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Screening key genes and signaling pathways in colorectal cancer by integrated bioinformatics analysis
The aim of the present study was to identify potential key genes associated with the progression and prognosis of colorectal cancer (CRC). Differentially expressed genes (DEGs) between CRC and normal samples were screened by integrated analysis of gene expression profile datasets, including the Gene...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6625394/ https://www.ncbi.nlm.nih.gov/pubmed/31173250 http://dx.doi.org/10.3892/mmr.2019.10336 |
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author | Yu, Chang Chen, Fuqiang Jiang, Jianjun Zhang, Hong Zhou, Meijuan |
author_facet | Yu, Chang Chen, Fuqiang Jiang, Jianjun Zhang, Hong Zhou, Meijuan |
author_sort | Yu, Chang |
collection | PubMed |
description | The aim of the present study was to identify potential key genes associated with the progression and prognosis of colorectal cancer (CRC). Differentially expressed genes (DEGs) between CRC and normal samples were screened by integrated analysis of gene expression profile datasets, including the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was conducted to identify the biological role of DEGs. In addition, a protein-protein interaction network and survival analysis were used to identify the key genes. The profiles of GSE9348, GSE22598 and GSE113513 were downloaded from the GEO database. A total of 405 common DEGs were identified, including 236 down- and 169 upregulated. GO analysis revealed that the downregulated DEGs were mainly enriched in ‘detoxification of copper ion’ [biological process, (BP)], ‘oxidoreductase activity, acting on CH-OH group of donors, NAD or NADP as acceptor’ [molecular function, (MF)] and ‘brush border’ [cellular component, (CC)]. Upregulated DEGs were mainly involved in ‘nuclear division’ (BP), ‘snoRNA binding’ (MF) and ‘nucleolar part’ (CC). KEGG pathway analysis revealed that DEGs were mainly involved in ‘mineral absorption’, ‘nitrogen metabolism’, ‘cell cycle’ and ‘caffeine metabolism’. A PPI network was constructed with 268 nodes and 1,027 edges. The top one module was selected, and it was revealed that module-related genes were mainly enriched in the GO terms ‘sister chromatid segregation’ (BP), ‘chemokine activity’ (MF), and ‘condensed chromosome (CC)’. The KEGG pathway was mainly enriched in ‘cell cycle’, ‘progesterone-mediated oocyte maturation’, ‘chemokine signaling pathway’, ‘IL-17 signaling pathway’, ‘legionellosis’, and ‘rheumatoid arthritis’. DNA topoisomerase II-α (TOP2A), mitotic arrest deficient 2 like 1 (MAD2L1), cyclin B1 (CCNB1), checkpoint kinase 1 (CHEK1), cell division cycle 6 (CDC6) and ubiquitin conjugating enzyme E2 C (UBE2C) were indicated as hub genes. Furthermore, survival analysis revealed that TOP2A, MAD2L1, CDC6 and CHEK1 may serve as prognostic biomarkers in CRC. The present study provided insights into the molecular mechanism of CRC that may be useful in further investigations. |
format | Online Article Text |
id | pubmed-6625394 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-66253942019-07-31 Screening key genes and signaling pathways in colorectal cancer by integrated bioinformatics analysis Yu, Chang Chen, Fuqiang Jiang, Jianjun Zhang, Hong Zhou, Meijuan Mol Med Rep Articles The aim of the present study was to identify potential key genes associated with the progression and prognosis of colorectal cancer (CRC). Differentially expressed genes (DEGs) between CRC and normal samples were screened by integrated analysis of gene expression profile datasets, including the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was conducted to identify the biological role of DEGs. In addition, a protein-protein interaction network and survival analysis were used to identify the key genes. The profiles of GSE9348, GSE22598 and GSE113513 were downloaded from the GEO database. A total of 405 common DEGs were identified, including 236 down- and 169 upregulated. GO analysis revealed that the downregulated DEGs were mainly enriched in ‘detoxification of copper ion’ [biological process, (BP)], ‘oxidoreductase activity, acting on CH-OH group of donors, NAD or NADP as acceptor’ [molecular function, (MF)] and ‘brush border’ [cellular component, (CC)]. Upregulated DEGs were mainly involved in ‘nuclear division’ (BP), ‘snoRNA binding’ (MF) and ‘nucleolar part’ (CC). KEGG pathway analysis revealed that DEGs were mainly involved in ‘mineral absorption’, ‘nitrogen metabolism’, ‘cell cycle’ and ‘caffeine metabolism’. A PPI network was constructed with 268 nodes and 1,027 edges. The top one module was selected, and it was revealed that module-related genes were mainly enriched in the GO terms ‘sister chromatid segregation’ (BP), ‘chemokine activity’ (MF), and ‘condensed chromosome (CC)’. The KEGG pathway was mainly enriched in ‘cell cycle’, ‘progesterone-mediated oocyte maturation’, ‘chemokine signaling pathway’, ‘IL-17 signaling pathway’, ‘legionellosis’, and ‘rheumatoid arthritis’. DNA topoisomerase II-α (TOP2A), mitotic arrest deficient 2 like 1 (MAD2L1), cyclin B1 (CCNB1), checkpoint kinase 1 (CHEK1), cell division cycle 6 (CDC6) and ubiquitin conjugating enzyme E2 C (UBE2C) were indicated as hub genes. Furthermore, survival analysis revealed that TOP2A, MAD2L1, CDC6 and CHEK1 may serve as prognostic biomarkers in CRC. The present study provided insights into the molecular mechanism of CRC that may be useful in further investigations. D.A. Spandidos 2019-08 2019-06-04 /pmc/articles/PMC6625394/ /pubmed/31173250 http://dx.doi.org/10.3892/mmr.2019.10336 Text en Copyright: © Yu 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 Yu, Chang Chen, Fuqiang Jiang, Jianjun Zhang, Hong Zhou, Meijuan Screening key genes and signaling pathways in colorectal cancer by integrated bioinformatics analysis |
title | Screening key genes and signaling pathways in colorectal cancer by integrated bioinformatics analysis |
title_full | Screening key genes and signaling pathways in colorectal cancer by integrated bioinformatics analysis |
title_fullStr | Screening key genes and signaling pathways in colorectal cancer by integrated bioinformatics analysis |
title_full_unstemmed | Screening key genes and signaling pathways in colorectal cancer by integrated bioinformatics analysis |
title_short | Screening key genes and signaling pathways in colorectal cancer by integrated bioinformatics analysis |
title_sort | screening key genes and signaling pathways in colorectal cancer by integrated bioinformatics analysis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6625394/ https://www.ncbi.nlm.nih.gov/pubmed/31173250 http://dx.doi.org/10.3892/mmr.2019.10336 |
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