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Identification of potential therapeutic targets for colorectal cancer by bioinformatics analysis
The aim of the present study was to identify potential therapeutic targets for colorectal cancer (CRC). The gene expression profile GSE32323, containing 34 samples, including 17 specimens of CRC tissues and 17 of paired normal tissues from CRC patients, was downloaded from the Gene Expression Omnibu...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5228398/ https://www.ncbi.nlm.nih.gov/pubmed/28105216 http://dx.doi.org/10.3892/ol.2016.5328 |
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author | Yan, Ming Song, Maomin Bai, Rixing Cheng, Shi Yan, Wenmao |
author_facet | Yan, Ming Song, Maomin Bai, Rixing Cheng, Shi Yan, Wenmao |
author_sort | Yan, Ming |
collection | PubMed |
description | The aim of the present study was to identify potential therapeutic targets for colorectal cancer (CRC). The gene expression profile GSE32323, containing 34 samples, including 17 specimens of CRC tissues and 17 of paired normal tissues from CRC patients, was downloaded from the Gene Expression Omnibus database. Following data preprocessing using the Affy and preprocessCore packages, the differentially-expressed genes (DEGs) between the two types of samples were identified with the Linear Models for Microarray Analysis package. Next, functional and pathway enrichment analysis of the DEGs was performed using the Database for Annotation Visualization and Integrated Discovery. The protein-protein interaction (PPI) network was established using the Search Tool for the Retrieval of Interacting Genes database. Utilizing WebGestalt, the potential microRNAs (miRNAs/miRs) of the DEGs were screened and the integrated miRNA-target network was built. A cohort of 1,347 DEGs was identified, the majority of which were mainly enriched in cell cycle-related biological processes and pathways. Cyclin-dependent kinase 1 (CDK1), cyclin B1 (CCNB1), MAD2 mitotic arrest deficient-like 1 (MAD2L1) and BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) were prominent in the PPI network, while the over-represented genes in the integrated miRNA-target network were SRY (sex determining region Y)-box 4 (SOX4; targeted by hsa-mir-129), v-myc avian myelocytomatosis viral oncogene homolog (MYC; targeted by hsa-let-7c and hsa-mir-145) and cyclin D1 (CCND1; targeted by hsa-let-7b). CDK1, CCNB1 and CCND1 were also associated with the p53 signaling pathway. Overall, several genes associated with the cell cycle and p53 pathway were identified as biomarkers for CRC. CDK1, CCNB1, MAD2L1, BUB1B, SOX4, collagen type I α2 chain and MYC may play significant roles in CRC progression by affecting the cell cycle-related pathways, while CDK1, CCNB1 and CCND1 may serve as crucial regulators in the p53 signaling pathway. Furthermore, SOX4, MYC and CCND1 may be targets of miR-129, hsa-mir-145 and hsa-let-7c, respectively. However, further validation of these data is required. |
format | Online Article Text |
id | pubmed-5228398 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-52283982017-01-19 Identification of potential therapeutic targets for colorectal cancer by bioinformatics analysis Yan, Ming Song, Maomin Bai, Rixing Cheng, Shi Yan, Wenmao Oncol Lett Articles The aim of the present study was to identify potential therapeutic targets for colorectal cancer (CRC). The gene expression profile GSE32323, containing 34 samples, including 17 specimens of CRC tissues and 17 of paired normal tissues from CRC patients, was downloaded from the Gene Expression Omnibus database. Following data preprocessing using the Affy and preprocessCore packages, the differentially-expressed genes (DEGs) between the two types of samples were identified with the Linear Models for Microarray Analysis package. Next, functional and pathway enrichment analysis of the DEGs was performed using the Database for Annotation Visualization and Integrated Discovery. The protein-protein interaction (PPI) network was established using the Search Tool for the Retrieval of Interacting Genes database. Utilizing WebGestalt, the potential microRNAs (miRNAs/miRs) of the DEGs were screened and the integrated miRNA-target network was built. A cohort of 1,347 DEGs was identified, the majority of which were mainly enriched in cell cycle-related biological processes and pathways. Cyclin-dependent kinase 1 (CDK1), cyclin B1 (CCNB1), MAD2 mitotic arrest deficient-like 1 (MAD2L1) and BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) were prominent in the PPI network, while the over-represented genes in the integrated miRNA-target network were SRY (sex determining region Y)-box 4 (SOX4; targeted by hsa-mir-129), v-myc avian myelocytomatosis viral oncogene homolog (MYC; targeted by hsa-let-7c and hsa-mir-145) and cyclin D1 (CCND1; targeted by hsa-let-7b). CDK1, CCNB1 and CCND1 were also associated with the p53 signaling pathway. Overall, several genes associated with the cell cycle and p53 pathway were identified as biomarkers for CRC. CDK1, CCNB1, MAD2L1, BUB1B, SOX4, collagen type I α2 chain and MYC may play significant roles in CRC progression by affecting the cell cycle-related pathways, while CDK1, CCNB1 and CCND1 may serve as crucial regulators in the p53 signaling pathway. Furthermore, SOX4, MYC and CCND1 may be targets of miR-129, hsa-mir-145 and hsa-let-7c, respectively. However, further validation of these data is required. D.A. Spandidos 2016-12 2016-10-31 /pmc/articles/PMC5228398/ /pubmed/28105216 http://dx.doi.org/10.3892/ol.2016.5328 Text en Copyright: © Yan 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 Yan, Ming Song, Maomin Bai, Rixing Cheng, Shi Yan, Wenmao Identification of potential therapeutic targets for colorectal cancer by bioinformatics analysis |
title | Identification of potential therapeutic targets for colorectal cancer by bioinformatics analysis |
title_full | Identification of potential therapeutic targets for colorectal cancer by bioinformatics analysis |
title_fullStr | Identification of potential therapeutic targets for colorectal cancer by bioinformatics analysis |
title_full_unstemmed | Identification of potential therapeutic targets for colorectal cancer by bioinformatics analysis |
title_short | Identification of potential therapeutic targets for colorectal cancer by bioinformatics analysis |
title_sort | identification of potential therapeutic targets for colorectal cancer by bioinformatics analysis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5228398/ https://www.ncbi.nlm.nih.gov/pubmed/28105216 http://dx.doi.org/10.3892/ol.2016.5328 |
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