Integrative bioinformatics analysis of ACS enzymes as candidate prognostic and diagnostic biomarkers in colon adenocarcinoma

Abstract

Background and purpose: Acyl-CoA synthetase (ACS) enzymes play an important role in the activation of fatty acids. While many studies have found correlations between the expression levels of ACS enzymes with the progression, growth, and survival of cancer cells, their role and expression patterns in colon adenocarcinoma are still greatly unknown and demand further investigation. Experimental approach: The expression data of colon adenocarcinoma samples were downloaded from the Cancer Genome Atlas (TCGA) database. Normalization and differential expression analysis were performed to identify differentially expressed genes (DEGs). Gene set enrichment analysis was applied to identify top enriched genes from ACS enzymes in cancer samples. Gene ontology and protein-protein interaction analyses were performed for the prediction of molecular functions and interactions. Survival analysis and receiver operating characteristic test (ROC) were performed to find potential prognostic and diagnostic biomarkers. Findings/Results: ACSL6 and ACSM5 genes demonstrated more significant differential expression and LogFC value compared to other ACS enzymes and also achieved the highest enrichment scores. Gene ontology analysis predicted the involvement of top DEGs in fatty acids metabolism, while protein-protein interaction network analysis presented strong interactions between ACSLs, ACSSs, ACSMs, and ACSBG enzymes with each other. Survival analysis suggested ACSM3 and ACSM5 as potential prognostic biomarkers, while the ROC test predicted stronger diagnostic potential for ACSM5, ACSS2, and ACSF2 genes. Conclusion and implications: Our findings revealed the expression patterns, prognostic, and diagnostic biomarker potential of ACS enzymes in colon adenocarcinoma. ACSM3, ACSM5, ACSS2, and ACSF2 genes are suggested as possible prognostic and diagnostic biomarkers.