Interlaboratory variability of Ki67 staining in breast cancer

Luminal A versus luminal B breast cancer: MammaTyper mRNA versus immunohistochemical subtyping with an emphasis on standardised Ki67 labelling-based or mitotic activity index-based proliferation assessment

AIMS

Proliferation assessment by the use of Ki67 is a crucial component in intrinsic subtyping of luminal breast cancers (BCs), but suffers from variability between laboratories, observers, and methods. MammaTyper is a quantitative molecular tool that measures mRNA levels of ERBB2, ESR1, PGR and MKI67 in BC, and interprets the results according to the St Gallen 2013 consensus recommendations. We compared MammaTyper with immunohistochemistry (IHC)-based subtypes, with a focus on standardised proliferation assessment.

METHODS AND RESULTS

We analysed the agreement in assigning subtypes between MammaTyper and receptor IHC in 101 unifocal luminal HER2-negative early BCs of no special type. Two Ki67 counting protocols, Ki67-Global (Ki67-G) and Ki67-HotSpot (Ki67-H), recommended by the International Ki67 in BC Working Group, and the mitotic activity index (MAI) were used for proliferation assessment. The proportions of BCs identified as luminal A and as luminal B were 55% and 45% for MammaTyper, 55% and 45% for IHC + Ki67-G, 36% and 64% for IHC + Ki67-H, and 56% and 44% for IHC + MAI. The levels of agreement between MammaTyper-based and IHC-based subtyping were 84% (κ = 0.679) for IHC + Ki67-G, 72% (κ = 0.462) for IHC + Ki67-H, and 89% (κ = 0.779) for IHC + MAI.

CONCLUSIONS

High rates of agreement between mRNA-based and IHC-based intrinsic subtyping of luminal HER2-negative BC can be achieved. However, the agreement between IHC-based and MammaTyper-based luminal subtypes depends on the proliferation assessment method, and was highest when the MAI was used. Further comparative clinical studies are needed to determine which method is to be preferred, including analysis of cost-effectiveness.

The prognostic and predictive potential of Ki-67 in triple-negative breast cancer

As a cell proliferation biomarker, Ki-67 is principally used in ER+/HER2− breast cancer. However, the importance and the best cutoff point of Ki-67 in triple-negative breast cancer (TNBC) remains unclear and was evaluated in this study.A total of 1800 patients with early invasive TNBC between 2011 and 2016 at Fudan University Shanghai Cancer Center were consecutively recruited for this study. The optimal cutoff for Ki-67 was assessed by Cutoff Finder. Propensity score matching (PSM, ratio = 1:2) was performed to match the Ki-67^low group with the Ki-67^high group. Overall survival (OS) and disease-free survival (DFS) were compared between the two groups using the Kaplan-Meier method and Cox regression model. The most relevant cutoff value for Ki-67 for prognosis was 30% (p = 0.008). At the cutoff point of 30%, worse DFS and OS were observed in the Ki-67^high group. In multivariate analyses, N-stage (p < 0.001), T-stage (p = 0.038), and Ki-67 at the 30% threshold (p = 0.020) were independently linked to OS. In subgroup analysis, Ki-67 cutoff at 30% had prognostic and predictive potential for DFS with either tumor size ≤2 cm (p = 0.008) or lymph node-negative (N−) (p = 0.038) and especially with T₁N₀M₀ (stage I) TNBCs. For 945 N− TNBC patients, adjuvant chemotherapy (CT) was associated with better OS in the Ki-67^high group (p = 0.017) than in the Ki-67^low group (p = 0.875). For stage I/Ki-67^low patients, adjuvant CT did not affect DFS (p = 0.248). Thus, Ki-67 cutoff at 30% had early independent prognostic and predictive potential for OS and DFS in TNBCs, and Ki-67 > 30% was significantly associated with worse prognosis, especially for stage I patients. For stage I/Ki-67^low TNBC patients, the advantage of CT is unclear, providing the basis for future de-escalation therapy.

Good staining quality ensuring the reproducibility of Ki67 assessment

AIMS

Although Ki67 labelling index (LI) is a prognostic and predictive marker in breast cancer, its accuracy and reproducibility must be validated before its clinical application. We aimed to evaluate the agreement of Ki67 LI in clinical practice in Taiwan.

METHODS

We conducted a Ki67 immunohistochemistry (IHC) proficiency test. The participants performed the Ki67 IHC test and measured the Ki67 LI of 10 cases of breast cancer tissue on a microarray slide. The staining quality was centrally reviewed based on the Ki67 staining of the tonsil surface epithelium.

RESULTS

Ki67 staining and counting methods are diverse in Taiwan. The reproducibility of Ki67 LI was poor to good (intraclass correlation coefficient: 0.581, 95% CI 0.354 to 0.802). The reproducibility and agreement in the high staining quality group were significantly higher than those in the low staining quality group. The majority of the Ki67 LIs derived from the low staining quality group were underestimated. Different counting methods did not reveal significant differences when determining Ki67 LI with microarray sections.

CONCLUSIONS

We suggest using the surface epithelium of the tonsil as external control and achieving optimal staining results that consist of a high positive parabasal layer, a low positive intermediate layer and a negative superficial layer. Good Ki67 staining quality can minimise the staining variations among different laboratories, and it is essential for the reproducibility of Ki67 LI.

Agreement between molecular subtyping and surrogate subtype classification: a contemporary population-based study of ER-positive/HER2-negative primary breast cancer

PURPOSE

Oestrogen receptor-positive (ER+) and human epidermal receptor 2-negative (HER2-) breast cancers are classified as Luminal A or B based on gene expression, but immunohistochemical markers are used for surrogate subtyping. The aims of this study were to examine the agreement between molecular subtyping (MS) and surrogate subtyping and to identify subgroups consisting mainly of Luminal A or B tumours.

METHODS

The cohort consisted of 2063 patients diagnosed between 2013-2017, with primary ER+/HER2- breast cancer, analysed by RNA sequencing. Surrogate subtyping was performed according to three algorithms (St. Gallen 2013, Maisonneuve and our proposed Grade-based classification). Agreement (%) and kappa statistics (κ) were used as concordance measures and ROC analysis for luminal distinction. Ki67, progesterone receptor (PR) and histological grade (HG) were further investigated as surrogate markers.

RESULTS

The agreement rates between the MS and St. Gallen 2013, Maisonneuve and Grade-based classifications were 62% (κ = 0.30), 66% (κ = 0.35) and 70% (κ = 0.41), respectively. PR did not contribute to distinguishing Luminal A from B tumours (auROC = 0.56). By classifying HG1-2 tumours as Luminal A-like and HG3 as Luminal B-like, agreement with MS was 80% (κ = 0.46). Moreover, by combining HG and Ki67 status, a large subgroup of patients (51% of the cohort) having > 90% Luminal A tumours could be identified.

CONCLUSIONS

Agreement between MS and surrogate classifications was generally poor. However, a post hoc analysis showed that a combination of HG and Ki67 could identify patients very likely to have Luminal A tumours according to MS.

Clinical Validation of BCT Scores With Prognostic Factors in Hormone Receptor-positive, HER2-negative Early Breast Cancer

BACKGROUND/AIM

Multigene profiling assays provide strong evidence for predicting the prognosis of breast cancer. In this study, we aimed to evaluate the clinical validation of the BCT score with various prognostic factors.

MATERIALS AND METHODS

A total of 133 cases of hormone receptor-positive, cT1N0 breast cancers were analyzed. Risk stratification using the BCT score (Low, n=105; High, n=28) was analyzed with Ki67 index, p53 mutation, Immunohistochemistry 4 (IHC4) score, Nottingham Prognostic Index (NPI) and online PREDICT.

RESULTS

Ki67 index and NPI showed strong correlations with risk stratification based on BCT scores. Although the IHC4 score and online PREDICT were not associated with BCT score, there was a significant tendency of association with the online PREDICT results as the time of overall survival was increasing.

CONCLUSION

Risk classification based on BCT scores might have a clinical significance as a prognostic marker in hormone receptor-positive, HER2-negative, early breast cancer.

Ki-67 assessment in early breast cancer: SAKK28/12 validation study on the IBCSG VIII and IBCSG IX cohort

The assessment of Ki-67 in early-stage breast cancer has become an important diagnostic tool in planning adjuvant therapy, particularly for the administration of additional chemotherapy to hormone-responsive patients. An accurate determination of the Ki-67 index is of the utmost importance; however, the reproducibility is currently unsatisfactory. In this study, we addressed the predictive/prognostic value of Ki-67 index assessed by using the most reproducible methods, which were identified in the pilot phase. Paraffin blocks obtained from patients with moderately differentiated, estrogen receptor (ER)-positive early-stage breast cancer in Switzerland, who were originally randomized to the treatment arms with and without chemotherapy in the IBCSG VIII-IX trials, were retrieved. Of these 344 randomized patients, we identified 158 patients (82 treated with and 76 treated without chemotherapy) for whom sufficient tumour tissue was available. The presence of Ki-67 was assessed visually by counting 2000 cells at the periphery (A) and estimating the number of positive cells in five different peripheral regions (C), which was determined to be the most reproducible method identified the pilot phase. The prognostic and predictive value was assessed by calculating the breast cancer-free interval (BCFI) and overall survival (OS) rate. Ki-67 was considered a numerical and categorical variable when different cut-off values were used (10%, 14%, 20% and 30%). An mRNA-based subtyping by using the MammaTyper kit with the application of a 20% Ki-67 immunohistochemistry (IHC) cut-off equivalent was also performed. 158 of 344 randomized patients could be included in the Ki-67 analysis. The mean Ki-67 values obtained by using the two methods differed (A: 21.32% and C: 16.07%). Ki-67 assessed by using method A with a cut-off of 10% was a predictive marker for OS, as the hazard ratio (>10% vs. <=10%) in patients with chemotherapy was 0.48 with a 95% confidence interval of [0.19–1.19]. Further, the HR of patients treated without chemotherapy was 3.72 with a 95% confidence interval of [1.16–11.96] (p_interaction=0.007). Higher Ki-67 index was not associated with outcome and using the 10% Ki-67 cut-off there was an opposite association for patients with and without chemotherapy. Ki-67 assessments with IHC significantly correlated with MammaTyper results (p=0.002). The exact counting method (A) performed via a light-microscope revealed the predictive value of Ki-67 assessment with a 10% cut-off value. Further analyses employing image analyses and/or mRNA-based-assessments in larger populations are warranted.

Impact of molecular subtypes on the prediction of distant recurrence in estrogen receptor (ER) positive, human epidermal growth factor receptor 2 (HER2) negative breast cancer upon five years of endocrine therapy

Background

Current evidence suggests that patients with Luminal A early breast cancer can skip chemotherapy or extended endocrine therapy, but immunohistochemistry-based biomarker analysis for St Gallen subtyping may not be reproducible. We asked whether RT-qPCR can be used instead to address this clinical question.

Methods

RNA was extracted from tumor material derived from ER+/HER2- patients receiving adjuvant endocrine treatment for low-risk cancers and was semi-quantified by RT-qPCR with the MammaTyper®. St Gallen subtypes were based on the mRNA expression of ERBB2/HER2, ESR1/ER, PGR/PR and MKI67/Ki67 after dichotomizing at predefined cut-offs. Differences in distant disease-free survival (DDFS) were assessed by Kaplan Meier analysis and Cox regression.

Results

With a median follow up of 7.8 years, there were ten events in the group of 195 Luminal A-like tumors (5.1%) and 18 events in the remaining 127 tumors (14.1%), consisting mostly of Luminal B-like cases (N = 119). Luminal A-like had significantly better DDFS over the entire follow-up period (HR 0.35, 95% CIs 0.16–0.76, p = 0.0078) with a trend towards reduced probability of recurrences also in the late phase (> 5 years) (HR 0.20, p = 0.052). The survival advantage spanning the entire follow-up period persisted in the pN0 or pN0-N1 subgroups or after correcting for clinicopathological parameters. MKI67 alone significantly predicted for worse DDFS (HR 2.62, 95% CIs 1.24–5.56, p = 0.0088).

Conclusions

St Gallen Luminal A-like tumors identified by RT-qPCR display markedly low rates of distant recurrence at ten years follow-up. Patients with such tumors could be spared chemotherapy due to the obviously unfavourable benefit/toxicity ratio.

Analytical validation of a standardised scoring protocol for Ki67 immunohistochemistry on breast cancer excision whole sections: an international multicentre collaboration

AIMS

The nuclear proliferation marker Ki67 assayed by immunohistochemistry has multiple potential uses in breast cancer, but an unacceptable level of interlaboratory variability has hampered its clinical utility. The International Ki67 in Breast Cancer Working Group has undertaken a systematic programme to determine whether Ki67 measurement can be analytically validated and standardised among laboratories. This study addresses whether acceptable scoring reproducibility can be achieved on excision whole sections.

METHODS AND RESULTS

Adjacent sections from 30 primary ER⁺ breast cancers were centrally stained for Ki67 and sections were circulated among 23 pathologists in 12 countries. All pathologists scored Ki67 by two methods: (i) global: four fields of 100 tumour cells each were selected to reflect observed heterogeneity in nuclear staining; (ii) hot-spot: the field with highest apparent Ki67 index was selected and up to 500 cells scored. The intraclass correlation coefficient (ICC) for the global method [confidence interval (CI) = 0.87; 95% CI = 0.799-0.93] marginally met the prespecified success criterion (lower 95% CI ≥ 0.8), while the ICC for the hot-spot method (0.83; 95% CI = 0.74-0.90) did not. Visually, interobserver concordance in location of selected hot-spots varies between cases. The median times for scoring were 9 and 6 min for global and hot-spot methods, respectively.

CONCLUSIONS

The global scoring method demonstrates adequate reproducibility to warrant next steps towards evaluation for technical and clinical validity in appropriate cohorts of cases. The time taken for scoring by either method is practical using counting software we are making publicly available. Establishment of external quality assessment schemes is likely to improve the reproducibility between laboratories further.

Refinement of breast cancer molecular classification by miRNA expression profiles

Background

Accurate classification of breast cancer using gene expression profiles has contributed to a better understanding of the biological mechanisms behind the disease and has paved the way for better prognostication and treatment prediction.

Results

We found that miRNA profiles largely recapitulate intrinsic subtypes. In the case of HER2-enriched tumors a small set of miRNAs including the HER2-encoded mir-4728 identifies the group with very high specificity. We also identified differential expression of the miR-99a/let-7c/miR-125b miRNA cluster as a marker for separation of the Luminal A and B subtypes. High expression of this miRNA cluster is linked to better overall survival among patients with Luminal A tumors. Correlation between the miRNA cluster and their precursor LINC00478 is highly significant suggesting that its expression could help improve the accuracy of present day’s signatures.

Conclusions

We show here that miRNA expression can be translated into mRNA profiles and that the inclusion of miRNA information facilitates the molecular diagnosis of specific subtypes, in particular the clinically relevant sub-classification of luminal tumors.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5887-7) contains supplementary material, which is available to authorized users.

GTSE1 is involved in breast cancer progression in p53 mutation-dependent manner

Background

With the rapid development of the high throughput detection techniques, tumor-related Omics data has become an important source for studying the mechanism of tumor progression including breast cancer, one of the major malignancies worldwide. A previous study has shown that the G2 and S phase-expressed-1 (GTSE1) can act as an oncogene in several human cancers. However, its functional roles in breast cancer remain elusive.

Method

In this study, we analyzed breast cancer data downloaded from The Cancer Genome Atlas (TCGA) databases and other online database including the Oncomine, bc-GenExMiner and PROGgeneV2 database to identify the molecules contributing to the progression of breast cancer. The GTSE1 expression levels were investigated using qRT-PCR, immunoblotting and IHC. The biological function of GTSE1 in the growth, migration and invasion of breast cancer was examined in MDA-MB-231, MDA-MB-468 and MCF7 cell lines. The in vitro cell proliferative, migratory and invasive abilities were evaluated by MTS, colony formation and transwell assay, respectively. The role of GTSE1 in the growth and metastasis of breast cancer were revealed by in vivo investigation using BALB/c nude mice.

Results

We showed that the expression level of GTSE1 was upregulated in breast cancer specimens and cell lines, especially in triple negative breast cancer (TNBC) and p53 mutated breast cancer cell lines. Importantly, high GTSE1 expression was positively correlated with histological grade and poor survival. We demonstrated that GTSE1 could promote breast cancer cell growth by activating the AKT pathway and enhance metastasis by regulating the Epithelial-Mesenchymal transition (EMT) pathway. Furthermore, it could cause multidrug resistance in breast cancer cells. Interestingly, we found that GTSE1 could regulate the p53 function to alter the cell cycle distribution dependent on the mutation state of p53.

Conclusion

Our results reveal that GTSE1 played a key role in the progression of breast cancer, indicating that GTSE1 could serve as a novel biomarker to aid in the assessment of the prognosis of breast cancer.

Electronic supplementary material

The online version of this article (10.1186/s13046-019-1157-4) contains supplementary material, which is available to authorized users.

Ki67 Quantitative Interpretation: Insights using Image Analysis

Background:

Proliferation markers, especially Ki67, are increasingly important in diagnosis and prognosis. The best method for calculating Ki67 is still the subject of debate.

Materials and Methods:

We evaluated an image analysis tool for quantitative interpretation of Ki67 in neuroendocrine tumors and compared it to manual counts. We expanded a primary digital pathology platform to include the Leica Biosystems image analysis nuclear algorithm. Slides were digitized using a Leica Aperio AT2 Scanner and accessed through the Cerner CoPath LIS interfaced with Aperio eSlideManager through Aperio ImageScope. Selected regions of interest (ROIs) were manually defined and annotated to include tumor cells only; they were then analyzed with the algorithm and by four pathologists counting on printed images. After validation, the algorithm was used to examine the impact of the size and number of areas selected as ROIs.

Results:

The algorithm provided reproducible results that were obtained within seconds, compared to up to 55 min of manual counting that varied between users. Benefits of image analysis identified by users included accuracy, time savings, and ease of viewing. Access to the algorithm allowed rapid comparisons of Ki67 counts in ROIs that varied in numbers of cells and selection of fields, the outputs demonstrated that the results vary around defined cutoffs that provide tumor grade depending on the number of cells and ROIs counted.

Conclusions:

Digital image analysis provides accurate and reproducible quantitative data faster than manual counts. However, access to this tool allows multiple analyses of a single sample to use variable numbers of cells and selection of variable ROIs that can alter the result in clinically significant ways. This study highlights the potential risk of hard cutoffs of continuous variables and indicates that standardization of number of cells and number of regions selected for analysis should be incorporated into guidelines for Ki67 calculations.

Precision immunoprofiling by image analysis and artificial intelligence

Clinical success of immunotherapy is driving the need for new prognostic and predictive assays to inform patient selection and stratification. This requirement can be met by a combination of computational pathology and artificial intelligence. Here, we critically assess computational approaches supporting the development of a standardized methodology in the assessment of immune-oncology biomarkers, such as PD-L1 and immune cell infiltrates. We examine immunoprofiling through spatial analysis of tumor-immune cell interactions and multiplexing technologies as a predictor of patient response to cancer treatment. Further, we discuss how integrated bioinformatics can enable the amalgamation of complex morphological phenotypes with the multiomics datasets that drive precision medicine. We provide an outline to machine learning (ML) and artificial intelligence tools and illustrate fields of application in immune-oncology, such as pattern-recognition in large and complex datasets and deep learning approaches for survival analysis. Synergies of surgical pathology and computational analyses are expected to improve patient stratification in immuno-oncology. We propose that future clinical demands will be best met by (1) dedicated research at the interface of pathology and bioinformatics, supported by professional societies, and (2) the integration of data sciences and digital image analysis in the professional education of pathologists.

Fluoro-Chromogenic Labelling for Detection of MCM2 to Assess Proliferation Activity in HER2-amplified Breast Carcinomas

Minichromosome Maintenance Protein 2 (MCM2) is critical in initiating DNA replication during the cell division process. As expressed intensively in all phases of the active cell cycle, MCM2 has been proposed as a novel biomarker to determine cellular proliferation. We aimed at clarifying the prevalence and clinical significance of MCM2 in HER2-amplified breast cancer subtype. MCM2 expression was studied in 142 primary HER2-amplified breast carcinomas by applying a novel fluoro-chromogenic immunohistochemistry and tailored digital image analysis to determine labelling index (MCM2-LI). The presence of MCM2 was detected with HRP-conjugated polymer and visualized with 3, 3'-diaminobenzidine tetrahydrochloride, in cytokeratin (CK)-positive and Cy2-IgG-labelled breast cancer cells of epithelial origin. Stained slides were digitized by scanning sequentially under bright field (for MCM2) and fluorescence (for CK) illumination. Multilayer JPEG2000 images were analyzed with ImmunoRatio 2.5 (accessory in SlideVantage 1.2 software) utilizing its bright field and fluorescence image-blending mode to display MCM2-CK dual-positive cells. MCM2-LI was retrospectively compared with histopathologic characteristics and patients' clinical outcome. MCM2 protein-expressing cells (median MCM2-LI, 63.5%) were more frequent than those of Ki67 (median Ki67 labelling index, 33%). Significant correlations were found between high MCM2-LI, high Ki67 labelling index, negative hormone receptor (ER, PR) statuses, high grade of malignancy, and high cyclin E expression. MCM2-LI was not shown to be predictive of disease recurrence during the median follow-up of 5.3 years but was shown to be useful to distinguish aggressive-type HER2-amplified breast carcinomas with high malignancy grade and hormone receptor negativity. The fluoro-chromogenic double-labelling immunohistochemistry accompanied with digital image analysis provides an accurate carcinoma-specific determination of MCM2-LI on a single tumor section.

Fit-for-Purpose Immunohistochemical Biomarkers

There are two aspects of immunohistochemistry (IHC) that are relevant to practicing pathologist: (1) understanding of IHC biomarker panels that are suitable for diagnostic, prognostic and predictive testing, and (2) understanding of IHC quality assurance (QA), which makes sure that the tests in these panels work as they should. The two aspects are closely linked together and call for collaborative approach between pathologists and IHC laboratory technologists as both need to be involved in developing and maintaining IHC biomarkers that are "fit-for-purpose". This article reviews the most current IHC QA concepts that are imminently material to practicing pathologists with emphasis on challenges that are specific to endocrine pathology.

An inter-observer Ki67 reproducibility study applying two different assessment methods: on behalf of the Danish Scientific Committee of Pathology, Danish breast cancer cooperative group (DBCG)

INTRODUCTION

In 2011, the St. Gallen Consensus Conference introduced the use of pathology to define the intrinsic breast cancer subtypes by application of immunohistochemical (IHC) surrogate markers ER, PR, HER2 and Ki67 with a specified Ki67 cutoff (>14%) for luminal B-like definition. Reports concerning impaired reproducibility of Ki67 estimation and threshold inconsistency led to the initiation of this quality assurance study (2013-2015). The aim of the study was to investigate inter-observer variation for Ki67 estimation in malignant breast tumors by two different quantification methods (assessment method and count method) including measure of agreement between methods.

MATERIAL AND METHODS

Fourteen experienced breast pathologists from 12 pathology departments evaluated 118 slides from a consecutive series of malignant breast tumors. The staining interpretation was performed according to both the Danish and Swedish guidelines. Reproducibility was quantified by intra-class correlation coefficient (ICC) and Lights Kappa with dichotomization of observations at the larger than (>) 20% threshold. The agreement between observations by the two quantification methods was evaluated by Bland-Altman plot.

RESULTS

For the fourteen raters the median ranged from 20% to 40% by the assessment method and from 22.5% to 36.5% by the count method. Light's Kappa was 0.664 for observation by the assessment method and 0.649 by the count method. The ICC was 0.82 (95% CI: 0.77-0.86) by the assessment method vs. 0.84 (95% CI: 0.80-0.87) by the count method.

CONCLUSION

Although the study in general showed a moderate to good inter-observer agreement according to both ICC and Lights Kappa, still major discrepancies were identified in especially the mid-range of observations. Consequently, for now Ki67 estimation is not implemented in the DBCG treatment algorithm.