Performance of three-biomarker immunohistochemistry for intrinsic breast cancer subtyping in the AMBER consortium

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. AmbrosoneAndrew F. Olshan, Melissa A. Troester

Research output: Contribution to journalArticle

26 Citations (Scopus)

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 IHCstained 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 RNAbased 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 nonbasallike, 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. Cancer Epidemiol Biomarkers Prev; 25(3); 470-8.

Original languageEnglish (US)
Pages (from-to)470-478
Number of pages9
JournalCancer Epidemiology Biomarkers and Prevention
Volume25
Issue number3
DOIs
StatePublished - Mar 1 2016

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Epidemiology
Biomarkers
Immunohistochemistry
Breast Neoplasms
Progesterone Receptors
Estrogen Receptors
RNA
Neoplasms
Tumor Biomarkers
African Americans
Epidemiologic Studies
Research Design
Hormones

ASJC Scopus subject areas

  • Epidemiology
  • Oncology

Cite this

Performance of three-biomarker immunohistochemistry for intrinsic breast cancer subtyping in the AMBER consortium. / Allott, Emma H.; Cohen, Stephanie M.; Geradts, Joseph; Sun, Xuezheng; Khoury, Thaer; Bshara, Wiam; Zirpoli, Gary R.; Miller, C. Ryan; Hwang, Helena; Thorne, Leigh B.; O'Connor, Siobhan; Tse, Chiu Kit; Bell, Mary B.; Hu, Zhiyuan; Li, Yan; Kirk, Erin L.; Bethea, Traci N.; Perou, Charles M.; Palmer, Julie R.; Ambrosone, Christine B.; Olshan, Andrew F.; Troester, Melissa A.

In: Cancer Epidemiology Biomarkers and Prevention, Vol. 25, No. 3, 01.03.2016, p. 470-478.

Research output: Contribution to journalArticle

Allott, EH, Cohen, SM, Geradts, J, Sun, X, Khoury, T, Bshara, W, Zirpoli, GR, Miller, CR, Hwang, H, Thorne, LB, O'Connor, S, Tse, CK, Bell, MB, Hu, Z, Li, Y, Kirk, EL, Bethea, TN, Perou, CM, Palmer, JR, Ambrosone, CB, Olshan, AF & Troester, MA 2016, 'Performance of three-biomarker immunohistochemistry for intrinsic breast cancer subtyping in the AMBER consortium', Cancer Epidemiology Biomarkers and Prevention, vol. 25, no. 3, pp. 470-478. https://doi.org/10.1158/1055-9965.EPI-15-0874
Allott, Emma H. ; Cohen, Stephanie M. ; Geradts, Joseph ; Sun, Xuezheng ; Khoury, Thaer ; Bshara, Wiam ; Zirpoli, Gary R. ; Miller, C. Ryan ; Hwang, Helena ; Thorne, Leigh B. ; O'Connor, Siobhan ; Tse, Chiu Kit ; Bell, Mary B. ; Hu, Zhiyuan ; Li, Yan ; Kirk, Erin L. ; Bethea, Traci N. ; Perou, Charles M. ; Palmer, Julie R. ; Ambrosone, Christine B. ; Olshan, Andrew F. ; Troester, Melissa A. / Performance of three-biomarker immunohistochemistry for intrinsic breast cancer subtyping in the AMBER consortium. In: Cancer Epidemiology Biomarkers and Prevention. 2016 ; Vol. 25, No. 3. pp. 470-478.
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title = "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 IHCstained 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 RNAbased 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 nonbasallike, 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. Cancer Epidemiol Biomarkers Prev; 25(3); 470-8.",
author = "Allott, {Emma H.} and Cohen, {Stephanie M.} and Joseph Geradts and Xuezheng Sun and Thaer Khoury and Wiam Bshara and Zirpoli, {Gary R.} and Miller, {C. Ryan} and Helena Hwang and Thorne, {Leigh B.} and Siobhan O'Connor and Tse, {Chiu Kit} and Bell, {Mary B.} and Zhiyuan Hu and Yan Li and Kirk, {Erin L.} and Bethea, {Traci N.} and Perou, {Charles M.} and Palmer, {Julie R.} and Ambrosone, {Christine B.} and Olshan, {Andrew F.} and Troester, {Melissa A.}",
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T1 - Performance of three-biomarker immunohistochemistry for intrinsic breast cancer subtyping in the AMBER consortium

AU - Allott, Emma H.

AU - Cohen, Stephanie M.

AU - Geradts, Joseph

AU - Sun, Xuezheng

AU - Khoury, Thaer

AU - Bshara, Wiam

AU - Zirpoli, Gary R.

AU - Miller, C. Ryan

AU - Hwang, Helena

AU - Thorne, Leigh B.

AU - O'Connor, Siobhan

AU - Tse, Chiu Kit

AU - Bell, Mary B.

AU - Hu, Zhiyuan

AU - Li, Yan

AU - Kirk, Erin L.

AU - Bethea, Traci N.

AU - Perou, Charles M.

AU - Palmer, Julie R.

AU - Ambrosone, Christine B.

AU - Olshan, Andrew F.

AU - Troester, Melissa A.

PY - 2016/3/1

Y1 - 2016/3/1

N2 - 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 IHCstained 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 RNAbased 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 nonbasallike, 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. Cancer Epidemiol Biomarkers Prev; 25(3); 470-8.

AB - 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 IHCstained 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 RNAbased 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 nonbasallike, 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. Cancer Epidemiol Biomarkers Prev; 25(3); 470-8.

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