Background: Gastric cancer is the third leading cause of cancer-related mortality worldwide.According to The Cancer Genome Atlas (TCGA), it can be classified into four molecular subtypes, including microsatellite instability (MSI) and genomically stable (GS) subtypes, which display distinct clinical and pathological features.However, differences in their tumor microenvironment, particularly metabolic reprogramming, remain poorly understood.Methods: Single-cell RNA sequencing data from gastric cancer patients classified as GS or MSI were enrolled.Cell clusters were identified and annotated to compare cellular landscapes between subtypes.Differential gene expression and pathway analyses were performed among malignant epithelial cells.Key genes related to oxidative phosphorylation were identified using LASSO regression, and their expression was further validated in the TCGA dataset.Patient-derived xenograft models were used to compare tumor growth rates, ATP levels, and expression of oxidative phosphorylation -related genes.Results: Single-cell transcriptomic analysis revealed eight major cell types in MSI tumors.Compared to the GS subtype, MSI samples showed significantly greater infiltration of T cells and a lower proportion of epithelial cells.Malignant cells from MSI samples exhibited increased activity of oxidative phosphorylation pathways.LASSO regression identified five oxidative phosphorylation-related genes that were consistently overexpressed in MSI tumors in both single-cell and TCGA datasets.In Patient-derived xenograft models, MSI tumors grew more rapidly and demonstrated higher ATP levels and elevated expression of the five oxidative phosphorylation-related genes compared to MSS tumors.Conclusion: Our study reveals enhanced oxidative phosphorylation metabolism in MSI gastric cancer at single-cell resolution and identifies five oxidative phosphorylation-related genes that may serve as potential therapeutic targets for this subtype.
Ang et al. (Mon,) studied this question.