Prognostic significance and immune landscape of a fatty acid metabolism-related gene signature in colon adenocarcinoma

Abstract

Background: Fatty acid metabolism (FAM), as a hallmark of caner, plays important roles in tumor initiation and carcinogenesis. However, the significance of fatty acid metabolism-related genes in colon adenocarcinoma (COAD) are largely unknown.Methods: RNA sequencing data and clinical information were downloaded from the Cancer Genome Atlas (TCGA) cohort. Univariate and multivariate Cox regression analyses were utilized to construct a fatty acid metabolism-related gene signature. Kaplan-Meier survival and receiver operating characteristic (ROC) analyses were used to verify the performance of this signature. GEO datasets were applied to validate the signature. Maftools package was utilized to analyze the mutation profiles of this signature. Correlation between the risk signature and stemness scores was compared by RNA stemness score (RNAss). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set variation analysis (GSVA) were performed to explore the potential functions and signaling pathways. Immune landscape of the signature was explored by analyzing different immune cells infiltration, immune functions and microsatellite instability. A nomogram was constructed by combining the risk signature and multiple clinical factors. Expression levels and prognostic values of the risk genes were revealed in the cancer genome atlas and GEO databases. Moreover, the expression the risk genes were measured in cell lines using real time quantitative PCR (qRT-PCR).Results: Eight fatty acid metabolism-related genes (CD36, ENO3, MORC2, PTGR1, SUCLG2, ELOVL3, ELOVL6 and CPT2) were used to construct a risk signature. This signature demonstrated better prognostic value than other clinicopathological parameters, with AUC value was 0.734 according to the cancer genome atlas database. There was negative correlation between the riskscore and RNA stemness score. The patients in the high-risk group demonstrated higher infiltration of M0 macrophages, and less infiltration of activated CD4 memory T cells and Eosinophils. There were more MSI patients in the high-risk group than those in the low-risk group (38% vs. 30%). The risk scores of patients in the MSI group were slightly higher than those in the microsatellite stability group. Gene ontology, kyoto encyclopedia of genes and genomes and gene set variation analysis enrichment analyses showed that several metabolism-related functions and signaling pathways were enriched. A nomogram showed good predictive capability of the signature. Moreover, qRT-PCR revealed upregulated expression of ENO3, MORC2, SUCLG2 and ELOVL6, and downregulated expression of CPT2 in all examined colon adenocarcinoma cell lines.Conclusion: This study provided novel insights into a fatty acid metabolism-related signature in the prognosis an immune landscape of colon adenocarcinoma patients.

Identification of cell differentiation trajectory-related gene signature to reveal the prognostic significance and immune landscape in prostate cancer based on multiomics analysis

“…The analysis of gene mutation data was performed using the “Maftools” software, and comparisons were made with previous methodologies to assess the correlation between the risk score and RNA stem score [ 31 ]. Additionally, Gene Set Variation Analysis (GSVA) was carried out using the “limma” “GSEABase” and “GSVA” packages [ 32 ].…”

Prognostic significance and immune landscape of a cell cycle progression-related risk model in bladder cancer

“…The “survival” and “survminer’’ packages were used to identify prognostic CCP-related genes; previous literature techniques are cited [ 27 ]. In order to identify important genes and create risk models, univariate and multivariate Cox regression analyses were carried out.…”

“…With reference to earlier literature studies, an RNA expression based (full set of accessible genes) score was computed to assess the cancer stemness index (RNA stemness score, RNAss) [ 29 ]. Referring to other research methods [ 27 ], the link between the RNA stemness score and the CCP-related model risk score was evaluated.…”

“…Using the “survival” package, univariate and multivariate Cox regression analysis were carried out. The “survival”, “survminer”, and “timeROC’’ programs in R software were then used to assess the CCP-related risk model with a number of clinical factors, with reference to earlier literature methods [ 27 ].…”

“…R software, a statistically sound program with extensive literature documentation, was used for data processing (version 4.2.1). Every statistical and data processing technique has reference to earlier publications in the literature [ 12 , 22 , 27 ]. The t-test was used to compare groups, and P < 0.05 was chosen as the threshold for statistical significance.…”