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NanoString-based breast cancer risk prediction for women with sclerosing adenosis

PURPOSE: Sclerosing adenosis (SA), found in ¼ of benign breast disease (BBD) biopsies, is a histological feature characterized by lobulocentric proliferation of acini and stromal fibrosis and confers a two-fold increase in breast cancer risk compared to women in the general population. We evaluated...

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Autores principales: Winham, Stacey J., Mehner, Christine, Heinzen, Ethan P., Broderick, Brendan T., Stallings-Mann, Melody, Nassar, Aziza, Vierkant, Robert A., Hoskin, Tanya L., Frank, Ryan D., Wang, Chen, Denison, Lori A., Vachon, Celine M., Frost, Marlene H., Hartmann, Lynn C., Aubrey Thompson, E., Sherman, Mark E., Visscher, Daniel W., Degnim, Amy C., Radisky, Derek C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5668350/
https://www.ncbi.nlm.nih.gov/pubmed/28798985
http://dx.doi.org/10.1007/s10549-017-4441-z
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author Winham, Stacey J.
Mehner, Christine
Heinzen, Ethan P.
Broderick, Brendan T.
Stallings-Mann, Melody
Nassar, Aziza
Vierkant, Robert A.
Hoskin, Tanya L.
Frank, Ryan D.
Wang, Chen
Denison, Lori A.
Vachon, Celine M.
Frost, Marlene H.
Hartmann, Lynn C.
Aubrey Thompson, E.
Sherman, Mark E.
Visscher, Daniel W.
Degnim, Amy C.
Radisky, Derek C.
author_facet Winham, Stacey J.
Mehner, Christine
Heinzen, Ethan P.
Broderick, Brendan T.
Stallings-Mann, Melody
Nassar, Aziza
Vierkant, Robert A.
Hoskin, Tanya L.
Frank, Ryan D.
Wang, Chen
Denison, Lori A.
Vachon, Celine M.
Frost, Marlene H.
Hartmann, Lynn C.
Aubrey Thompson, E.
Sherman, Mark E.
Visscher, Daniel W.
Degnim, Amy C.
Radisky, Derek C.
author_sort Winham, Stacey J.
collection PubMed
description PURPOSE: Sclerosing adenosis (SA), found in ¼ of benign breast disease (BBD) biopsies, is a histological feature characterized by lobulocentric proliferation of acini and stromal fibrosis and confers a two-fold increase in breast cancer risk compared to women in the general population. We evaluated a NanoString-based gene expression assay to model breast cancer risk using RNA derived from formalin-fixed, paraffin-embedded (FFPE) biopsies with SA. METHODS: The study group consisted of 151 women diagnosed with SA between 1967 and 2001 within the Mayo BBD cohort, of which 37 subsequently developed cancer within 10 years (cases) and 114 did not (controls). RNA was isolated from benign breast biopsies, and NanoString-based methods were used to assess expression levels of 61 genes, including 35 identified by previous array-based profiling experiments and 26 from biological insight. Diagonal linear discriminant analysis of these data was used to predict cancer within 10 years. Predictive performance was assessed with receiver operating characteristic area under the curve (ROC-AUC) values estimated from 5-fold cross-validation. RESULTS: Gene expression prediction models achieved cross-validated ROC-AUC estimates ranging from 0.66 to 0.70. Performing univariate associations within each of the five folds consistently identified genes DLK2, EXOC6, KIT, RGS12, and SORBS2 as significant; a model with only these five genes showed cross-validated ROC-AUC of 0.75, which compared favorably to risk prediction using established clinical models (Gail/BCRAT: 0.57; BBD-BC: 0.67). CONCLUSIONS: Our results demonstrate that biomarkers of breast cancer risk can be detected in benign breast tissue years prior to cancer development in women with SA. These markers can be assessed using assay methods optimized for RNA derived from FFPE biopsy tissues which are commonly available. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10549-017-4441-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-56683502017-11-16 NanoString-based breast cancer risk prediction for women with sclerosing adenosis Winham, Stacey J. Mehner, Christine Heinzen, Ethan P. Broderick, Brendan T. Stallings-Mann, Melody Nassar, Aziza Vierkant, Robert A. Hoskin, Tanya L. Frank, Ryan D. Wang, Chen Denison, Lori A. Vachon, Celine M. Frost, Marlene H. Hartmann, Lynn C. Aubrey Thompson, E. Sherman, Mark E. Visscher, Daniel W. Degnim, Amy C. Radisky, Derek C. Breast Cancer Res Treat Brief Report PURPOSE: Sclerosing adenosis (SA), found in ¼ of benign breast disease (BBD) biopsies, is a histological feature characterized by lobulocentric proliferation of acini and stromal fibrosis and confers a two-fold increase in breast cancer risk compared to women in the general population. We evaluated a NanoString-based gene expression assay to model breast cancer risk using RNA derived from formalin-fixed, paraffin-embedded (FFPE) biopsies with SA. METHODS: The study group consisted of 151 women diagnosed with SA between 1967 and 2001 within the Mayo BBD cohort, of which 37 subsequently developed cancer within 10 years (cases) and 114 did not (controls). RNA was isolated from benign breast biopsies, and NanoString-based methods were used to assess expression levels of 61 genes, including 35 identified by previous array-based profiling experiments and 26 from biological insight. Diagonal linear discriminant analysis of these data was used to predict cancer within 10 years. Predictive performance was assessed with receiver operating characteristic area under the curve (ROC-AUC) values estimated from 5-fold cross-validation. RESULTS: Gene expression prediction models achieved cross-validated ROC-AUC estimates ranging from 0.66 to 0.70. Performing univariate associations within each of the five folds consistently identified genes DLK2, EXOC6, KIT, RGS12, and SORBS2 as significant; a model with only these five genes showed cross-validated ROC-AUC of 0.75, which compared favorably to risk prediction using established clinical models (Gail/BCRAT: 0.57; BBD-BC: 0.67). CONCLUSIONS: Our results demonstrate that biomarkers of breast cancer risk can be detected in benign breast tissue years prior to cancer development in women with SA. These markers can be assessed using assay methods optimized for RNA derived from FFPE biopsy tissues which are commonly available. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10549-017-4441-z) contains supplementary material, which is available to authorized users. Springer US 2017-08-10 2017 /pmc/articles/PMC5668350/ /pubmed/28798985 http://dx.doi.org/10.1007/s10549-017-4441-z 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.
spellingShingle Brief Report
Winham, Stacey J.
Mehner, Christine
Heinzen, Ethan P.
Broderick, Brendan T.
Stallings-Mann, Melody
Nassar, Aziza
Vierkant, Robert A.
Hoskin, Tanya L.
Frank, Ryan D.
Wang, Chen
Denison, Lori A.
Vachon, Celine M.
Frost, Marlene H.
Hartmann, Lynn C.
Aubrey Thompson, E.
Sherman, Mark E.
Visscher, Daniel W.
Degnim, Amy C.
Radisky, Derek C.
NanoString-based breast cancer risk prediction for women with sclerosing adenosis
title NanoString-based breast cancer risk prediction for women with sclerosing adenosis
title_full NanoString-based breast cancer risk prediction for women with sclerosing adenosis
title_fullStr NanoString-based breast cancer risk prediction for women with sclerosing adenosis
title_full_unstemmed NanoString-based breast cancer risk prediction for women with sclerosing adenosis
title_short NanoString-based breast cancer risk prediction for women with sclerosing adenosis
title_sort nanostring-based breast cancer risk prediction for women with sclerosing adenosis
topic Brief Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5668350/
https://www.ncbi.nlm.nih.gov/pubmed/28798985
http://dx.doi.org/10.1007/s10549-017-4441-z
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