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Are online prediction tools a valid alternative to genomic profiling in the context of systemic treatment of ER-positive breast cancer?

BACKGROUND: Clinicians use clinical and pathological parameters, such as tumour size, grade and nodal status, to make decisions on adjuvant treatments for breast cancer. However, therapeutic decisions based on these features tend to vary due to their subjectivity. Computational and mathematical algo...

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Autores principales: Wazir, Umar, Mokbel, Kinan, Carmichael, Amtul, Mokbel, Kefah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5583984/
https://www.ncbi.nlm.nih.gov/pubmed/28878809
http://dx.doi.org/10.1186/s11658-017-0049-x
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author Wazir, Umar
Mokbel, Kinan
Carmichael, Amtul
Mokbel, Kefah
author_facet Wazir, Umar
Mokbel, Kinan
Carmichael, Amtul
Mokbel, Kefah
author_sort Wazir, Umar
collection PubMed
description BACKGROUND: Clinicians use clinical and pathological parameters, such as tumour size, grade and nodal status, to make decisions on adjuvant treatments for breast cancer. However, therapeutic decisions based on these features tend to vary due to their subjectivity. Computational and mathematical algorithms were developed using clinical outcome data from breast cancer registries, such as Adjuvant! Online and NHS PREDICT. More recently, assessments of molecular profiles have been applied in the development of better prognostic tools. METHODS: Based on the available literature on online registry-based tools and genomic assays, we evaluated whether these online tools could be valid and accurate alternatives to genomic and molecular profiling of the individual breast tumour in aiding therapeutic decisions, particularly in patients with early ER-positive breast cancer. RESULTS AND CONCLUSIONS: Early breast cancer is currently considered a systemic disease and a complex ecosystem with behaviour determined by the complex genetic and molecular signatures of the tumour cells, mammary stem cells, microenvironment and host immune system. We anticipate that molecular profiling will continue to evolve, expanding beyond the primary tumour to include the tumour microenvironment, cancer stem cells and host immune system. This should further refine therapeutic decisions and optimise clinical outcome. This article was specially invited by the editors and represents work by leading researchers.
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spelling pubmed-55839842017-09-06 Are online prediction tools a valid alternative to genomic profiling in the context of systemic treatment of ER-positive breast cancer? Wazir, Umar Mokbel, Kinan Carmichael, Amtul Mokbel, Kefah Cell Mol Biol Lett Mini Review BACKGROUND: Clinicians use clinical and pathological parameters, such as tumour size, grade and nodal status, to make decisions on adjuvant treatments for breast cancer. However, therapeutic decisions based on these features tend to vary due to their subjectivity. Computational and mathematical algorithms were developed using clinical outcome data from breast cancer registries, such as Adjuvant! Online and NHS PREDICT. More recently, assessments of molecular profiles have been applied in the development of better prognostic tools. METHODS: Based on the available literature on online registry-based tools and genomic assays, we evaluated whether these online tools could be valid and accurate alternatives to genomic and molecular profiling of the individual breast tumour in aiding therapeutic decisions, particularly in patients with early ER-positive breast cancer. RESULTS AND CONCLUSIONS: Early breast cancer is currently considered a systemic disease and a complex ecosystem with behaviour determined by the complex genetic and molecular signatures of the tumour cells, mammary stem cells, microenvironment and host immune system. We anticipate that molecular profiling will continue to evolve, expanding beyond the primary tumour to include the tumour microenvironment, cancer stem cells and host immune system. This should further refine therapeutic decisions and optimise clinical outcome. This article was specially invited by the editors and represents work by leading researchers. BioMed Central 2017-09-04 /pmc/articles/PMC5583984/ /pubmed/28878809 http://dx.doi.org/10.1186/s11658-017-0049-x Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Mini Review
Wazir, Umar
Mokbel, Kinan
Carmichael, Amtul
Mokbel, Kefah
Are online prediction tools a valid alternative to genomic profiling in the context of systemic treatment of ER-positive breast cancer?
title Are online prediction tools a valid alternative to genomic profiling in the context of systemic treatment of ER-positive breast cancer?
title_full Are online prediction tools a valid alternative to genomic profiling in the context of systemic treatment of ER-positive breast cancer?
title_fullStr Are online prediction tools a valid alternative to genomic profiling in the context of systemic treatment of ER-positive breast cancer?
title_full_unstemmed Are online prediction tools a valid alternative to genomic profiling in the context of systemic treatment of ER-positive breast cancer?
title_short Are online prediction tools a valid alternative to genomic profiling in the context of systemic treatment of ER-positive breast cancer?
title_sort are online prediction tools a valid alternative to genomic profiling in the context of systemic treatment of er-positive breast cancer?
topic Mini Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5583984/
https://www.ncbi.nlm.nih.gov/pubmed/28878809
http://dx.doi.org/10.1186/s11658-017-0049-x
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