Ki-67 Expression in Breast Cancer Tissue Microarrays: Assessing Tumor Heterogeneity, Concordance With Full Section, and Scoring Methods

Fit-for-Purpose Ki-67 Immunohistochemistry Assays for Breast Cancer

New therapies are being developed for breast cancer, and in this process, some "old" biomarkers are reutilized and given a new purpose. It is not always recognized that by changing a biomarker's intended use, a new biomarker assay is created. The Ki-67 biomarker is typically assessed by immunohistochemistry (IHC) to provide a proliferative index in breast cancer. Canadian laboratories assessed the analytical performance and diagnostic accuracy of their Ki-67 IHC laboratory-developed tests (LDTs) of relevance for the LDTs' clinical utility. Canadian clinical IHC laboratories enrolled in the Canadian Biomarker Quality Assurance Pilot Run for Ki-67 in breast cancer by invitation. The Dako Ki-67 IHC pharmDx assay was employed as a study reference assay. The Dako central laboratory was the reference laboratory. Participants received unstained slides of breast cancer tissue microarrays with 32 cases and performed their in-house Ki-67 assays. The results were assessed using QuPath, an open-source software application for bioimage analysis. Positive percent agreement (PPA, sensitivity) and negative percent agreement (NPA, specificity) were calculated against the Dako Ki-67 IHC pharmDx assay for 5%, 10%, 20%, and 30% cutoffs. Overall, PPA and NPA varied depending on the selected cutoff; participants were more successful with 5% and 10%, than with 20% and 30% cutoffs. Only 4 of 16 laboratories had robust IHC protocols with acceptable PPA for all cutoffs. The lowest PPA for the 5% cutoff was 85%, for 10% was 63%, for 20% was 14%, and for 30% was 13%. The lowest NPA for the 5% cutoff was 50%, for 10% was 33%, for 20% was 50%, and for 30% was 57%. Despite many years of international efforts to standardize IHC testing for Ki-67 in breast cancer, our results indicate that Canadian clinical LDTs have a wide analytical sensitivity range and poor agreement for 20% and 30% cutoffs. The poor agreement was not due to the readout but rather due to IHC protocol conditions. International Ki-67 in Breast Cancer Working Group (IKWG) recommendations related to Ki-67 IHC standardization cannot take full effect without reliable fit-for-purpose reference materials that are required for the initial assay calibration, assay performance monitoring, and proficiency testing.

Protein expression of the gp78 E3 ligase predicts poor breast cancer outcome based on race

Women of African ancestry suffer higher rates of breast cancer mortality compared with all other groups in the United States. Though the precise reasons for these disparities remain unclear, many recent studies have implicated a role for differences in tumor biology. Using an epitope-validated antibody against the endoplasmic reticulum-associated E3 ligase, gp78, we show that elevated levels of gp78 in patient breast cancer cells predict poor survival. Moreover, high levels of gp78 are associated with poor outcomes in both ER+ and ER- tumors, and breast cancers expressing elevated amounts of gp78 protein are enriched in gene expression pathways that influence cell cycle, metabolism, receptor-mediated signaling, and cell stress response pathways. In multivariate analysis adjusted for subtype and grade, gp78 protein is an independent predictor of poor outcomes in women of African ancestry. Furthermore, gene expression signatures, derived from patients stratified by gp78 protein expression, are strong predictors of recurrence and pathological complete response in retrospective clinical trial data and share many common features with gene sets previously identified to be overrepresented in breast cancers based on race. These findings implicate a prominent role for gp78 in tumor progression and offer insights into our understanding of racial differences in breast cancer outcomes.

Expression of estrogen and progesterone receptors, HER2 protein and Ki-67 proliferation index in breast carcinoma in both tumor tissue and tissue microarray

Breast cancer treatment is tailored to molecular subtypes, which are classified by cell type and by presence of estrogen and progesterone receptors, HER2 overexpression and Ki-67 proliferation index. In routine pathological practice, these markers are detected in tumor tissue using immunohistochemistry, which requires four immunohistochemical antibodies for each patient. We developed a new tissue microarray procedure using a punch device with a 6 mm core diameter. The presence of estrogen and progesterone receptors, HER2 expression and the Ki-67 proliferation index of tumor tissues of 50 breast carcinoma patients had been determined using the conventional approach. We created three tissue microarray blocks, each containing samples from 14 main tumor tissues. One tissue microarray block was created with samples taken from eight main tumor tissues. Sections were cut from the four blocks and subjected to immunohistochemical staining; the original samples and the microarrays then were compared. We found significant agreement between estrogen receptor, progesterone receptor and HER-2 expression as well as Ki-67 proliferation index status of the original tumor tissues and the tissue microarray. Our tissue microarray technique using a single 6 mm core is a reliable and cost-effective method for determining estrogen and progesterone receptors, HER-2 status and Ki-67 proliferation index levels in patients with early breast carcinoma.

Kaiso (ZBTB33) subcellular partitioning functionally links LC3A/B, the tumor microenvironment, and breast cancer survival

The use of digital pathology for the histomorphologic profiling of pathological specimens is expanding the precision and specificity of quantitative tissue analysis at an unprecedented scale; thus, enabling the discovery of new and functionally relevant histological features of both predictive and prognostic significance. In this study, we apply quantitative automated image processing and computational methods to profile the subcellular distribution of the multi-functional transcriptional regulator, Kaiso (ZBTB33), in the tumors of a large racially diverse breast cancer cohort from a designated health disparities region in the United States. Multiplex multivariate analysis of the association of Kaiso’s subcellular distribution with other breast cancer biomarkers reveals novel functional and predictive linkages between Kaiso and the autophagy-related proteins, LC3A/B, that are associated with features of the tumor immune microenvironment, survival, and race. These findings identify effective modalities of Kaiso biomarker assessment and uncover unanticipated insights into Kaiso’s role in breast cancer progression.

Through automated image analysis, Singhal et al quantify nuclear versus cytoplasmic distribution of the Kaiso transcription factor in breast cancer patient tissue. They find that Kaiso distribution correlates with breast cancer subtype and overall survival, and discover a link between cytoplasmic Kaiso and autophagy marker LC3.

Detection of Ki67 Hot-Spots of Invasive Breast Cancer Based on Convolutional Neural Networks Applied to Mutual Information of H&E and Ki67 Whole Slide Images

Ki67 hot-spot detection and its evaluation in invasive breast cancer regions play a significant role in routine medical practice. The quantification of cellular proliferation assessed by Ki67 immunohistochemistry is an established prognostic and predictive biomarker that determines the choice of therapeutic protocols. In this paper, we present three deep learning-based approaches to automatically detect and quantify Ki67 hot-spot areas by means of the Ki67 labeling index. To this end, a dataset composed of 100 whole slide images (WSIs) belonging to 50 breast cancer cases (Ki67 and H&E WSI pairs) was used. Three methods based on CNN classification were proposed and compared to create the tumor proliferation map. The best results were obtained by applying the CNN to the mutual information acquired from the color deconvolution of both the Ki67 marker and the H&E WSIs. The overall accuracy of this approach was 95%. The agreement between the automatic Ki67 scoring and the manual analysis is promising with a Spearman’s ρ correlation of 0.92. The results illustrate the suitability of this CNN-based approach for detecting hot-spots areas of invasive breast cancer in WSI.

Digital Image Analysis of Ki-67 Stained Tissue Microarrays and Recurrence in Tamoxifen-Treated Breast Cancer Patients

Purpose

The proliferation marker Ki-67 has been used as a prognostic marker to separate low- and high-risk breast cancer subtypes and guide treatment decisions for adjuvant chemotherapy. The association of Ki-67 with response to tamoxifen therapy is unclear. High-throughput automated scoring of Ki-67 might enable standardization of quantification and definition of clinical cut-off values. We hypothesized that digital image analysis (DIA) of Ki-67 can be used to evaluate proliferation in breast cancer tumors, and that Ki-67 may be associated with tamoxifen resistance in early-stage breast cancer.

Patients and Methods

Here, we apply DIA technology from Visiopharm using a custom designed algorithm for quantifying the expression of Ki-67, in a case–control study nested in the Danish Breast Cancer Group clinical database, consisting of stages I, II, or III breast cancer patients of 35–69 years of age, diagnosed during 1985–2001, in the Jutland peninsula, Denmark. We assessed DIA-Ki-67 score on tissue microarrays (TMAs) from breast cancer patients in a case–control study including 541 ER-positive and 300 ER-negative recurrent cases and their non-recurrent controls, matched on ER-status, cancer stage, menopausal status, year of diagnosis, and county of residence. We used logistic regression to estimate odds ratios and associated 95% confidence intervals to determine the association of Ki-67 expression with recurrence risk, adjusting for matching factors, chemotherapy, type of surgery, receipt of radiation therapy, age category, and comorbidity.

Results

Ki-67 was not associated with increased risk of recurrence in tamoxifen-treated patients (ORadj =0.72, 95% CI 0.54, 0.96) or ER-negative patients (ORadj =0.85, 95% CI 0.54, 1.34).

Conclusion

Our findings suggest that Ki-67 digital image analysis in TMAs is not associated with increased risk of recurrence among tamoxifen-treated ER-positive breast cancer or ER-negative breast cancer patients. Overall, our findings do not support an increased risk of recurrence associated with Ki-67 expression.

Racial Differences in the Association Between Luminal Master Regulator Gene Expression Levels and Breast Cancer Survival

PURPOSE

Compared with their European American (EA) counterparts, African American (AA) women are more likely to die from breast cancer in the United States. This disparity is greatest in hormone receptor-positive subtypes. Here we uncover biological factors underlying this disparity by comparing functional expression and prognostic significance of master transcriptional regulators of luminal differentiation.

EXPERIMENTAL DESIGN

Data and biospecimens from 262 AA and 293 EA patients diagnosed with breast cancer from 2001 to 2010 at a major medical center were analyzed by IHC for functional biomarkers of luminal differentiation, including estrogen receptor (ESR1) and its pioneer factors, FOXA1 and GATA3. Integrated comparison of protein levels with network-level gene expression analysis uncovered predictive correlations with race and survival.

RESULTS

Univariate or multivariate HRs for overall survival, estimated from digital IHC scoring of nuclear antigen, show distinct differences in the magnitude and significance of these biomarkers to predict survival based on race: ESR1 [EA HR = 0.47; 95% confidence interval (CI), 0.31-0.72 and AA HR = 0.77; 95% CI, 0.48-1.18]; FOXA1 (EA HR = 0.38; 95% CI, 0.23-0.63 and AA HR = 0.53; 95% CI, 0.31-0.88), and GATA3 (EA HR = 0.36; 95% CI, 0.23-0.56; AA HR = 0.57; CI, 0.56-1.4). In addition, we identify genes in the downstream regulons of these biomarkers highly correlated with race and survival.

CONCLUSIONS

Even within clinically homogeneous tumor groups, regulatory networks that drive mammary luminal differentiation reveal race-specific differences in their association with clinical outcome. Understanding these biomarkers and their downstream regulons will elucidate the intrinsic mechanisms that drive racial disparities in breast cancer survival.

Utility of synthetic MRI in predicting the Ki-67 status of oestrogen receptor-positive breast cancer: a feasibility study

AIM

To evaluate the utility of synthetic magnetic resonance imaging (MRI) of the breast in predicting the Ki-67 status in patients with oestrogen receptor (ER)-positive breast cancer.

MATERIALS AND METHODS

Forty-nine patients with 50 histopathologically proven breast cancers who underwent additional synthetic MRI were enrolled in the present study. Using synthetic MRI images, T1 and T2 relaxation times and their standard deviations (SD) in the breast lesions before (T1-Pre, T2-Pre, PD-Pre, SD of T1-Pre, SD of T2-Pre, SD of PD-Pre) and after (T1-Gd, T2-Gd, PD-Gd, SD of T1-Gd, SD of T2-Gd, SD of PD-Gd) contrast agent injection were obtained. These quantitative values were compared between the low Ki-67 expression (<14%) lesions (low-proliferation group: n=23) and high Ki-67 expression (≥14%) lesions (high-proliferation group: n=27).

RESULTS

The univariate analysis showed that the SD of T1-Gd (p<0.001) and T2-Gd (p=0.042) were significantly higher in the high-proliferation group than in the low-proliferation group. Multivariate analysis further showed that the SD of T1-Gd was a significant and independent predictor of Ki-67 expression, with an area under the receiver operating characteristic (AUROC) curve of 0.885. The sensitivity, specificity, and accuracy of the SD of T1-Gd with an optimal cut-off value of 98.5 were 77.8%, 87%, and 82%, respectively.

CONCLUSION

The SD of T1-Gd obtained from synthetic MRI was useful to predict Ki-67 status.

Breast cancer stromal clotting activation (Tissue Factor and thrombin): A pre-invasive phenomena that is prognostic in invasion

Background

Tumor stroma, of which fibroblasts are the most abundant cell, resembles a non‐healing wound, where a procoagulant environment creates a permissive milieu for cancer growth. We aimed to determine if tumor expression of coagulation factors (procoagulant phenotype), and systemic hypercoagulability, occur at the preinvasive (ductal carcinoma in situ; DCIS) stage and correlate with breast cancer subtype, disease‐free survival (DFS), and overall survival (OS).

Methods

In a prospective cohort of early breast cancer (DCIS, n = 76; invasive, n = 248) tumor, normal breast and plasma were examined. Fibroblast and epithelial expression of Tissue Factor (TF), thrombin, PAR1, PAR2, and plasma thrombin‐antithrombin (TAT) and D‐dimer were correlated with clinicopathological data, and 5‐year survival.

Results

Fibroblast expression of TF, thrombin, and PAR1 was increased in DCIS and invasive cancer compared to normal breast fibroblasts (P ≤ .003, all). Fibroblast TF, thrombin, PAR1, and PAR2 was increased in cancers with high Ki67, high grade, ER‐ (vs ER+), and HER2+ (vs HER2‐) (all P < .05). On univariate analysis, fibroblast TF expression was inversely associated with DFS (P = .04) and OS (P = .02). D‐dimer was higher in node positive (507 (CI: 411‐625) ng/mL, n = 68) vs negative patients (428 (CI: 387‐472) ng/mL, n = 171, P = .004) and inversely associated with OS (P = .047). On multivariate analysis, plasma TAT was associated with reduced OS (HR 3.26, CI 1.16‐3.1, P = .02), with a high plasma TAT (≥3.2 ng/mL) associated with > 3‐fold mortality risk compared to low TAT.

Conclusion

This demonstrates procoagulant phenotypic changes occur in fibroblasts at the preinvasive stage. Fibroblast procoagulant phenotype is associated with aggressive breast cancer subtypes and reduced survival. Coagulation may be a therapeutic target in breast cancer.

Storage Conditions and Immunoreactivity of Breast Cancer Subtyping Markers in Tissue Microarray Sections

Loss of immunoreactivity in tissue sections has been shown to occur when slide sections are stored at room temperature for prolonged periods of time. We conducted a systematic investigation to determine the extent of staining loss in various storage conditions to determine an optimal storage method. We investigated 6 antibodies that are commonly used for breast cancer subtyping in research studies with immunohistochemistry (ER, PR, HER2, CK5/6, EGFR, and Ki67) in formalin-fixed paraffin-embedded breast tissue microarrays consisting of 148 patients. Tissue microarrays were sectioned at various time points: fresh, 1 week, 1 month, 6 months, and 12 months before staining. Slides sectioned at each time point were stored in 5 storage conditions: desiccator, paraffin dipped, 4°C, -20°C, and -80°C. Immunohistochemistry scores were assessed over time with McNemar Test and Bowker Test of Symmetry. Desiccator storage was the only storage condition that did not show any loss in immunoreactivity for any antibody or time point in our study. Paraffin coated slides were the most difficult storage method operationally and also showed the most loss in immunoreactivity. Storing sections in a desiccator was the most effective method for minimizing immunoreactivity loss. Cold storage at 4°C is an intermediate option that is not as protective as a desiccator, but offers the advantage of being accessible to virtually all research labs.

Delay to Formalin Fixation (Cold Ischemia Time) Effect on Breast Cancer Molecules

OBJECTIVES

The gold standard of examining breast biomarkers, including estrogen receptor (ER)/progesterone receptor (PR)/human epidermal growth factor receptor 2 (HER2)/Ki-67, is to perform these assays on formalin-fixed, paraffin-embedded tissue. However, preanalytical variables may confound these assays. One of these factors is delay to formalin fixation (DFF). The purpose of this review is to evaluate each study that investigated the effect of DFF on breast biomarkers and other molecules.

METHODS

Thirteen primary research articles were identified by the literature search. The credibility of the studies was judged based on the degree of controlling other confounding factors. Nine studies had a prospective design with a high number of controlled variables.

RESULTS

Most of the studies concluded that DFF had an effect on ER/PR/HER2. Some of these studies showed that DFF had negative effect on other markers used either clinically or for research purposes.

CONCLUSIONS

The vast majority of the studies agree that DFF has negative effect on breast biomarkers.