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The Ion Channel-Related Gene Signatures Correlated With Diagnosis, Prognosis, and Individualized Treatment in Patients With Clear Cell Renal Cell Carcinoma
Background: Early detection and precise prognostic evaluation of clear cell renal cell carcinoma (ccRCC) are crucial for patient life expectancy. Ion channel-related genes (ICRGs) are of great diagnostic and prognostic value as components that maintain the normal structure of the kidney. Therefore,...
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/PMC9198310/ https://www.ncbi.nlm.nih.gov/pubmed/35721115 http://dx.doi.org/10.3389/fphar.2022.889142 |
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author | Zhu, Zhenpeng Lei, Zhenchuan Qian, Jinqin Zhang, Cuijian Gong, Yanqing Yin, Guicao Li, Yifan Li, Xuesong Lin, Jian Zhou, Liqun |
author_facet | Zhu, Zhenpeng Lei, Zhenchuan Qian, Jinqin Zhang, Cuijian Gong, Yanqing Yin, Guicao Li, Yifan Li, Xuesong Lin, Jian Zhou, Liqun |
author_sort | Zhu, Zhenpeng |
collection | PubMed |
description | Background: Early detection and precise prognostic evaluation of clear cell renal cell carcinoma (ccRCC) are crucial for patient life expectancy. Ion channel-related genes (ICRGs) are of great diagnostic and prognostic value as components that maintain the normal structure of the kidney. Therefore, we systematically explored the diagnostic, prognostic, and therapeutic value of ICRGs in ccRCC using the multi-database. Methods: RNA transcriptome profiles and clinical data of ccRCC patients were extracted and integrated from public databases including The Cancer Genome Atlas, ICGC, GEO, and E-MTAB databases. Ion channel-related genes were obtained from the literature collection. The diagnostic signature was performed using the LASSO and SVM-REF analyses. Meanwhile, the prognostic signature was conducted using the LASSO analyses. Molecular subtyping was performed using the ConsensusClusterPlus and the corresponding therapeutic targets were evaluated using the pRRophetic package. In addition, a prognostic nomogram was constructed based on the results of cox regression analyses. Results: We successfully constructed diagnostic signatures for five ICRGs and prognostic signatures for 10 ICRGs with AUC values greater than 0.7, showing good predictive performance. Based on the median risk score, we found that high-risk patients had a significantly worse prognosis. We also divided ccRCC patients into two clusters according to prognostic ICRGs, and there was a significant survival outcome between the two clusters and different sensitivity to diverse clinical therapeutic strategies. Meanwhile, we constructed a nomogram based on clinical molecules and signatures, and its predictive efficacy was better than the signature or the present tumor-node-metastasis staging system. Conclusion: In this study, we established useful signatures for early detection, prognosis evaluation, and individualized treatment for ccRCC. Moreover, KCNJ16 deserves to be explored comprehensively in the future. |
format | Online Article Text |
id | pubmed-9198310 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91983102022-06-16 The Ion Channel-Related Gene Signatures Correlated With Diagnosis, Prognosis, and Individualized Treatment in Patients With Clear Cell Renal Cell Carcinoma Zhu, Zhenpeng Lei, Zhenchuan Qian, Jinqin Zhang, Cuijian Gong, Yanqing Yin, Guicao Li, Yifan Li, Xuesong Lin, Jian Zhou, Liqun Front Pharmacol Pharmacology Background: Early detection and precise prognostic evaluation of clear cell renal cell carcinoma (ccRCC) are crucial for patient life expectancy. Ion channel-related genes (ICRGs) are of great diagnostic and prognostic value as components that maintain the normal structure of the kidney. Therefore, we systematically explored the diagnostic, prognostic, and therapeutic value of ICRGs in ccRCC using the multi-database. Methods: RNA transcriptome profiles and clinical data of ccRCC patients were extracted and integrated from public databases including The Cancer Genome Atlas, ICGC, GEO, and E-MTAB databases. Ion channel-related genes were obtained from the literature collection. The diagnostic signature was performed using the LASSO and SVM-REF analyses. Meanwhile, the prognostic signature was conducted using the LASSO analyses. Molecular subtyping was performed using the ConsensusClusterPlus and the corresponding therapeutic targets were evaluated using the pRRophetic package. In addition, a prognostic nomogram was constructed based on the results of cox regression analyses. Results: We successfully constructed diagnostic signatures for five ICRGs and prognostic signatures for 10 ICRGs with AUC values greater than 0.7, showing good predictive performance. Based on the median risk score, we found that high-risk patients had a significantly worse prognosis. We also divided ccRCC patients into two clusters according to prognostic ICRGs, and there was a significant survival outcome between the two clusters and different sensitivity to diverse clinical therapeutic strategies. Meanwhile, we constructed a nomogram based on clinical molecules and signatures, and its predictive efficacy was better than the signature or the present tumor-node-metastasis staging system. Conclusion: In this study, we established useful signatures for early detection, prognosis evaluation, and individualized treatment for ccRCC. Moreover, KCNJ16 deserves to be explored comprehensively in the future. Frontiers Media S.A. 2022-06-01 /pmc/articles/PMC9198310/ /pubmed/35721115 http://dx.doi.org/10.3389/fphar.2022.889142 Text en Copyright © 2022 Zhu, Lei, Qian, Zhang, Gong, Yin, Li, Li, Lin and Zhou. 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 | Pharmacology Zhu, Zhenpeng Lei, Zhenchuan Qian, Jinqin Zhang, Cuijian Gong, Yanqing Yin, Guicao Li, Yifan Li, Xuesong Lin, Jian Zhou, Liqun The Ion Channel-Related Gene Signatures Correlated With Diagnosis, Prognosis, and Individualized Treatment in Patients With Clear Cell Renal Cell Carcinoma |
title | The Ion Channel-Related Gene Signatures Correlated With Diagnosis, Prognosis, and Individualized Treatment in Patients With Clear Cell Renal Cell Carcinoma |
title_full | The Ion Channel-Related Gene Signatures Correlated With Diagnosis, Prognosis, and Individualized Treatment in Patients With Clear Cell Renal Cell Carcinoma |
title_fullStr | The Ion Channel-Related Gene Signatures Correlated With Diagnosis, Prognosis, and Individualized Treatment in Patients With Clear Cell Renal Cell Carcinoma |
title_full_unstemmed | The Ion Channel-Related Gene Signatures Correlated With Diagnosis, Prognosis, and Individualized Treatment in Patients With Clear Cell Renal Cell Carcinoma |
title_short | The Ion Channel-Related Gene Signatures Correlated With Diagnosis, Prognosis, and Individualized Treatment in Patients With Clear Cell Renal Cell Carcinoma |
title_sort | ion channel-related gene signatures correlated with diagnosis, prognosis, and individualized treatment in patients with clear cell renal cell carcinoma |
topic | Pharmacology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9198310/ https://www.ncbi.nlm.nih.gov/pubmed/35721115 http://dx.doi.org/10.3389/fphar.2022.889142 |
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