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Identification of aberrantly methylated differentially expressed genes in prostate carcinoma using integrated bioinformatics

BACKGROUND: Methylation plays a key role in the aetiology and pathogenesis of prostate cancer (PCa). This study aimed to identify aberrantly methylated differentially expressed genes (DEGs) and pathways in PCa and explore the underlying mechanisms of tumourigenesis. METHODS: Expression profile (GSE2...

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Autores principales: Wu, Kai, Yin, Xiaotao, Jin, Yipeng, Liu, Fangfang, Gao, Jiangping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6402097/
https://www.ncbi.nlm.nih.gov/pubmed/30872976
http://dx.doi.org/10.1186/s12935-019-0763-8
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author Wu, Kai
Yin, Xiaotao
Jin, Yipeng
Liu, Fangfang
Gao, Jiangping
author_facet Wu, Kai
Yin, Xiaotao
Jin, Yipeng
Liu, Fangfang
Gao, Jiangping
author_sort Wu, Kai
collection PubMed
description BACKGROUND: Methylation plays a key role in the aetiology and pathogenesis of prostate cancer (PCa). This study aimed to identify aberrantly methylated differentially expressed genes (DEGs) and pathways in PCa and explore the underlying mechanisms of tumourigenesis. METHODS: Expression profile (GSE29079) and methylation profile (GSE76938) datasets were obtained from the Gene Expression Omnibus (GEO). We used R 3.4.4 software to assess aberrantly methylated DEGs. The Cancer Genome Atlas (TCGA) RNA sequencing and Illumina HumanMethylation450 DNA methylation data were utilized to validate screened genes. Functional enrichment analysis of the screened genes was performed, and a protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Gens (STRING). The results were visualized in Cytoscape. After confirmation using TCGA, cBioPortal was used to examine alterations in genes of interest. Then, protein localization in PCa cells was observed using immunohistochemistry. RESULTS: Overall, 536 hypomethylated upregulated genes were identified that were enriched in biological processes such as negative regulation of transcription, osteoblast differentiation, intracellular signal transduction, and the Wnt signalling pathway. Pathway enrichment showed significant changes in factors involved in AMPK signalling, cancer, and adherens junction pathways. The hub oncogenes were AKT1, PRDM10, and FASN. Additionally, 322 hypermethylated downregulated genes were identified that demonstrated enrichment in biological processes including positive regulation of the MAPK cascade, muscle contraction, ageing, and signal transduction. Pathway analysis indicated enrichment in arrhythmogenic right ventricular cardiomyopathy (ARVC), focal adhesion, dilated cardiomyopathy, and PI3K-AKT signalling. The hub tumour suppressor gene was FLNA. Immunohistochemistry showed that AKT1, FASN, and FLNA were mainly expressed in PCa cell cytoplasm, while PRDM10 was mainly expressed in nuclei. CONCLUSIONS: Our results identify numerous novel genetic and epigenetic regulatory networks and offer molecular evidence crucial to understanding the pathogenesis of PCa. Aberrantly methylated hub genes, including AKT1, PRDM10, FASN, and FLNA, can be used as biomarkers for accurate PCa diagnosis and treatment. In conclusion, our study suggests that AKT1, PRDM10, and FASN may be tumour promoters and that FLNA may be a tumour suppressor in PCa. We hope these findings will draw more attention to these hub genes in future cancer studies.
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spelling pubmed-64020972019-03-14 Identification of aberrantly methylated differentially expressed genes in prostate carcinoma using integrated bioinformatics Wu, Kai Yin, Xiaotao Jin, Yipeng Liu, Fangfang Gao, Jiangping Cancer Cell Int Primary Research BACKGROUND: Methylation plays a key role in the aetiology and pathogenesis of prostate cancer (PCa). This study aimed to identify aberrantly methylated differentially expressed genes (DEGs) and pathways in PCa and explore the underlying mechanisms of tumourigenesis. METHODS: Expression profile (GSE29079) and methylation profile (GSE76938) datasets were obtained from the Gene Expression Omnibus (GEO). We used R 3.4.4 software to assess aberrantly methylated DEGs. The Cancer Genome Atlas (TCGA) RNA sequencing and Illumina HumanMethylation450 DNA methylation data were utilized to validate screened genes. Functional enrichment analysis of the screened genes was performed, and a protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Gens (STRING). The results were visualized in Cytoscape. After confirmation using TCGA, cBioPortal was used to examine alterations in genes of interest. Then, protein localization in PCa cells was observed using immunohistochemistry. RESULTS: Overall, 536 hypomethylated upregulated genes were identified that were enriched in biological processes such as negative regulation of transcription, osteoblast differentiation, intracellular signal transduction, and the Wnt signalling pathway. Pathway enrichment showed significant changes in factors involved in AMPK signalling, cancer, and adherens junction pathways. The hub oncogenes were AKT1, PRDM10, and FASN. Additionally, 322 hypermethylated downregulated genes were identified that demonstrated enrichment in biological processes including positive regulation of the MAPK cascade, muscle contraction, ageing, and signal transduction. Pathway analysis indicated enrichment in arrhythmogenic right ventricular cardiomyopathy (ARVC), focal adhesion, dilated cardiomyopathy, and PI3K-AKT signalling. The hub tumour suppressor gene was FLNA. Immunohistochemistry showed that AKT1, FASN, and FLNA were mainly expressed in PCa cell cytoplasm, while PRDM10 was mainly expressed in nuclei. CONCLUSIONS: Our results identify numerous novel genetic and epigenetic regulatory networks and offer molecular evidence crucial to understanding the pathogenesis of PCa. Aberrantly methylated hub genes, including AKT1, PRDM10, FASN, and FLNA, can be used as biomarkers for accurate PCa diagnosis and treatment. In conclusion, our study suggests that AKT1, PRDM10, and FASN may be tumour promoters and that FLNA may be a tumour suppressor in PCa. We hope these findings will draw more attention to these hub genes in future cancer studies. BioMed Central 2019-03-05 /pmc/articles/PMC6402097/ /pubmed/30872976 http://dx.doi.org/10.1186/s12935-019-0763-8 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Primary Research
Wu, Kai
Yin, Xiaotao
Jin, Yipeng
Liu, Fangfang
Gao, Jiangping
Identification of aberrantly methylated differentially expressed genes in prostate carcinoma using integrated bioinformatics
title Identification of aberrantly methylated differentially expressed genes in prostate carcinoma using integrated bioinformatics
title_full Identification of aberrantly methylated differentially expressed genes in prostate carcinoma using integrated bioinformatics
title_fullStr Identification of aberrantly methylated differentially expressed genes in prostate carcinoma using integrated bioinformatics
title_full_unstemmed Identification of aberrantly methylated differentially expressed genes in prostate carcinoma using integrated bioinformatics
title_short Identification of aberrantly methylated differentially expressed genes in prostate carcinoma using integrated bioinformatics
title_sort identification of aberrantly methylated differentially expressed genes in prostate carcinoma using integrated bioinformatics
topic Primary Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6402097/
https://www.ncbi.nlm.nih.gov/pubmed/30872976
http://dx.doi.org/10.1186/s12935-019-0763-8
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