Background: Necroptosis, a cell death of caspase-independence, plays a pivotal role in cancer biological regulation. Although necroptosis is closely associated with oncogenesis, cancer metastasis, and immunity, there remains a lack of studies determining the role of necroptosis-related genes (NRGs) in the highly immunogenic cancer type, kidney renal clear cell carcinoma (KIRC). Methods: The information of clinicopathology and transcriptome was extracted from TCGA database. Following the division into the train and test cohorts, a three-NRGs (TLR3, FASLG, ZBP1) risk model was identified in train cohort by LASSO regression. The overall survival (OS) comparison was conducted between different risk groups through Kaplan-Meier analysis, which was further validated in test cohort. The Cox proportional hazards regression model was introduced to assess its impact of clinicopathological factors and risk score on survival. ESTIMATE and CIBERSORT algorithms were introduced to evaluate immune microenvironment, while enrichment analysis was conducted to explore the biological significance. Correlation analysis was applied for the correlation assessment between checkpoint gene expression and risk score, between gene expression and therapeutic response. Gene expressions from TCGA were verified by GEO datasets and immunohistochemistry (IHC) analysis. Results: This NRGs-related signature predicted poorer OS in high-risk group, which was also verified in test cohort. Risk score could also independently predict survival outcome of KIRC. Significant changes were also found in immune microenvironment and checkpoint gene expressions between different risk groups, with immune functional enrichment in high-risk group. Interestingly, therapeutic response was correlated with the expressions of NRGs. The expressions of NRGs from TCGA were consistent with those from GEO datasets and IHC analysis.
Conclusion:The NRGs-related signature functions as a novel prognostic predictor of immune microenvironment and therapeutic response in KIRC.