Characterization of pyruvate metabolism and citric acid cycle patterns predicts response to immunotherapeutic and ferroptosis in gastric cancer

Background Gastric cancer is one of the most common malignancies of the digestive system with a high lethal rate. Studies have shown that inherited and acquired mutations in pyruvate metabolism and citric acid cycle (P-CA) enzymes are involved in tumorigenesis and tumor development. However, it is unclear how different P-CA patterns affect the tumor microenvironment (TME), which is critical for cancer progression. Methods This study mainly concentrated on investigating the role of the P-CA patterns in multicellular immune cell infiltration of GC TME. First, the expression levels of P-CA regulators were profiled in GC samples from The Cancer Genome Atlas and Gene Expression Omnibus cohorts to construct a consensus clustering analysis and identify three distinct P-CA clusters. GSVA was conducted to reveal the different biological processes in three P-CA clusters. Subsequently, 1127 cluster-related differentially expressed genes were identified, and prognostic-related genes were screened using univariate Cox regression analysis. A scoring system was then set up to quantify the P-CA gene signature and further evaluate the response of the patients to the immunotherapy. Results We found that GC patients in the high P-CA score group had a higher tumor mutational burden, higher microsatellite instability, and better prognosis. The opposite was observed in the low P-CA score group. Interestingly, we demonstrated P-CA gene cluster could predict the sensitivity to immunotherapy and ferroptosis-induced therapy. Conclusion Collectively, the P-CA gene signature in this study exhibits potential roles in the tumor microenvironment and predicts the response to immunotherapeutic. The identification of these P-CA patterns may significantly accelerate the strategic development of immunotherapy for GC.

Automated summary

This study investigated the role of pyruvate metabolism and citric acid cycle patterns in the tumor microenvironment of gastric cancer. The findings suggest that these patterns can predict the response to immunotherapy and may accelerate the development of immunotherapeutic strategies for gastric cancer.