Identification of ferroptosis-related signature with potential implications in prognosis and immunotherapy of renal cell carcinoma.

Abstract

Developing individualized therapies for different renal cell carcinoma patients is pivotal for improving the efficacy of immunotherapy. It has been reported that ferroptosis is involved in T cell-mediated anti-tumor immunity, and that therapeutic approaches targeting tumor ferroptosis pathway in combination with immune checkpoint blockade drugs improve the efficacy of cancer immunotherapy. This study focused specifically on ferroptosis genes to identify novel biomarkers that reflect prognosis in different renal cell carcinoma subtypes. LASSO algorithm and multivariate Cox regression were initiated for identifying ferroptosis-related multigene risk signature (FRGsig) and established a FRGsig score model. We used multiple tumor microenvironment gene signatures and methods to infer tumor microenvironment status and immune cell invasion levels. Our study found that high FRGsig score was associated with poor prognosis in patients with predominant histologic subtypes of renal cell carcinoma. And high FRGsig score samples had higher levels of anti-tumor immunity cells infiltration, and there was a feedback mechanism whereby anti-tumor inflammation promoted the recruitment or differentiation of immunosuppressive cells. FRGsig was a potential biomarker for predicting the response to immune checkpoint blockade therapy in kidney clear cell carcinoma and kidney papillary cell carcinoma, and the kidney papillary cell carcinoma patients with high FRGsig was associated with better response to anti-VEGF therapy. Our findings provided further insights into assessing immunotherapy sensitivity of predominant histologic subtypes of renal cell carcinoma. FRGsig might be a potential biomarker for predicting the efficacy of angiogenic blocking drugs or immune checkpoint inhibitors in different renal cell carcinoma subtypes, enabling more precise patient selection.