Integrative bioinformatics analysis of a prognostic index and immunotherapeutic targets in renal cell carcinoma

Renal cell carcinoma (RCC) is one of the most common malignancies. The immunogenomic landscape signature significantly correlates with the progression and prognosis of RCC. Novel therapeutic targets and prognostic indices in RCC are highly desirable. The TCGA database enables comprehensive immunogenomic landscape analysis. Differentially expressed immune-related genes (IRGs) were obtained from TCGA and GO analyses, and KEGG pathway analyses were performed to explore their functions and molecular mechanisms. Multivariable Cox analysis was utilized to calculate the risk score of each patient and locate survival-associated IRGs, thereby constructing a novel immune-related gene-based prognostic index (IRGPI). The correlation between IRGPI and immune cell infiltration was also investigated. A total of 41 differentially expressed IRGs were notably related to prognosis in RCC. GO functions and KEGG pathway analyses demonstrated that these genes were primarily associated with the tumour immune response and cytokine-cytokine receptor interaction pathway. An IRGPI based on seventeen survival-associated differentially expressed IRGs was constructed and exhibited a moderate predictive value in the prognosis of RCC patients and a powerful identification ability in refining the risk stratification of RCC patients. A close correlation was found between IRGPI and specific clinicopathological parameters, including age, gender, pathological stage, tumour stage, lymph node metastasis and distant metastasis. A positive correlation was found between IRGPI and the infiltration levels of neutrophils, dendritic cells, CD8 + T cells and B cells. Our results demonstrated the clinical significance and potential function of IRGs, providing additional data for prognostic risk prediction and immunotherapeutic target selection in RCC.