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Open Access 01-12-2016 | Research article

Intratumoral heterogeneity as a source of discordance in breast cancer biomarker classification

Authors: Emma H. Allott, Joseph Geradts, Xuezheng Sun, Stephanie M. Cohen, Gary R. Zirpoli, Thaer Khoury, Wiam Bshara, Mengjie Chen, Mark E. Sherman, Julie R. Palmer, Christine B. Ambrosone, Andrew F. Olshan, Melissa A. Troester

Published in: Breast Cancer Research | Issue 1/2016

Abstract

Background

Spatial heterogeneity in biomarker expression may impact breast cancer classification. The aims of this study were to estimate the frequency of spatial heterogeneity in biomarker expression within tumors, to identify technical and biological factors contributing to spatial heterogeneity, and to examine the impact of discordant biomarker status within tumors on clinical record agreement.

Methods

Tissue microarrays (TMAs) were constructed using two to four cores (1.0 mm) for each of 1085 invasive breast cancers from the Carolina Breast Cancer Study, which is part of the AMBER Consortium. Immunohistochemical staining for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) was quantified using automated digital imaging analysis. The biomarker status for each core and for each case was assigned using clinical thresholds. Cases with core-to-core biomarker discordance were manually reviewed to distinguish intratumoral biomarker heterogeneity from misclassification of biomarker status by the automated algorithm. The impact of core-to-core biomarker discordance on case-level agreement between TMAs and the clinical record was evaluated.

Results

On the basis of automated analysis, discordant biomarker status between TMA cores occurred in 9 %, 16 %, and 18 % of cases for ER, PR, and HER2, respectively. Misclassification of benign epithelium and/or ductal carcinoma in situ as invasive carcinoma by the automated algorithm was implicated in discordance among cores. However, manual review of discordant cases confirmed spatial heterogeneity as a source of discordant biomarker status between cores in 2 %, 7 %, and 8 % of cases for ER, PR, and HER2, respectively. Overall, agreement between TMA and clinical record was high for ER (94 %), PR (89 %), and HER2 (88 %), but it was reduced in cases with core-to-core discordance (agreement 70 % for ER, 61 % for PR, and 57 % for HER2).

Conclusions

Intratumoral biomarker heterogeneity may impact breast cancer classification accuracy, with implications for clinical management. Both manually confirmed biomarker heterogeneity and misclassification of biomarker status by automated image analysis contribute to discordant biomarker status between TMA cores. Given that manually confirmed heterogeneity is uncommon (<10 % of cases), large studies are needed to study the impact of heterogeneous biomarker expression on breast cancer classification and outcomes.

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Title: Intratumoral heterogeneity as a source of discordance in breast cancer biomarker classification
Authors: Emma H. Allott
Joseph Geradts
Xuezheng Sun
Stephanie M. Cohen
Gary R. Zirpoli
Thaer Khoury
Wiam Bshara
Mengjie Chen
Mark E. Sherman
Julie R. Palmer
Christine B. Ambrosone
Andrew F. Olshan
Melissa A. Troester
Publication date: 01-12-2016
Publisher: BioMed Central
Published in: Breast Cancer Research / Issue 1/2016
Electronic ISSN: 1465-542X
DOI: https://doi.org/10.1186/s13058-016-0725-1

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