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A risk signature based on necroptotic-process-related genes predicts prognosis and immune therapy response in kidney cell carcinoma
Necroptosis is a regulated form of cell necroptotic process, playing a pivotal role in tumors. In renal cell cancer (RCC), inhibiting necroptosis could promote the proliferation of tumor cells. However, the molecular mechanisms and prognosis prediction of necroptotic-process-related genes in RCC are...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9524857/ https://www.ncbi.nlm.nih.gov/pubmed/36189275 http://dx.doi.org/10.3389/fimmu.2022.922929 |
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author | Li, Jingxian Liu, Xun Qi, Yuanjiong Liu, Yang Du, E. Zhang, Zhihong |
author_facet | Li, Jingxian Liu, Xun Qi, Yuanjiong Liu, Yang Du, E. Zhang, Zhihong |
author_sort | Li, Jingxian |
collection | PubMed |
description | Necroptosis is a regulated form of cell necroptotic process, playing a pivotal role in tumors. In renal cell cancer (RCC), inhibiting necroptosis could promote the proliferation of tumor cells. However, the molecular mechanisms and prognosis prediction of necroptotic-process-related genes in RCC are still unclear. In this study, we first identified the necroptotic process prognosis-related genes (NPRGss) by analyzing the kidney renal clear cell carcinoma (KIRC) data in The Cancer Genome Atlas (TCGA, n=607). We systematically analyzed the expression alteration, clinical relevance, and molecular mechanisms of NPRGss in renal clear cell carcinoma. We constructed an NPRGs risk signature utilizing the least absolute shrinkage and selection operator (LASSO) Cox regression analysis on the basis of the expression of seven NPRGss. We discovered that the overall survival (OS) of KIRC patients differed significantly in high- or low-NPRGs-risk groups. The univariate/multivariate Cox regression revealed that the NPRGs risk signature was an independent prognosis factor in RCC. The gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used to explore the molecular mechanisms of NPRGss. Immune-/metabolism-related pathways showed differential enrichment in high-/low-NPRGs-risk groups. The E-MTAB-1980, TCGA-KIRP, GSE78220, the cohort of Alexandra et al., and IMvigor210 cohort datasets were respectively used as independent validation cohorts of NPRGs risk signature. The patients in high- or low-NPRGs-risk groups showed different drug sensitivity, immune checkpoint expression, and immune therapy response. Finally, we established a nomogram based on the NPRGs risk signature, stage, grade, and age for eventual clinical translation; the nomogram possesses an accurate and stable prediction effect. The signature could predict patients’ prognosis and therapy response, which provides the foundation for further clinical therapeutic strategies for RCC patients. |
format | Online Article Text |
id | pubmed-9524857 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95248572022-10-01 A risk signature based on necroptotic-process-related genes predicts prognosis and immune therapy response in kidney cell carcinoma Li, Jingxian Liu, Xun Qi, Yuanjiong Liu, Yang Du, E. Zhang, Zhihong Front Immunol Immunology Necroptosis is a regulated form of cell necroptotic process, playing a pivotal role in tumors. In renal cell cancer (RCC), inhibiting necroptosis could promote the proliferation of tumor cells. However, the molecular mechanisms and prognosis prediction of necroptotic-process-related genes in RCC are still unclear. In this study, we first identified the necroptotic process prognosis-related genes (NPRGss) by analyzing the kidney renal clear cell carcinoma (KIRC) data in The Cancer Genome Atlas (TCGA, n=607). We systematically analyzed the expression alteration, clinical relevance, and molecular mechanisms of NPRGss in renal clear cell carcinoma. We constructed an NPRGs risk signature utilizing the least absolute shrinkage and selection operator (LASSO) Cox regression analysis on the basis of the expression of seven NPRGss. We discovered that the overall survival (OS) of KIRC patients differed significantly in high- or low-NPRGs-risk groups. The univariate/multivariate Cox regression revealed that the NPRGs risk signature was an independent prognosis factor in RCC. The gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used to explore the molecular mechanisms of NPRGss. Immune-/metabolism-related pathways showed differential enrichment in high-/low-NPRGs-risk groups. The E-MTAB-1980, TCGA-KIRP, GSE78220, the cohort of Alexandra et al., and IMvigor210 cohort datasets were respectively used as independent validation cohorts of NPRGs risk signature. The patients in high- or low-NPRGs-risk groups showed different drug sensitivity, immune checkpoint expression, and immune therapy response. Finally, we established a nomogram based on the NPRGs risk signature, stage, grade, and age for eventual clinical translation; the nomogram possesses an accurate and stable prediction effect. The signature could predict patients’ prognosis and therapy response, which provides the foundation for further clinical therapeutic strategies for RCC patients. Frontiers Media S.A. 2022-09-16 /pmc/articles/PMC9524857/ /pubmed/36189275 http://dx.doi.org/10.3389/fimmu.2022.922929 Text en Copyright © 2022 Li, Liu, Qi, Liu, Du and Zhang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Immunology Li, Jingxian Liu, Xun Qi, Yuanjiong Liu, Yang Du, E. Zhang, Zhihong A risk signature based on necroptotic-process-related genes predicts prognosis and immune therapy response in kidney cell carcinoma |
title | A risk signature based on necroptotic-process-related genes predicts prognosis and immune therapy response in kidney cell carcinoma |
title_full | A risk signature based on necroptotic-process-related genes predicts prognosis and immune therapy response in kidney cell carcinoma |
title_fullStr | A risk signature based on necroptotic-process-related genes predicts prognosis and immune therapy response in kidney cell carcinoma |
title_full_unstemmed | A risk signature based on necroptotic-process-related genes predicts prognosis and immune therapy response in kidney cell carcinoma |
title_short | A risk signature based on necroptotic-process-related genes predicts prognosis and immune therapy response in kidney cell carcinoma |
title_sort | risk signature based on necroptotic-process-related genes predicts prognosis and immune therapy response in kidney cell carcinoma |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9524857/ https://www.ncbi.nlm.nih.gov/pubmed/36189275 http://dx.doi.org/10.3389/fimmu.2022.922929 |
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