Kidney renal clear cell
carcinoma (KIRC) has high morbidity and gradually increased in recent years, and the rate of progression once relapsed is high. At present, owing to lack of effective prognosis predicted markers and post-recurrence
drug selection guidelines, the prognosis of KIRC patients is greatly affected. Necroptosis is a regulated form of cell
necrosis in a way that is independent of
caspase. Induced necroptosis is considered an effective strategy in
chemotherapy and targeted drugs, and it can also be used to improve the efficacy of
immunotherapy. Herein, we quantified the necroptosis landscape of KIRC patients from The
Cancer Genome Atlas (TCGA) database and divided them into two distinct necroptosis-related patterns (C1 and C2) through the non-negative matrix factorization (NMF) algorithm. Multi-analysis revealed the differences in clinicopathological characteristics and
tumor immune microenvironment (TIME). Then, we constructed the NRG prognosis signature (NRGscore), which contained 10 NRGs (PLK1, APP, TNFRSF21, CXCL8, MYCN, TNFRSF1A,
TRAF2, HSP90AA1, STUB1, and FLT3). We confirmed that NRGscore could be used as an independent prognostic marker for KIRC patients and performed excellent stability and accuracy. A nomogram model was also established to provide a more beneficial prognostic
indicator for the clinic. We found that NRGscore was significantly correlated with clinicopathological characteristics, TIME, and
tumor mutation burden (TMB) of KIRC patients. Moreover, NRGscore had effective guiding significance for
immunotherapy,
chemotherapy, and targeted drugs.