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Frequency of breast cancer subtypes among African American women in the AMBER consortium

BACKGROUND: Breast cancer subtype can be classified using standard clinical markers (estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2)), supplemented with additional markers. However, automated biomarker scoring and classification schemes have not...

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Autores principales: Allott, Emma H., Geradts, Joseph, Cohen, Stephanie M., Khoury, Thaer, Zirpoli, Gary R., Bshara, Wiam, Davis, Warren, Omilian, Angela, Nair, Priya, Ondracek, Rochelle P., Cheng, Ting-Yuan David, Miller, C. Ryan, Hwang, Helena, Thorne, Leigh B., O’Connor, Siobhan, Bethea, Traci N., Bell, Mary E., Hu, Zhiyuan, Li, Yan, Kirk, Erin L., Sun, Xuezheng, Ruiz-Narvaez, Edward A., Perou, Charles M., Palmer, Julie R., Olshan, Andrew F., Ambrosone, Christine B., Troester, Melissa A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5801839/
https://www.ncbi.nlm.nih.gov/pubmed/29409530
http://dx.doi.org/10.1186/s13058-018-0939-5
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author Allott, Emma H.
Geradts, Joseph
Cohen, Stephanie M.
Khoury, Thaer
Zirpoli, Gary R.
Bshara, Wiam
Davis, Warren
Omilian, Angela
Nair, Priya
Ondracek, Rochelle P.
Cheng, Ting-Yuan David
Miller, C. Ryan
Hwang, Helena
Thorne, Leigh B.
O’Connor, Siobhan
Bethea, Traci N.
Bell, Mary E.
Hu, Zhiyuan
Li, Yan
Kirk, Erin L.
Sun, Xuezheng
Ruiz-Narvaez, Edward A.
Perou, Charles M.
Palmer, Julie R.
Olshan, Andrew F.
Ambrosone, Christine B.
Troester, Melissa A.
author_facet Allott, Emma H.
Geradts, Joseph
Cohen, Stephanie M.
Khoury, Thaer
Zirpoli, Gary R.
Bshara, Wiam
Davis, Warren
Omilian, Angela
Nair, Priya
Ondracek, Rochelle P.
Cheng, Ting-Yuan David
Miller, C. Ryan
Hwang, Helena
Thorne, Leigh B.
O’Connor, Siobhan
Bethea, Traci N.
Bell, Mary E.
Hu, Zhiyuan
Li, Yan
Kirk, Erin L.
Sun, Xuezheng
Ruiz-Narvaez, Edward A.
Perou, Charles M.
Palmer, Julie R.
Olshan, Andrew F.
Ambrosone, Christine B.
Troester, Melissa A.
author_sort Allott, Emma H.
collection PubMed
description BACKGROUND: Breast cancer subtype can be classified using standard clinical markers (estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2)), supplemented with additional markers. However, automated biomarker scoring and classification schemes have not been standardized. The aim of this study was to optimize tumor classification using automated methods in order to describe subtype frequency in the African American Breast Cancer Epidemiology and Risk (AMBER) consortium. METHODS: Using immunohistochemistry (IHC), we quantified the expression of ER, PR, HER2, the proliferation marker Ki67, and two basal-like biomarkers, epidermal growth factor receptor (EGFR) and cytokeratin (CK)5/6, in 1381 invasive breast tumors from African American women. RNA-based (prediction analysis of microarray 50 (PAM50)) subtype, available for 574 (42%) cases, was used to optimize classification. Subtype frequency was calculated, and associations between subtype and tumor characteristics were estimated using logistic regression. RESULTS: Relative to ER, PR and HER2 from medical records, central IHC staining and the addition of Ki67 or combined tumor grade improved accuracy for classifying PAM50-based luminal subtypes. Few triple negative cases (< 2%) lacked EGFR and CK5/6 expression, thereby providing little improvement in accuracy for identifying basal-like tumors. Relative to luminal A subtype, all other subtypes had higher combined grade and were larger, and ER-/HER2+ tumors were more often lymph node positive and late stage tumors. The frequency of basal-like tumors was 31%, exceeded only slightly by luminal A tumors (37%). CONCLUSIONS: Our findings indicate that automated IHC-based classification produces tumor subtype frequencies approximating those from PAM50-based classification and highlight high frequency of basal-like and low frequency of luminal A breast cancer in a large study of African American women. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13058-018-0939-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-58018392018-02-14 Frequency of breast cancer subtypes among African American women in the AMBER consortium Allott, Emma H. Geradts, Joseph Cohen, Stephanie M. Khoury, Thaer Zirpoli, Gary R. Bshara, Wiam Davis, Warren Omilian, Angela Nair, Priya Ondracek, Rochelle P. Cheng, Ting-Yuan David Miller, C. Ryan Hwang, Helena Thorne, Leigh B. O’Connor, Siobhan Bethea, Traci N. Bell, Mary E. Hu, Zhiyuan Li, Yan Kirk, Erin L. Sun, Xuezheng Ruiz-Narvaez, Edward A. Perou, Charles M. Palmer, Julie R. Olshan, Andrew F. Ambrosone, Christine B. Troester, Melissa A. Breast Cancer Res Research Article BACKGROUND: Breast cancer subtype can be classified using standard clinical markers (estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2)), supplemented with additional markers. However, automated biomarker scoring and classification schemes have not been standardized. The aim of this study was to optimize tumor classification using automated methods in order to describe subtype frequency in the African American Breast Cancer Epidemiology and Risk (AMBER) consortium. METHODS: Using immunohistochemistry (IHC), we quantified the expression of ER, PR, HER2, the proliferation marker Ki67, and two basal-like biomarkers, epidermal growth factor receptor (EGFR) and cytokeratin (CK)5/6, in 1381 invasive breast tumors from African American women. RNA-based (prediction analysis of microarray 50 (PAM50)) subtype, available for 574 (42%) cases, was used to optimize classification. Subtype frequency was calculated, and associations between subtype and tumor characteristics were estimated using logistic regression. RESULTS: Relative to ER, PR and HER2 from medical records, central IHC staining and the addition of Ki67 or combined tumor grade improved accuracy for classifying PAM50-based luminal subtypes. Few triple negative cases (< 2%) lacked EGFR and CK5/6 expression, thereby providing little improvement in accuracy for identifying basal-like tumors. Relative to luminal A subtype, all other subtypes had higher combined grade and were larger, and ER-/HER2+ tumors were more often lymph node positive and late stage tumors. The frequency of basal-like tumors was 31%, exceeded only slightly by luminal A tumors (37%). CONCLUSIONS: Our findings indicate that automated IHC-based classification produces tumor subtype frequencies approximating those from PAM50-based classification and highlight high frequency of basal-like and low frequency of luminal A breast cancer in a large study of African American women. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13058-018-0939-5) contains supplementary material, which is available to authorized users. BioMed Central 2018-02-06 2018 /pmc/articles/PMC5801839/ /pubmed/29409530 http://dx.doi.org/10.1186/s13058-018-0939-5 Text en © The Author(s). 2018 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 Research Article
Allott, Emma H.
Geradts, Joseph
Cohen, Stephanie M.
Khoury, Thaer
Zirpoli, Gary R.
Bshara, Wiam
Davis, Warren
Omilian, Angela
Nair, Priya
Ondracek, Rochelle P.
Cheng, Ting-Yuan David
Miller, C. Ryan
Hwang, Helena
Thorne, Leigh B.
O’Connor, Siobhan
Bethea, Traci N.
Bell, Mary E.
Hu, Zhiyuan
Li, Yan
Kirk, Erin L.
Sun, Xuezheng
Ruiz-Narvaez, Edward A.
Perou, Charles M.
Palmer, Julie R.
Olshan, Andrew F.
Ambrosone, Christine B.
Troester, Melissa A.
Frequency of breast cancer subtypes among African American women in the AMBER consortium
title Frequency of breast cancer subtypes among African American women in the AMBER consortium
title_full Frequency of breast cancer subtypes among African American women in the AMBER consortium
title_fullStr Frequency of breast cancer subtypes among African American women in the AMBER consortium
title_full_unstemmed Frequency of breast cancer subtypes among African American women in the AMBER consortium
title_short Frequency of breast cancer subtypes among African American women in the AMBER consortium
title_sort frequency of breast cancer subtypes among african american women in the amber consortium
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5801839/
https://www.ncbi.nlm.nih.gov/pubmed/29409530
http://dx.doi.org/10.1186/s13058-018-0939-5
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