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Identification of crucial genes and pathways associated with colorectal cancer by bioinformatics analysis

Colorectal cancer (CRC) is a prevalent malignant tumour type arising from the colon and rectum. The present study aimed to explore the molecular mechanisms of the development and progression of CRC. Initially, differentially expressed genes (DEGs) between CRC tissues and corresponding non-cancerous...

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Autores principales: Liu, Xiaoqun, Liu, Xiangdong, Qiao, Tiankui, Chen, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7039150/
https://www.ncbi.nlm.nih.gov/pubmed/32194683
http://dx.doi.org/10.3892/ol.2020.11278
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author Liu, Xiaoqun
Liu, Xiangdong
Qiao, Tiankui
Chen, Wei
author_facet Liu, Xiaoqun
Liu, Xiangdong
Qiao, Tiankui
Chen, Wei
author_sort Liu, Xiaoqun
collection PubMed
description Colorectal cancer (CRC) is a prevalent malignant tumour type arising from the colon and rectum. The present study aimed to explore the molecular mechanisms of the development and progression of CRC. Initially, differentially expressed genes (DEGs) between CRC tissues and corresponding non-cancerous tissues were obtained by analysing the GSE15781 microarray dataset. The Database for Annotation, Visualization and Integrated Discovery was then utilized for functional and pathway enrichment analysis of the DEGs. Subsequently, a protein-protein interaction (PPI) network was created using the Search Tool for the Retrieval of Interacting Genes and Proteins database and visualized by Cytoscape software. Furthermore, CytoNCA, a Cytoscape plugin, was used for centrality analysis of the PPI network to identify crucial genes. Finally, UALCAN was employed to validate the expression of the crucial genes and to estimate their effect on the survival of patients with colon cancer by Kaplan-Meier curves and log-rank tests. A total of 1,085 DEGs, including 496 upregulated and 589 downregulated genes, were screened out. The DEGs identified were enriched in various pathways, including ‘metabolic pathway’, ‘cell cycle’, ‘DNA replication’, ‘nitrogen metabolism’, ‘p53 signalling’ and ‘fatty acid degradation’. PPI network analysis suggested that interleukin-6, MYC, NOTCH1, inhibin subunit βA (INHBA), CDK1, cyclin (CCN)B1 and CCNA2 were crucial genes, and their expression levels were markedly upregulated. Survival analysis suggested that upregulated INHBA significantly decreased the survival probability of patients with CRC. Conversely, upregulation of CCNB1 and CCNA2 expression levels were associated with increased survival probabalities. The identified DEGs, particularly the crucial genes, may enhance the current understanding of the genesis and progression of CRC, and certain genes, including INHBA, CCNB1 and CCNA2, may be candidate diagnostic and prognostic markers, as well as targets for the treatment of CRC.
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spelling pubmed-70391502020-03-19 Identification of crucial genes and pathways associated with colorectal cancer by bioinformatics analysis Liu, Xiaoqun Liu, Xiangdong Qiao, Tiankui Chen, Wei Oncol Lett Articles Colorectal cancer (CRC) is a prevalent malignant tumour type arising from the colon and rectum. The present study aimed to explore the molecular mechanisms of the development and progression of CRC. Initially, differentially expressed genes (DEGs) between CRC tissues and corresponding non-cancerous tissues were obtained by analysing the GSE15781 microarray dataset. The Database for Annotation, Visualization and Integrated Discovery was then utilized for functional and pathway enrichment analysis of the DEGs. Subsequently, a protein-protein interaction (PPI) network was created using the Search Tool for the Retrieval of Interacting Genes and Proteins database and visualized by Cytoscape software. Furthermore, CytoNCA, a Cytoscape plugin, was used for centrality analysis of the PPI network to identify crucial genes. Finally, UALCAN was employed to validate the expression of the crucial genes and to estimate their effect on the survival of patients with colon cancer by Kaplan-Meier curves and log-rank tests. A total of 1,085 DEGs, including 496 upregulated and 589 downregulated genes, were screened out. The DEGs identified were enriched in various pathways, including ‘metabolic pathway’, ‘cell cycle’, ‘DNA replication’, ‘nitrogen metabolism’, ‘p53 signalling’ and ‘fatty acid degradation’. PPI network analysis suggested that interleukin-6, MYC, NOTCH1, inhibin subunit βA (INHBA), CDK1, cyclin (CCN)B1 and CCNA2 were crucial genes, and their expression levels were markedly upregulated. Survival analysis suggested that upregulated INHBA significantly decreased the survival probability of patients with CRC. Conversely, upregulation of CCNB1 and CCNA2 expression levels were associated with increased survival probabalities. The identified DEGs, particularly the crucial genes, may enhance the current understanding of the genesis and progression of CRC, and certain genes, including INHBA, CCNB1 and CCNA2, may be candidate diagnostic and prognostic markers, as well as targets for the treatment of CRC. D.A. Spandidos 2020-03 2020-01-09 /pmc/articles/PMC7039150/ /pubmed/32194683 http://dx.doi.org/10.3892/ol.2020.11278 Text en Copyright: © Liu 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
Liu, Xiaoqun
Liu, Xiangdong
Qiao, Tiankui
Chen, Wei
Identification of crucial genes and pathways associated with colorectal cancer by bioinformatics analysis
title Identification of crucial genes and pathways associated with colorectal cancer by bioinformatics analysis
title_full Identification of crucial genes and pathways associated with colorectal cancer by bioinformatics analysis
title_fullStr Identification of crucial genes and pathways associated with colorectal cancer by bioinformatics analysis
title_full_unstemmed Identification of crucial genes and pathways associated with colorectal cancer by bioinformatics analysis
title_short Identification of crucial genes and pathways associated with colorectal cancer by bioinformatics analysis
title_sort identification of crucial genes and pathways associated with colorectal cancer by bioinformatics analysis
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7039150/
https://www.ncbi.nlm.nih.gov/pubmed/32194683
http://dx.doi.org/10.3892/ol.2020.11278
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AT chenwei identificationofcrucialgenesandpathwaysassociatedwithcolorectalcancerbybioinformaticsanalysis