Conclusion
A gene signature related to cholesterol metabolism was developed and validated to forecast the prognosis of ccRCC, demonstrating a correlation with immune infiltration. Cholesterol metabolic genes such as SCARB1, were expected to contribute to the diagnosis and precision treatment of both ccRCC and skin cutaneous melanoma.
Methods
Gene expression profiles and clinical information of individuals diagnosed with prevalent malignant tumors were obtained from the TCGA database. For survival analysis, Kaplan-Meier curves were used. Consensus clustering was utilized to identify distinct molecular clusters. LASSO regression analysis was utilized to construct a novel prognostic signature. Differential analysis was used to analyze the differences in gene expression and various evaluation indicators between different subgroups. RT-qPCR and Immunohistochemistry were performed to examine the gene expression. Small interfering RNA transfection, CCK-8, and clone formation assays were conducted to verify the function of the target gene in ccRCC cell lines.
Objective
The metabolism of cholesterol has been found to be closely related to the proliferation, invasion, and metastasis of tumors. The purpose of this study was to investigate the correlation between cholesterol metabolic genes and the prognosis of clear cell renal cell carcinoma (ccRCC).
Results
Based on genes involved in cholesterol metabolism related to survival, two molecular ccRCC subtypes were identified with distinct clinical, immune, and biological features. A molecular signature which would be utilized to evaluate the prognosis and the immune status of the tumor microenvironment of ccRCC patients was also established. The SCARB1-mediated cholesterol-dependent metabolism occurred both in ccRCC and skin cutaneous melanoma.