Performance of Three-Biomarker Immunohistochemistry for Intrinsic Breast Cancer Subtyping in the AMBER Consortium.

Abstract

BACKGROUND:

Classification of breast cancer into intrinsic subtypes has clinical and epidemiologic importance. To examine accuracy of IHC-based methods for identifying intrinsic subtypes, a three-biomarker IHC panel was compared with the clinical record and RNA-based intrinsic (PAM50) subtypes.

METHODS:

Automated scoring of estrogen receptor (ER), progesterone receptor (PR), and HER2 was performed on IHC-stained tissue microarrays comprising 1,920 cases from the African American Breast Cancer Epidemiology and Risk (AMBER) consortium. Multiple cores (1-6/case) were collapsed to classify cases, and automated scoring was compared with the clinical record and to RNA-based subtyping.

RESULTS:

Automated analysis of the three-biomarker IHC panel produced high agreement with the clinical record (93% for ER and HER2, and 88% for PR). Cases with low tumor cellularity and smaller core size had reduced agreement with the clinical record. IHC-based definitions had high agreement with the clinical record regardless of hormone receptor positivity threshold (1% vs. 10%), but a 10% threshold produced highest agreement with RNA-based intrinsic subtypes. Using a 10% threshold, IHC-based definitions identified the basal-like intrinsic subtype with high sensitivity (86%), although sensitivity was lower for luminal A, luminal B, and HER2-enriched subtypes (76%, 40%, and 37%, respectively).

CONCLUSION:

Three-biomarker IHC-based subtyping has reasonable accuracy for distinguishing basal-like from nonbasal-like, although additional biomarkers are required for accurate classification of luminal A, luminal B, and HER2-enriched cancers.

IMPACT:

Epidemiologic studies relying on three-biomarker IHC status for subtype classification should use caution when distinguishing luminal A from luminal B and when interpreting findings for HER2-enriched cancers.

• Authors: Emma H Allott, Stephanie M Cohen, Joseph Geradts, Xuezheng Sun, Thaer Khoury, Wiam Bshara, Gary R Zirpoli, C Ryan Miller, Helena Hwang, Leigh B Thorne, Siobhan O'Connor, Chiu-Kit Tse, Mary B Bell, Zhiyuan Hu, Yan Li, Erin L Kirk, Traci N Bethea, Charles M Perou, Julie R Palmer, Christine B Ambrosone, Andrew F Olshan, Melissa A Troester
• Journal: Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology (Cancer Epidemiol Biomarkers Prev) Vol. 25 Issue 3 Pg. 470-8 (Mar 2016) ISSN: 1538-7755 [Electronic] United States
• PMID: 26711328 (Publication Type: Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't)
• Copyright: ©2015 American Association for Cancer Research.

Topics

• Breast Neoplasms (immunology, pathology)
• Female
• Humans
• Immunohistochemistry
• Tissue Array Analysis