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Identification of CXCL10 as a Prognostic Biomarker for Clear Cell Renal Cell Carcinoma

BACKGROUND: One of the widespread forms of kidney tumor is clear cell renal cell carcinoma (ccRCC), with poor prognosis and insensitivity to radio chemotherapy as there is limited capacity to understand the disease mechanism. This study aims at identifying potential biomarkers and the underlying pro...

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Autores principales: Qu, Genyi, Wang, Hao, Yan, Huiqin, Liu, Genlin, Wu, Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8918693/
https://www.ncbi.nlm.nih.gov/pubmed/35296026
http://dx.doi.org/10.3389/fonc.2022.857619
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author Qu, Genyi
Wang, Hao
Yan, Huiqin
Liu, Genlin
Wu, Min
author_facet Qu, Genyi
Wang, Hao
Yan, Huiqin
Liu, Genlin
Wu, Min
author_sort Qu, Genyi
collection PubMed
description BACKGROUND: One of the widespread forms of kidney tumor is clear cell renal cell carcinoma (ccRCC), with poor prognosis and insensitivity to radio chemotherapy as there is limited capacity to understand the disease mechanism. This study aims at identifying potential biomarkers and the underlying processes of ccRCC using bioinformatics analysis. METHODS: Transcriptome data of relevant samples were downloaded from The Cancer Genome Atlas (TCGA) database. R software was used to screen differentially expressed genes (DEGs) using the “edgeR” package. Two types of analysis—Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment—were accomplished by applying Database for Annotation, Visualization, and Integrated Discovery (DAVID) and Search Tool for the Retrieval of Interacting Genes database (STRING) online bioinformatics tools. A protein–protein interaction (PPI) network of the identified DEGs was constructed using Cytoscape software, and hub genes were subsequently selected via the Cytohubba plug-in. The selected genes were input into Oncomine for verification. Finally, selected hub genes were analyzed by doing survival analysis to notice the relationship between survival (OS) rate and the selected genes’ level of expression. RESULTS: There were 1,855 DEGs found connected to ccRCC, with 1,207 upregulated genes and 648 downregulated genes. G-protein-coupled receptor signaling pathway, integral component of membrane, calcium ion binding, and cytokine–cytokine receptor interaction were among the DEGs discovered. Oncomine confirmed the top six hub genes from the PPI network (C3, CXCR3, CXCL10, CCR5, CCL4, and CCL5). A high level of expression of CXCL10, one of these hub genes, was linked to a poor prognosis in individuals with ccRCC. The results of survival analysis showed that the expression level of CXCL10 was significantly correlated with the prognosis of ccRCC patients (p < 0.05). CONCLUSIONS: From the analysis, the following results were drawn: CXCL10 might be a potential prognostic biomarker and novel therapeutic target for ccRCC.
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spelling pubmed-89186932022-03-15 Identification of CXCL10 as a Prognostic Biomarker for Clear Cell Renal Cell Carcinoma Qu, Genyi Wang, Hao Yan, Huiqin Liu, Genlin Wu, Min Front Oncol Oncology BACKGROUND: One of the widespread forms of kidney tumor is clear cell renal cell carcinoma (ccRCC), with poor prognosis and insensitivity to radio chemotherapy as there is limited capacity to understand the disease mechanism. This study aims at identifying potential biomarkers and the underlying processes of ccRCC using bioinformatics analysis. METHODS: Transcriptome data of relevant samples were downloaded from The Cancer Genome Atlas (TCGA) database. R software was used to screen differentially expressed genes (DEGs) using the “edgeR” package. Two types of analysis—Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment—were accomplished by applying Database for Annotation, Visualization, and Integrated Discovery (DAVID) and Search Tool for the Retrieval of Interacting Genes database (STRING) online bioinformatics tools. A protein–protein interaction (PPI) network of the identified DEGs was constructed using Cytoscape software, and hub genes were subsequently selected via the Cytohubba plug-in. The selected genes were input into Oncomine for verification. Finally, selected hub genes were analyzed by doing survival analysis to notice the relationship between survival (OS) rate and the selected genes’ level of expression. RESULTS: There were 1,855 DEGs found connected to ccRCC, with 1,207 upregulated genes and 648 downregulated genes. G-protein-coupled receptor signaling pathway, integral component of membrane, calcium ion binding, and cytokine–cytokine receptor interaction were among the DEGs discovered. Oncomine confirmed the top six hub genes from the PPI network (C3, CXCR3, CXCL10, CCR5, CCL4, and CCL5). A high level of expression of CXCL10, one of these hub genes, was linked to a poor prognosis in individuals with ccRCC. The results of survival analysis showed that the expression level of CXCL10 was significantly correlated with the prognosis of ccRCC patients (p < 0.05). CONCLUSIONS: From the analysis, the following results were drawn: CXCL10 might be a potential prognostic biomarker and novel therapeutic target for ccRCC. Frontiers Media S.A. 2022-02-28 /pmc/articles/PMC8918693/ /pubmed/35296026 http://dx.doi.org/10.3389/fonc.2022.857619 Text en Copyright © 2022 Qu, Wang, Yan, Liu and Wu 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
Qu, Genyi
Wang, Hao
Yan, Huiqin
Liu, Genlin
Wu, Min
Identification of CXCL10 as a Prognostic Biomarker for Clear Cell Renal Cell Carcinoma
title Identification of CXCL10 as a Prognostic Biomarker for Clear Cell Renal Cell Carcinoma
title_full Identification of CXCL10 as a Prognostic Biomarker for Clear Cell Renal Cell Carcinoma
title_fullStr Identification of CXCL10 as a Prognostic Biomarker for Clear Cell Renal Cell Carcinoma
title_full_unstemmed Identification of CXCL10 as a Prognostic Biomarker for Clear Cell Renal Cell Carcinoma
title_short Identification of CXCL10 as a Prognostic Biomarker for Clear Cell Renal Cell Carcinoma
title_sort identification of cxcl10 as a prognostic biomarker for clear cell renal cell carcinoma
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8918693/
https://www.ncbi.nlm.nih.gov/pubmed/35296026
http://dx.doi.org/10.3389/fonc.2022.857619
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