Gene expression profile analysis of colorectal cancer to investigate potential mechanisms using bioinformatics

Gene expression profile analysis of colorectal cancer to investigate potential mechanisms using bioinformatics

This study aimed to explore the underlying molecular mechanisms of colorectal cancer (CRC) using bioinformatics analysis. Using GSE4107 datasets downloaded from the Gene Expression Omnibus, the differentially expressed genes (DEGs) were screened by comparing the RNA expression from the colonic mucos...

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Main Authors: Kou, Yubin, Zhang, Suya, Chen, Xiaoping, Hu, Sanyuan
Format: Online
Language:English
Published: Dove Medical Press 2015
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4399548/
id pubmed-4399548
recordtype oai_dc
spelling pubmed-43995482015-04-24 Gene expression profile analysis of colorectal cancer to investigate potential mechanisms using bioinformatics Kou, Yubin Zhang, Suya Chen, Xiaoping Hu, Sanyuan Original Research This study aimed to explore the underlying molecular mechanisms of colorectal cancer (CRC) using bioinformatics analysis. Using GSE4107 datasets downloaded from the Gene Expression Omnibus, the differentially expressed genes (DEGs) were screened by comparing the RNA expression from the colonic mucosa between 12 CRC patients and ten healthy controls using a paired t-test. The Gene Ontology (GO) functional and pathway enrichment analyses of DEGs were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) software followed by the construction of a protein–protein interaction (PPI) network. In addition, hub gene identification and GO functional and pathway enrichment analyses of the modules were performed. A total of 612 up- and 639 downregulated genes were identified. The upregulated DEGs were mainly involved in the regulation of cell growth, migration, and the MAPK signaling pathway. The downregulated DEGs were significantly associated with oxidative phosphorylation, Alzheimer’s disease, and Parkinson’s disease. Moreover, FOS, FN1, PPP1CC, and CYP2B6 were selected as hub genes in the PPI networks. Two modules (up-A and up-B) in the upregulated PPI network and three modules (d-A, d-B, and d-C) in the downregulated PPI were identified with the threshold of Molecular Complex Detection (MCODE) Molecular Complex Detection (MCODE) score ≥4 and nodes ≥6. The genes in module up-A were significantly enriched in neuroactive ligand–receptor interactions and the calcium signaling pathway. The genes in module d-A were enriched in four pathways, including oxidative phosphorylation and Parkinson’s disease. DEGs, such as FOS, FN1, PPP1CC, and CYP2B6, may be used as potential targets for CRC diagnosis and treatment. Dove Medical Press 2015-04-08 /pmc/articles/PMC4399548/ /pubmed/25914544 http://dx.doi.org/10.2147/OTT.S78974 Text en © 2015 Kou et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
repository_type Open Access Journal
institution_category Foreign Institution
institution US National Center for Biotechnology Information
building NCBI PubMed
collection Online Access
language English
format Online
author Kou, Yubin
Zhang, Suya
Chen, Xiaoping
Hu, Sanyuan
spellingShingle Kou, Yubin
Zhang, Suya
Chen, Xiaoping
Hu, Sanyuan
Gene expression profile analysis of colorectal cancer to investigate potential mechanisms using bioinformatics
author_facet Kou, Yubin
Zhang, Suya
Chen, Xiaoping
Hu, Sanyuan
author_sort Kou, Yubin
title Gene expression profile analysis of colorectal cancer to investigate potential mechanisms using bioinformatics
title_short Gene expression profile analysis of colorectal cancer to investigate potential mechanisms using bioinformatics
title_full Gene expression profile analysis of colorectal cancer to investigate potential mechanisms using bioinformatics
title_fullStr Gene expression profile analysis of colorectal cancer to investigate potential mechanisms using bioinformatics
title_full_unstemmed Gene expression profile analysis of colorectal cancer to investigate potential mechanisms using bioinformatics
title_sort gene expression profile analysis of colorectal cancer to investigate potential mechanisms using bioinformatics
description This study aimed to explore the underlying molecular mechanisms of colorectal cancer (CRC) using bioinformatics analysis. Using GSE4107 datasets downloaded from the Gene Expression Omnibus, the differentially expressed genes (DEGs) were screened by comparing the RNA expression from the colonic mucosa between 12 CRC patients and ten healthy controls using a paired t-test. The Gene Ontology (GO) functional and pathway enrichment analyses of DEGs were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) software followed by the construction of a protein–protein interaction (PPI) network. In addition, hub gene identification and GO functional and pathway enrichment analyses of the modules were performed. A total of 612 up- and 639 downregulated genes were identified. The upregulated DEGs were mainly involved in the regulation of cell growth, migration, and the MAPK signaling pathway. The downregulated DEGs were significantly associated with oxidative phosphorylation, Alzheimer’s disease, and Parkinson’s disease. Moreover, FOS, FN1, PPP1CC, and CYP2B6 were selected as hub genes in the PPI networks. Two modules (up-A and up-B) in the upregulated PPI network and three modules (d-A, d-B, and d-C) in the downregulated PPI were identified with the threshold of Molecular Complex Detection (MCODE) Molecular Complex Detection (MCODE) score ≥4 and nodes ≥6. The genes in module up-A were significantly enriched in neuroactive ligand–receptor interactions and the calcium signaling pathway. The genes in module d-A were enriched in four pathways, including oxidative phosphorylation and Parkinson’s disease. DEGs, such as FOS, FN1, PPP1CC, and CYP2B6, may be used as potential targets for CRC diagnosis and treatment.
publisher Dove Medical Press
publishDate 2015
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4399548/
_version_ 1613212426176561152

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