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Screening of potential therapy targets for prostate cancer using integrated analysis of two gene expression profiles

The aim of the present study was to analyze potential therapy targets for prostate cancer using integrated analysis of two gene expression profiles. First, gene expression profiles GSE38241 and GSE3933 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) b...

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Autores principales: Zhao, Rui, Wang, Yao, Zhang, Muchun, Gu, Xinquan, Wang, Weihua, Tan, Jiufeng, Wei, Xin, Jin, Ning
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5662906/
https://www.ncbi.nlm.nih.gov/pubmed/29113170
http://dx.doi.org/10.3892/ol.2017.6879
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author Zhao, Rui
Wang, Yao
Zhang, Muchun
Gu, Xinquan
Wang, Weihua
Tan, Jiufeng
Wei, Xin
Jin, Ning
author_facet Zhao, Rui
Wang, Yao
Zhang, Muchun
Gu, Xinquan
Wang, Weihua
Tan, Jiufeng
Wei, Xin
Jin, Ning
author_sort Zhao, Rui
collection PubMed
description The aim of the present study was to analyze potential therapy targets for prostate cancer using integrated analysis of two gene expression profiles. First, gene expression profiles GSE38241 and GSE3933 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between prostate cancer and normal control samples were identified using the Linear Models for Microarray Data package. Pathway enrichment analysis of DEGs was performed using Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes. Furthermore, protein-protein interaction (PPI) networks of DEGs were constructed, on the basis of the Search Tool for the Retrieval of Interacting Genes/Proteins database. The Molecular Complex Detection was utilized to perform module analysis of the PPI networks. In addition, transcriptional regulatory networks were constructed on the basis of the associations between transcription factors (TFs) and target genes. A total of 529 DEGs were identified, including 129 upregulated genes that were primarily associated with to the cell cycle. Additionally, 400 downregulated genes were identified, which were principally enriched in the pathways associated with vascular smooth muscle contraction and focal adhesion. Cell Division Cycle Associated 8, Cell Division Cycle 45, Ubiquitin Conjugating Enzyme E2 C and Thymidine Kinase 1 were identified as hub genes in the upregulated sub-network. Furthermore, the upregulated TF E2F, and the downregulated TF Early Growth Response 1, were identified to be critical in the transcriptional regulatory networks. The identified DEGs and TFs may have critical roles in the progression of prostate cancer, and may be used as target molecules for treating prostate cancer.
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spelling pubmed-56629062017-11-06 Screening of potential therapy targets for prostate cancer using integrated analysis of two gene expression profiles Zhao, Rui Wang, Yao Zhang, Muchun Gu, Xinquan Wang, Weihua Tan, Jiufeng Wei, Xin Jin, Ning Oncol Lett Articles The aim of the present study was to analyze potential therapy targets for prostate cancer using integrated analysis of two gene expression profiles. First, gene expression profiles GSE38241 and GSE3933 were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between prostate cancer and normal control samples were identified using the Linear Models for Microarray Data package. Pathway enrichment analysis of DEGs was performed using Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes. Furthermore, protein-protein interaction (PPI) networks of DEGs were constructed, on the basis of the Search Tool for the Retrieval of Interacting Genes/Proteins database. The Molecular Complex Detection was utilized to perform module analysis of the PPI networks. In addition, transcriptional regulatory networks were constructed on the basis of the associations between transcription factors (TFs) and target genes. A total of 529 DEGs were identified, including 129 upregulated genes that were primarily associated with to the cell cycle. Additionally, 400 downregulated genes were identified, which were principally enriched in the pathways associated with vascular smooth muscle contraction and focal adhesion. Cell Division Cycle Associated 8, Cell Division Cycle 45, Ubiquitin Conjugating Enzyme E2 C and Thymidine Kinase 1 were identified as hub genes in the upregulated sub-network. Furthermore, the upregulated TF E2F, and the downregulated TF Early Growth Response 1, were identified to be critical in the transcriptional regulatory networks. The identified DEGs and TFs may have critical roles in the progression of prostate cancer, and may be used as target molecules for treating prostate cancer. D.A. Spandidos 2017-11 2017-09-04 /pmc/articles/PMC5662906/ /pubmed/29113170 http://dx.doi.org/10.3892/ol.2017.6879 Text en Copyright: © Zhao et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Zhao, Rui
Wang, Yao
Zhang, Muchun
Gu, Xinquan
Wang, Weihua
Tan, Jiufeng
Wei, Xin
Jin, Ning
Screening of potential therapy targets for prostate cancer using integrated analysis of two gene expression profiles
title Screening of potential therapy targets for prostate cancer using integrated analysis of two gene expression profiles
title_full Screening of potential therapy targets for prostate cancer using integrated analysis of two gene expression profiles
title_fullStr Screening of potential therapy targets for prostate cancer using integrated analysis of two gene expression profiles
title_full_unstemmed Screening of potential therapy targets for prostate cancer using integrated analysis of two gene expression profiles
title_short Screening of potential therapy targets for prostate cancer using integrated analysis of two gene expression profiles
title_sort screening of potential therapy targets for prostate cancer using integrated analysis of two gene expression profiles
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5662906/
https://www.ncbi.nlm.nih.gov/pubmed/29113170
http://dx.doi.org/10.3892/ol.2017.6879
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