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Identification of potential therapeutic targets for papillary thyroid carcinoma by bioinformatics analysis

The aim of the present study was to identify potential therapeutic targets for papillary thyroid carcinoma (PTC) and to investigate the possible mechanism underlying this disease. The gene expression profile, GSE53157, was downloaded from the Gene Expression Omnibus database. Only 10 chips, includin...

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Autores principales: ZHAO, MING, WANG, KE-JING, TAN, ZHUO, ZHENG, CHUAN-MING, LIANG, ZHONG, ZHAO, JIAN-QIANG
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4726925/
https://www.ncbi.nlm.nih.gov/pubmed/26870166
http://dx.doi.org/10.3892/ol.2015.3829
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author ZHAO, MING
WANG, KE-JING
TAN, ZHUO
ZHENG, CHUAN-MING
LIANG, ZHONG
ZHAO, JIAN-QIANG
author_facet ZHAO, MING
WANG, KE-JING
TAN, ZHUO
ZHENG, CHUAN-MING
LIANG, ZHONG
ZHAO, JIAN-QIANG
author_sort ZHAO, MING
collection PubMed
description The aim of the present study was to identify potential therapeutic targets for papillary thyroid carcinoma (PTC) and to investigate the possible mechanism underlying this disease. The gene expression profile, GSE53157, was downloaded from the Gene Expression Omnibus database. Only 10 chips, including 3 specimens of normal thyroid tissues and 7 specimens of well-differentiated thyroid carcinomas, were analyzed in the present study. Differentially-expressed genes (DEGs) between PTC patients and normal individuals were identified. Next, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses of DEGs were performed. Modules in the protein-protein interaction (PPI) network were identified. Significant target genes were selected from the microRNA (miRNA) regulatory network. Furthermore, the integrated network was constructed with the miRNA regulatory and PPI network modules, and key target genes were screened. A total of 668 DEGs were identified. Modules M1, M2 and M3 were identified from the PPI network. From the modules, DEGs of cyclin-dependent kinase inhibitor 1A, S100 calcium binding protein A6 (S100A6), dual specificity phosphatase 5, keratin 19, met proto-oncogene (MET) and lectin galactoside-binding soluble 3 were included in the Malacards database. In the miRNA regulatory and integrated networks, genes of cyclin-dependent kinase inhibitor 1C (CDKN1C), peroxisome proliferator-activated receptor γ, aryl hydrocarbon receptor, basic helix-loop-helix family, member e40 and reticulon 1 were the key target genes. S100A6, MET and CDKN1C may exhibit key roles in the progression and development of PTC, and may be used as specific therapeutic targets in the treatment of PTC. However, further experiments are required to confirm these results.
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spelling pubmed-47269252016-02-11 Identification of potential therapeutic targets for papillary thyroid carcinoma by bioinformatics analysis ZHAO, MING WANG, KE-JING TAN, ZHUO ZHENG, CHUAN-MING LIANG, ZHONG ZHAO, JIAN-QIANG Oncol Lett Articles The aim of the present study was to identify potential therapeutic targets for papillary thyroid carcinoma (PTC) and to investigate the possible mechanism underlying this disease. The gene expression profile, GSE53157, was downloaded from the Gene Expression Omnibus database. Only 10 chips, including 3 specimens of normal thyroid tissues and 7 specimens of well-differentiated thyroid carcinomas, were analyzed in the present study. Differentially-expressed genes (DEGs) between PTC patients and normal individuals were identified. Next, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses of DEGs were performed. Modules in the protein-protein interaction (PPI) network were identified. Significant target genes were selected from the microRNA (miRNA) regulatory network. Furthermore, the integrated network was constructed with the miRNA regulatory and PPI network modules, and key target genes were screened. A total of 668 DEGs were identified. Modules M1, M2 and M3 were identified from the PPI network. From the modules, DEGs of cyclin-dependent kinase inhibitor 1A, S100 calcium binding protein A6 (S100A6), dual specificity phosphatase 5, keratin 19, met proto-oncogene (MET) and lectin galactoside-binding soluble 3 were included in the Malacards database. In the miRNA regulatory and integrated networks, genes of cyclin-dependent kinase inhibitor 1C (CDKN1C), peroxisome proliferator-activated receptor γ, aryl hydrocarbon receptor, basic helix-loop-helix family, member e40 and reticulon 1 were the key target genes. S100A6, MET and CDKN1C may exhibit key roles in the progression and development of PTC, and may be used as specific therapeutic targets in the treatment of PTC. However, further experiments are required to confirm these results. D.A. Spandidos 2016-01 2015-10-26 /pmc/articles/PMC4726925/ /pubmed/26870166 http://dx.doi.org/10.3892/ol.2015.3829 Text en Copyright: © Zhao 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
ZHAO, MING
WANG, KE-JING
TAN, ZHUO
ZHENG, CHUAN-MING
LIANG, ZHONG
ZHAO, JIAN-QIANG
Identification of potential therapeutic targets for papillary thyroid carcinoma by bioinformatics analysis
title Identification of potential therapeutic targets for papillary thyroid carcinoma by bioinformatics analysis
title_full Identification of potential therapeutic targets for papillary thyroid carcinoma by bioinformatics analysis
title_fullStr Identification of potential therapeutic targets for papillary thyroid carcinoma by bioinformatics analysis
title_full_unstemmed Identification of potential therapeutic targets for papillary thyroid carcinoma by bioinformatics analysis
title_short Identification of potential therapeutic targets for papillary thyroid carcinoma by bioinformatics analysis
title_sort identification of potential therapeutic targets for papillary thyroid carcinoma by bioinformatics analysis
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4726925/
https://www.ncbi.nlm.nih.gov/pubmed/26870166
http://dx.doi.org/10.3892/ol.2015.3829
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