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Quantitative Justification of the Change From 10% to 30% for Human Epidermal Growth Factor Receptor 2 Scoring in the American Society of Clinical Oncology/College of American Pathologists Guidelines: Tumor Heterogeneity in Breast Cancer and Its Implications for Tissue Microarray–Based Assessment of Outcome

Christopher B. Moeder, Jennifer M. Giltnane, Malini Harigopal, Annette Molinaro, Andrew Robinson, Karen Gelmon, David Huntsman, Robert L. Camp, David L. Rimm

From the Departments of Pathology and Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT; Division of Medical Oncology, and Genetic Pathology Evaluation Centre, Department of Pathology, British Columbia Cancer Agency; Department of Pathology, Vancouver General Hospital; and Department of Pathology, University of British Columbia, Vancouver, British Columbia, Canada

Address reprint requests to David L. Rimm, MD, PhD, Department of Pathology, Yale University School of Medicine, 310 Cedar St, PO Box 208023, New Haven, CT 06520-8023; e-mail: david.rimm{at}yale.edu

Purpose The variability in scoring of immunohistochemistry, whether a result of true heterogeneity or artifacts in preparation, has led to decreased reliability in companion diagnostics and the recommendation for new standards (eg, the American Society of Clinical Oncology/College of American Pathologists [ASCO-CAP] guidelines). The basis of this problem is the amount of tissue required to be representative of an entire tumor. Because protein expression on tissue microarrays (TMAs) can be rigorously measured and one 0.6-mm spot is equivalent to two to three high-power fields, we used TMAs to assess levels of heterogeneity and to determine optimal representation as a function of outcome.

Patients and Methods We analyzed estrogen receptor (ER), progesterone receptor, and human epidermal growth factor receptor 2 (HER-2) expression in two cohorts (n = 676 and n = 152) on a series of four to five separate TMA cores and assessed heterogeneity by linear regression analysis. Minimum, average, and maximum scores were generated for each set, which were then assessed for prognostic and predictive value.

Results Each marker shows some heterogeneity, but average r values between 0.7 and 0.8 are seen between TMA spots. Analysis for prognostic value shows that the highest maximum score (of five spots) is the most prognostic for ER, whereas a high HER-2 minimum score is most prognostic for poor outcome and most predictive of response to trastuzumab.

Conclusion These results suggest that the representivity required for each biomarker may be a function of its role in tumorigenesis. Furthermore, these results provide scientific basis for the ASCO-CAP guidelines for assessment of HER-2 expression but perhaps suggest that the 30% figure is still too conservative.

Supported by the an Avon-National Cancer Institute (NCI) Progress for Patients grant, NCI Grants No. R33 CA 106709 and R33 CA 110511 (D.L.R.) and K22 KCA123146A (A.M.), and a Medical Scientist Training Program grant (J.M.G.).

Terms in blue are defined in the glossary, found at the end of this article and online at www.jco.org.

C.B.M. and J.M.G. both contributed equally to this work.

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.

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