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Identification of core genes associated with prostate cancer progression and outcome via bioinformatics analysis in multiple databases

ABSTRACT: The morbidity and mortality of prostate carcinoma has increased in recent years and has become the second most common ale malignant carcinoma worldwide. The interaction mechanisms between different genes and signaling pathways, however, are still unclear. METHODS: Variation analysis of GSE...

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Autores principales: Wang, Yutao, Wang, Jianfeng, Yan, Kexin, Lin, Jiaxing, Zheng, Zhenhua, Bi, Jianbin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120053/
https://www.ncbi.nlm.nih.gov/pubmed/32266115
http://dx.doi.org/10.7717/peerj.8786
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author Wang, Yutao
Wang, Jianfeng
Yan, Kexin
Lin, Jiaxing
Zheng, Zhenhua
Bi, Jianbin
author_facet Wang, Yutao
Wang, Jianfeng
Yan, Kexin
Lin, Jiaxing
Zheng, Zhenhua
Bi, Jianbin
author_sort Wang, Yutao
collection PubMed
description ABSTRACT: The morbidity and mortality of prostate carcinoma has increased in recent years and has become the second most common ale malignant carcinoma worldwide. The interaction mechanisms between different genes and signaling pathways, however, are still unclear. METHODS: Variation analysis of GSE38241, GSE69223, GSE46602 and GSE104749 were realized by GEO2R in Gene Expression Omnibus database. Function enrichment was analyzed by DAVID.6.8. Furthermore, the PPI network and the significant module were analyzed by Cytoscape, STRING and MCODE.GO. Pathway analysis showed that the 20 candidate genes were closely related to mitosis, cell division, cell cycle phases and the p53 signaling pathway. A total of six independent prognostic factors were identified in GSE21032 and TCGA PRAD. Oncomine database and The Human Protein Atlas were applied to explicit that six core genes were over expression in prostate cancer compared to normal prostate tissue in the process of transcriptional and translational. Finally, gene set enrichment were performed to identified the related pathway of core genes involved in prostate cancer. RESULT: Hierarchical clustering analysis revealed that these 20 core genes were mostly related to carcinogenesis and development. CKS2, TK1, MKI67, TOP2A, CCNB1 and RRM2 directly related to the recurrence and prognosis of prostate cancer. This result was verified by TCGA database and GSE21032. CONCLUSION: These core genes play a crucial role in tumor carcinogenesis, development, recurrence, metastasis and progression. Identifying these genes could help us to understand the molecular mechanisms and provide potential biomarkers for the diagnosis and treatment of prostate cancer.
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spelling pubmed-71200532020-04-07 Identification of core genes associated with prostate cancer progression and outcome via bioinformatics analysis in multiple databases Wang, Yutao Wang, Jianfeng Yan, Kexin Lin, Jiaxing Zheng, Zhenhua Bi, Jianbin PeerJ Bioinformatics ABSTRACT: The morbidity and mortality of prostate carcinoma has increased in recent years and has become the second most common ale malignant carcinoma worldwide. The interaction mechanisms between different genes and signaling pathways, however, are still unclear. METHODS: Variation analysis of GSE38241, GSE69223, GSE46602 and GSE104749 were realized by GEO2R in Gene Expression Omnibus database. Function enrichment was analyzed by DAVID.6.8. Furthermore, the PPI network and the significant module were analyzed by Cytoscape, STRING and MCODE.GO. Pathway analysis showed that the 20 candidate genes were closely related to mitosis, cell division, cell cycle phases and the p53 signaling pathway. A total of six independent prognostic factors were identified in GSE21032 and TCGA PRAD. Oncomine database and The Human Protein Atlas were applied to explicit that six core genes were over expression in prostate cancer compared to normal prostate tissue in the process of transcriptional and translational. Finally, gene set enrichment were performed to identified the related pathway of core genes involved in prostate cancer. RESULT: Hierarchical clustering analysis revealed that these 20 core genes were mostly related to carcinogenesis and development. CKS2, TK1, MKI67, TOP2A, CCNB1 and RRM2 directly related to the recurrence and prognosis of prostate cancer. This result was verified by TCGA database and GSE21032. CONCLUSION: These core genes play a crucial role in tumor carcinogenesis, development, recurrence, metastasis and progression. Identifying these genes could help us to understand the molecular mechanisms and provide potential biomarkers for the diagnosis and treatment of prostate cancer. PeerJ Inc. 2020-03-31 /pmc/articles/PMC7120053/ /pubmed/32266115 http://dx.doi.org/10.7717/peerj.8786 Text en © 2020 Wang et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Wang, Yutao
Wang, Jianfeng
Yan, Kexin
Lin, Jiaxing
Zheng, Zhenhua
Bi, Jianbin
Identification of core genes associated with prostate cancer progression and outcome via bioinformatics analysis in multiple databases
title Identification of core genes associated with prostate cancer progression and outcome via bioinformatics analysis in multiple databases
title_full Identification of core genes associated with prostate cancer progression and outcome via bioinformatics analysis in multiple databases
title_fullStr Identification of core genes associated with prostate cancer progression and outcome via bioinformatics analysis in multiple databases
title_full_unstemmed Identification of core genes associated with prostate cancer progression and outcome via bioinformatics analysis in multiple databases
title_short Identification of core genes associated with prostate cancer progression and outcome via bioinformatics analysis in multiple databases
title_sort identification of core genes associated with prostate cancer progression and outcome via bioinformatics analysis in multiple databases
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120053/
https://www.ncbi.nlm.nih.gov/pubmed/32266115
http://dx.doi.org/10.7717/peerj.8786
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