Development of a Comprehensive Gene Signature Linking Hypoxia, Glycolysis, Lactylation, and Metabolomic Insights in Gastric Cancer Through the Integration of Bulk and Single-Cell RNA-Seq Data

Background: Hypoxia and anaerobic glycolysis are cancer hallmarks and sources of the metabolite lactate. Intriguingly, lactate-induced protein lactylation is considered a novel epigenetic mechanism that predisposes cells toward a malignant state. However, the significance of comprehensive hypoxia-glycolysis-lactylation-related genes (HGLRGs) in cancer is unclear. We aimed to construct a model centered around HGLRGs for predicting survival, metabolic features, drug responsiveness, and immune response in gastric cancer.

Methods: The integration of bulk and single-cell RNA-Seq data was achieved using data obtained from the TCGA and GEO databases to analyze HGLRG expression patterns. A HGLRG risk-score model was developed based on univariate Cox regression and a LASSO-Cox regression model and subsequently validated. Additionally, the relationships between the identified HGLRG signature and multiple metabolites, drug sensitivity and various cell clusters were explored.

Results: Thirteen genes were identified as constituting the HGLRG signature. Using this signature, we established predictive models, including HGLRG risk scores and nomogram and Cox regression models. The stratification of patients into high- and low-risk groups based on HGLRG risk scores showed a better prognosis in the latter. The high-risk group displayed increased sensitivity to cytotoxic drugs and targeted inhibitors. The expression of the HGLRG displayed a strong correlation with amino acids and lipid metabolites. Notably, a significant difference in immune infiltration, such as that of M1 macrophages and CD8 T cells, was correlated with the HGLRG signature. The abundant within the mesenchymal components was highlighted by single-cell transcriptomics.

Conclusion: The innovative HGLRG signature demonstrates efficacy in predicting survival and providing a practical clinical model for gastric cancer. The HGLRG signature reflects the internal metabolism, drug responsiveness, and immune microenvironment components of gastric cancer and is expected to boost patients' response to targeted therapy and immunotherapy.