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Bioinformatic analysis and identification of potential prognostic microRNAs and mRNAs in thyroid cancer

Thyroid cancer is one of the most common endocrine malignancies. Multiple evidences revealed that a large number of microRNAs and mRNAs were abnormally expressed in thyroid cancer tissues. These microRNAs and mRNAs play important roles in tumorigenesis. In the present study, we identified 72 microRN...

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Autores principales: Tang, Jianing, Kong, Deguang, Cui, Qiuxia, Wang, Kun, Zhang, Dan, Yuan, Qianqian, Liao, Xing, Gong, Yan, Wu, Gaosong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5937477/
https://www.ncbi.nlm.nih.gov/pubmed/29740512
http://dx.doi.org/10.7717/peerj.4674
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author Tang, Jianing
Kong, Deguang
Cui, Qiuxia
Wang, Kun
Zhang, Dan
Yuan, Qianqian
Liao, Xing
Gong, Yan
Wu, Gaosong
author_facet Tang, Jianing
Kong, Deguang
Cui, Qiuxia
Wang, Kun
Zhang, Dan
Yuan, Qianqian
Liao, Xing
Gong, Yan
Wu, Gaosong
author_sort Tang, Jianing
collection PubMed
description Thyroid cancer is one of the most common endocrine malignancies. Multiple evidences revealed that a large number of microRNAs and mRNAs were abnormally expressed in thyroid cancer tissues. These microRNAs and mRNAs play important roles in tumorigenesis. In the present study, we identified 72 microRNAs and 1,766 mRNAs differentially expressed between thyroid cancer tissues and normal thyroid tissues and evaluated their prognostic values using Kaplan-Meier survival curves by log-rank test. Seven microRNAs (miR-146b, miR-184, miR-767, miR-6730, miR-6860, miR-196a-2 and miR-509-3) were associated with the overall survival. Among them, three microRNAs were linked with six differentially expressed mRNAs (miR-767 was predicted to target COL10A1, PLAG1 and PPP1R1C; miR-146b was predicted to target MMP16; miR-196a-2 was predicted to target SYT9). To identify the key genes in the protein-protein interaction network , we screened out the top 10 hub genes (NPY, NMU, KNG1, LPAR5, CCR3, SST, PPY, GABBR2, ADCY8 and SAA1) with higher degrees. Only LPAR5 was associated with the overall survival. Multivariate analysis demonstrated that miR-184, miR-146b, miR-509-3 and LPAR5 were an independent risk factors for prognosis. Our results of the present study identified a series of prognostic microRNAs and mRNAs that have the potential to be the targets for treatment of thyroid cancer.
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spelling pubmed-59374772018-05-08 Bioinformatic analysis and identification of potential prognostic microRNAs and mRNAs in thyroid cancer Tang, Jianing Kong, Deguang Cui, Qiuxia Wang, Kun Zhang, Dan Yuan, Qianqian Liao, Xing Gong, Yan Wu, Gaosong PeerJ Bioinformatics Thyroid cancer is one of the most common endocrine malignancies. Multiple evidences revealed that a large number of microRNAs and mRNAs were abnormally expressed in thyroid cancer tissues. These microRNAs and mRNAs play important roles in tumorigenesis. In the present study, we identified 72 microRNAs and 1,766 mRNAs differentially expressed between thyroid cancer tissues and normal thyroid tissues and evaluated their prognostic values using Kaplan-Meier survival curves by log-rank test. Seven microRNAs (miR-146b, miR-184, miR-767, miR-6730, miR-6860, miR-196a-2 and miR-509-3) were associated with the overall survival. Among them, three microRNAs were linked with six differentially expressed mRNAs (miR-767 was predicted to target COL10A1, PLAG1 and PPP1R1C; miR-146b was predicted to target MMP16; miR-196a-2 was predicted to target SYT9). To identify the key genes in the protein-protein interaction network , we screened out the top 10 hub genes (NPY, NMU, KNG1, LPAR5, CCR3, SST, PPY, GABBR2, ADCY8 and SAA1) with higher degrees. Only LPAR5 was associated with the overall survival. Multivariate analysis demonstrated that miR-184, miR-146b, miR-509-3 and LPAR5 were an independent risk factors for prognosis. Our results of the present study identified a series of prognostic microRNAs and mRNAs that have the potential to be the targets for treatment of thyroid cancer. PeerJ Inc. 2018-05-04 /pmc/articles/PMC5937477/ /pubmed/29740512 http://dx.doi.org/10.7717/peerj.4674 Text en ©2018 Tang et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Tang, Jianing
Kong, Deguang
Cui, Qiuxia
Wang, Kun
Zhang, Dan
Yuan, Qianqian
Liao, Xing
Gong, Yan
Wu, Gaosong
Bioinformatic analysis and identification of potential prognostic microRNAs and mRNAs in thyroid cancer
title Bioinformatic analysis and identification of potential prognostic microRNAs and mRNAs in thyroid cancer
title_full Bioinformatic analysis and identification of potential prognostic microRNAs and mRNAs in thyroid cancer
title_fullStr Bioinformatic analysis and identification of potential prognostic microRNAs and mRNAs in thyroid cancer
title_full_unstemmed Bioinformatic analysis and identification of potential prognostic microRNAs and mRNAs in thyroid cancer
title_short Bioinformatic analysis and identification of potential prognostic microRNAs and mRNAs in thyroid cancer
title_sort bioinformatic analysis and identification of potential prognostic micrornas and mrnas in thyroid cancer
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5937477/
https://www.ncbi.nlm.nih.gov/pubmed/29740512
http://dx.doi.org/10.7717/peerj.4674
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