty-five GC patients receiving chemotherapy plus a PD-1 inhibitor to assess the CMG signature using multiplex immunohistochemistry.
Results
Our analysis revealed two cholesterol metabolism subtypes in GC: Cholesterol Metabolism Type 1 (CMT1) and Cholesterol Metabolism Type 2 (CMT2). These subtypes exhibited distinct patterns: CMT1 indicated heightened cholesterol biosynthesis, while CMT2 showed abnormal cholesterol transport. CMT2 was associated with unfavorable clinical features, enriched malignant pathways, and a pro-tumor immune microenvironment. Furthermore, we developed a five-CMG prognostic signature (ABCA1, NR1H3, TSPO, NCEH1, and HMGCR) that effectively predicted the prognosis of patients with GC and their response to chemotherapy plus a PD-1 inhibitor. This signature was validated in a clinical cohort using multiplex immunohistochemistry.