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Identification of potential diagnostic and prognostic biomarkers for prostate cancer

Prostate cancer (PCa) is one of the most common malignant tumors worldwide. The aim of the present study was to determine potential diagnostic and prognostic biomarkers for PCa. The GSE103512 dataset was downloaded, and the differentially expressed genes (DEGs) were screened. Gene Ontology (GO), Kyo...

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Autores principales: Zhang, Qiang, Yin, Xiujuan, Pan, Zhiwei, Cao, Yingying, Han, Shaojie, Gao, Guojun, Gao, Zhiqin, Pan, Zhifang, Feng, Weiguo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6757266/
https://www.ncbi.nlm.nih.gov/pubmed/31579071
http://dx.doi.org/10.3892/ol.2019.10765
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author Zhang, Qiang
Yin, Xiujuan
Pan, Zhiwei
Cao, Yingying
Han, Shaojie
Gao, Guojun
Gao, Zhiqin
Pan, Zhifang
Feng, Weiguo
author_facet Zhang, Qiang
Yin, Xiujuan
Pan, Zhiwei
Cao, Yingying
Han, Shaojie
Gao, Guojun
Gao, Zhiqin
Pan, Zhifang
Feng, Weiguo
author_sort Zhang, Qiang
collection PubMed
description Prostate cancer (PCa) is one of the most common malignant tumors worldwide. The aim of the present study was to determine potential diagnostic and prognostic biomarkers for PCa. The GSE103512 dataset was downloaded, and the differentially expressed genes (DEGs) were screened. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction (PPI) analyses of DEGs were performed. The result of GO analysis suggested that the DEGs were mostly enriched in ‘carboxylic acid catabolic process’, ‘cell apoptosis’, ‘cell proliferation’ and ‘cell migration’. KEGG analysis results indicated that the DEGs were mostly concentrated in ‘metabolic pathways’, ‘ECM-receptor interaction’, the ‘PI3K-Akt pathway’ and ‘focal adhesion’. The PPI analysis results showed that Golgi membrane protein 1 (GOLM1), melanoma inhibitory activity member 3 (MIA3), ATP citrate lyase (ACLY) and G protein subunit β2 (GNB2) were the key genes in PCa, and the Module analysis revealed that they were associated with ‘ECM-receptor interaction’, ‘focal adhesion’, the ‘PI3K-Akt pathway’ and the ‘metabolic pathway’. Subsequently, the gene expression was confirmed using Gene Expression Profiling Interactive Analysis and the Human Protein Atlas. The results demonstrated that GOLM1 and ACLY expression was significantly upregulated (P<0.05) in PCa compared with that in normal tissues. Receiver operating characteristic and survival analyses were performed. The results showed that area under the curve values of these genes all exceeded 0.85, and high expression of these genes was associated with poor survival in patients with PCa. In conclusion, this study identified GOLM1 and ACLY in PCa, which may be potential diagnostic and prognostic biomarker of PCa.
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spelling pubmed-67572662019-10-02 Identification of potential diagnostic and prognostic biomarkers for prostate cancer Zhang, Qiang Yin, Xiujuan Pan, Zhiwei Cao, Yingying Han, Shaojie Gao, Guojun Gao, Zhiqin Pan, Zhifang Feng, Weiguo Oncol Lett Articles Prostate cancer (PCa) is one of the most common malignant tumors worldwide. The aim of the present study was to determine potential diagnostic and prognostic biomarkers for PCa. The GSE103512 dataset was downloaded, and the differentially expressed genes (DEGs) were screened. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction (PPI) analyses of DEGs were performed. The result of GO analysis suggested that the DEGs were mostly enriched in ‘carboxylic acid catabolic process’, ‘cell apoptosis’, ‘cell proliferation’ and ‘cell migration’. KEGG analysis results indicated that the DEGs were mostly concentrated in ‘metabolic pathways’, ‘ECM-receptor interaction’, the ‘PI3K-Akt pathway’ and ‘focal adhesion’. The PPI analysis results showed that Golgi membrane protein 1 (GOLM1), melanoma inhibitory activity member 3 (MIA3), ATP citrate lyase (ACLY) and G protein subunit β2 (GNB2) were the key genes in PCa, and the Module analysis revealed that they were associated with ‘ECM-receptor interaction’, ‘focal adhesion’, the ‘PI3K-Akt pathway’ and the ‘metabolic pathway’. Subsequently, the gene expression was confirmed using Gene Expression Profiling Interactive Analysis and the Human Protein Atlas. The results demonstrated that GOLM1 and ACLY expression was significantly upregulated (P<0.05) in PCa compared with that in normal tissues. Receiver operating characteristic and survival analyses were performed. The results showed that area under the curve values of these genes all exceeded 0.85, and high expression of these genes was associated with poor survival in patients with PCa. In conclusion, this study identified GOLM1 and ACLY in PCa, which may be potential diagnostic and prognostic biomarker of PCa. D.A. Spandidos 2019-10 2019-08-16 /pmc/articles/PMC6757266/ /pubmed/31579071 http://dx.doi.org/10.3892/ol.2019.10765 Text en Copyright: © Zhang 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
Zhang, Qiang
Yin, Xiujuan
Pan, Zhiwei
Cao, Yingying
Han, Shaojie
Gao, Guojun
Gao, Zhiqin
Pan, Zhifang
Feng, Weiguo
Identification of potential diagnostic and prognostic biomarkers for prostate cancer
title Identification of potential diagnostic and prognostic biomarkers for prostate cancer
title_full Identification of potential diagnostic and prognostic biomarkers for prostate cancer
title_fullStr Identification of potential diagnostic and prognostic biomarkers for prostate cancer
title_full_unstemmed Identification of potential diagnostic and prognostic biomarkers for prostate cancer
title_short Identification of potential diagnostic and prognostic biomarkers for prostate cancer
title_sort identification of potential diagnostic and prognostic biomarkers for prostate cancer
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6757266/
https://www.ncbi.nlm.nih.gov/pubmed/31579071
http://dx.doi.org/10.3892/ol.2019.10765
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