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Development and validation of a novel anoikis-related gene signature in clear cell renal cell carcinoma
BACKGROUND: Despite numerous treatments available, clear cell renal cell carcinoma (ccRCC) remains a deadly and invasive cancer. Anoikis-related genes (ARGs) are essential regulators of tumor metastasis and development. However, the potential roles of ARGs in ccRCC remain unclear. METHODS: Based on...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10641395/ https://www.ncbi.nlm.nih.gov/pubmed/37965453 http://dx.doi.org/10.3389/fonc.2023.1211103 |
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author | Wu, Qihang Sun, Yuxiang Qin, Xiangcheng Li, Maomao Huang, Shuaishuai Wang, Xue Weng, Guobin |
author_facet | Wu, Qihang Sun, Yuxiang Qin, Xiangcheng Li, Maomao Huang, Shuaishuai Wang, Xue Weng, Guobin |
author_sort | Wu, Qihang |
collection | PubMed |
description | BACKGROUND: Despite numerous treatments available, clear cell renal cell carcinoma (ccRCC) remains a deadly and invasive cancer. Anoikis-related genes (ARGs) are essential regulators of tumor metastasis and development. However, the potential roles of ARGs in ccRCC remain unclear. METHODS: Based on the TCGA-KIRC cohort and GeneCards database, we identified differentially expressed ARGs in ccRCC. Then a 4 ARGs risk model was created by Cox regression and LASSO. The Kaplan-Meier and receiver operating characteristic (ROC) curves were utilized to verify the predictive efficacy of the prognostic signature. Subsequently, the possible molecular mechanism of ARGs was investigated by functional enrichment analysis. To assess the immune infiltration, immune checkpoint genes, and immune function in various risk groups, single sample gene set enrichment (ssGSEA) algorithm was employed. Furthermore, the low-risk and high-risk groups were compared in terms of tumor mutation burden (TMB). Ultimately, we analyzed the protein expression of these four ARGs utilizing the western blot test. RESULTS: Four genes were utilized to create a risk signature that may predict prognosis, enabling the classification of KIRC patients into groups with low or high risk. The reliability of the signature was examined utilizing survival analysis and ROC analysis. According to the multivariate Cox regression result, the risk score was a reliable independent prognostic predictor for KIRC patients. The novel risk model could differentiate between KIRC patients with various clinical outcomes and represent KIRC’s specific immune status. An analysis of the correlation of TMB and risk score indicated a positive correlation between them, with high TMB being potentially linked to worse outcomes. CONCLUSION: Based on our findings, the prognostic signature of ARGs may be employed as an independent prognostic factor for ccRCC patients. It may introduce alternative perspectives on prognosis evaluation and serve as a prominent reference for personalized and precise therapy in KIRC. |
format | Online Article Text |
id | pubmed-10641395 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-106413952023-11-14 Development and validation of a novel anoikis-related gene signature in clear cell renal cell carcinoma Wu, Qihang Sun, Yuxiang Qin, Xiangcheng Li, Maomao Huang, Shuaishuai Wang, Xue Weng, Guobin Front Oncol Oncology BACKGROUND: Despite numerous treatments available, clear cell renal cell carcinoma (ccRCC) remains a deadly and invasive cancer. Anoikis-related genes (ARGs) are essential regulators of tumor metastasis and development. However, the potential roles of ARGs in ccRCC remain unclear. METHODS: Based on the TCGA-KIRC cohort and GeneCards database, we identified differentially expressed ARGs in ccRCC. Then a 4 ARGs risk model was created by Cox regression and LASSO. The Kaplan-Meier and receiver operating characteristic (ROC) curves were utilized to verify the predictive efficacy of the prognostic signature. Subsequently, the possible molecular mechanism of ARGs was investigated by functional enrichment analysis. To assess the immune infiltration, immune checkpoint genes, and immune function in various risk groups, single sample gene set enrichment (ssGSEA) algorithm was employed. Furthermore, the low-risk and high-risk groups were compared in terms of tumor mutation burden (TMB). Ultimately, we analyzed the protein expression of these four ARGs utilizing the western blot test. RESULTS: Four genes were utilized to create a risk signature that may predict prognosis, enabling the classification of KIRC patients into groups with low or high risk. The reliability of the signature was examined utilizing survival analysis and ROC analysis. According to the multivariate Cox regression result, the risk score was a reliable independent prognostic predictor for KIRC patients. The novel risk model could differentiate between KIRC patients with various clinical outcomes and represent KIRC’s specific immune status. An analysis of the correlation of TMB and risk score indicated a positive correlation between them, with high TMB being potentially linked to worse outcomes. CONCLUSION: Based on our findings, the prognostic signature of ARGs may be employed as an independent prognostic factor for ccRCC patients. It may introduce alternative perspectives on prognosis evaluation and serve as a prominent reference for personalized and precise therapy in KIRC. Frontiers Media S.A. 2023-10-26 /pmc/articles/PMC10641395/ /pubmed/37965453 http://dx.doi.org/10.3389/fonc.2023.1211103 Text en Copyright © 2023 Wu, Sun, Qin, Li, Huang, Wang and Weng 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 | Oncology Wu, Qihang Sun, Yuxiang Qin, Xiangcheng Li, Maomao Huang, Shuaishuai Wang, Xue Weng, Guobin Development and validation of a novel anoikis-related gene signature in clear cell renal cell carcinoma |
title | Development and validation of a novel anoikis-related gene signature in clear cell renal cell carcinoma |
title_full | Development and validation of a novel anoikis-related gene signature in clear cell renal cell carcinoma |
title_fullStr | Development and validation of a novel anoikis-related gene signature in clear cell renal cell carcinoma |
title_full_unstemmed | Development and validation of a novel anoikis-related gene signature in clear cell renal cell carcinoma |
title_short | Development and validation of a novel anoikis-related gene signature in clear cell renal cell carcinoma |
title_sort | development and validation of a novel anoikis-related gene signature in clear cell renal cell carcinoma |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10641395/ https://www.ncbi.nlm.nih.gov/pubmed/37965453 http://dx.doi.org/10.3389/fonc.2023.1211103 |
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