Integrative analysis and prognostication in gastric cancer: unveiling the role of mitochondrial genomics with the MLRScore model.

Abstract

Gastric cancer, a leading cause of cancer-related mortality globally, presents significant challenges in prognosis and treatment due to its heterogeneity. This study aimed to elucidate the role of mitochondrial-related genes (MRGs) in gastric cancer and develop a prognostic model. We analyzed RNA sequencing data and clinical information of 412 gastric cancer samples from The Cancer Genome Atlas (TCGA). A comprehensive list of 1136 MRGs was curated from the MitoCarta3.0 database, leading to the identification of 110 differentially expressed MRGs between gastric cancer and normal tissues. Using univariate and multivariate Cox regression analyses, we constructed the Mitochondrial-Related Risk Score (MLRScore), a prognostic model incorporating five key MRGs. The model was validated in training and testing cohorts and exhibited promising prognostic capability. Additionally, we investigated the relationship between MLRScore and immune cell infiltration, somatic mutations, tumor mutation burden (TMB), and response to chemotherapy. The MLRScore was found to correlate with distinct immune landscapes and chemotherapeutic sensitivities, suggesting its potential utility in guiding personalized treatment strategies. Our study not only provides a novel tool for prognostic assessment in gastric cancer but also underscores the importance of mitochondrial dynamics in tumor biology and patient stratification.