Abstract
Clear cell renal cell carcinomas (ccRCCs) are highly immune infiltrated and many of them benefits from immunotherapy with checkpoint inhibitors including anti-PD-L1 or anti-PD1 agents. But the effect of immune gene on clinical outcome in ccRCCs has not been fully studied. Here, we show in this study that an immune-associated gene panel has prognostic value for clear cell renal cell carcinomas. We performed single sample Gene Sets Enrichment Analysis (ssGSEA) as well as Cell type Identification by Estimating Subsets of RNA Transcripts (CIBERSORT) algorithms on patient-matched normal renal and RCCs tissue to characterise two immunophenotypes and immunological characteristic subpopulations. Furthermore, Lasso Cox regression was applied to develop a novel prognosis-associated model for ccRCC patients based on immune-gene panel. Results were verified by Gene Expression Omnibus (GEO) data set and coordinated with clinicopathologic characteristics of ccRCCs, along with genomic signatures. Finally, based on the above perspectives, we generated a nomogram with a high prognostic efficiency for ccRCC patient. Overall, this study offers a unique perspective to improve the accuracy of prognosis prediction and treatment with immunotherapy.
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