Correlation analysis of fatty acid metabolism-related genes and the prognosis of ovarian cancer

Abstract Background Increasing evidence suggests that abnormal fatty acid metabolism (FAM) is a switch triggering tumor progression. The aim of this study was to explore the prognostic value of FAM-related genes (FAMRGs) in serous ovarian cancer (SOC) by bioinformatics analysis and to develop a novel FAM-related prognostic signature. Methods Clinicopathological characteristics and FAMRGs were obtained from The Cancer Genome Atlas database and the Molecular Signatures Database. The limma R package and Cox regression were used to determine the FAM-related signature. The Kaplan-Meier curve and Cox regression were used to evaluate the prognostic value of the risk score, after which gene set variation analysis was performed to explore the biological functions. The immune cell infiltration level was analyzed. The potential response to immune checkpoint inhibitor (ICI) therapy was evaluated by the tumor immune dysfunction and exclusion algorithm. Finally, RT-PCR analysis was performed to measure the expression levels of 9 prognostic genes. Results Nine FAMRGs that were significantly associated with SOC prognosis were screened out, and a robust risk scoring model was constructed. This risk score was also an independent prognostic factor for patients with SOC. Patients with high-risk scores were characterized by poor clinical outcomes, lower levels of immune cell infiltration, and elevated TIDE scores. In addition, patients with low-risk scores may be better candidates for ICI therapy. Conclusions Our data suggest that the abnormal expression of 9 FAM-related genes is closely related to the progression of SOC. Moreover, a novel FAM-related prognostic signature may contribute to immunotherapy consultation for SOC.