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Weighted correlation network and differential expression analyses identify candidate genes associated with BRAF gene in melanoma

BACKGROUND: Primary cutaneous malignant melanoma is a cancer of the pigment cells of the skin, some of which are accompanied by BRAF mutation. Melanoma incidence and mortality rates have been rising around the world. As the current knowledge about pathogenesis, clinical and genetic features of cutan...

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Autores principales: Zhao, Bin, You, Yanqiu, Wan, Zheng, Ma, Yunhan, Huo, Yani, Liu, Hongyi, Zhou, Yuanyuan, Quan, Wei, Chen, Weibin, Zhang, Xiaohong, Li, Fujun, Zhao, Yilin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6441238/
https://www.ncbi.nlm.nih.gov/pubmed/30925905
http://dx.doi.org/10.1186/s12881-019-0791-1
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author Zhao, Bin
You, Yanqiu
Wan, Zheng
Ma, Yunhan
Huo, Yani
Liu, Hongyi
Zhou, Yuanyuan
Quan, Wei
Chen, Weibin
Zhang, Xiaohong
Li, Fujun
Zhao, Yilin
author_facet Zhao, Bin
You, Yanqiu
Wan, Zheng
Ma, Yunhan
Huo, Yani
Liu, Hongyi
Zhou, Yuanyuan
Quan, Wei
Chen, Weibin
Zhang, Xiaohong
Li, Fujun
Zhao, Yilin
author_sort Zhao, Bin
collection PubMed
description BACKGROUND: Primary cutaneous malignant melanoma is a cancer of the pigment cells of the skin, some of which are accompanied by BRAF mutation. Melanoma incidence and mortality rates have been rising around the world. As the current knowledge about pathogenesis, clinical and genetic features of cutaneous melanoma is not very clear, we aim to use bioinformatics to identify the potential key genes involved in the expression and mutation status of BRAF. METHODS: Firstly, we used UCSC public hub datasets of melanoma (Lin et al., Cancer Res 68(3):664, 2008) to perform weighted genes co-expression network analysis (WGCNA) and differentially expressed genes analysis (DEGs), respectively. Secondly, overlapping genes between significant gene modules and DEGs were screened and validated at transcriptional levels and overall survival in TCGA and GTEx datasets. Lastly, the functional enrichment analysis was accomplished to find biological functions on the web-server database. RESULTS: We performed weighted correlation network and differential expression analyses, using gene expression data in melanoma samples. We identified 20 genes whose expression was correlated with the mutation status of BRAF. For further validation, three of these genes (CYR61, DUSP1, and RNASE4) were found to have similar expression patterns in skin tumors from TCGA compared with normal skin samples from GTEx. We also found that weak expression of these three genes was associated with worse overall survival in the TCGA data. These three genes were involved in the nucleic acid metabolic process. CONCLUSION: In this study, CYR61, DUSP1, and RNASE4 were identified as potential genes of interest for future molecular studies in melanoma, which would improve our understanding of its causes and underlying molecular events. These candidate genes may provide a promising avenue of future research for therapeutic targets in melanoma. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12881-019-0791-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-64412382019-04-11 Weighted correlation network and differential expression analyses identify candidate genes associated with BRAF gene in melanoma Zhao, Bin You, Yanqiu Wan, Zheng Ma, Yunhan Huo, Yani Liu, Hongyi Zhou, Yuanyuan Quan, Wei Chen, Weibin Zhang, Xiaohong Li, Fujun Zhao, Yilin BMC Med Genet Research Article BACKGROUND: Primary cutaneous malignant melanoma is a cancer of the pigment cells of the skin, some of which are accompanied by BRAF mutation. Melanoma incidence and mortality rates have been rising around the world. As the current knowledge about pathogenesis, clinical and genetic features of cutaneous melanoma is not very clear, we aim to use bioinformatics to identify the potential key genes involved in the expression and mutation status of BRAF. METHODS: Firstly, we used UCSC public hub datasets of melanoma (Lin et al., Cancer Res 68(3):664, 2008) to perform weighted genes co-expression network analysis (WGCNA) and differentially expressed genes analysis (DEGs), respectively. Secondly, overlapping genes between significant gene modules and DEGs were screened and validated at transcriptional levels and overall survival in TCGA and GTEx datasets. Lastly, the functional enrichment analysis was accomplished to find biological functions on the web-server database. RESULTS: We performed weighted correlation network and differential expression analyses, using gene expression data in melanoma samples. We identified 20 genes whose expression was correlated with the mutation status of BRAF. For further validation, three of these genes (CYR61, DUSP1, and RNASE4) were found to have similar expression patterns in skin tumors from TCGA compared with normal skin samples from GTEx. We also found that weak expression of these three genes was associated with worse overall survival in the TCGA data. These three genes were involved in the nucleic acid metabolic process. CONCLUSION: In this study, CYR61, DUSP1, and RNASE4 were identified as potential genes of interest for future molecular studies in melanoma, which would improve our understanding of its causes and underlying molecular events. These candidate genes may provide a promising avenue of future research for therapeutic targets in melanoma. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12881-019-0791-1) contains supplementary material, which is available to authorized users. BioMed Central 2019-03-29 /pmc/articles/PMC6441238/ /pubmed/30925905 http://dx.doi.org/10.1186/s12881-019-0791-1 Text en © The Author(s). 2019 Open Access This 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
Zhao, Bin
You, Yanqiu
Wan, Zheng
Ma, Yunhan
Huo, Yani
Liu, Hongyi
Zhou, Yuanyuan
Quan, Wei
Chen, Weibin
Zhang, Xiaohong
Li, Fujun
Zhao, Yilin
Weighted correlation network and differential expression analyses identify candidate genes associated with BRAF gene in melanoma
title Weighted correlation network and differential expression analyses identify candidate genes associated with BRAF gene in melanoma
title_full Weighted correlation network and differential expression analyses identify candidate genes associated with BRAF gene in melanoma
title_fullStr Weighted correlation network and differential expression analyses identify candidate genes associated with BRAF gene in melanoma
title_full_unstemmed Weighted correlation network and differential expression analyses identify candidate genes associated with BRAF gene in melanoma
title_short Weighted correlation network and differential expression analyses identify candidate genes associated with BRAF gene in melanoma
title_sort weighted correlation network and differential expression analyses identify candidate genes associated with braf gene in melanoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6441238/
https://www.ncbi.nlm.nih.gov/pubmed/30925905
http://dx.doi.org/10.1186/s12881-019-0791-1
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