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Identification of key pathways and genes in PTEN mutation prostate cancer by bioinformatics analysis

BACKGROUND: Prostate cancer (Pca) remains one of the leading adult malignancies. PTEN (Phosphatase and Tensin Homolog) mutant is the top common mutated genes in prostate cancer, which makes it a promising biomarker in future individualized treatment. METHODS: We obtained gene expression data of pros...

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Autores principales: Sun, Jian, Li, Shugen, Wang, Fei, Fan, Caibin, Wang, Jianqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6889628/
https://www.ncbi.nlm.nih.gov/pubmed/31791268
http://dx.doi.org/10.1186/s12881-019-0923-7
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author Sun, Jian
Li, Shugen
Wang, Fei
Fan, Caibin
Wang, Jianqing
author_facet Sun, Jian
Li, Shugen
Wang, Fei
Fan, Caibin
Wang, Jianqing
author_sort Sun, Jian
collection PubMed
description BACKGROUND: Prostate cancer (Pca) remains one of the leading adult malignancies. PTEN (Phosphatase and Tensin Homolog) mutant is the top common mutated genes in prostate cancer, which makes it a promising biomarker in future individualized treatment. METHODS: We obtained gene expression data of prostate cancer from TCGA (The Cancer Genome Atlas) database for analysis. We analyzed the DEGs (differentially expressed genes), and used online tools or software to analyze Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene set enrichment analysis (GSEA), Search Tool for the Retrieval of Interacting Genes/Proteins, and Molecular Complex Detection. RESULTS: Latest TCGA data showed PTEN mutation in about 22% patients. 1736 DEGs in total were identified. Results of gene functional enrichment analyses showed that muscle contraction, negative regulation of growth and multiple metabolic progression were significantly enriched. GNG13, ACTN2, POTEE, ACTA1, MYH6, MYH3, MYH7, MYL1, TNNC1 and TNNC2 were the top ten hub genes. Patients with PTEN mutation showed relatively decreased mRNA expression level of PTEN. Survival analysis indicated the risk of disease recurrence in patients with PTEN mutation. CONCLUSIONS: Our findings suggested that PTEN mutation in prostate cancer may induce changes in a variety of genes and pathways and affect disease progression, suggesting the significance of PTEN mutation in individualized treatment of prostate cancer.
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spelling pubmed-68896282019-12-11 Identification of key pathways and genes in PTEN mutation prostate cancer by bioinformatics analysis Sun, Jian Li, Shugen Wang, Fei Fan, Caibin Wang, Jianqing BMC Med Genet Research Article BACKGROUND: Prostate cancer (Pca) remains one of the leading adult malignancies. PTEN (Phosphatase and Tensin Homolog) mutant is the top common mutated genes in prostate cancer, which makes it a promising biomarker in future individualized treatment. METHODS: We obtained gene expression data of prostate cancer from TCGA (The Cancer Genome Atlas) database for analysis. We analyzed the DEGs (differentially expressed genes), and used online tools or software to analyze Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene set enrichment analysis (GSEA), Search Tool for the Retrieval of Interacting Genes/Proteins, and Molecular Complex Detection. RESULTS: Latest TCGA data showed PTEN mutation in about 22% patients. 1736 DEGs in total were identified. Results of gene functional enrichment analyses showed that muscle contraction, negative regulation of growth and multiple metabolic progression were significantly enriched. GNG13, ACTN2, POTEE, ACTA1, MYH6, MYH3, MYH7, MYL1, TNNC1 and TNNC2 were the top ten hub genes. Patients with PTEN mutation showed relatively decreased mRNA expression level of PTEN. Survival analysis indicated the risk of disease recurrence in patients with PTEN mutation. CONCLUSIONS: Our findings suggested that PTEN mutation in prostate cancer may induce changes in a variety of genes and pathways and affect disease progression, suggesting the significance of PTEN mutation in individualized treatment of prostate cancer. BioMed Central 2019-12-02 /pmc/articles/PMC6889628/ /pubmed/31791268 http://dx.doi.org/10.1186/s12881-019-0923-7 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 Research Article
Sun, Jian
Li, Shugen
Wang, Fei
Fan, Caibin
Wang, Jianqing
Identification of key pathways and genes in PTEN mutation prostate cancer by bioinformatics analysis
title Identification of key pathways and genes in PTEN mutation prostate cancer by bioinformatics analysis
title_full Identification of key pathways and genes in PTEN mutation prostate cancer by bioinformatics analysis
title_fullStr Identification of key pathways and genes in PTEN mutation prostate cancer by bioinformatics analysis
title_full_unstemmed Identification of key pathways and genes in PTEN mutation prostate cancer by bioinformatics analysis
title_short Identification of key pathways and genes in PTEN mutation prostate cancer by bioinformatics analysis
title_sort identification of key pathways and genes in pten mutation prostate cancer by bioinformatics analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6889628/
https://www.ncbi.nlm.nih.gov/pubmed/31791268
http://dx.doi.org/10.1186/s12881-019-0923-7
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