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Predictive and prognostic transcriptomic biomarkers in soft tissue sarcomas
Soft tissue sarcomas (STS) are rare and heterogeneous tumours comprising over 80 different histological subtypes. Treatment options remain limited in advanced STS with high rates of recurrence following resection of localised disease. Prognostication in clinical practice relies predominantly on hist...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7935908/ https://www.ncbi.nlm.nih.gov/pubmed/33674685 http://dx.doi.org/10.1038/s41698-021-00157-4 |
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author | Merry, Eve Thway, Khin Jones, Robin L. Huang, Paul H. |
author_facet | Merry, Eve Thway, Khin Jones, Robin L. Huang, Paul H. |
author_sort | Merry, Eve |
collection | PubMed |
description | Soft tissue sarcomas (STS) are rare and heterogeneous tumours comprising over 80 different histological subtypes. Treatment options remain limited in advanced STS with high rates of recurrence following resection of localised disease. Prognostication in clinical practice relies predominantly on histological grading systems as well as sarcoma nomograms. Rapid developments in gene expression profiling technologies presented opportunities for applications in sarcoma. Molecular profiling of sarcomas has improved our understanding of the cancer biology of these rare cancers and identified potential novel therapeutic targets. In particular, transcriptomic signatures could play a role in risk classification in sarcoma to aid prognostication. Unlike other solid and haematological malignancies, transcriptomic signatures have not yet reached routine clinical use in sarcomas. Herein, we evaluate early developments in gene expression profiling in sarcomas that laid the foundations for transcriptomic signature development. We discuss the development and clinical evaluation of key transcriptomic biomarker signatures in sarcomas, including Complexity INdex in SARComas (CINSARC), Genomic Grade Index, and hypoxia-associated signatures. Prospective validation of these transcriptomic signatures is required, and prospective trials are in progress to evaluate reliability for clinical application. We anticipate that integration of these gene expression signatures alongside existing prognosticators and other Omics methodologies, including proteomics and DNA methylation analysis, could improve the identification of ‘high-risk’ patients who would benefit from more aggressive or selective treatment strategies. Moving forward, the incorporation of these transcriptomic prognostication signatures in clinical practice will undoubtedly advance precision medicine in the routine clinical management of sarcoma patients. |
format | Online Article Text |
id | pubmed-7935908 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-79359082021-03-19 Predictive and prognostic transcriptomic biomarkers in soft tissue sarcomas Merry, Eve Thway, Khin Jones, Robin L. Huang, Paul H. NPJ Precis Oncol Review Article Soft tissue sarcomas (STS) are rare and heterogeneous tumours comprising over 80 different histological subtypes. Treatment options remain limited in advanced STS with high rates of recurrence following resection of localised disease. Prognostication in clinical practice relies predominantly on histological grading systems as well as sarcoma nomograms. Rapid developments in gene expression profiling technologies presented opportunities for applications in sarcoma. Molecular profiling of sarcomas has improved our understanding of the cancer biology of these rare cancers and identified potential novel therapeutic targets. In particular, transcriptomic signatures could play a role in risk classification in sarcoma to aid prognostication. Unlike other solid and haematological malignancies, transcriptomic signatures have not yet reached routine clinical use in sarcomas. Herein, we evaluate early developments in gene expression profiling in sarcomas that laid the foundations for transcriptomic signature development. We discuss the development and clinical evaluation of key transcriptomic biomarker signatures in sarcomas, including Complexity INdex in SARComas (CINSARC), Genomic Grade Index, and hypoxia-associated signatures. Prospective validation of these transcriptomic signatures is required, and prospective trials are in progress to evaluate reliability for clinical application. We anticipate that integration of these gene expression signatures alongside existing prognosticators and other Omics methodologies, including proteomics and DNA methylation analysis, could improve the identification of ‘high-risk’ patients who would benefit from more aggressive or selective treatment strategies. Moving forward, the incorporation of these transcriptomic prognostication signatures in clinical practice will undoubtedly advance precision medicine in the routine clinical management of sarcoma patients. Nature Publishing Group UK 2021-03-05 /pmc/articles/PMC7935908/ /pubmed/33674685 http://dx.doi.org/10.1038/s41698-021-00157-4 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Review Article Merry, Eve Thway, Khin Jones, Robin L. Huang, Paul H. Predictive and prognostic transcriptomic biomarkers in soft tissue sarcomas |
title | Predictive and prognostic transcriptomic biomarkers in soft tissue sarcomas |
title_full | Predictive and prognostic transcriptomic biomarkers in soft tissue sarcomas |
title_fullStr | Predictive and prognostic transcriptomic biomarkers in soft tissue sarcomas |
title_full_unstemmed | Predictive and prognostic transcriptomic biomarkers in soft tissue sarcomas |
title_short | Predictive and prognostic transcriptomic biomarkers in soft tissue sarcomas |
title_sort | predictive and prognostic transcriptomic biomarkers in soft tissue sarcomas |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7935908/ https://www.ncbi.nlm.nih.gov/pubmed/33674685 http://dx.doi.org/10.1038/s41698-021-00157-4 |
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