Systematically higher Ki67 scores on core biopsy samples compared to corresponding resection specimen in breast cancer: a multi-operator and multi-institutional study.

Ki67 has potential clinical importance in breast cancer but has yet to see broad acceptance due to inter-laboratory variability. Here we tested an open source and calibrated automated digital image analysis (DIA) platform to: (i) investigate the comparability of Ki67 measurement across corresponding core biopsy and resection specimen cases, and (ii) assess section to section differences in Ki67 scoring. Two sets of 60 previously stained slides containing 30 core-cut biopsy and 30 corresponding resection specimens from 30 estrogen receptor-positive breast cancer patients were sent to 17 participating labs for automated assessment of average Ki67 expression. The blocks were centrally cut and immunohistochemically (IHC) stained for Ki67 (MIB-1 antibody). The QuPath platform was used to evaluate tumoral Ki67 expression. Calibration of the DIA method was performed as in published studies. A guideline for building an automated Ki67 scoring algorithm was sent to participating labs. Very high correlation and no systematic error (p = 0.08) was found between consecutive Ki67 IHC sections. Ki67 scores were higher for core biopsy slides compared to paired whole sections from resections (p ≤ 0.001; median difference: 5.31%). The systematic discrepancy between core biopsy and corresponding whole sections was likely due to pre-analytical factors (tissue handling, fixation). Therefore, Ki67 IHC should be tested on core biopsy samples to best reflect the biological status of the tumor.

Predictive Biomarkers for Endocrine Therapy: Retrospective Study in Tamoxifen and Exemestane Adjuvant Multinational (TEAM) Trial.

Background: Aromatase inhibitors improve disease-free survival compared with tamoxifen in postmenopausal women with hormone receptor-positive breast cancer. The Tamoxifen and Exemestane Adjuvant Multinational (TEAM) trial compared exemestane monotherapy with sequential therapy of tamoxifen followed by exemestane. The trial failed to show a statistically significant difference between treatment arms. A robust translational program was established to investigate predictive biomarkers. Methods: A tissue microarray was retrospectively constructed using a subset of patient tissues (n = 4631) from the TEAM trial (n = 9766). Immunohistochemistry was performed for biomarkers, classed into three groups: MAPK pathway, NF-kappa B pathway, and estrogen receptor (ER) phosphorylation. Expression was analyzed for association with relapse-free survival (RFS) at 2.5 and 10 years and treatment regimen using Kaplan-Meier curves and log-rank analysis. All statistical tests were two-sided. Results: In univariate analysis, ER167 (hazard ratio [HR] = 0.71, 95% confidence interval [CI] = 0.59 to 0.85, P < .001), IKKα (HR = 0.74, 95% CI = 0.60 to 0.92, P = .005), Raf-1338 (HR = 0.64, 95% CI = 0.52 to 0.80, P < .001), and p44/42 MAPK202/204 (HR = 0.77, 95% CI = 0.64 to 0.92, P = .004) were statistically significantly associated with improved RFS at 10 years in patients receiving sequential therapy. Associations were strengthened when IKKα, Raf-1338, and ER167 were combined into a cumulative prognostic score (HR = 0.64, 95% CI = 0.52 to 0.77, P < .001). Patients with an all negative IKKα, Raf-1338, and ER167 score favored exemestane monotherapy (odds ratio = 0.56, 95% CI = 0.35 to 0.90). In multivariable analysis, the IKKα, Raf-1338, and ER167 score (P = .001) was an independent prognostic factor for RFS at 10 years in patients receiving sequential therapy. Conclusions: The IKKα, Raf-1338, and ER167 score is an independent predictive biomarker for lower recurrence on sequential therapy. Negative expression may further offer predictive value for exemestane monotherapy.

Molecular stratification of early breast cancer identifies drug targets to drive stratified medicine.

Many women with hormone receptor-positive early breast cancer can be managed effectively with endocrine therapies alone. However, additional systemic chemotherapy treatment is necessary for others. The clinical challenges in managing high-risk women are to identify existing and novel druggable targets, and to identify those who would benefit from these therapies. Therefore, we performed mRNA abundance analysis using the Tamoxifen and Exemestane Adjuvant Multinational (TEAM) trial pathology cohort to identify a signature of residual risk following endocrine therapy and pathways that are potentially druggable. A panel of genes compiled from academic and commercial multiparametric tests as well as genes of importance to breast cancer pathogenesis was used to profile 3825 patients. A signature of 95 genes, including nodal status, was validated to stratify endocrine-treated patients into high-risk and low-risk groups based on distant relapse-free survival (DRFS; Hazard Ratio = 5.05, 95% CI 3.53-7.22, p = 7.51 × 10-19). This risk signature was also found to perform better than current multiparametric tests. When the 95-gene prognostic signature was applied to all patients in the validation cohort, including patients who received adjuvant chemotherapy, the signature remained prognostic (HR = 4.76, 95% CI 3.61-6.28, p = 2.53× 10-28). Functional gene interaction analyses identified six significant modules representing pathways involved in cell cycle control, mitosis and receptor tyrosine signaling; containing a number of genes with existing targeted therapies for use in breast or other malignancies. Thus the identification of high-risk patients using this prognostic signature has the potential to also prioritize patients for treatment with these targeted therapies.

Virtual tissue microarrays: a novel and viable approach to optimizing tissue microarrays for biomarker research applied to ductal carcinoma in situ.

AIMS: Tissue microarrays (TMAs) are effective tools for performing high-throughput standardization analyses of biomarkers, but evidence indicating the core number required to be representative of the whole tumour is lacking. Ductal carcinoma in situ (DCIS) is a non-obligate precursor of invasive breast cancer. The number and size of cores that can best represent a DCIS lesion are unknown. Rather than performing extensive experiments using several variants of physical TMAs, the aim of this study was to develop a 'virtual TMA' approach that is effective at optimizing biomarker discovery and validation. METHODS AND RESULTS: Whole DCIS sections from 95 patients were evaluated by immunohistochemistry for oestrogen receptor (ER), progesterone receptor (PgR), HER2, and Ki67. Histoscores were generated manually for ER, PgR, and HER2, as well as percentage positivity for Ki67. Slides were scanned using the FDA-approved Ariol SL50 Image Analysis system, and the virtual array (V-Array) module was used. Virtual cores created virtual TMAs, and our validated scoring classifiers were applied. Automated histoscores and percentage positivity were determined, and compared against increasing numbers of cores. The optimal number of cores was based on concordant results between virtual TMAs and corresponding whole sections. CONCLUSIONS: We have shown that virtual arrays constitute an important tool in digital pathology in both research and clinical settings.

GSK3ß and cyclin D1 expression predicts outcome in early breast cancer patients.

Glycogen synthase kinase 3ß (GSK3ß) is phosphorylated and inactivated by the phosphoinositide 3 kinase PI3K/Akt pathway. Activation of Akt phosphorylates GSK3ß preventing phosphorylation of cyclin D1 which leads to accumulation and nuclear localisation of cyclin D1, activation of CDK4/6 and cell cycle progression. The CCND1 gene found at chromosome 11q13 has been shown to be amplified in approximately 15 % of breast cancers. Cyclin D1, the product of the CCND1 gene, is one of the most commonly overexpressed proteins in breast cancer. Protein expression for GSK3ß, phosphorylated-GSK3ß (p-GSK3ß), cyclin D1 and gene expression of CCND1 were examined in tissue microarrays of 1,686 patients from the Edinburgh Breast Conservation Series. High GSK3ß expression was associated with reduced distant relapse-free survival (DRFS), while no association between p-GSK3ß and breast cancer-specific survival was seen. CCND1 amplification is also associated with poor DRFS. On the contrary, cyclin D1 overexpression is associated with an increase in DRFS. Multivariate analysis was performed. We suggest that analysis of both GSK3ß and cyclin D1 expressions can be considered as a marker of good prognosis in early breast cancer.

Expression of activated type I receptor tyrosine kinases in early breast cancer.

Overexpression of EGFR, HER2 and HER3 are known to be associated with poor outcome in breast cancer. Few studies have examined the clinical impact of activation of these proteins. In the present study, we evaluated EGFR, HER2 and HER3 and the activated (phosphorylated) forms of these proteins in patients with early breast cancer. EGFR, HER2, HER3, pEGFR, pHER2 and pHER3 expression was determined by immunohistochemical analysis of tissue microarrays constructed from tumours within the Edinburgh Breast Conservation Series (BCS). The BCS represents a fully-documented consecutive cohort of 1,812 patients treated by breast conservation surgery in a single institution. Our results demonstrate overexpression of HER2 and pHER2 to be associated with a significant reduction in overall survival (OS) (HR: 1.66, 95 % CI 1.22-2.26, p = 0.001 and HR: 1.57, 95 % CI 1.22-2.03, p = 0.001, respectively) and distant relapse-free survival (DRFS) (HR: 1.63, 95 % CI 1.23-2.18, p = 0.001 and HR: 1.55, 95 % CI 1.23-1.97, p = 0.0002, respectively). Paradoxically, expression of pEGFR was associated with a significantly improved OS (HR: 0.67 95 % CI 0.50-0.91, p = 0.01) and DRFS (HR: 0.73, 95 % CI 0.56-0.96, p = 0.025). Expression of activated EGFR/HER2 provides additional information on ER positive breast cancer patients and suggests alternative treatment for those in this subgroup.

The p160 ER co-regulators predict outcome in ER negative breast cancer.

The SRC family of ER co-regulators are frequently overexpressed in breast cancer. Overexpression of AIB1 appears to be linked to hormone resistance in HER2 positive breast cancer. However, the role of these co-regulators in ER negative disease is poorly understood. SRC1, SRC2 and AIB1 expression was determined by immunohistochemical analysis of tissue microarrays constructed from tumours within the Edinburgh Breast Conservation Series (BCS). The BCS represents a fully documented consecutive cohort of 1,812 patients treated by breast conservation surgery in a single institution. Our results demonstrate tumours that overexpress both HER2 and AIB1 were associated with markedly reduced relapse free, distant relapse free and overall survival compared to HER2 and AIB1 only overexpressing tumours irrespective of ER status. In ER negative disease both SRC1 and AIB1 were linked to early relapse and death. The SRC family of ER co-regulators is involved in early relapse and resistance in both ER negative and ER positive breast cancer challenging the conventional concept that this effect is mediated solely via the ER.