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Accurate prediction of response to endocrine therapy in breast cancer patients: current and future biomarkers

Approximately 70% of patients have breast cancers that are oestrogen receptor alpha positive (ER+) and are therefore candidates for endocrine treatment. Many of these patients relapse in the years during or following completion of adjuvant endocrine therapy. Thus, many ER+ cancers have primary resis...

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Autores principales: Selli, Cigdem, Dixon, J. Michael, Sims, Andrew H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5131493/
https://www.ncbi.nlm.nih.gov/pubmed/27903276
http://dx.doi.org/10.1186/s13058-016-0779-0
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author Selli, Cigdem
Dixon, J. Michael
Sims, Andrew H.
author_facet Selli, Cigdem
Dixon, J. Michael
Sims, Andrew H.
author_sort Selli, Cigdem
collection PubMed
description Approximately 70% of patients have breast cancers that are oestrogen receptor alpha positive (ER+) and are therefore candidates for endocrine treatment. Many of these patients relapse in the years during or following completion of adjuvant endocrine therapy. Thus, many ER+ cancers have primary resistance or develop resistance to endocrine therapy during treatment. Recent improvements in our understanding of how tumours evolve during treatment with endocrine agents have identified both changes in gene expression and mutational profiles, in the primary cancer as well as in circulating tumour cells. Analysing these changes has the potential to improve the prediction of which specific patients will respond to endocrine treatment. Serially profiled biopsies during treatment in the neoadjuvant setting offer promise for accurate and early prediction of response to both current and novel drugs and allow investigation of mechanisms of resistance. In addition, recent advances in monitoring tumour evolution through non-invasive (liquid) sampling of circulating tumour cells and cell-free tumour DNA may provide a method to detect resistant clones and allow implementation of personalized treatments for metastatic breast cancer patients. This review summarises current and future biomarkers and signatures for predicting response to endocrine treatment, and discusses the potential for using approved drugs and novel agents to improve outcomes. Increased prediction accuracy is likely to require sequential sampling, utilising preoperative or neoadjuvant treatment and/or liquid biopsies and an improved understanding of both the dynamics and heterogeneity of breast cancer.
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spelling pubmed-51314932016-12-12 Accurate prediction of response to endocrine therapy in breast cancer patients: current and future biomarkers Selli, Cigdem Dixon, J. Michael Sims, Andrew H. Breast Cancer Res Review Approximately 70% of patients have breast cancers that are oestrogen receptor alpha positive (ER+) and are therefore candidates for endocrine treatment. Many of these patients relapse in the years during or following completion of adjuvant endocrine therapy. Thus, many ER+ cancers have primary resistance or develop resistance to endocrine therapy during treatment. Recent improvements in our understanding of how tumours evolve during treatment with endocrine agents have identified both changes in gene expression and mutational profiles, in the primary cancer as well as in circulating tumour cells. Analysing these changes has the potential to improve the prediction of which specific patients will respond to endocrine treatment. Serially profiled biopsies during treatment in the neoadjuvant setting offer promise for accurate and early prediction of response to both current and novel drugs and allow investigation of mechanisms of resistance. In addition, recent advances in monitoring tumour evolution through non-invasive (liquid) sampling of circulating tumour cells and cell-free tumour DNA may provide a method to detect resistant clones and allow implementation of personalized treatments for metastatic breast cancer patients. This review summarises current and future biomarkers and signatures for predicting response to endocrine treatment, and discusses the potential for using approved drugs and novel agents to improve outcomes. Increased prediction accuracy is likely to require sequential sampling, utilising preoperative or neoadjuvant treatment and/or liquid biopsies and an improved understanding of both the dynamics and heterogeneity of breast cancer. BioMed Central 2016-12-01 2016 /pmc/articles/PMC5131493/ /pubmed/27903276 http://dx.doi.org/10.1186/s13058-016-0779-0 Text en © The Author(s). 2016 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 Review
Selli, Cigdem
Dixon, J. Michael
Sims, Andrew H.
Accurate prediction of response to endocrine therapy in breast cancer patients: current and future biomarkers
title Accurate prediction of response to endocrine therapy in breast cancer patients: current and future biomarkers
title_full Accurate prediction of response to endocrine therapy in breast cancer patients: current and future biomarkers
title_fullStr Accurate prediction of response to endocrine therapy in breast cancer patients: current and future biomarkers
title_full_unstemmed Accurate prediction of response to endocrine therapy in breast cancer patients: current and future biomarkers
title_short Accurate prediction of response to endocrine therapy in breast cancer patients: current and future biomarkers
title_sort accurate prediction of response to endocrine therapy in breast cancer patients: current and future biomarkers
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5131493/
https://www.ncbi.nlm.nih.gov/pubmed/27903276
http://dx.doi.org/10.1186/s13058-016-0779-0
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