Construction and validation of a post-translational modification-related signature to predict the effect of immune therapies in gastric cancer.

Gastric cancer (GC) is a highly heterogeneous malignancy of the digestive system. Treatment outcomes and prognosis for GC vary significantly depending on the molecular subtype. Protein posttranslational modifications (PTMs), including Ubiquitination, SUMOylation, and NEDDylation, have been implicated in the emergence and progression of GC, though the precise mechanisms remain unclear. Therefore, it is critical to elucidate the prognosis and treatment role of PTM-related genes (PRGs) in GC by Cox regression and clustering analysis. In this study, we utilized PRGs to classify GC into three molecular subtypes. Using LASSO and Cox regression analyses, we developed a PTM-related prognostic signature consisting of six prognostic PRGs in the TCGA-STAD cohort, and we validated this signature in the independent GSE62254 dataset. The resulting risk score has the ability to forecast the overall survival (OS) in GC patients. This signature stratifies patients into high- and low-risk groups with significantly different OS outcomes (p < 0.001). Notably, lower risk scores correlate with higher tumor mutation burden (TMB) values, lower TIDE scores, higher MSI-H ratios, and better responses to immunotherapy. Collectively, our results provide a basis for PTM-related research and construct a prognostic signature for GC. This signature holds promise for advancing diagnostic strategies and enhancing therapeutic approches in GC.