Abstract
BACKGROUND: Gastric cancer (GC), originating from gastric mucosa epithelial cells, is a global health issue, ranking as the fifth most common cancer and fourth in cancer-related deaths. Stomach adenocarcinoma (STAD) accounts for 95% of GC cases. Emerging evidence suggests a link between manganese (Mn) metabolism and GC, but the role of Mn metabolism-related genes (MMRGs) in STAD is unclear. This study aims to bridge this gap of Mn metabolism through the development of a robust prognostic signature derived from The Cancer Genome Atlas (TCGA) data. METHODS: We used RNA-sequencing data and clinical information from TCGA to identify STAD subtypes and developed a Mn metabolism scoring model to predict STAD prognosis. RESULTS: An extensive clustering analysis of 115 prognostic MMRGs related to GC facilitated the distinction of two unique subtypes classified as Cluster 1 (C1) and Cluster 2 (C2). The subsequent Kaplan-Meier survival analysis revealed that the C1 subtype had a better survival rate than the C2 subtype. Additionally, a statistically significant difference was observed between the two subtypes in terms of patient age and tumor grade. The box plot examination revealed a marked difference in the immune cell populations, including a diminished presence of B cells, CD4(+) T cells, endothelial cells, and macrophages in the C1 samples compared with the C2 samples. A majority of immune checkpoints, particularly CTLA4, HAVCR2, IGSF8, ITPRIPL1, LAG3, PDCD1, PDCD1LG2, and TIGIT, exhibited significantly higher expression levels in the C2 group than in the C1 group. Our findings revealed that a total of 13 genes were upregulated, while 1,146 genes were downregulated in the C1 cohort. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis highlighted significant pathways, including the extracellular matrix (ECM)-receptor interaction, focal adhesion, and proteoglycans in cancer. Furthermore, the Gene Ontology (GO) analysis revealed that the enriched biological processes included ECM organization, cell-substrate adhesion, and cell-matrix adhesion. STAD patients were further categorized into high- and low-MMRG groups based on MMRGs. This meticulous analysis identified seven prognostic markers: APOD, AKR1B1, CGB5, GAMT, VTN, SERPINE1, and GPX3. The expression levels of two specific genes, APOD and GPX3, were found to be significantly increased in both the fibroblast and myofibroblast subtypes in STAD based on the singe-cell RNA-sequencing data. Box plots demonstrated that AKR1B1 and GAMT were expressed across all nine identified cell subtypes, while VTN and SERPINE1 were lowly expressed across the same nine subtypes. CONCLUSIONS: This study developed a prognostic model for STAD using the expression levels of MMRGs. Our findings provide insights that could inform future targeted therapeutic approaches.