Fatty Acid Metabolism Signature Contributes to the Molecular Diagnosis of a Malignant Gastric Cancer Subtype with Poor Prognosis and Lower Mutation Burden.

Background: Gastric cancer (GC) is a common gastrointestinal tumor with high morbidity and mortality. Fatty acid metabolism (FAM) contributes to GC development. Patents have been issued for the use of compositions comprising fatty acid analogues for the treatment of many clinical conditions. However, its clinical significance and its relationship with tumor-related mutations have not been thoroughly discovered. This study was conducted to analyze and explore FAM-related genes' molecular characteristics, prognostic significance, and association with tumor- related mutations.

Methods: The gastric adenocarcinoma's transcriptome, clinical data, and tumor mutation load (TMB) data were downloaded from TCGA and GEO databases. The differentially expressed FAM genes (FAM DEGs) between cancer and control samples were screened, and their correlation with TMB and survival was analyzed. A PPI network of FAM DEGs was constructed, and a downscaling clustering analysis was performed based on the expression of the FAM DEGs. Further immuno- infiltration and GO/KEGG enrichment analyses of the identified FAM clusters were performed to explore their heterogeneity in biological functions. The effects of FAM score and gastric cancer (STAD) on TMB, MSI, survival prognosis, and drug sensitivity were jointly analyzed, and finally, a single-gene analysis of the obtained core targets was performed.

Results: Through differential analysis, 68 FAM DEGs were obtained, and they were highly associated with STAD tumor mutation load. In addition, a high FAM DEGs CNV rate was observed. The PPI network showed a complex mutual correlation between the FAM DEGs. Consensus clustering classified the patients into three clusters based on the FAM DEGs, and the clusters presented different survival rates. The GSVA and immune infiltration analysis revealed that metabolism, apoptosis, and immune infiltration-related pathways were variated. In addition, FAM genes, STAD prognostic risk genes, and PCA scores were closely associated with the survival status of STAD patients. FAM score was closely correlated with STAD TMB, MSI, and immunotherapy, and the TMB values in the low FAM score group were significantly higher than those in the high FAM score group. Finally, combining the above results, it was found that the core gene PTGS1 performed best in predicting STAD survival prognosis and TMB/MSI/immunotherapy.

Conclusion: Fatty acid metabolism genes affect the development of gastric adenocarcinoma and can predict the survival prognosis, tumor mutational load characteristics, and drug therapy sensitivity of STAD patients, which can help explore more effective immunotherapy targets for GC.