Abstract
BACKGROUND: Colorectal cancer (CRC) belongs to the class of significantly malignant tumors found in humans. Recently, dysregulated fatty acid metabolism (FAM) has been a topic of attention due to its modulation in cancer, specifically CRC. However, the regulatory FAM pathways in CRC require comprehensive elucidation. METHODS: The clinical and gene expression data of 175 fatty acid metabolic genes (FAMGs) linked with colon adenocarcinoma (COAD) and normal cornerstone genes were gathered through The Cancer Genome Atlas (TCGA)-COAD corroborating with the Molecular Signature Database v7.2 (MSigDB). Initially, crucial prognostic genes were selected by uni- and multi-variate Cox proportional regression analyses; then, depending upon these identified signature genes and clinical variables, a nomogram was generated. Lastly, to assess tumor immune characteristics, concomitant evaluation of tumor immune evasion/risk scoring were elucidated. RESULTS: A 8-gene signature, including ACBD4, ACOX1, CD36, CPT2, ELOVL3, ELOVL6, ENO3, and SUCLG2, was generated, and depending upon this, CRC patients were categorized within high-risk (H-R) and low-risk (L-R) cohorts. Furthermore, risk and age-based nomograms indicated moderate discrimination and good calibration. The data confirmed that the 8-gene model efficiently predicted CRC patients' prognosis. Moreover, according to the conjoint analysis of tumor immune evasion and the risk scorings, the H-R cohort had an immunosuppressive tumor microenvironment, which caused a substandard prognosis. CONCLUSION: This investigation established a FAMGs-based prognostic model with substantially high predictive value, providing the possibility for improved individualized treatment for CRC individuals.