Identification of subtypes of clear cell renal cell carcinoma and construction of a prognostic model based on fatty acid metabolism genes

Abstract

Background: The effects of fatty acid metabolism in many tumors have been widely reported. Due to the diversity of lipid synthesis, uptake, and transformation in clear cell renal cell carcinoma (ccRCC) cells, many studies have shown that ccRCC is associated with fatty acid metabolism. The study aimed was to explore the impact of fatty acid metabolism genes on the prognosis and immunotherapy of ccRCC. Methods: Two subtypes were distinguished by unsupervised clustering analysis based on the expression of 309 fatty acid metabolism genes. A prognostic model was constructed by lasso algorithm and multivariate COX regression analysis using fatty acid metabolism genes as the signatures. The tumor microenvironment between subtypes and between risk groups was further analyzed. The International Cancer Genome Consortium cohort was used for external validation of the model. Results: The analysis showed that subtype B had a poorer prognosis and a higher degree of immune infiltration. The high-risk group had a poorer prognosis and higher tumor microenvironment scores. The nomogram could accurately predict patient survival. Conclusion: Fatty acid metabolism may affect the prognosis and immune infiltration of patients with ccRCC. The analysis was performed to understand the potential role of fatty acid metabolism genes in the immune infiltration and prognosis of patients. These findings have implications for individualized treatment, prognosis, and immunization for patients with ccRCC.