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Identification of MX2 as a Novel Prognostic Biomarker for Sunitinib Resistance in Clear Cell Renal Cell Carcinoma

BACKGROUND: Antiangiogenic agents that specifically target vascular endothelial growth factor receptor (VEGFR), such as sunitinib, have been utilized as the standard therapy for metastatic clear cell renal cell carcinoma (ccRCC) patients. However, most patients eventually show no responses to the ta...

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Autores principales: Wei, Yuang, Chen, Xinglin, Ren, Xiaohan, Wang, Bao, Zhang, Qian, Bu, Hengtao, Qian, Jian, Shao, Pengfei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8299280/
https://www.ncbi.nlm.nih.gov/pubmed/34306023
http://dx.doi.org/10.3389/fgene.2021.680369
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author Wei, Yuang
Chen, Xinglin
Ren, Xiaohan
Wang, Bao
Zhang, Qian
Bu, Hengtao
Qian, Jian
Shao, Pengfei
author_facet Wei, Yuang
Chen, Xinglin
Ren, Xiaohan
Wang, Bao
Zhang, Qian
Bu, Hengtao
Qian, Jian
Shao, Pengfei
author_sort Wei, Yuang
collection PubMed
description BACKGROUND: Antiangiogenic agents that specifically target vascular endothelial growth factor receptor (VEGFR), such as sunitinib, have been utilized as the standard therapy for metastatic clear cell renal cell carcinoma (ccRCC) patients. However, most patients eventually show no responses to the targeted drugs, and the mechanisms for the resistance remain unclear. This study is aimed to identify pivotal molecules and to uncover their potential functions involved in this adverse event in ccRCC treatment. METHODS: Two datasets, GSE64052 and GSE76068, were obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using the limma package in R software. The gene set enrichment analysis (GSEA) was conducted using clusterProfiler package. A protein–protein interaction (PPI) network was built using the STRING database and Cytoscape software. Kaplan—Meier survival curves were plotted using R software. qRT-PCR and Western blotting were used to detect the MX2 and pathway expression in RCC cell lines. Sunitinib-resistant cell lines were constructed, and loss-of-function experiments were conducted by knocking down MX2. All statistical analyses were performed using R version 3.6.1 and SPSS 23.0. RESULTS: A total of 760 DEGs were derived from two datasets in GEO database, and five hub genes were identified, among which high-level MX2 exhibited a pronounced correlation with poor overall survival (OS) in sunitinib-resistant ccRCC patients. Clinical correlation analysis and Gene Set Variation Analysis (GSVA) on MX2 showed that the upregulation of MX2 was significantly related to the malignant phenotype of ccRCC, and it was involved in several pathways and biological processes associated with anticancer drug resistance. qRT-PCR and Western blotting revealed that MX2 was distinctly upregulated in sunitinib-resistant RCC cell lines. Colony formation assay and Cell Counting Kit-8 (CCK8) assay showed that MX2 strongly promoted resistant capability to sunitinib of ccRCC cells. CONCLUSION: MX2 is a potent indicator for sunitinib resistance and a therapeutic target in ccRCC patients.
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spelling pubmed-82992802021-07-24 Identification of MX2 as a Novel Prognostic Biomarker for Sunitinib Resistance in Clear Cell Renal Cell Carcinoma Wei, Yuang Chen, Xinglin Ren, Xiaohan Wang, Bao Zhang, Qian Bu, Hengtao Qian, Jian Shao, Pengfei Front Genet Genetics BACKGROUND: Antiangiogenic agents that specifically target vascular endothelial growth factor receptor (VEGFR), such as sunitinib, have been utilized as the standard therapy for metastatic clear cell renal cell carcinoma (ccRCC) patients. However, most patients eventually show no responses to the targeted drugs, and the mechanisms for the resistance remain unclear. This study is aimed to identify pivotal molecules and to uncover their potential functions involved in this adverse event in ccRCC treatment. METHODS: Two datasets, GSE64052 and GSE76068, were obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using the limma package in R software. The gene set enrichment analysis (GSEA) was conducted using clusterProfiler package. A protein–protein interaction (PPI) network was built using the STRING database and Cytoscape software. Kaplan—Meier survival curves were plotted using R software. qRT-PCR and Western blotting were used to detect the MX2 and pathway expression in RCC cell lines. Sunitinib-resistant cell lines were constructed, and loss-of-function experiments were conducted by knocking down MX2. All statistical analyses were performed using R version 3.6.1 and SPSS 23.0. RESULTS: A total of 760 DEGs were derived from two datasets in GEO database, and five hub genes were identified, among which high-level MX2 exhibited a pronounced correlation with poor overall survival (OS) in sunitinib-resistant ccRCC patients. Clinical correlation analysis and Gene Set Variation Analysis (GSVA) on MX2 showed that the upregulation of MX2 was significantly related to the malignant phenotype of ccRCC, and it was involved in several pathways and biological processes associated with anticancer drug resistance. qRT-PCR and Western blotting revealed that MX2 was distinctly upregulated in sunitinib-resistant RCC cell lines. Colony formation assay and Cell Counting Kit-8 (CCK8) assay showed that MX2 strongly promoted resistant capability to sunitinib of ccRCC cells. CONCLUSION: MX2 is a potent indicator for sunitinib resistance and a therapeutic target in ccRCC patients. Frontiers Media S.A. 2021-07-09 /pmc/articles/PMC8299280/ /pubmed/34306023 http://dx.doi.org/10.3389/fgene.2021.680369 Text en Copyright © 2021 Wei, Chen, Ren, Wang, Zhang, Bu, Qian and Shao. 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
Wei, Yuang
Chen, Xinglin
Ren, Xiaohan
Wang, Bao
Zhang, Qian
Bu, Hengtao
Qian, Jian
Shao, Pengfei
Identification of MX2 as a Novel Prognostic Biomarker for Sunitinib Resistance in Clear Cell Renal Cell Carcinoma
title Identification of MX2 as a Novel Prognostic Biomarker for Sunitinib Resistance in Clear Cell Renal Cell Carcinoma
title_full Identification of MX2 as a Novel Prognostic Biomarker for Sunitinib Resistance in Clear Cell Renal Cell Carcinoma
title_fullStr Identification of MX2 as a Novel Prognostic Biomarker for Sunitinib Resistance in Clear Cell Renal Cell Carcinoma
title_full_unstemmed Identification of MX2 as a Novel Prognostic Biomarker for Sunitinib Resistance in Clear Cell Renal Cell Carcinoma
title_short Identification of MX2 as a Novel Prognostic Biomarker for Sunitinib Resistance in Clear Cell Renal Cell Carcinoma
title_sort identification of mx2 as a novel prognostic biomarker for sunitinib resistance in clear cell renal cell carcinoma
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8299280/
https://www.ncbi.nlm.nih.gov/pubmed/34306023
http://dx.doi.org/10.3389/fgene.2021.680369
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