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Identification of diagnostic biomarkers via weighted correlation network analysis in colorectal cancer using a system biology approach
Colorectal cancer (CRC) is the third most frequent cancer to be diagnosed in both females and males necessitating identification of effective biomarkers. An in-silico system biology approach called weighted gene co-expression network analysis (WGCNA) can be used to examine gene expression in a compl...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10442394/ https://www.ncbi.nlm.nih.gov/pubmed/37604903 http://dx.doi.org/10.1038/s41598-023-40953-5 |
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author | Ghafouri-Fard, Soudeh Safarzadeh, Arash Taheri, Mohammad Jamali, Elena |
author_facet | Ghafouri-Fard, Soudeh Safarzadeh, Arash Taheri, Mohammad Jamali, Elena |
author_sort | Ghafouri-Fard, Soudeh |
collection | PubMed |
description | Colorectal cancer (CRC) is the third most frequent cancer to be diagnosed in both females and males necessitating identification of effective biomarkers. An in-silico system biology approach called weighted gene co-expression network analysis (WGCNA) can be used to examine gene expression in a complicated network of regulatory genes. In the current study, the co-expression network of DEGs connected to CRC and their target genes was built using the WGCNA algorithm. GO and KEGG pathway analysis were carried out to learn more about the biological role of the DEmRNAs. These findings revealed that the genes were mostly enriched in the biological processes that were involved in the regulation of hormone levels, extracellular matrix organization, and extracellular structure organization. The intersection of genes between hub genes and DEmRNAs showed that DKC1, PA2G4, LYAR and NOLC1 were the clinically final hub genes of CRC. |
format | Online Article Text |
id | pubmed-10442394 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-104423942023-08-23 Identification of diagnostic biomarkers via weighted correlation network analysis in colorectal cancer using a system biology approach Ghafouri-Fard, Soudeh Safarzadeh, Arash Taheri, Mohammad Jamali, Elena Sci Rep Article Colorectal cancer (CRC) is the third most frequent cancer to be diagnosed in both females and males necessitating identification of effective biomarkers. An in-silico system biology approach called weighted gene co-expression network analysis (WGCNA) can be used to examine gene expression in a complicated network of regulatory genes. In the current study, the co-expression network of DEGs connected to CRC and their target genes was built using the WGCNA algorithm. GO and KEGG pathway analysis were carried out to learn more about the biological role of the DEmRNAs. These findings revealed that the genes were mostly enriched in the biological processes that were involved in the regulation of hormone levels, extracellular matrix organization, and extracellular structure organization. The intersection of genes between hub genes and DEmRNAs showed that DKC1, PA2G4, LYAR and NOLC1 were the clinically final hub genes of CRC. Nature Publishing Group UK 2023-08-21 /pmc/articles/PMC10442394/ /pubmed/37604903 http://dx.doi.org/10.1038/s41598-023-40953-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Ghafouri-Fard, Soudeh Safarzadeh, Arash Taheri, Mohammad Jamali, Elena Identification of diagnostic biomarkers via weighted correlation network analysis in colorectal cancer using a system biology approach |
title | Identification of diagnostic biomarkers via weighted correlation network analysis in colorectal cancer using a system biology approach |
title_full | Identification of diagnostic biomarkers via weighted correlation network analysis in colorectal cancer using a system biology approach |
title_fullStr | Identification of diagnostic biomarkers via weighted correlation network analysis in colorectal cancer using a system biology approach |
title_full_unstemmed | Identification of diagnostic biomarkers via weighted correlation network analysis in colorectal cancer using a system biology approach |
title_short | Identification of diagnostic biomarkers via weighted correlation network analysis in colorectal cancer using a system biology approach |
title_sort | identification of diagnostic biomarkers via weighted correlation network analysis in colorectal cancer using a system biology approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10442394/ https://www.ncbi.nlm.nih.gov/pubmed/37604903 http://dx.doi.org/10.1038/s41598-023-40953-5 |
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