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Background Breast cancer is a highly heterogeneous disease where variations of biomarker expression may exist between individual foci of a cancer (intra-tumoral heterogeneity). The extent of variation of biomarker expression in the cancer cells, distribution of cell types in the local tumor microenvironment and their spatial arrangement could impact on diagnosis, treatment planning and subsequent response to treatment. Methods Using quantitative multiplex immunofluorescence (MxIF) imaging, we assessed the level of variations in biomarker expression levels among individual cells, density of cell cluster groups and spatial arrangement of immune subsets from regions sampled from 38 multi-focal breast cancers that were processed using whole-mount histopathology techniques. Molecular profiling was conducted to determine the intrinsic molecular subtype of each analysed region. Results A subset of cancers (34.2%) showed intra-tumoral regions with more than one molecular subtype classification. High levels of intra-tumoral variations in biomarker expression levels were observed in the majority of cancers studied, particularly in Luminal A cancers. HER2 expression quantified with MxIF did not correlate well with HER2 gene expression, nor with clinical HER2 scores. Unsupervised clustering revealed the presence of various cell clusters with unique IHC4 protein co-expression patterns and the composition of these clusters were mostly similar among intra-tumoral regions. MxIF with immune markers and image patch analysis classified immune niche phenotypes and the prevalence of each phenotype in breast cancer subtypes was illustrated. Conclusions Our work illustrates the extent of spatial heterogeneity in biomarker expression and immune phenotypes, and highlights the importance of a comprehensive spatial assessment of the disease for prognosis and treatment planning.

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.

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. Genetics: Expression signature identifies high-risk patients A gene expression signature identifies breast cancer patients who do poorly after endocrine therapy and might benefit from extra treatment. A team led by John Bartlett and Paul Boutros from the Ontario Institute for Cancer Research in Toronto, Canada, measured the activity levels of 165 genes known to be involved in breast cancer development in tumor samples from 3825 patients with early estrogen receptor-positive disease. The patients received either endocrine therapies (tamoxifen or an aromatase inhibitor) alone or additional chemotherapy as well. The researchers identified a 95-gene expression signature that, when combined with a determination of whether the cancer has spread into the lymph nodes, can help predict which patients are at high risk of disease progression, regardless of whether they received chemotherapy or not. These patients could be prioritized for additional drug therapies.

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.

Abstract 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.

Glycogen synthase kinase 3β (GSK3β) is phosphorylated and inactivated by the phosphoinositide 3 kinase PI3K/Akt pathway. Activation of Akt phosphorylates GSK3β 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 GSK3β, phosphorylated-GSK3β (p-GSK3β), cyclin D1 and gene expression of CCND1 were examined in tissue microarrays of 1,686 patients from the Edinburgh Breast Conservation Series. High GSK3β expression was associated with reduced distant relapse-free survival (DRFS), while no association between p-GSK3β 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 GSK3β and cyclin D1 expressions can be considered as a marker of good prognosis in early breast cancer.

Glycogen synthase kinase 3β (GSK3β) is phosphorylated and inactivated by the phosphoinositide 3 kinase PI3K/Akt pathway. Activation of Akt phosphorylates GSK3β preventing phosphorylation of cyclin D1 which leads to accumulation and nuclear localization 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 GSK3β, phosphorylated-GSK3β (p-GSK3β), cyclin D1 and gene expression of CCND1 were examined in tissue microarrays of 1,686 patients from the Edinburgh Breast Conservation Series. High GSK3β expression was associated with reduced distant relapse-free survival (DRFS), while no association between p-GSK3β 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 GSK3β and cyclin D1 expressions can be considered as a marker of good prognosis in early breast cancer.[PUBLICATION ABSTRACT]

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.