4.6 Article

Identification and Quantification of Necroptosis Landscape on Therapy and Prognosis in Kidney Renal Clear Cell Carcinoma

Journal

FRONTIERS IN GENETICS
Volume 13, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2022.832046

Keywords

kidney renal clear cell carcinoma; necroptosis; tumor immune microenvironment; prognostic signature; nomogram; bioinformatics

Funding

  1. National Natural Science Foundation of China [82072838]
  2. Huazhong University of Science and Technology [2019kfyXKJC06]
  3. Tongji Outstanding Young Researcher Funding [2020YQ13]

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In this study, the necroptosis landscape of KIRC patients was quantified and two distinct necroptosis-related patterns were identified. A stable and accurate prognostic marker called NRGscore was constructed, which showed significant correlations with clinicopathological characteristics, tumor immune microenvironment, and tumor mutation burden of KIRC patients. NRGscore also had effective guiding significance for immunotherapy, chemotherapy, and targeted drugs.
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.

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