4.6 Article

A prognosis model for clear cell renal cell carcinoma based on four necroptosis-related genes

Journal

FRONTIERS IN MEDICINE
Volume 9, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fmed.2022.942991

Keywords

necroptosis; clear cell renal cell carcinoma; prognosis; platinum drug resistance; genes

Funding

  1. Key Research and Development Program of Hubei Province
  2. [2020BCB051]

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In this study, a risk model based on necroptosis-related genes (NRGs) was constructed using COX regression analysis to predict the prognosis of patients with clear cell renal cell carcinoma (ccRCC). The results showed that patients in the high-risk group had shorter survival time and the predictive model had high accuracy. The study provides new insights into the biological mechanisms of necroptosis in ccRCC patients.
Necroptosis is a type of caspase-independent cell death, and it plays a critical role in regulating the development of cancer. To date, little is known about the role of necroptosis-related genes (NRGs) in clear cell renal cell carcinoma (ccRCC). In this study, we downloaded data regarding the expression of NRGs and overall survival (OS) from The Cancer Genome Atlas (TCGA) database and constructed a risk model to determine the prognostic features of necroptosis using COX regression analysis. Patients with ccRCC were divided into low-risk and high-risk groups based on their risk scores. Thereafter, Kaplan-Meier curves were used to evaluate OS, and receiver operating characteristic (ROC) curves were used to determine the accuracy of prediction. Stratified analyses were performed according to different clinical variables. Furthermore, we assessed the correlation between clinical variables and risk scores; the NRGs with differential expression were mainly enriched in positive regulation of intracellular transport and platinum resistance pathways. We constructed prognostic signatures for OS based on four NRGs and showed that the survival time was significantly longer in the low-risk groups than in the high-risk groups (p < 0.001). The area of the ROC curve for OS was 0.717, indicating excellent predictive accuracy of the established model. Therefore, a predictive model based on NRGs was constructed, which can predict the prognosis of patients and provides insights into the biological mechanisms underlying necroptosis in patients with ccRCC.

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