Development and Clinical Validation of a Novel 5 Gene Signature Based on Fatty Acid Metabolism‐Related Genes in Oral Squamous Cell Carcinoma

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Background/Aim.Lipid metabolism disorders play a crucial role in tumor development and progression. The aim of the study focused on constructing a novel prognostic model of oral squamous cell carcinoma (OSCC) patients using fatty acid metabolism‐related genes. Methods. Microarray test and data from The Cancer Genome Atlas (TCGA) were used to identify differentially expressed genes related to fatty acid metabolism. The quantitative real‐time polymerase chain reaction (qRT‐PCR) was then used to validate the expression of targeted fatty acid metabolism genes. A risk predictive scoring model of fatty acid metabolism‐related genes was generated using a multivariate Cox model. The efficacy of this model was assessed by time‐dependent receiver operating characteristic curve (ROC). Results. 14 fatty acid metabolism‐related genes were identified by microarray test and TCGA database analysis and then confirmed by PCR. Finally, a 5 gene signature (ACACB, FABP3, PDK4, PPARG, and PLIN5) was constructed and a RiskScore was calculated for each patient. Compared to the high RiskScore group, the low RiskScore group had better overall survival (OS) (p = 0.02). The RiskScore derived from a 5 gene signature was a prognostic factor (HR: 3.73, 95% CI: 1.38, 10.09) for OSCC patients. The predictive classification efficiencies of RiskScore were evaluated and the area under the curve (AUC) values for 1, 3, and 5 years were 0.613, 0.652, and 0.681, respectively. Then we compared the predictive performance of the prognostic model with or without the RiskScore. The 5 gene‐derived RiskScore can improve the predictive performance with AUC values of 0.760, 0.803, and 0.830 for 1, 3, and 5 years OS in prognostic model including the RiskScore. While the predicted AUC values of the model without RiskScore for 1, 3, and 5 years OS were 0.699, 0.715, and 0.714, respectively. Conclusion. We developed a predictive score model using 5 fatty acid metabolism‐related genes, which could be a potential prognostic indicator in OSCC.