Novel fatty acid metabolism biomarkers reveal prognosis and immune microenvironment in cervical cancer

Abstract

Abstract Accelerated research has increasingly shown that aberrant fatty acid metabolism played an important role in cancer progression and immune microenvironment remodeling. Nevertheless, the role of fatty acid metabolism in cervical cancer is unclear. Here, we downloaded the gene set of fatty acid metabolism from the MSigDB database and classified cervical cancer into three separate genomic stage types - C1, C2 and C3. Kaplan-Meier survival analysis revealed considerable differences in survival rates between the three stages (P < 0.05). Furthermore, MCPcounter analysis demonstrated that CD8 + T-cell infiltration was more frequent in C3, and this stage had the best prognosis. Notably, the C3 stage, with the best prognosis, had a higher frequency of CD8 + T-cell infiltration, whereas the C1 stage, with the worst prognosis, had a higher frequency of fibroblast infiltration (P < 0.05). We conducted weighted gene co-expression network analysis (WGCNA) on the three molecular types to identify the module with the highest correlation (the blue module), select co-expressed genes with an association greater than 0.3, and determine the intersection of the differential genes of the three molecular types. A new prognostic model of fatty acid metabolism genomics was developed. Survival analysis demonstrated that individuals in the low-risk group had higher immune and stromal scores and better overall survival rates. Six genes within this model displayed a negative correlation with immune checkpoints overall. In the immune efficacy analysis, individuals in the low-risk group exhibited higher immune efficacy than those in the high-risk group in the IPS score, The level of immune dysfunction was higher in the low-risk group than in the high-risk group in the TIDE algorithm. Conversely, the immune escape capacity was higher in the high-risk group than in the low-risk group, and the level of immunotherapy was higher overall in the high-risk group than in the low-risk group (P < 0.05). Mechanistically, the high-risk group exhibited significant enrichment in several pathways such as intercellular interactions, cell-matrix remodeling, angiogenesis, and epithelial-mesenchymal transition pathways. In conclusion, the predictive model for cervical cancer based on fatty acid metabolism reveals the possibility of predicting the prognosis and potential efficacy of immunotherapy for patients with cervical cancer.