Impact of tissue sampling on accuracy of Ki67 immunohistochemistry evaluation in breast cancer

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.

Intra-tumor heterogeneity in breast cancer has limited impact on transcriptomic-based molecular profiling

“…PR and Ki-67 expression tended to be more spatially heterogeneous compared to ER and HER2 (Additional file 1 : Figure S1). Similar findings have been reported by us and others before [ 34 – 36 ].

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“…Variations in ER, PR and HER2 expression in spatially separated tumor samples has been reported before and is sometimes associated with heterogeneity in morphology [ 35 , 38 , 39 ]. Proliferation markers such as Ki-67 are also subjected to substantial intra-tumor heterogeneity [ 36 ] with higher expression in certain hot-spots and in the tumor invasive margins [ 34 ]. Determining the tumor grade and molecular subtype by IHC surrogate classification are highly sensitive to the cut-off of the Ki-67 score and the region of the tumor investigated [ 40 , 41 ].…”

The use of automated Ki67 analysis to predict Oncotype DX risk-of-recurrence categories in early-stage breast cancer

“…In such tumors, the hot spots of higher-than-average proliferative indices are clinically meaningful [ 52 , 53 ]. Consequently, automated analysis of tissue microarrays, or of manually-selected tumor regions, incur the same potential for selection bias as do manual scoring approaches [ 20 , 54 ]. We addressed this problem by segmenting each slide image into tiles prior to analysis; since the entire image was subsequently analyzed, the hot spots emerged naturally as the tiles with the highest Ki67 scores.…”

Ki-67 Expression in Breast Cancer Tissue Microarrays

“…There were cases where the TMA core had a higher Ki-67 score than the FS, particularly with single 0.6-mm cores (Tables 1 and 2). Plancoulaine et al 23 and Besusparis et al 24 studied the impact of sampling on the accuracy of Ki-67 in BC. They included 297 BC cases (189 cases of luminal type) and performed TMA simulation using hexagonal tiling with the size of each hexagon 0.75 mm, equivalent to an approximately 1.0-mm core.…”