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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2020
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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. |
format | Online Article Text |
id | pubmed-7039150 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
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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