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Identification of key genes involved in the pathogenesis of cutaneous melanoma using bioinformatics analysis

OBJECTIVE: Malignant melanoma is a highly invasive cancer whose pathogenesis remains unclear. We analyzed the microarray dataset GDS1375 in the Gene Expression Omnibus database to search for key genes involved in the occurrence and development of melanoma. METHODS: The dataset included 52 samples (7...

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Autores principales: Chen, Jianqin, Sun, Wen, Mo, Nian, Chen, Xiangjun, Yang, Lihong, Tu, Shaozhong, Zhang, Siwen, Liu, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7113699/
https://www.ncbi.nlm.nih.gov/pubmed/31937175
http://dx.doi.org/10.1177/0300060519895867
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author Chen, Jianqin
Sun, Wen
Mo, Nian
Chen, Xiangjun
Yang, Lihong
Tu, Shaozhong
Zhang, Siwen
Liu, Jing
author_facet Chen, Jianqin
Sun, Wen
Mo, Nian
Chen, Xiangjun
Yang, Lihong
Tu, Shaozhong
Zhang, Siwen
Liu, Jing
author_sort Chen, Jianqin
collection PubMed
description OBJECTIVE: Malignant melanoma is a highly invasive cancer whose pathogenesis remains unclear. We analyzed the microarray dataset GDS1375 in the Gene Expression Omnibus database to search for key genes involved in the occurrence and development of melanoma. METHODS: The dataset included 52 samples (7 normal skin and 45 melanoma samples). We identified differentially expressed genes (DEGs) between the two groups and used integrated discovery databases for Gene Ontology (GO) and Kyoto Gene and Genome Encyclopedia (KEGG) pathway analyses. In addition, we used the STRING and MCODE plugins of Cytoscape to visualize the protein-protein interactions (PPI) for these DEGs. RESULTS: A total of 509 upregulated and 618 downregulated DEGs were identified, which were enriched in GO terms including integrin binding, protein binding, and structural constituent of cytoskeleton, and in KEGG pathways such as melanogenesis, prostate cancer, focal adhesion, and renin secretion. Three major modules from the PPI networks and 10 hub genes were identified, including CDC20, GNB2, PPP2R1A, AURKB, POLR2E, and AGTR1. Overall survival was low when these six hub genes were highly expressed. CONCLUSION: This bioinformatics analysis identified hub genes that may promote the development of melanoma and represent potential new biomarkers for diagnosis and treatment of melanoma.
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spelling pubmed-71136992020-04-09 Identification of key genes involved in the pathogenesis of cutaneous melanoma using bioinformatics analysis Chen, Jianqin Sun, Wen Mo, Nian Chen, Xiangjun Yang, Lihong Tu, Shaozhong Zhang, Siwen Liu, Jing J Int Med Res Pre-Clinical Research Report OBJECTIVE: Malignant melanoma is a highly invasive cancer whose pathogenesis remains unclear. We analyzed the microarray dataset GDS1375 in the Gene Expression Omnibus database to search for key genes involved in the occurrence and development of melanoma. METHODS: The dataset included 52 samples (7 normal skin and 45 melanoma samples). We identified differentially expressed genes (DEGs) between the two groups and used integrated discovery databases for Gene Ontology (GO) and Kyoto Gene and Genome Encyclopedia (KEGG) pathway analyses. In addition, we used the STRING and MCODE plugins of Cytoscape to visualize the protein-protein interactions (PPI) for these DEGs. RESULTS: A total of 509 upregulated and 618 downregulated DEGs were identified, which were enriched in GO terms including integrin binding, protein binding, and structural constituent of cytoskeleton, and in KEGG pathways such as melanogenesis, prostate cancer, focal adhesion, and renin secretion. Three major modules from the PPI networks and 10 hub genes were identified, including CDC20, GNB2, PPP2R1A, AURKB, POLR2E, and AGTR1. Overall survival was low when these six hub genes were highly expressed. CONCLUSION: This bioinformatics analysis identified hub genes that may promote the development of melanoma and represent potential new biomarkers for diagnosis and treatment of melanoma. SAGE Publications 2020-01-15 /pmc/articles/PMC7113699/ /pubmed/31937175 http://dx.doi.org/10.1177/0300060519895867 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by-nc/4.0/ Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Pre-Clinical Research Report
Chen, Jianqin
Sun, Wen
Mo, Nian
Chen, Xiangjun
Yang, Lihong
Tu, Shaozhong
Zhang, Siwen
Liu, Jing
Identification of key genes involved in the pathogenesis of cutaneous melanoma using bioinformatics analysis
title Identification of key genes involved in the pathogenesis of cutaneous melanoma using bioinformatics analysis
title_full Identification of key genes involved in the pathogenesis of cutaneous melanoma using bioinformatics analysis
title_fullStr Identification of key genes involved in the pathogenesis of cutaneous melanoma using bioinformatics analysis
title_full_unstemmed Identification of key genes involved in the pathogenesis of cutaneous melanoma using bioinformatics analysis
title_short Identification of key genes involved in the pathogenesis of cutaneous melanoma using bioinformatics analysis
title_sort identification of key genes involved in the pathogenesis of cutaneous melanoma using bioinformatics analysis
topic Pre-Clinical Research Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7113699/
https://www.ncbi.nlm.nih.gov/pubmed/31937175
http://dx.doi.org/10.1177/0300060519895867
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