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Towards a more precise and individualized assessment of breast cancer risk

Many clinically based models are available for breast cancer risk assessment; however, these models are not particularly useful at the individual level, despite being designed with that intent. There is, therefore, a significant need for improved, precise individualized risk assessment. In this Rese...

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Autores principales: Wood, Marie E., Farina, Nicholas H., Ahern, Thomas P., Cuke, Melissa E., Stein, Janet L., Stein, Gary S., Lian, Jane B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6402518/
https://www.ncbi.nlm.nih.gov/pubmed/30787204
http://dx.doi.org/10.18632/aging.101803
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author Wood, Marie E.
Farina, Nicholas H.
Ahern, Thomas P.
Cuke, Melissa E.
Stein, Janet L.
Stein, Gary S.
Lian, Jane B.
author_facet Wood, Marie E.
Farina, Nicholas H.
Ahern, Thomas P.
Cuke, Melissa E.
Stein, Janet L.
Stein, Gary S.
Lian, Jane B.
author_sort Wood, Marie E.
collection PubMed
description Many clinically based models are available for breast cancer risk assessment; however, these models are not particularly useful at the individual level, despite being designed with that intent. There is, therefore, a significant need for improved, precise individualized risk assessment. In this Research Perspective, we highlight commonly used clinical risk assessment models and recent scientific advances to individualize risk assessment using precision biomarkers. Genome-wide association studies have identified >100 single nucleotide polymorphisms (SNPs) associated with breast cancer risk, and polygenic risk scores (PRS) have been developed by several groups using this information. The ability of a PRS to improve risk assessment is promising; however, validation in both genetically and ethnically diverse populations is needed. Additionally, novel classes of biomarkers, such as microRNAs, may capture clinically relevant information based on epigenetic regulation of gene expression. Our group has recently identified a circulating-microRNA signature predictive of long-term breast cancer in a prospective cohort of high-risk women. While progress has been made, the importance of accurate risk assessment cannot be understated. Precision risk assessment will identify those women at greatest risk of developing breast cancer, thus avoiding overtreatment of women at average risk and identifying the most appropriate candidates for chemoprevention or surgical prevention.
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spelling pubmed-64025182019-03-11 Towards a more precise and individualized assessment of breast cancer risk Wood, Marie E. Farina, Nicholas H. Ahern, Thomas P. Cuke, Melissa E. Stein, Janet L. Stein, Gary S. Lian, Jane B. Aging (Albany NY) Research Perspective Many clinically based models are available for breast cancer risk assessment; however, these models are not particularly useful at the individual level, despite being designed with that intent. There is, therefore, a significant need for improved, precise individualized risk assessment. In this Research Perspective, we highlight commonly used clinical risk assessment models and recent scientific advances to individualize risk assessment using precision biomarkers. Genome-wide association studies have identified >100 single nucleotide polymorphisms (SNPs) associated with breast cancer risk, and polygenic risk scores (PRS) have been developed by several groups using this information. The ability of a PRS to improve risk assessment is promising; however, validation in both genetically and ethnically diverse populations is needed. Additionally, novel classes of biomarkers, such as microRNAs, may capture clinically relevant information based on epigenetic regulation of gene expression. Our group has recently identified a circulating-microRNA signature predictive of long-term breast cancer in a prospective cohort of high-risk women. While progress has been made, the importance of accurate risk assessment cannot be understated. Precision risk assessment will identify those women at greatest risk of developing breast cancer, thus avoiding overtreatment of women at average risk and identifying the most appropriate candidates for chemoprevention or surgical prevention. Impact Journals 2019-02-20 /pmc/articles/PMC6402518/ /pubmed/30787204 http://dx.doi.org/10.18632/aging.101803 Text en Copyright © 2019 Wood et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY) 3.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Perspective
Wood, Marie E.
Farina, Nicholas H.
Ahern, Thomas P.
Cuke, Melissa E.
Stein, Janet L.
Stein, Gary S.
Lian, Jane B.
Towards a more precise and individualized assessment of breast cancer risk
title Towards a more precise and individualized assessment of breast cancer risk
title_full Towards a more precise and individualized assessment of breast cancer risk
title_fullStr Towards a more precise and individualized assessment of breast cancer risk
title_full_unstemmed Towards a more precise and individualized assessment of breast cancer risk
title_short Towards a more precise and individualized assessment of breast cancer risk
title_sort towards a more precise and individualized assessment of breast cancer risk
topic Research Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6402518/
https://www.ncbi.nlm.nih.gov/pubmed/30787204
http://dx.doi.org/10.18632/aging.101803
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