Prediction of the immunological and prognostic value of five signatures related to fatty acid metabolism in patients with cervical cancer - Zeng, Qiongjing; Jiang, Huici; Lu, Fang; Fu, Mingxu; Bi, Yingying; Zhou, Zengding; Cheng, Jiajing; Qin, Jinlong (Frontiers in Oncology, 2022)
A growing attention has been attached to the role of fatty acid metabolism (FAM) in the development of cancer, and cervical cancer (CC) is still the primary cause of cancer-associated death in women worldwide. Therefore, it is imperative to explore the possible prognostic significance of FAM in CC. In this study, CC samples and corresponding normal samples were acquired from the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx). Single sample gene set enrichment analysis (ssGSEA) was conducted for calculating FAM-related scores (FAMRs) to screen FAM-related genes (FAMRGs). Two subtypes related to FAM were identified by consistent clustering. Among them, subtype C2 had a poor prognosis, and C1 had a high level of immune cell infiltration, while C2 had a high possibility of immune escape and was insensitive to chemotherapy drugs. Based on the differentially expressed genes (DEGs) in the two subtypes, a 5-gene signature (PLCB4, FBLN5, TSPAN8, CST6, and SERPINB7) was generated by the least absolute shrinkage and selection operator (LASSO) and Akaike information criterion (AIC). The model demonstrated a high prognostic accuracy (area under the curve (AUC)>0.7) in multiple cohorts and was one independent prognostic factor for CC patients. Accordingly, FAMRGs can be adopted as a biomarker for the prediction of CC patients’ prognosis and help guide the immunotherapy of CC.