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Identification of castration‐resistant prostate cancer‐related hub genes using weighted gene co‐expression network analysis

Prostate cancer is the most common malignancy in urinary system and brings heavy burdens in men. We downloaded gene expression profile of mRNA and related clinical data of GSE70768 data set from public database. Weighted gene co‐expression network analysis (WGCNA) was used to identify the relationsh...

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Autores principales: Cheng, Yifei, Li, Lu, Qin, Zongshi, Li, Xiao, Qi, Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7348158/
https://www.ncbi.nlm.nih.gov/pubmed/32485038
http://dx.doi.org/10.1111/jcmm.15432
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author Cheng, Yifei
Li, Lu
Qin, Zongshi
Li, Xiao
Qi, Feng
author_facet Cheng, Yifei
Li, Lu
Qin, Zongshi
Li, Xiao
Qi, Feng
author_sort Cheng, Yifei
collection PubMed
description Prostate cancer is the most common malignancy in urinary system and brings heavy burdens in men. We downloaded gene expression profile of mRNA and related clinical data of GSE70768 data set from public database. Weighted gene co‐expression network analysis (WGCNA) was used to identify the relationships between gene modules and clinical features, as well as the candidate genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were developed to investigate the potential functions of related hub genes. Importantly, basic experiments were performed to verify the relationship between hub genes and the phenotype previously identified. Lastly, copy number variation (CNV) analysis was conducted to explore the genetical alteration. WGCNA identified that black module was the most relevant module which was tightly related to castration‐resistant prostate cancer (CRPC) phenotype. KEGG and GO analysis results revealed genes in black module were mainly related to RNA splicing. Additionally, 9 genes were chosen as hub genes and heterogeneous nuclear ribonucleoprotein A2/B1 (HNRNPA2B1), golgin A8 family member B (GOLGA8B) and mitogen‐activated protein kinase 8 interacting protein 3 (MAPK8IP3) were identified to be associated with PCa progression and prognosis. Moreover, all above three genes were highly expressed in CRPC‐like cells and their suppression led to hindered cell proliferation in vitro. Finally, CNV analysis found that amplification was the main type of alteration of the 3 hub genes. Our study found that HNRNPA2B1, GOLGA8B and MAPK8IP3 were identified to be tightly associated with tumour progression and prognosis, and further researches are needed before clinical application.
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spelling pubmed-73481582020-07-14 Identification of castration‐resistant prostate cancer‐related hub genes using weighted gene co‐expression network analysis Cheng, Yifei Li, Lu Qin, Zongshi Li, Xiao Qi, Feng J Cell Mol Med Original Articles Prostate cancer is the most common malignancy in urinary system and brings heavy burdens in men. We downloaded gene expression profile of mRNA and related clinical data of GSE70768 data set from public database. Weighted gene co‐expression network analysis (WGCNA) was used to identify the relationships between gene modules and clinical features, as well as the candidate genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were developed to investigate the potential functions of related hub genes. Importantly, basic experiments were performed to verify the relationship between hub genes and the phenotype previously identified. Lastly, copy number variation (CNV) analysis was conducted to explore the genetical alteration. WGCNA identified that black module was the most relevant module which was tightly related to castration‐resistant prostate cancer (CRPC) phenotype. KEGG and GO analysis results revealed genes in black module were mainly related to RNA splicing. Additionally, 9 genes were chosen as hub genes and heterogeneous nuclear ribonucleoprotein A2/B1 (HNRNPA2B1), golgin A8 family member B (GOLGA8B) and mitogen‐activated protein kinase 8 interacting protein 3 (MAPK8IP3) were identified to be associated with PCa progression and prognosis. Moreover, all above three genes were highly expressed in CRPC‐like cells and their suppression led to hindered cell proliferation in vitro. Finally, CNV analysis found that amplification was the main type of alteration of the 3 hub genes. Our study found that HNRNPA2B1, GOLGA8B and MAPK8IP3 were identified to be tightly associated with tumour progression and prognosis, and further researches are needed before clinical application. John Wiley and Sons Inc. 2020-06-02 2020-07 /pmc/articles/PMC7348158/ /pubmed/32485038 http://dx.doi.org/10.1111/jcmm.15432 Text en © 2020 The Authors. Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Cheng, Yifei
Li, Lu
Qin, Zongshi
Li, Xiao
Qi, Feng
Identification of castration‐resistant prostate cancer‐related hub genes using weighted gene co‐expression network analysis
title Identification of castration‐resistant prostate cancer‐related hub genes using weighted gene co‐expression network analysis
title_full Identification of castration‐resistant prostate cancer‐related hub genes using weighted gene co‐expression network analysis
title_fullStr Identification of castration‐resistant prostate cancer‐related hub genes using weighted gene co‐expression network analysis
title_full_unstemmed Identification of castration‐resistant prostate cancer‐related hub genes using weighted gene co‐expression network analysis
title_short Identification of castration‐resistant prostate cancer‐related hub genes using weighted gene co‐expression network analysis
title_sort identification of castration‐resistant prostate cancer‐related hub genes using weighted gene co‐expression network analysis
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7348158/
https://www.ncbi.nlm.nih.gov/pubmed/32485038
http://dx.doi.org/10.1111/jcmm.15432
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