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Identification and Quantification of Necroptosis Landscape on Therapy and Prognosis in Kidney Renal Clear Cell Carcinoma
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...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8882778/ https://www.ncbi.nlm.nih.gov/pubmed/35237304 http://dx.doi.org/10.3389/fgene.2022.832046 |
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author | Xin, Sheng Mao, Jiaquan Duan, Chen Wang, Jiaxin Lu, Yuchao Yang, Jun Hu, Jia Liu, Xiaming Guan, Wei Wang, Tao Wang, Shaogang Liu, Jihong Song, Wen Song, Xiaodong |
author_facet | Xin, Sheng Mao, Jiaquan Duan, Chen Wang, Jiaxin Lu, Yuchao Yang, Jun Hu, Jia Liu, Xiaming Guan, Wei Wang, Tao Wang, Shaogang Liu, Jihong Song, Wen Song, Xiaodong |
author_sort | Xin, Sheng |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8882778 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88827782022-03-01 Identification and Quantification of Necroptosis Landscape on Therapy and Prognosis in Kidney Renal Clear Cell Carcinoma Xin, Sheng Mao, Jiaquan Duan, Chen Wang, Jiaxin Lu, Yuchao Yang, Jun Hu, Jia Liu, Xiaming Guan, Wei Wang, Tao Wang, Shaogang Liu, Jihong Song, Wen Song, Xiaodong Front Genet Genetics 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. Frontiers Media S.A. 2022-02-14 /pmc/articles/PMC8882778/ /pubmed/35237304 http://dx.doi.org/10.3389/fgene.2022.832046 Text en Copyright © 2022 Xin, Mao, Duan, Wang, Lu, Yang, Hu, Liu, Guan, Wang, Wang, Liu, Song and Song. 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 | Genetics Xin, Sheng Mao, Jiaquan Duan, Chen Wang, Jiaxin Lu, Yuchao Yang, Jun Hu, Jia Liu, Xiaming Guan, Wei Wang, Tao Wang, Shaogang Liu, Jihong Song, Wen Song, Xiaodong Identification and Quantification of Necroptosis Landscape on Therapy and Prognosis in Kidney Renal Clear Cell Carcinoma |
title | Identification and Quantification of Necroptosis Landscape on Therapy and Prognosis in Kidney Renal Clear Cell Carcinoma |
title_full | Identification and Quantification of Necroptosis Landscape on Therapy and Prognosis in Kidney Renal Clear Cell Carcinoma |
title_fullStr | Identification and Quantification of Necroptosis Landscape on Therapy and Prognosis in Kidney Renal Clear Cell Carcinoma |
title_full_unstemmed | Identification and Quantification of Necroptosis Landscape on Therapy and Prognosis in Kidney Renal Clear Cell Carcinoma |
title_short | Identification and Quantification of Necroptosis Landscape on Therapy and Prognosis in Kidney Renal Clear Cell Carcinoma |
title_sort | identification and quantification of necroptosis landscape on therapy and prognosis in kidney renal clear cell carcinoma |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8882778/ https://www.ncbi.nlm.nih.gov/pubmed/35237304 http://dx.doi.org/10.3389/fgene.2022.832046 |
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