Abstract

BackgroundGene expression studies have identified molecular subtypes of breast cancer with implications to chemotherapy recommendations. For distinction of these types, a combination of immunohistochemistry (IHC) markers, including proliferative activity of tumor cells, estimated by Ki67 labeling index is used. Clinical studies are frequently based on IHC performed on tissue microarrays (TMA) with variable tissue sampling. This raises the need for evidence-based sampling criteria for individual IHC biomarker studies. We present a novel tissue sampling simulation model and demonstrate its application on Ki67 assessment in breast cancer tissue taking intratumoral heterogeneity into account.MethodsWhole slide images (WSI) of 297 breast cancer sections, immunohistochemically stained for Ki67, were subjected to digital image analysis (DIA). Percentage of tumor cells stained for Ki67 was computed for hexagonal tiles super-imposed on the WSI. From this, intratumoral Ki67 heterogeneity indicators (Haralick’s entropy values) were extracted and used to dichotomize the tumors into homogeneous and heterogeneous subsets. Simulations with random selection of hexagons, equivalent to 0.75 mm circular diameter TMA cores, were performed. The tissue sampling requirements were investigated in relation to tumor heterogeneity using linear regression and extended error analysis.ResultsThe sampling requirements were dependent on the heterogeneity of the biomarker expression. To achieve a coefficient error of 10 %, 5–6 cores were needed for homogeneous cases, 11–12 cores for heterogeneous cases; in mixed tumor population 8 TMA cores were required. Similarly, to achieve the same accuracy, approximately 4,000 nuclei must be counted when the intratumor heterogeneity is mixed/unknown. Tumors of low proliferative activity would require larger sampling (10–12 TMA cores, or 6,250 nuclei) to achieve the same error measurement results as for highly proliferative tumors.ConclusionsOur data show that optimal tissue sampling for IHC biomarker evaluation is dependent on the heterogeneity of the tissue under study and needs to be determined on a per use basis. We propose a method that can be applied to determine the sampling strategy for specific biomarkers, tissues and study targets. In addition, our findings highlight the benefit of high-capacity computer-based IHC measurement techniques to improve accuracy of the testing.Electronic supplementary materialThe online version of this article (doi:10.1186/s13000-016-0525-z) contains supplementary material, which is available to authorized users.

Highlights

  • Gene expression studies have identified molecular subtypes of breast cancer with implications to chemotherapy recommendations

  • We investigate if a similar relationship exists between relative error measurements CEArea and CENuclei as function of the Ki67 proliferation activity indicator by fitting coefficient of error (CE) as function of Ki67 to CE 1⁄4 a x−b: This is done for each choice of set of hexagonal cores (HexN), for a set of bins used for dichotomizing by nuclei count and for all three classes of heterogeneity

  • The global average of Ki67 labeling index (Ki67 LI) values estimated by digital image analysis (DIA) of the Whole slide images (WSI) was almost identical to the results obtained by hexagonal tiling (HexT)

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Summary

Introduction

Gene expression studies have identified molecular subtypes of breast cancer with implications to chemotherapy recommendations. For distinction of these types, a combination of immunohistochemistry (IHC) markers, including proliferative activity of tumor cells, estimated by Ki67 labeling index is used. Clinical studies are frequently based on IHC performed on tissue microarrays (TMA) with variable tissue sampling. This raises the need for evidence-based sampling criteria for individual IHC biomarker studies. Gene expression studies have identified distinct molecular subtypes of breast cancer (Luminal A, Luminal B, HER2-enriched, basal-like and normal breast-like) with markedly different behavior and prognosis [1]. Great effort has been made to standardize the techniques for manual and digital/automated Ki67 LI measurement, including criteria for tissue sampling, hotspot detection, and digital image analysis (DIA) tools [4,5,6,7,8,9,10,11]

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