Identification of m 7 G-related Subtypes, Validation of Prognostic Models, and Tumor Immune Microenvironment in Gastric Cancer

Background: Gastric cancer (GC) ranks as the fourth most prevalent cancer globally, with heterogeneous prognosis and high mortality rates. Numerous studies have highlighted the close association between the occurrence and progression of gastric cancer and the N7-methylguanosine (m7G) mechanism. This study aims to determine the clinical significance of m7G-related genes (m7Gs) in gastric cancer prognosis and investigate their potential connection with the tumor immune microenvironment Methods: Gastric cancer data was obtained from the Cancer Genome Atlas (TCGA) library to generate the m7G pattern prognosis-related genes (m7G-PRGs) matrix. Two distinct m7G typings were initially identified, followed by unsupervised clustering based on m7G-related cluster C1 and C2 (m7G-C1/2) integrated differentially expressed genes (DEGs) to acquire a scoring system. The m7G-related prognostic model (m7G-RPM) was then constructed, with key prognostic genes experimentally validated through Western blot analysis. Subsequently, gastric cancer patients were stratified into high/low-scoring subgroups using the calculated median m7G_score, facilitating the investigation of prognosis-related mechanisms. Furthermore, biological signaling pathways were systematically enriched, a nomogram was developed, and TIME in gastric cancer was assessed. Results: Alterations in m7Gs are associated with a poor prognosis, with the primary outcome being hypermethylation in cancer, which regulates immune signaling and promotes cellular infiltration. Two distinct m7G clusters were identified, revealing m7Gs' bidirectional regulatory role in clinicopathological features and the TIME. A nomogram containing seven variable genes improved the clinical applicability of m7G-RPM, with increased solute carrier family 39 member 4 (SLC39A4) and matrix metallopeptidase 7 (MMP7) expression observed in gastric cancer cells. The m7G_score was significantly associated with microsatellite instability (MSI), tumor mutation burden (TMB), chemotherapeutic drug sensitivity, and cancer stem cell (CSC) index. Conclusion: A comprehensive analysis of m7G s in gastric cancer confirmed their potential role in genetic alterations, TIME, clinical traits, and prognosis, especially in tumor-infiltrating immune cells (TIICs). We constructed a novel prognostic model based on m7Gs and performed preliminary validation of the screened genes. These findings present innovative perspectives for assessing the prognosis of gastric cancer and guiding individualized immunotherapy strategies for patients.