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Multi-omics Signatures and Translational Potential to Improve Thyroid Cancer Patient Outcome
Recent advances in high-throughput molecular and multi-omics technologies have improved our understanding of the molecular changes associated with thyroid cancer initiation and progression. The translation into clinical use based on molecular profiling of thyroid tumors has allowed a significant imp...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6966476/ https://www.ncbi.nlm.nih.gov/pubmed/31835496 http://dx.doi.org/10.3390/cancers11121988 |
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author | Boufraqech, Myriem Nilubol, Naris |
author_facet | Boufraqech, Myriem Nilubol, Naris |
author_sort | Boufraqech, Myriem |
collection | PubMed |
description | Recent advances in high-throughput molecular and multi-omics technologies have improved our understanding of the molecular changes associated with thyroid cancer initiation and progression. The translation into clinical use based on molecular profiling of thyroid tumors has allowed a significant improvement in patient risk stratification and in the identification of targeted therapies, and thereby better personalized disease management and outcome. This review compiles the following: (1) the major molecular alterations of the genome, epigenome, transcriptome, proteome, and metabolome found in all subtypes of thyroid cancer, thus demonstrating the complexity of these tumors and (2) the great translational potential of multi-omics studies to improve patient outcome. |
format | Online Article Text |
id | pubmed-6966476 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-69664762020-01-27 Multi-omics Signatures and Translational Potential to Improve Thyroid Cancer Patient Outcome Boufraqech, Myriem Nilubol, Naris Cancers (Basel) Review Recent advances in high-throughput molecular and multi-omics technologies have improved our understanding of the molecular changes associated with thyroid cancer initiation and progression. The translation into clinical use based on molecular profiling of thyroid tumors has allowed a significant improvement in patient risk stratification and in the identification of targeted therapies, and thereby better personalized disease management and outcome. This review compiles the following: (1) the major molecular alterations of the genome, epigenome, transcriptome, proteome, and metabolome found in all subtypes of thyroid cancer, thus demonstrating the complexity of these tumors and (2) the great translational potential of multi-omics studies to improve patient outcome. MDPI 2019-12-10 /pmc/articles/PMC6966476/ /pubmed/31835496 http://dx.doi.org/10.3390/cancers11121988 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Boufraqech, Myriem Nilubol, Naris Multi-omics Signatures and Translational Potential to Improve Thyroid Cancer Patient Outcome |
title | Multi-omics Signatures and Translational Potential to Improve Thyroid Cancer Patient Outcome |
title_full | Multi-omics Signatures and Translational Potential to Improve Thyroid Cancer Patient Outcome |
title_fullStr | Multi-omics Signatures and Translational Potential to Improve Thyroid Cancer Patient Outcome |
title_full_unstemmed | Multi-omics Signatures and Translational Potential to Improve Thyroid Cancer Patient Outcome |
title_short | Multi-omics Signatures and Translational Potential to Improve Thyroid Cancer Patient Outcome |
title_sort | multi-omics signatures and translational potential to improve thyroid cancer patient outcome |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6966476/ https://www.ncbi.nlm.nih.gov/pubmed/31835496 http://dx.doi.org/10.3390/cancers11121988 |
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