Development and validation of hierarchical signature for precision individualized therapy based on the landscape associated with necroptosis in clear cell renal cell carcinoma

Abstract

Abstract Background Increasing evidences show that necroptosis has a unique clinical significance in the occurrence and development of multiple diseases. Here, we systematically evaluated the role of necroptosis in clear cell renal cell carcinoma (ccRCC) and analyzed its regulatory patterns. Results We screened 97 necroptosis-related genes and demonstrated that they were dysregulated in ccRCC. Through Cox analysis and LASSO regression, a prognostic prediction signature including seven genes was built. Receiver operating characteristic (ROC) curves and Kaplan-Meier (KM) analyses both showed that the model was accurate, and univariate/multivariate Cox analysis showed that as an independent prognostic factor, the higher the risk score, the poorer the survival outcome. Besides, the predicted scores based on the signature were observably associated with immune-cell infiltration and mutation of specific genes. In addition, the risk score could potentially predict the patients’ responsiveness to different chemotherapy regimens. In specific, Nivolumab is more effective for patients with higher scores. Conclusion The necroptosis-related signature we constructed can accurately predict the prognosis of ccRCC patients, and further providing clues for targeted, individualized therapy.