Abstract 5543: Hetmap: Evaluating tumor heterogeneity in immunohistochemistry-stained breast cancer tissue

Abstract

Immunohistochemisty assays examining the HER2 receptor in breast cancer is the most widely adopted example of a companion diagnostic approach, which seeks to dictate therapeutic strategy based on a molecular description of a patient's disease. There are well-established guidelines for selecting patients for anti HER2 adjuvant therapies in breast cancer treatment, yet the current HER2 companion diagnostic approach is qualitative, does not sufficiently account for intratumor heterogeneity, and does not utilize any additional information about tumor cells that score beyond a specific threshold level. A major contributing factor for the failure of both treatment and diagnostic paradigm is thought to be intratumor heterogeneity. This lack of information in the scoring paradigm may contribute to inappropriate patient selection and explain why the disease in many trastuzumab treated patients progresses or becomes recurrent. Thus, a quantitative clinical measurement of heterogeneity in immunohistochemistry staining would be useful in better predicting patient therapeutic response. To answer this, we created a heterogeneity scoring approach (HetMap) that allows the visualization of an individual patient's IHC heterogeneity in the context of a cell population. We combined HER2 semi-quantitative analysis with the use of ecology diversity statistics to evaluate cell-level heterogeneity (consistency of protein expression within neighboring cells in a tumor nest) and tumor-level heterogeneity (differences of protein expression across a tumor as represented by a tissue section). We evaluated the approach on HER2 immunohistochemistry stained breast cancer samples, using 200 specimens across two different CLIA laboratories, with three pathologists at each laboratory each outlining regions of tumor for scoring by automatic cell-based image analysis. HetMap was evaluated using three different scoring schemes: HER2 scoring according to ASCO/CAP guidelines, H-Score and a new continuous HER2 score (HER2cont). Cell-level heterogeneity, reported either as an average or the maximum area of heterogeneity across a slide, had low levels of dependency on the pathologist choice of region. Tumor-level heterogeneity measurements had more dependence on the pathologist choice of regions. Significantly, discordant pathologist assessments of IHC scores in the +2, or equivocal score, range occurred most in tumors with high heterogeneity, leading to potentially major clinical impact. Thus, HetMap is a measure of heterogeneity, by which pathologists, oncologists, and drug development organizations can view cell-level and tumor-level heterogeneity for a patient for a given marker in the context of an entire patient cohort. Including such measures of heterogeneity in diagnostic approaches can help establish better thresholds for patient selection, thereby improving patient response. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 5543. doi:1538-7445.AM2012-5543