title: Intratumoral heterogeneity as a source of discordance in breast cancer biomarker classification.
abstract: 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.
  
  
  
  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.
  
  
  
  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).
  
  
  
  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.
authors.affiliation: Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.|Department of Epidemiology, University of North Carolina at Chapel Hill, 135 Dauer Drive, CB 7435, Chapel Hill, NC, 27599, USA.
authors.forename: Emma H
authors.initials: EH
authors.lastname: Allott
authors.affiliation: Department of Pathology, Brigham & Women's Hospital, Boston, MA, USA.
authors.forename: Joseph
authors.initials: J
authors.lastname: Geradts
authors.affiliation: Department of Epidemiology, University of North Carolina at Chapel Hill, 135 Dauer Drive, CB 7435, Chapel Hill, NC, 27599, USA.
authors.forename: Xuezheng
authors.initials: X
authors.lastname: Sun
authors.affiliation: Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
authors.forename: Stephanie M
authors.initials: SM
authors.lastname: Cohen
authors.affiliation: Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, NY, USA.
authors.forename: Gary R
authors.initials: GR
authors.lastname: Zirpoli
authors.affiliation: Department of Pathology, Roswell Park Cancer Institute, Buffalo, NY, USA.
authors.forename: Thaer
authors.initials: T
authors.lastname: Khoury
authors.affiliation: Department of Pathology, Roswell Park Cancer Institute, Buffalo, NY, USA.
authors.forename: Wiam
authors.initials: W
authors.lastname: Bshara
authors.affiliation: Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.|Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
authors.forename: Mengjie
authors.initials: M
authors.lastname: Chen
authors.affiliation: Division of Cancer Prevention, National Cancer Institute, Bethesda, MD, USA.
authors.forename: Mark E
authors.initials: ME
authors.lastname: Sherman
authors.affiliation: Slone Epidemiology Center, Boston University, Boston, MA, USA.
authors.forename: Julie R
authors.initials: JR
authors.lastname: Palmer
authors.affiliation: Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, NY, USA.
authors.forename: Christine B
authors.initials: CB
authors.lastname: Ambrosone
authors.affiliation: Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.|Department of Epidemiology, University of North Carolina at Chapel Hill, 135 Dauer Drive, CB 7435, Chapel Hill, NC, 27599, USA.
authors.forename: Andrew F
authors.initials: AF
authors.lastname: Olshan
authors.affiliation: Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. troester@unc.edu.|Department of Epidemiology, University of North Carolina at Chapel Hill, 135 Dauer Drive, CB 7435, Chapel Hill, NC, 27599, USA. troester@unc.edu.
authors.forename: Melissa A
authors.initials: MA
authors.lastname: Troester
mesh_terms: D014408:Biomarkers, Tumor; D001706:Biopsy; D001943:Breast Neoplasms / Q000175:diagnosis / Q000378:metabolism* / Q000473:pathology*; D005260:Female; D006801:Humans; D007150:Immunohistochemistry; D011379:Prognosis; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000235:genetics / Q000378:metabolism; D011960:Receptors, Estrogen / Q000235:genetics / Q000378:metabolism; D011980:Receptors, Progesterone / Q000235:genetics / Q000378:metabolism; D012680:Sensitivity and Specificity; D046888:Tissue Array Analysis / Q000379:methods
chemical_list: D014408:Biomarkers, Tumor; D018719:Erb-b2 Receptor Tyrosine Kinases; D011960:Receptors, Estrogen; D011980:Receptors, Progesterone
keywords: Automated algorithm; Digital pathology; Discordance; Estrogen receptor; HER2; Immunohistochemistry; Intratumoral heterogeneity; Progesterone receptor; Tissue microarray