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Background Although evaluation of nuclear morphology plays a crucial role in the diagnosis and categorisation of breast lesions, the criteria used to assess nuclear atypia rely on the subjective evaluation of several features that may result in inter- and intra-observer variation. This study aims to refine the definitions of cytonuclear features in various breast lesions. Methods ImageJ was used to assess the nuclear morphological features including nuclear diameter, axis length, perimeter, area, circularity, and roundness in 160 breast lesions comprising ductal carcinoma in situ (DCIS), invasive breast carcinoma of no special type (IBC-NST), tubular carcinoma, usual ductal hyperplasia (UDH), columnar cell change (CCC) and flat epithelial atypia (FEA). Reference cells included normal epithelial cells, red blood cells (RBCs) and lymphocytes. Results Reference cells showed size differences not only between normal epithelial cells and RBCs but also between RBCs in varied-sized blood vessels. Nottingham grade nuclear pleomorphism scores 1 and 3 cut-offs in IBC, compared to normal epithelial cells, were 1.4x that of mean maximum Feret's diameter and 2.4x that of mean nuclear area, respectively. Nuclear morphometrics were significantly different in low-grade IBC-NST vs. tubular carcinoma, low-grade DCIS vs. UDH, and in CCC vs. FEA. No differences in the nuclear features between grade matched DCIS and IBC were identified. Conclusion This study provides a guide for the assessment of nuclear atypia in breast lesions, refines the comparison with reference cells and highlights the potential diagnostic value of image analysis tools in the era of digital pathology.

Purpose This meta-analysis aimed to investigate whether receptor (estrogen receptor [ER], progesterone receptor [PR], and human epidermal growth factor receptor 2 [HER2]) discordances between primary and recurrent breast cancers affect patients’ survival. Methods Search terms contained ER, PR, and HER2 status details in both primary and recurrent tumors (local recurrence or distant metastasis) in addition to survival outcome data (overall survival [OS] or post-recurrence survival [PRS]). Results Loss of ER or PR in recurrent tumors was significantly associated with shorter OS as compared with receptor-positive concordance (hazard ratio [HR], 1.67; 95% confidence interval [% CI] 1.37–2.04; p p p = 0.03). Gain of PR was not a significant predictor of longer survival compared with receptor-negative concordance, but it could be related to better OS at distant metastasis. Both HER2 of loss and gain could be related to poor outcomes. Conclusion This meta-analysis showed that receptor conversion in recurrent tumors may affect patient survival as compared with receptor concordance.

Breast lesions with a prominent myoepithelial cell component constitute a heterogeneous group of benign and malignant neoplastic proliferations. These lesions are often dual epithelial-myoepithelial, but may be purely myoepithelial cell in nature. Benign epithelial-myoepithelial lesions typically maintain the morphology and immunophenotype of the normal bilayer epithelial myoepithelial structures. However, the distinction between the two cell components is not always clear-cut in malignant lesions in which the histogenesis of myoepithelial cells remains uncertain. Neoplastic biphasic epithelial-myoepithelial lesions of the breast include adenomyoepithelioma (AME), pleomorphic adenoma and adenoid cystic carcinoma. Four histological patterns of classical AME have been described: tubular, lobulated, spindle-cell and adenosis variants. Overlapping patterns occur and some AMEs display an intraductal papillary pattern that may represent a fifth variant. AME can be benign or malignant. Classical AME may show atypical features, which are not sufficient for the diagnosis of malignancy (atypical AME). Atypical AME is recognised as a lesion of uncertain malignant potential with limited metastatic capability. Based on the histological features, we propose a classification of malignant AME (M-AME) into three variants: M-AME in situ, M-AME invasive and AME with invasive carcinoma. In this review, we provide an overview of myoepithelial lesions of the breast focusing on the classification of AME to improve not only the consistency of reporting but also help to guide further management decision-making.

AimsThe mechanisms that drive breast cancer (BC) progression and poor outcome are not fully understood. The human heat shock protein 90 alpha family class A member 1 (HSP90α) encoded by the HSP90ΑA1 gene has a vital role in cellular responses to stress and is implicated in the development and progression of many cancers. The current study aims to explore the clinical and prognostic importance of HSP90α in BC.MethodsThe Molecular Taxonomy of Breast Cancer International Consortium (n=1980); The Cancer Genome Atlas (n=1097) and the Breast Cancer Gene-Expression Miner (Bc-GenExMiner) BC datasets (n=5056) were used to evaluate HSP90ΑA1 mRNA expression. HSP90α protein expression was further assessed using immunohistochemistry in a large (n=911) well-characterised BC series. The association between mRNA and protein expressions with other clinicopathological parameters and outcome was analysed.ResultsHigh expression of HSP90ΑA1 both at the mRNA and protein levels was significantly associated with characteristics of BC poor prognosis, including high grade, lymphovascular invasion, poor Nottingham Prognostic Index and positive expression of p53 and PIK3CA. Outcome analysis revealed that high HSP90α protein expression is an independent predictor of shorter BC-specific survival.ConclusionHSP90α can be used as a potential prognostic marker in BC. Further mechanistic studies are warranted to determine the underlying molecular mechanisms mediated by HSP90α in BC.

Background Lymphovascular invasion (LVI) is a prognostic factor in early-stage invasive breast cancer (BC). Through bioinformatics, data analyses of multiple BC cohorts revealed the positive association between interferon-stimulated gene 15 (ISG15) LVI status. Thus, we explored the prognostic significance of ISG15 in BC. Methods The prognostic significance of ISG15 mRNA was assessed in METABRIC (n = 1980), TCGA (n = 854) and Kaplan–Meier Plotter (n = 3951). ISG15 protein was evaluated using immunohistochemistry (n = 859) in early-stage invasive BC patients with long-term follow-up. The associations between ISG15 expression and clinicopathological features, expression of immune cell markers and patient outcome data were evaluated. Results High mRNA and protein ISG15 expression were associated with LVI, higher histological grade, larger tumour size, hormonal receptor negativity, HER2 positivity, p53 and Ki67. High ISG15 protein expression was associated with HER2-enriched BC subtypes and immune markers (CD8, FOXP3 and CD68). High ISG15 mRNA and ISG15 expressions were associated with poor patient outcome. Cox proportional multivariate analysis revealed that the elevated ISG15 expression was an independent prognostic factor of shorter BC-specific survival. Conclusion This study provides evidence for the role of ISG15 in LVI development and BC prognosis. Further functional studies in BC are warranted to evaluate the therapeutic potential of ISG15.

Background Hypertrophy of the nucleolus is a distinctive cytological feature of malignant cells and corresponds to aggressive behaviour. This study aimed to identify the key gene associated with nucleolar prominence (NP) in breast cancer (BC) and determine its prognostic significance. Methods From The Cancer Genome Atlas (TCGA) cohort, digital whole slide images identified cancers having NP served as label and an information theory algorithm was applied to find which mRNA gene best explained NP. Dyskerin Pseudouridine Synthase 1 (DKC1) was identified. DKC1 expression was assessed using mRNA data of Molecular Taxonomy of Breast Cancer International Consortium (METABRIC, n = 1980) and TCGA (n = 855). DKC1 protein expression was assessed using immunohistochemistry in Nottingham BC cohort (n = 943). Results Nuclear and nucleolar expressions of DKC1 protein were significantly associated with higher tumour grade (p p p DKC1 mRNA and protein expressions were independent risk factors for BCSS (p Conclusion DKC1 expression is strongly correlated with NP and its overexpression in BC is associated with unfavourable clinicopathological characteristics and poor outcome. This has been a detailed example in the correlation of phenotype with genotype.

© 2020 The Authors. Histopathology published by John Wiley & Sons Ltd Aims: Tumour genotype and phenotype are related and can predict outcome. In this study, we hypothesised that the visual assessment of breast cancer (BC) morphological features can provide valuable insight into underlying molecular profiles. Methods and results: The Cancer Genome Atlas (TCGA) BC cohort was used (n=743) and morphological features, including Nottingham grade and its components and nucleolar prominence, were assessed utilising whole-slide images (WSIs). Two independent scores were assigned, and discordant cases were utilised to represent cases with intermediate morphological features. Differentially expressed genes (DEGs) were identified for each feature, compared among concordant/discordant cases and tested for specific pathways. Concordant grading was observed in 467 of 743 (63%) of cases. Among concordant case groups, eight common DEGs (UGT8, DDC, RGR, RLBP1, SPRR1B, CXorf49B, PSAPL1 and SPRR2G) were associated with overall tumour grade and its components. These genes are related mainly to cellular proliferation, differentiation and metabolism. The number of DEGs in cases with discordant grading was larger than those identified in concordant cases. The largest number of DEGs was observed in discordant grade 1:3 cases (n=1185). DEGs were identified for each discordant component. Some DEGs were uniquely associated with well-defined specific morphological features, whereas expression/co-expression of other genes was identified across multiple features and underlined intermediate morphological features. Conclusion: Morphological features are probably related to distinct underlying molecular profiles that drive both morphology and behaviour. This study provides further evidence to support the use of image-based analysis of WSIs, including artificial intelligence algorithms, to predict tumour molecular profiles and outcome.

During the last decade, a dramatic rise in the development and application of artificial intelligence (AI) tools for use in pathology services has occurred. This trend is often expected to continue and reshape the field of pathology in the coming years. The deployment of computational pathology and applications of AI tools can be considered as a paradigm shift that will change pathology services, making them more efficient and capable of meeting the needs of this era of precision medicine. Despite the success of AI models, the translational process from discovery to clinical applications has been slow. The gap between self-contained research and clinical environment may be too wide and has been largely neglected. In this review, we cover the current and prospective applications of AI in pathology. We examine its applications in diagnosis and prognosis, and we offer insights for considerations that could improve clinical applicability of these tools. Then, we discuss its potential to improve workflow efficiency, and its benefits in pathologist education. Finally, we review the factors that could influence adoption in clinical practices and the associated regulatory processes.

Aims The aims of this study were to review the histological features useful for the identification of metastases to the breast and to investigate the impression that this diagnosis has become more common. Methods and results The histological features of metastases to the breast from 2008 to 2018 were reviewed. Seventy-four biopsies from 66 patients were identified: 1% compared with primary carcinoma of the breast. Non-haematological metastases comprised 0.75% compared with 0.3% in a series from 1996 to 2005. The most common tumour types were pulmonary carcinoma (22), lymphoma (15), melanoma (13), gastrointestinal carcinoma (eight) and serous papillary carcinoma (four). In 73% there were histological features that were not typical of primary mammary carcinoma. Some metastases were histologically similar to breast cancer and the history was essential to making the correct diagnosis. Useful histological clues included small-cell morphology for pulmonary carcinoma, glands containing necrosis for gastrointestinal carcinoma, intranuclear inclusions, marked pleomorphism and spindle cells for melanoma, clear cells for renal carcinoma, papillary architecture for serous papillary carcinoma and sheets of centroblasts or nodules of centroblasts and centrocytes for lymphoma. Useful immunohistochemical markers included TTF-1 for pulmonary carcinoma, S100, melan-A and HMB45 for melanoma, CK20 and CDX2 for colorectal carcinoma, PAX8 and WT1 for serous papillary carcinoma and lymphoid markers for lymphomas, in addition to the absence of expression of mammary markers ER, GATA3 and GCDFP-15. Conclusion The majority of metastases to the breast have histological clues to the diagnosis. Immunohistochemistry is helpful. This diagnosis is being made more frequently.

Tall cell carcinoma with reverse polarity is a rare subtype of breast carcinoma with solid and papillary growth and nuclear features reminiscent of those of the tall cell variant of papillary thyroid carcinoma. These tumors harbor recurrent IDH2 R172 hotspot mutations or TET2 mutations, co-occurring with mutations in PI3K pathway genes. Diagnosis of tall cell carcinomas with reverse polarity is challenging in view of their rarity and the range of differential diagnosis. We sought to determine the sensitivity and specificity of IDH2 R172 immunohistochemistry for the detection of IDH2 R172 hotspot mutations in this entity. We evaluated 14 tall cell carcinomas with reverse polarity (ten excision and five core needle biopsy specimens), 13 intraductal papillomas, 16 solid papillary carcinomas, and 5 encapsulated papillary carcinomas by Sanger sequencing of the IDH2 R172 hotspot locus and of exons 9 and 20 of PIK3CA, and by immunohistochemistry using monoclonal antibodies (11C8B1) to the IDH2 R172S mutation. The 14 tall cell carcinomas with reverse polarity studied harbored IDH2 R172 hotspot mutations, which co-occurred with PIK3CA hotspot mutations in 50% of cases. None of the other papillary neoplasms analyzed displayed IDH2 R172 mutations, however PIK3CA hotspot mutations were detected in 54% of intraductal papillomas, 6% of solid papillary carcinomas, and 20% of encapsulated papillary carcinomas tested. Immunohistochemical analysis with anti-IDH2 R172S antibodies (11C8B1) detected IDH2 R172 mutated protein in 93% (14/15) of tall cell carcinomas with reverse polarity samples including excision (n = 9/10) and core needle biopsy specimens (n = 5), whereas the remaining papillary neoplasms (n = 34) were negative. Our findings demonstrate that immunohistochemical analysis of IDH2 R172 is highly sensitive and specific for the detection of IDH2 R172 hotspot mutations, and likely suitable as a diagnostic tool in the evaluation of excision and core needle biopsy material of tall cell carcinomas with reverse polarity.

Purpose BMI1, which is a major component of the polycomb group complex 1, is an essential epigenetic repressor of multiple regulatory genes and has been identified as a cancer stem cell (CSC) marker in several cancers. However, its role in breast cancer (BC) remains to be defined. In this study, we have evaluated the prognostic significance of BMI1 among the different molecular subtypes and assessed its association with other breast CSC markers (BCSC). Material and method BMI1 copy number and mRNA was assessed in large and well-characterised cohorts of early-stage BC patients [METABRIC (n = 1980) and the Bc-GenExMiner (n = 9616) databases]. BMI1 protein expression was assessed using tissue microarray and immunohistochemistry in a cohort of 870 invasive BC patients with long-term outcome data and the expression of a panel of BCSC markers was monitored. Result BMI1 expression, prognostic significance and its association with BCSC markers were differed between molecular classes. In the luminal oestrogen receptor-positive (ER+) BC, BMI1 showed significantly higher expression compared to ER− tumours. BMI1 showed positive correlation with favourable prognostic features and it was negatively associated with the expression of key BCSC markers (ALDH1A1, CD24, CD44, CD133, SOX10 and SOX9). High expression of BMI1 was associated with longer breast cancer-specific survival (BCSS) independent of other prognostic variables. In the basal triple negative BC subtype, BMI1 expression showed positive association with CD133 and SOX10 and it was significantly associated with shorter BCSS. Conclusion High BMI1 expression is associated with clinicopathological variables and outcome in BC. However, this association is dependent on the molecular subtypes. Further functional assessment to detect its underlying mechanistic roles in BC subtypes is warranted.

Aim The rate of deployment of digital pathology (DP) systems for primary diagnosis in the UK is accelerating. The flexibility and resilience of digital versus standard glass slides could be of great benefit in the NHS breast screening programme (NHSBSP). This study aims to document the safety and benefits of DP for preoperative tissue diagnosis of screen-detected breast lesions. Methods and results Concordance data for glass and digital slides of the same cases from four sites were subjected to detailed concordance-discordance analysis. A literature review of DP in the primary diagnosis of breast lesions is presented, making this the most comprehensive synthesis of digital breast cancer histopathological diagnostic data to date. Detailed concordance analysis of experimental data from two histopathology departments reveals clinical concordance rates for breast biopsies of 96% (216 of 225) and 99.6% (249 of 250). Data from direct comparison validation studies in two histopathology departments, utilising the protocol recommended by the Royal College of Pathologists, found concordance rates for breast histology cases of 99.4% (180 of 181) and 99.0% (887 of 896). An intraobserver variation study for glass versus digital slides for difficult cases from the NHSBSP yielded a kappa statistic of 0.80, indicating excellent agreement. Discordances encountered in the studies most frequently concerned discrepancies in grading attributable to mitotic count-scoring and identification of weddelite. Conclusions The experience of four histopathology laboratories and our review of pre-existing literature suggests that DP is safe for the primary diagnosis of NHSBSP breast histology specimens, and does not increase the risk of misclassification.

Background PPFIA1 is an important regulator of cell migration and invasion, regulating focal adhesion signalling and disassembly. PPFIA1 is frequently amplified in breast cancer, and recent functional studies indicate that PPFIA1 is an important promoter of migration and invasion in breast cancer. This study aims to evaluate the utility of PPFIA1 expression in the luminal breast cancer as a prognostic marker to predict the response to endocrine therapy. Methods Large, well-characterised cohorts of primary luminal breast cancer patients with long-term follow-up was assessed for the clinical impact of PPFIA1 expression at the transcriptomic and proteomic levels. Prognostic significance of PPFIA1 and its relationship with clinical outcome and benefit of endocrine therapy were analysed. In addition, its association with other related-genes was analysed. Results There was significant association between PPFIA1 expression and a member of the liprin family that involves in cell invasion (PPFIBPI), and the cell cycle regulator (CCND1), whereas a negative association was observed with the tumour suppressor gene (CD82). Patients with high PPFIA1 expression were associated with high risk of recurrence, distant metastasis and death from breast cancer (P

Routine breast cancer screening has increased detection of pre-invasive lesions such as ductal carcinoma in situ (DCIS). Currently, DCIS cases are mostly treated with wide local excision combined with adjuvant radiotherapy and/or hormonal therapy, even though only 25% of DCIS treated with surgery alone recur with 50% of recurrences being invasive. At present, prediction of recurrence risk is based on histopathological features and patient characteristics but reliable identification of individual recurrence risk is still challenging. Certain genetic aberrations (i.e. copy number variation, somatic mutations) are associated with breast cancer progression. While most recurrences are assumed to be genetically related to the primary tumour (“clonal recurrence”), the prevalence of ipsilateral independent primary events (“non-clonal recurrence”) after treatment for DCIS is uncertain. If this is a substantial proportion of cases, their presence would compromise attempts to find tumour intrinsic biomarkers of recurrence. To enable the discovery of better recurrence biomarkers, this project initially aims to identify cases with primary DCIS and later clonal ipsilateral recurrence. Sections from formalin-fixed paraffin-embedded blocks from primary DCIS cases and their subsequent recurrences were obtained from Nottingham City Hospital (UK). Two pathologists reviewed representative sections to identify areas for microdissection. Tumour epithelial cells were needle-microdissected and DNA was isolated. Sequencing libraries were prepared using a) a custom capture panel of 110 breast cancer-related genes or b) NEBNext Ultra II for low-coverage whole-genome sequencing (LC-WGS) depending on DNA quality and quantity. Sequencing was then performed on Illumina NextSeq 500 system with an average coverage of a) 400x and b) 1.3x, respectively. Data was processed by an in-house bioinformatics pipeline to detect and filter for high confidence somatic variants. Copy number profiles were obtained using CopywriteR (panel off-target reads), PureCN (panel on-target reads) and Control-FREEC (LC-WGS). Of 33 patients initially ascertained on the basis of a recurrent breast event, 30 had an ipsilateral recurrent tumour after 4.7 years on average, and 24 primary/recurrence pairs had sufficient data available to determine clonality. Eighteen pairs (75%) were classified as clonal by the following criteria: occurring in similar locations, showing a similar or higher tumour grade, and sharing ≥ 3 copy number breakpoints or likely somatic variants in the genes included in the panel. Six pairs (25%) did not meet this criteria and were classified as non-clonal. Preliminary data analysis shows that invasive recurrences (n = 12) were detected on average 3 years later than DCIS recurrences (n = 6), despite constant surveillance. The most commonly observed somatic mutations occurred in the TP53 and PIK3CA genes. Genetic variants in TP53 and PIK3CA were equally common in primary tumours with clonal and non-clonal recurrence. Frequent copy number alterations involved losses on 16q as well as gains on 1q, 8q and 17q, whereat the 8q gain was less profound. The presence of 25% non-clonal recurrences shows that differentiating between clonal and non-clonal recurrences might be crucial for further recurrence risk biomarker discovery. Thus, this project will proceed with comparing genetic variation in primary DCIS with clonal recurrence to DCIS cases without later recurrence. These samples are currently being obtained and analysed. Citation Format: Dorothea Lesche, Hugo Saunders, Sakshi Mahale, Magnus Zenthoven, Siobhan Huges, Tanjina Kader, Niko Thio, Islam M Miligy, Jia-Min Pang, Andrew R Green, Emad A Rakha, Ian G Campbell, Stephen B Fox, Kylie Gorringe. Evaluation of genomic changes in ductal carcinoma in situ as potential biomarkers of recurrence risk [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-10-21.

Epidermal growth factor receptor (EGFR) and human epidermal growth factor receptor 3 (HER3) have been investigated as triple-negative breast cancer (TNBC) biomarkers. Reduced EGFR levels can be compensated by increases in HER3; thus, assaying EGFR and HER3 together may improve prognostic value. In a multi-institutional cohort of 510 TNBC patients, we analyzed the impact of HER3, EGFR, or combined HER3-EGFR protein expression in pre-treatment samples on breast cancer-specific and distant metastasis-free survival (BCSS and DMFS, respectively). A subset of 60 TNBC samples were RNA-sequenced using massive parallel sequencing. The combined HER3-EGFR score outperformed individual HER3 and EGFR scores, with high HER3-EGFR score independently predicting worse BCSS (Hazard Ratio [HR] = 2.30, p = 0.006) and DMFS (HR = 1.78, p = 0.041, respectively). TNBCs with high HER3-EGFR scores exhibited significantly suppressed ATM signaling and differential expression of a network predicted to be controlled by low TXN activity, resulting in activation of EGFR, PARP1, and caspases and inhibition of p53 and NFκB. Nuclear PARP1 protein levels were higher in HER3-EGFR-high TNBCs based on immunohistochemistry (p = 0.036). Assessing HER3 and EGFR protein expression in combination may identify which adjuvant chemotherapy-treated TNBC patients have a higher risk of treatment resistance and may benefit from a dual HER3-EGFR inhibitor and a PARP1 inhibitor.

Risk stratification of COVID‐19 patients is essential for pandemic management. Changes in the cell fitness marker, hFwe‐Lose, can precede the host immune response to infection, potentially making such a biomarker an earlier triage tool. Here, we evaluate whether hFwe‐Lose gene expression can outperform conventional methods in predicting outcomes (e.g., death and hospitalization) in COVID‐19 patients. We performed a post‐mortem examination of infected lung tissue in deceased COVID‐19 patients to determine hFwe‐Lose’s biological role in acute lung injury. We then performed an observational study (n = 283) to evaluate whether hFwe‐Lose expression (in nasopharyngeal samples) could accurately predict hospitalization or death in COVID‐19 patients. In COVID‐19 patients with acute lung injury, hFwe‐Lose is highly expressed in the lower respiratory tract and is co‐localized to areas of cell death. In patients presenting in the early phase of COVID‐19 illness, hFwe‐Lose expression accurately predicts subsequent hospitalization or death with positive predictive values of 87.8–100% and a negative predictive value of 64.1–93.2%. hFwe‐Lose outperforms conventional inflammatory biomarkers and patient age and comorbidities, with an area under the receiver operating characteristic curve (AUROC) 0.93–0.97 in predicting hospitalization/death. Specifically, this is significantly higher than the prognostic value of combining biomarkers (serum ferritin, D‐dimer, C‐reactive protein, and neutrophil–lymphocyte ratio), patient age and comorbidities (AUROC of 0.67–0.92). The cell fitness marker, hFwe‐Lose, accurately predicts outcomes in COVID‐19 patients. This finding demonstrates how tissue fitness pathways dictate the response to infection and disease and their utility in managing the current COVID‐19 pandemic., A post‐mortem examination of COVID‐19 infected lung tissues and an observational study were performed in order to evaluate whether expression of cell fitness marker hFwe‐Lose in patient's nasopharyngeal swabs could predict hospitalization or death from COVID‐19.

Visual assessment of mitotic figures in breast cancer (BC) remains a challenge. This is expected to be more pronounced in the digital pathology era. This study aims to refine the criteria of mitotic figure recognition, particularly in whole slide images (WSI).Haematoxylin and eosin (HE)-stained BC sections (n = 506) were examined using light microscopy (LM) and WSI. A set of features for identifying mitosis in WSI and to distinguish true figures from mimickers was developed. Changes in the mitotic count between the two platforms was explored. Morphological features of mitoses were recorded separately, including absence of nuclear membrane, chromatin hairy-like projections, shape, cytoplasmic features, mitotic cell size and relationship to surrounding cells. Each mitotic phase has its own mimickers. Fifty-eight per cent of mitoses showed absent hairy-like projection in WSI; however, 89% retained their ragged nuclear border, which distinguished them from mimickers including apoptotic cells, lymphocytes and dark elongated hyperchromatic structures. Mitosis in WSI showed loss of fine details, and there was a 20% average reduction rate of mitotic counts when compared to the same area on LM. Using refined mitosis recognition criteria in WSI resulted in a twofold improvement of interobserver concordance. However, when compared to LM, 19% of cases were underscored in WSIs.All morphological features of mitosis should be considered to enable recognition and differentiation from their mimickers, particularly in WSI, to ensure reliable BC grading. Refining mitotic cut-offs per specific area when using WSI, based on the degree of reduction and association with outcome, is warranted.

Breast cancer management depends on biomarkers including estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 (ER/PR/HER2). Though existing scoring systems are widely used and well-validated, they can involve costly preparation and variable interpretation. Additionally, discordances between histology and expected biomarker findings can prompt repeat testing to address biological, interpretative, or technical reasons for unexpected results. We developed three independent deep learning systems (DLS) to directly predict ER/PR/HER2 status for both focal tissue regions (patches) and slides using hematoxylin-and-eosin-stained (H&E) images as input. Models were trained and evaluated using pathologist annotated slides from three data sources. Areas under the receiver operator characteristic curve (AUCs) were calculated for test sets at both a patch-level (>135 million patches, 181 slides) and slide-level (n = 3274 slides, 1249 cases, 37 sites). Interpretability analyses were performed using Testing with Concept Activation Vectors (TCAV), saliency analysis, and pathologist review of clustered patches. The patch-level AUCs are 0.939 (95%CI 0.936–0.941), 0.938 (0.936–0.940), and 0.808 (0.802–0.813) for ER/PR/HER2, respectively. At the slide level, AUCs are 0.86 (95%CI 0.84–0.87), 0.75 (0.73–0.77), and 0.60 (0.56–0.64) for ER/PR/HER2, respectively. Interpretability analyses show known biomarker-histomorphology associations including associations of low-grade and lobular histology with ER/PR positivity, and increased inflammatory infiltrates with triple-negative staining. This study presents rapid breast cancer biomarker estimation from routine H&E slides and builds on prior advances by prioritizing interpretability of computationally learned features in the context of existing pathological knowledge. Breast cancer diagnosis and characterization involves evaluation of marker proteins found inside or on the surface of tumor cells. Three of the most important markers are estrogen receptor (ER), progesterone receptor (PR) and a receptor called HER2. The levels of these markers can influence how a person with breast cancer is treated in the clinic. This study explored the ability of machine learning – whereby computer software is trained to recognise and classify particular image features - to determine the status of these markers in digitized images, without the need for tissue stains. Our results demonstrate that machine learning can automatically predict the status of ER, PR and HER2 in pathology images and further testing identifies specific image features which enable these predictions. This type of approach may decrease costs and timelines and enable improved quality control in marker detection. Gamble and Jaroensri et al. develop deep learning systems to predict breast cancer biomarker status using H&E images. Their models enable slide-level and patch-level predictions for ER, PR and HER2, with interpretability analyses highlighting specific histological features associated with these markers.

The assessment of cell proliferation is a key morphological feature for diagnosing various pathological lesions and predicting their clinical behaviour. Visual assessment of mitotic figures in routine histological sections remains the gold-standard method to evaluate the proliferative activity and grading of cancer. Despite the apparent simplicity of such a well-established method, visual assessment of mitotic figures in breast cancer (BC) remains a challenging task with low concordance among pathologists which can lead to under or overestimation of tumour grade and hence affects management. Guideline recommendations for counting mitoses in BC have been published to standardise methodology and improve concordance; however, the results remain less satisfactory. Alternative approaches such as the use of the proliferation marker Ki67 have been recommended but these did not show better performance in terms of concordance or prognostic stratification. The advent of whole slide image technology has brought the issue of mitotic counting in BC into the light again with more challenges to develop objective criteria for identifying and scoring mitotic figures in digitalised images. Using reliable and reproducible morphological criteria can provide the highest degree of concordance among pathologists and could even benefit the further application of artificial intelligence (AI) in breast pathology, and this relies mainly on the explicit description of these figures. In this review, we highlight the morphology of mitotic figures and their mimickers, address the current caveats in counting mitoses in breast pathology and describe how to strictly apply the morphological criteria for accurate and reliable histological grade and AI models.

Spindle cell lesions of the breast comprise a heterogeneous group of lesions, ranging from reactive and benign processes to aggressive malignant tumours. Despite their rarity, they attract the attention of breast pathologists due to their overlapping morphological features and diagnostic challenges, particularly on core needle biopsy (CNB) specimens. Pathologists should recognise the wide range of differential diagnoses and be familiar with the diverse morphological appearances of these lesions to make an accurate diagnosis and to suggest proper management of the patients. Clinical history, immunohistochemistry, and molecular assays are helpful in making a correct diagnosis in morphologically challenging cases. In this review, we present our approach for the diagnosis of breast spindle cell lesions, highlighting the main features of each entity and the potential pitfalls, particularly on CNB. Breast spindle cell lesions are generally classified into two main categories: bland-appearing and malignant-appearing lesions. Each category includes a distinct list of differential diagnoses and a panel of immunohistochemical markers. In bland-appearing lesions, it is important to distinguish fibromatosis-like spindle cell metaplastic breast carcinoma from other benign entities and to distinguish fibromatosis from scar tissue. The malignant-appearing category includes spindle cell metaplastic carcinoma, stroma rich malignant phyllodes tumour, other primary and metastatic malignant spindle cell tumours of the breast, including angiosarcoma and melanoma, and benign mimics such as florid granulation tissue and nodular fasciitis.

Background The ASCO/CAP guidance on HER2 testing in breast cancer (BC) has recently changed. Group 2 tumours with immunohistochemistry score 2+ and HER2/CEP17 ratio ≥2.0 and HER2 copy number Methods 749 BC cases were identified from 11 institutions. The association between HER2 groups and pathological complete response (pCR) was assessed. Results 54% of immunohistochemistry HER2 positive (score 3+) BCs showed pCR, compared to 19% of immunohistochemistry 2+ FISH amplified cases. 27% of Group 2 treated with HER2 targeted therapy achieved pCR, compared to 19 and 11% in the combined Groups 1 + 3 and Groups 4 + 5, respectively. No difference in pCR rates was identified between Group 2 and Group 1 or combined Groups 1 + 3. However, Group 2 response rate was higher than Groups 4 + 5 (p = 0.017). Conclusion No difference in pCR was detected in tumours with a HER2/CEP17 ratio ≥2.0 and a HER2 score 2+ by IHC when stratified by HER2 gene copy number. Our data suggest that ASCO/CAP HER2 Group 2 carcinomas should be evaluated further with respect to eligibility for HER2 targeted therapy.

Background Management of breast ductal carcinoma in situ (DCIS) has various approaches with distinct institutional specific practice. Here, we review DCIS management in a single institution with emphasize on re-operation rates and outcome. Methods Breast ductal carcinoma in situ cases diagnosed at the Nottingham Breast Institute between 1987 and 2017 were identified (n = 1249). Clinicopathological data were collected. Cases were histologically reviewed, and different factors associated with primary operation selection, re-excision, presence of residual tumor in the re-excision specimens, use of radiotherapy and ipsilateral recurrences were analyzed. Results 34% of DCIS patients were initially treated by mastectomy and were more frequently symptomatic, of high nuclear tumor grade, size >40 mm, and associated with comedo necrosis and Paget's disease of the nipple. Further surgery was due to involved or narrow surgical margins. Residual tumor tissue was detected in 53% of the re-excision specimens. Re-excision rates of patients treated with breast-conserving surgery (BCS) were reduced from approximately 70% to 23%, and the final mastectomy rates decreased from 60% to 20%. Changes in surgical practice with acceptance of smaller excision margins and more frequent use of local radiotherapy have led to a significant decrease not only in the re-excision rate but also in the final mastectomy rate together with non-significant reduction in 5- and 10-year local recurrence rates. Conclusion Although BCS is increasingly the preferred primary surgical option for DCIS management, a proportion of low-risk DCIS patients continue to undergo re-excision surgery or completion mastectomy. Despite acceptance of smaller margins, recurrence rate is decreasing.

Legumain is a proteolytic enzyme that plays a role in the regulation of cell proliferation in invasive breast cancer. Studies evaluating its role in ductal carcinoma in situ (DCIS) are lacking. Here, we aimed to characterize legumain protein expression in DCIS and evaluate its prognostic significance. Legumain was assessed immunohistochemically in a tissue microarray of a well-characterized cohort of DCIS (n = 776 pure DCIS and n = 239 DCIS associated with invasive breast cancer (DCIS-mixed)). Legumain immunoreactivity was scored in tumor cells and surrounding stroma and related to clinicopathological parameters and patient outcome. High legumain expression was observed in 23% of pure DCIS and was associated with features of high-risk DCIS including higher nuclear grade, comedo necrosis, hormone receptor negativity, HER2 positivity, and higher proliferation index. Legumain expression was higher in DCIS associated with invasive breast cancer than in pure DCIS (p

© 2019, Cancer Research UK. Background: Previous studies have reported up to 50% of ductal carcinoma in situ (DCIS), is HER2 positive, but the frequency of HER2-positive invasive breast cancer (IBC) is lower. The aim of this study is to characterise HER2 status in DCIS and assess its prognostic value. Methods: HER2 status was evaluated in a large series of DCIS (n = 868), including pure DCIS and DCIS associated with IBC, prepared as tissue microarrays (TMAs). HER2 status was assessed using immunohistochemistry (IHC) and chromogenic in situ hybridisation (CISH). Results: In pure DCIS, HER2 protein was over-expressed in 9% of DCIS (3+), whereas 15% were HER2 equivocal (2+). Using CISH, the final HER2 status was positive in 20%. In mixed DCIS, HER2 amplification of the DCIS component was detected in 15% with amplification in the invasive component of only 12%. HER2-positive DCIS was associated with features of aggressiveness (p < 0.0001) and more frequent local recurrence (p = 0.03). On multivariate analysis, combined HER2+/Ki67+ profile was an independent predictor of local recurrence (p = 0.006). Conclusions: The frequency of HER2 positivity in DCIS is comparable to IBC- and HER2-positive DCIS is associated with features of poor prognosis. The majority of HER2 over-expression in DCIS is driven by gene amplification.

Background: About 60-80% of ductal carcinoma in situ (DCIS) cases are high-grade (HG) DCIS with an elevated risk of local recurrence (LR) even after a lumpectomy. Patients are often under or over treated due to the lack of accurate recurrence risk prediction models. Current prognostic models such as OncotypeDX and Van Nuys Prognostic Index (VNPI) lack consistency and are limited to a specific subset of patients. Here in this study, we show that the extent of centrosome amplification (CA) in a DCIS lesion can predict the risk of LR after lumpectomy. CA refers to presence of supernumerary or large centrosomes and is a characteristic of pre-invasive lesions, and breast tumors, and promotes erroneous mitoses and chromosomal instability. Methods: We have pioneered a semi-automated pipeline that integrates immunofluorescence confocal microscopy with digital image analysis and yields a quantitative Centrosomal Amplification Score (CAS) for each patients' tumor sample by evaluating severity and frequency of centrosomal aberrations therein. To this end, we first immunofluorescently stained centrosomes in formalin fixed paraffin embedded resection samples from DCIS patients (discovery cohort n=133 and a validation cohort n=119) using an antibody against γ-tubulin, and co-stained nuclei with DAPI. Next, we imaged the slides and processed the raw 3D image data using IMARIS Biplane 8.2 3D volume rendering software. Finally, we calculated centrosome numbers and volume in ˜250 cells from each patient sample. Using a mathematical algorithm, we generated a composite CAS score for each patient sample by integrating the numerical (CASi) and structural (CASm) aberrations. Results: We found that DCIS patients with recurrence exhibited higher CAS. Intriguingly, higher CAS was also associated with greater risk of developing ipsilateral breast events [Hazard ratio (HR) =7.58 for discovery cohort and HR=5.8 for validation cohort, p Conclusion: Our data compellingly show that CAS quantifies the risk of recurrence in DCIS patients with the highest concordance and provides a novel and innovative tool to tailor their treatment based on their risk profile. Citation Format: Mittal K, Kaur J, Wei G, Toss MS, Osan RM, Janssen EA, Søiland H, Rakha EA, Rida PC, Aneja R. A quantitative centrosomal amplification score (CAS) predicts local recurrence in ductal carcinoma in situ [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P5-18-02.

Current clinicopathological parameters are useful predictors of breast ductal carcinoma in situ behavior, but they are insufficient to define high-risk patients for disease progression precisely. Thioredoxin-interacting protein (TXNIP) is a key player of oxidative stress. This study aims to evaluate the role of TXNIP as a predictor of ductal carcinoma in situ progression. Tissue microarrays from 776 pure ductal carcinoma in situ and 239 mixed ductal carcinoma in situ and invasive tumors were constructed. All patients were treated at a single institution with a long-term follow-up and TXNIP expression was assessed using immunohistochemistry. TXNIP expression was investigated in terms of associations with clinicopathological and molecular features and patient outcome. Loss/reduced cytoplasmic expression of TXNIP was associated with features of aggressiveness including high nuclear grade (p = 1.6 × 10-5), presence of comedo necrosis (p = 0.001), and estrogen receptor negative (ER-)/HER2- ductal carcinoma in situ (p = 4.6 × 10-5). Univariate analysis showed an inverse association between TXNIP expression and outcome in terms of shorter local recurrence-free survival (p = 0.009). Multivariable analyses showed that independent predictors of ductal carcinoma in situ recurrence were low TXNIP expression (p = 0.005, HR = 0.51, and 95% CI: 0.32-0.81), larger ductal carcinoma in situ size, and high nuclear grade. TXNIP functions as a tumor suppressor gene with loss of its expression associated with ductal carcinoma in situ recurrence. TXNIP can be used as a potentially useful marker in prognostic stratification of ductal carcinoma in situ for management decisions.

Background: Phyllodes tumours (PT) are rare and distinct breast tumours, which span a morphological continuum. Classification into benign, borderline and malignant categories reflects their biology and clinical behaviour and is essential to guide management. This study aims to assess the diagnostic agreement of PT using the UK National Health Service Breast Screening Programme (NHSBSP) breast pathology external quality assurance (EQA) scheme data. Methods: 26 PTs were identified in the EQA scheme, which were diagnosed by an average of 607 participants/circulation. Data on diagnostic categories were collected, and representative slides were reviewed. The level of concordance between reporting pathologists was assessed. Results: There were 14 benign, 6 borderline and 6 malignant PT. The overall rate of diagnosis agreement was 86% when analysed as benign lesions, borderline PT and malignant lesions, which decreased to 79% when diagnosed as PT (irrespective of grade) and to 63% when the diagnosis was further refined to PT categories (benign, borderline and malignant PTs). The highest agreement rate was observed in malignant PT (86%) and the lowest in borderline PT (42%). Malignant heterologous elements, stromal overgrowth and leaf-like architecture are features associated with higher concordance rates. Lower priority features were stromal expansion, clefting, and multinodularity. Conclusion: The concordance of PT diagnosis, as an entity, is high, but its classification into benign, borderline and malignant has variable agreement levels, with borderline tumours having the lowest concordance rate. More research to refine the diagnostic criteria for categorisation of PT is warranted to improve concordance between pathologists.

Aims Although rare, malignant sarcomatoid breast tumours without evidence of epithelial differentiation comprise a diagnostic challenge with management implications. Earlier studies have generally considered these to be primary breast sarcomas; however, supporting evidence is lacking and management remains variable. This study aimed to provide an evidence-based approach to improve the consistency of diagnosis and management for such cases.Methods and results A large series (n = 140) of metaplastic breast carcinoma (MBC) diagnosed in Nottingham over 18 years was analysed. Only cases with available data on immunohistochemical expression of cytokeratins (CKs) were included. The prevalence and pattern of expression for various CKs were assessed and details of tumours negative for CKs were collected. A diagnostic approach based on our experience is provided. Forty-seven cases (34%) showed foci of conventional type invasive breast carcinoma or ductal carcinoma in situ (DCIS), while 93 cases (66%) were diagnosed as MBC based on morphology and/or CK expression. Ninety-seven cases (69%) were negative for one or more CKs, with 18 cases (13%) negative for five or more CKs. Eight cases (6%) lacked expression of all CKs tested. Further examination showed evidence of carcinomatous nature in five cases, and three were diagnosed as MBC following extensive diagnostic work-up and based on our experience.Conclusion This study suggests that MBC represents a spectrum of neoplasms, with some lacking CK expression. Sarcomatoid neoplasms of the breast lacking evidence of carcinomatous morphology and CK expression may represent an extreme end of differentiation that can be considered as carcinomas rather than sarcomas for management purposes (following extensive work-up).

Purpose Nucleolar protein 10 (NOP10) is required for ribosome biogenesis and telomere maintenance and plays a key role in carcinogenesis. This study aims to evaluate the clinical and prognostic significance of NOP10 in breast cancer (BC). Methods NOP10 expression was assessed at mRNA level employing the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (n = 1980) and Cancer Genome Atlas (TCGA) BC cohorts (n = 854). Protein expression was evaluated on tissue microarray of a large BC cohort (n = 1081) using immunohistochemistry. The correlation between NOP10 expression, clinicopathological parameters and patient outcome was assessed. Results NOP10 expression was detected in the nucleus and nucleolus of the tumour cells. At the transcriptomic and proteomic levels, NOP10 was significantly associated with aggressive BC features including high tumour grade, high nucleolar score and poor Nottingham Prognostic Index. High NOP10 protein expression was an independent predictor of poor outcome in the whole cohort and in triple-negative BC (TNBC) class (p = 0.002 & p = 0.014, respectively). In chemotherapy- treated patients, high NOP10 protein expression was significantly associated with shorter survival (p = 0.03) and was predictive of higher risk of death (p = 0.028) and development of distant metastasis (p = 0.02) independent of tumour size, nodal stage and tumour grade. Conclusion High NOP10 expression is a poor prognostic biomarker in BC and its expression can help in predicting chemotherapy resistance. Functional assessments are necessary to decipher the underlying mechanisms and to reveal its potential therapeutic values in various BC subtypes especially in the aggressive TNBC class.

Lymph node (LN) involvement is the strongest prognostic factor in operable breast cancer (BC). Therefore, accurate assessment of LN status is essential for management of BC patients. The introduction of sentinel LN approach reduced the need for extensive axillary surgery to achieve accurate staging. However, positive sentinel LN as determined on postoperative histological examination often leads to a second axillary operation to ensure an accurate staging and that positive non-sentinel LNs are removed. Although preoperative assessment of LN has improved significantly, its accuracy remains insufficient to avoid further axillary surgery and is not sufficient to predict the status of the LN. Therefore, intraoperative evaluation of the sentinel LN to determine the need for completing lymph node dissection in case of metastasis can provide an important approach to guide BC management decision making. This article reviews the techniques available and under development for intraoperative detection of sentinel LN metastasis in BC surgery. The key features of each technique are described in detail, emphasising the benefits offered by label-free optical techniques: minimal sample preparation, high spatial resolution, and immediate on-site implementation. Optical techniques have the potential to provide a cost-effective and accurate intraoperative platform for the assessment of SLN within the operating theatre.

The response of human epidermal growth factor receptor2 (HER2)- positive breast cancer (BC) patients to anti-HER2 targeted therapy is significant. However, the response is not uniform and a proportion of HER2-positive patients do not respond. This study aims to identify predictors of response in the neoadjuvant treatment and to assess the discordance rate of HER2 status between pre- and post-treatment specimens in HER2-positive BC patients. The study group comprised 500 BC patients treated with neoadjuvant chemotherapy (NACT) and/or neoadjuvant anti-HER2 therapy and surgery who had tumours that were 3+ or 2+ with HER2 immunohistochemistry (IHC). HER2 IHC 2+ tumours were classified into five groups by fluorescence in situ hybridisation (FISH) according to the 2018 ASCO/CAP guidelines of which Groups 1, 2 and 3 were considered HER2 amplified. Pathological complete response (pCR) was more frequent in HER2 IHC 3+ tumours than in HER2 IHC 2+/HER2 amplified tumours, when either in receipt of NACT alone (38% versus 13%; p = 0.22) or neoadjuvant anti-HER2 therapy (52% versus 20%; p < 0.001). Multivariate logistic regression analysis showed that HER2 IHC 3+ and histological grade 3 were independent predictors of pCR following neoadjuvant anti-HER2 therapy. In the HER2 IHC 2+/HER2 amplified tumours or ASCO/CAP FISH Group 1 alone, ER-negativity was an independent predictor of pCR following NACT and/or neoadjuvant anti-HER2 therapy. In the current study, 22% of HER2-positive tumours became HER2-negative by IHC and FISH following neoadjuvant treatment, the majority (74%) HER2 IHC 2+/HER2 amplified tumours. Repeat HER2 testing after neoadjuvant treatment should therefore be considered.

BackgroundInvasive lobular carcinoma (ILC) accounts for 10-15% of primary breast cancers and is typically estrogen receptor alpha positive (ER+) and ERBB2 non-amplified. Somatic mutations in ERBB2/3 are emerging as a tractable mechanism underlying enhanced human epidermal growth factor 2 (HER2) activity. We tested the hypothesis that therapeutically targetable ERBB2/3 mutations in primary ILC of the breast associate with poor survival outcome in large public datasets.MethodsWe performed in silico comparison of ERBB2 non-amplified cases of ER+ stage I-III primary ILC (N=279) and invasive ductal carcinoma (IDC, N=1,301) using METABRIC, TCGA and MSK-IMPACT information. Activating mutations amenable to HER2-directed therapy with neratinib were identified using existing functional data from in vitro cell line and xenograft experiments. Multivariate analysis of 10-year overall survival (OS) with tumor size, grade and lymph node status was performed using a Cox regression model. Differential gene expression analyses by ERBB2 mutation and amplification status was performed using weighted average differences and an in-silico model of response to neratinib derived from breast cancer cell lines.ResultsILC tumors comprised 17.7% of all cases in the dataset but accounted for 47.1% of ERBB2-mutated cases. Mutations in ERBB2 were enriched in ILC versus IDC cases (5.7%, N=16 vs. 1.4%, N=18, pERBB3 mutations were not enriched in ILC (1.1%, N=3 vs. 1.8%, N=23; p=0.604). Median OS for patients with ERBB2-mutant ILC tumors was 66 months versus 211 months for ERBB2 wild-type (p=0.0001), and 159 vs. 166 months (p=0.733) for IDC tumors. Targetable ERBB2 mutational status was an independent prognostic marker of 10-year OS – but only in ILC (hazard ratio, HR=3.7, 95% CI 1.2–11.0; p=0.021). Findings were validated using a novel ERBB2 mutation gene enrichment score (HR for 10-year OS in ILC=2.3, 95% CI 1.04–5.05; p=0.040).ConclusionsTargetable ERBB2 mutations are enriched in primary ILC and their detection represents an actionable strategy with the potential to improve patient outcomes. Biomarker-led clinical trials of adjuvant HER-targeted therapy are warranted for patients with ERBB2-mutated primary ILC.

BackgroundThe prognosis of patients with pancreatic neuroendocrine tumors (PanNET), the second most common type of pancreatic cancer, varies significantly, and up to 15% of patients develop metastasis. Although certain morphological characteristics of PanNETs have been associated with patient outcome, there are no available morphology-based prognostic markers. Given that current clinical histopathology markers are unable to identify high-risk PanNET patients, the development of accurate prognostic biomarkers is needed. Here, we describe a novel machine learning, multiclassification pipeline to predict the risk of metastasis using morphological information from whole tissue slides.MethodsDigital images from surgically resected tissues from 89 PanNET patients were used. Pathologist-annotated regions were extracted to train a convolutional neural network (CNN) to identify tiles consisting of PanNET, stroma, normal pancreas parenchyma, and fat. Computationally annotated cancer or stroma tiles and patient metastasis status were used to train CNN to calculate a region based metastatic risk score. Aggregation of the metastatic probability scores across the slide was performed to predict the risk of metastasis.ResultsThe ability of CNN to discriminate different tissues was high (per-tile accuracy >95%; whole slide cancer regions Jaccard index = 79%). Cancer and stromal tiles with high evaluated probability provided F1 scores of 0.82 and 0.69, respectively, when we compared tissues from patients who developed metastasis and those who did not. The final model identified low-risk (n = 76) and high-risk (n = 13) patients, as well as predicted metastasis-free survival (hazard ratio: 4.71) after adjusting for common clinicopathological variables, especially in grade I/II patients.ConclusionUsing slides from surgically resected PanNETs, our novel, multiclassification, deep learning pipeline was able to predict the risk of metastasis in PanNET patients. Our results suggest the presence of prognostic morphological patterns in PanNET tissues, and that these patterns may help guide clinical decision making.

Endocrine therapy is the mainstay of adjuvant treatment for patients with luminal breast cancer. Despite ongoing advances in endocrine therapy to date, a proportion of patients ultimately develop endocrine resistance, resulting in failure of therapy and poor prognosis. Therefore, as part of the growing concept of personalised medicine, the need for identification of predictive markers of endocrine therapy response at an early stage, is recognised. The METABRIC series was used to identify differentially expressed genes (DEGs) in term of response to adjuvant endocrine therapy. Drebrin 1 (DBN1) was identified as a key DEG associated with response to hormone treatment. Next, large, well-characterised cohorts of primary luminal breast cancer with long-term follow-up were assessed at the mRNA and protein levels for the value of DBN1 as a prognostic marker in luminal breast cancer, as well as its potential for predicting the benefit of endocrine therapy. DBN1 positivity was associated with aggressive clinicopathological variables and poor patient outcomes. Importantly, high DBN1 expression predicted relapse patients who were subject to adjuvant endocrine treatment. Our results further demonstrate that DBN1 is an independent prognostic marker in luminal breast cancer. Its association with the response to endocrine therapy and outcome provides evidence for DBN1 as a potential biomarker in luminal breast cancer, particularly for the benefit of endocrine treatment. Further functional investigations into the mechanisms underlying sensitivity to endocrine therapy is required.

Background Oestrogen receptor (ER) in invasive breast cancer (BC) predicts response to endocrine therapy (ET) and provides prognostic value. In this study, we investigated the value of ER expression in ductal carcinoma in situ (DCIS) in terms of outcome and the impact on ET decision. Methods In total, 643 pure DCIS, diagnosed at Nottingham University Hospitals, were assessed for ER. Clinicopathological data were correlated against ER status, together with assessment of recurrence rate. Results ER positivity was observed in 74% (475/643) of cases. ER positivity was associated with clinicopathological variables of good prognosis; however, outcome analysis revealed that ER status was not associated with local recurrence. In the intermediate- and high-grade ER-positive DCIS, 58% (11/19) and 63% (15/24) of the recurrences were invasive, respectively, comprising 7% and 6% of all ER-positive DCIS, respectively. Invasive recurrence in low-grade DCIS was infrequent (2%), and none of these patients died of BC. The ER status of the recurrent invasive tumours matched the primary DCIS ER status (94% in ipsilateral and 90% of contralateral recurrence). Conclusion The strong correlation between DCIS and invasive recurrence ER status and the clinical impact of ET justify discussion of the use of ET in ER-positive DCIS treated by breast-conserving surgery. The excellent outcome of low-grade DCIS, which was almost always ER-positive, does not, in the opinion of authors, justify the use of risk-reducing ET. Therefore, the decision on ET for DCIS should be personalised and consider grade, ER status and other characteristics.

Cyclin‐dependent kinase 5 (Cdk5) is an atypical member of the cyclin‐dependent kinase family and functions as a serine/threonine kinase that can be activated by non‐cyclin binding activators p35 or p39. Cdk5 expression and activity has been linked with the development and progression of cancer; however, its expression in breast cancer has not been fully described. Protein expression of Cdk5 was determined in a large cohort of early‐stage invasive breast cancer tumours (n = 1110) with long‐term follow‐up data using immunohistochemistry. Expression of CDK5 mRNA was assessed in the METABRIC cohort (n = 1980). Low nuclear and cytoplasmic expression of Cdk5 expression was significantly associated with shorter breast cancer‐specific survival (P = .004 and P = .001, respectively). Importantly, low nuclear and cytoplasmic expression of Cdk5 remained associated with survival in multivariate analysis, including potentially confounding factors (hazard ratio (HR) = 0.612, 95% confidence interval (CI) = 0.418‐0.896, P = .011 and HR = 0.507, 95% CI = 0.318‐0.809, P = .004, respectively). In addition, low nuclear and cytoplasmic expression of Cdk5 was significantly associated with clinicopathological criteria associated with adverse patient prognosis. Low CDK5 mRNA expression was associated with shorter patient survival (P = .005) in the METABRIC cohort; no associations between copy gain or loss and survival were observed. These data suggest that low Cdk5 expression is associated with poor clinical outcome of breast cancer patients and may be of clinical relevance.

AIMS Aldehyde dehydrogenase family 1 member A1 (ALDH1A1) is reportedly a key ALDH isozyme linked to the cancer stem cells (CSC) of many solid tumours, where it is involved in self-renewal, differentiation and self-protection. In this study, the prognostic significance of ALDH1A1 expression in early invasive breast cancer (BC) and its role as a BC stem cell (BCSC) were evaluated. METHODS AND RESULTS ALDH1A1 expression was assessed, using immunohistochemistry and tissue microarrays, in a large well-characterised BC cohort. ALDH1A1 mRNA expression was also assessed at transcriptomic levels, utilising data from the Molecular Taxonomy of Breast Cancer International Consortium. The associations of ALDH1A1 with clinicopathological parameters, other stem cell markers and patient outcomes were determined. ALDH1A1 was expressed in 71% of BC cases at both the protein and mRNA levels. High ALDH1A1 expression was associated with poor prognostic features, including high grade, poor Nottingham Prognostic Index (NPI), lymph node metastasis and highly proliferative ER+ (luminal B) and triple-negative (TNBC) subtypes. ALDH1A1 expression was positively correlated with the expression of CD44, CD24, TWIST, SOX9, EPCAM and CD133. The high immunoexpression of ALDH1A1 was significantly associated with poor BC-specific survival (P

The tumor–stroma ratio (TSR) was evaluated as a promising parameter for breast cancer prognostication in clinically relevant subgroups of patients. The TSR was assessed on hematoxylin and eosin‐stained tissue slides of 1,794 breast cancer patients from the Nottingham City Hospital. An independent second cohort of 737 patients from the Netherlands Cancer Institute to Antoni van Leeuwenhoek was used for evaluation. In the Nottingham Breast Cancer series, the TSR was an independent prognostic parameter for recurrence‐free survival (RFS; HR 1.35, 95% CI 1.10–1.66, p = 0.004). The interaction term was statistically significant for grade and triple‐negative status. Multivariate Cox regression analysis showed a more pronounced effect of the TSR for RFS in grade III tumors (HR 1.89, 95% CI 1.43–2.51, p, What's new? A tumor does not exist in isolation, and evaluation of its microenvironment or “stroma” could help determine clinical outcome in breast cancer. Here, the authors show that women with a stroma‐high tumor had a worse prognosis compared to women with a stroma‐low tumor. The prognostic value of the tumor‐stroma ratio was most discriminative in patients with grade III or triple negative breast cancer, thus making it a potential valuable factor to improve risk stratification for these patients.

Purpose The tumour microenvironment in older patients is subject to changes. The tumour–stroma ratio (TSR) was evaluated in order to estimate the amount of intra-tumoural stroma and to evaluate the prognostic value of the TSR in older patients with breast cancer (≥ 70 years). Methods Two retrospective cohorts, the FOCUS study (N = 619) and the Nottingham Breast Cancer series (N = 1793), were used for assessment of the TSR on haematoxylin and eosin stained tissue slides. Results The intra-tumoural stroma increases with age in the FOCUS study and the Nottingham Breast Cancer series (B 0.031, 95% CI 0.006–0.057, p = 0.016 and B 0.034, 95% CI 0.015–0.054, p Conclusions The intra-tumoural stroma increases with age. This might be the result of an activated tumour microenvironment. The TSR did not validate as an independent prognostic parameter in patients ≥ 70 years in contrast to young women with breast cancer as published previously.

Background Breast cancer (BC) is a disease with variable morphology, clinical behaviour and response to therapy. Identifying factors associated with the progression of early-stage BC can help understand the risk of metastasis and guide treatment decisions. Myxovirus resistance 1 (MX1), which is involved in the cellular antiviral mechanism, plays a role in some solid tumours; however, its role in invasive BC remains unknown. In this study, we aimed to explore the clinicopathological and prognostic significance of MX1 in BC. Methods MX1 was assessed at the protein level using tissue microarrays from a large well-annotated BC cohort (n = 845). The expression of MX1 mRNA was assessed at the transcriptomic level using the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC; n = 1980) and validated using three publicly available cohorts on Breast Cancer Gene-Expression Miner (bc-GenExMiner version 4.4). The associations between MX1 expression and clinicopathological factors, and outcome were evaluated. Results High MX1 protein expression was associated with features of aggressiveness, including large tumour size, high tumour grade, high Nottingham prognostic index scores, hormone receptor negativity and high Ki67 expression. High MX1 expression showed an association with poor patient outcome and it was an independent predictor of short BC-specific survival (p = 0.028; HR = 1.5; 95% CI = 1.0–2.2). Consistent with the protein results, high MX1 mRNA levels showed an association with features of aggressive behaviour and with shorter survival. Conclusion This study identified MX1 as an independent predictor of poor outcome in patients with BC. Further functional studies are needed to investigate the biological role of MX1 in BC and its potential value as a therapeutic target.

The absence of a robust risk stratification tool for triple negative breast cancer (TNBC) underlies imprecise and nonselective treatment of these patients with cytotoxic chemotherapy. This study aimed to interrogate transcriptomes of TNBC resected samples using next generation sequencing to identify novel biomarkers associated with disease outcomes. A subset of cases (n = 112) from a large, well-characterized cohort of primary TNBC (n = 333) were subjected to RNA-sequencing. Reads were aligned to the human reference genome (GRCH38.83) using the STAR aligner and gene expression quantified using HTSEQ. We identified genes associated with distant metastasis-free survival and breast cancer-specific survival by applying supervised artificial neural network analysis with gene selection to the RNA-sequencing data. The prognostic ability of these genes was validated using the Breast Cancer Gene-Expression Miner v4. 0 and Genotype 2 outcome datasets. Multivariate Cox regression analysis identified a prognostic gene signature that was independently associated with poor prognosis. Finally, we corroborated our results from the two-gene prognostic signature by their protein expression using immunohistochemistry. Artificial neural network identified two gene panels that strongly predicted distant metastasis-free survival and breast cancer-specific survival. Univariate Cox regression analysis of 21 genes common to both panels revealed that the expression level of eight genes was independently associated with poor prognosis (p

Endocrine therapy for oestrogen receptor-positive (ER+) breast cancer (BC) is arguably the most successful targeted cancer therapy to date. Nevertheless, resistance to endocrine therapy still occurs in a significant proportion of patients, limiting its clinical utility. ER+ or luminal BC, which represents approximately three-quarters of all breast malignancies, are biologically heterogeneous, with no distinct, clinically defined subclasses able to predict the benefit of endocrine therapy in early settings. To improve patient outcomes there is a clear need for improved understanding of the biology of the luminal BC, with subsequent translation into more effective methods of diagnosis to identify potential predictive biomarkers for endocrine therapy. This review summarises current knowledge of factors predictive of benefit of endocrine therapy and discusses why molecular classification systems of BC have yet to be translated into the clinic.

Background: Breast cancer (BC) is a heterogeneous disease characterised by variant biology, metabolic activity and patient outcome. This study aimed to evaluate the biological and prognostic value of the membrane solute carrier, SLC3A2 in BC with emphasis on the intrinsic molecular subtypes.\ud \ud Methods: SLC3A2 was assessed at the genomic level, using METABRIC data (n=1,980), and proteomic level, using immunohistochemistry on TMA sections constructed from a large well-characterised primary BC cohort (n=2,500). SLC3A2 expression was correlated with clinicopathological parameters, molecular subtypes, and patient outcome.\ud \ud Results: SLC3A2 mRNA and protein expression were strongly correlated with higher tumour grade and poor Nottingham prognostic index (NPI). High expression of SLC3A2 was observed in triple negative (TN), HER2+, and ER+ high proliferation subtypes. SLC3A2 mRNA and protein expression were significantly associated with the expression of c-MYC in all BC subtypes (p

Background As only a minor portion of the information present in histological sections is accessible by eye, recognition and quantification of complex patterns and relationships among constituents relies on digital image analysis. In this study, our working hypothesis was that, with the application of digital image analysis technology, visually unquantifiable breast cancer microarchitectural features can be rigorously assessed and tested as prognostic parameters for invasive breast carcinoma of no special type. Methods Digital image analysis was performed using public domain software (ImageJ) on tissue microarrays from a cohort of 696 patients, and validated with a commercial platform (Visiopharm). Quantified features included elements defining tumour microarchitecture, with emphasis on the extent of tumour-stroma interface. The differential prognostic impact of tumour nest microarchitecture in the four immunohistochemical surrogates for molecular classification was analysed. Prognostic parameters included axillary lymph node status, breast cancer-specific survival, and time to distant metastasis. Associations of each feature with prognostic parameters were assessed using logistic regression and Cox proportional models adjusting for age at diagnosis, grade, and tumour size. Results An arrangement in numerous small nests was associated with axillary lymph node involvement. The association was stronger in luminal tumours (odds ratio (OR) = 1.39, p = 0.003 for a 1-SD increase in nest number, OR = 0.75, p = 0.006 for mean nest area). Nest number was also associated with survival (hazard ratio (HR) = 1. 15, p = 0.027), but total nest perimeter was the parameter most significantly associated with survival in luminal tumours (HR = 1.26, p = 0.005). In the relatively small cohort of triple-negative tumours, mean circularity showed association with time to distant metastasis (HR = 1.71, p = 0.027) and survival (HR = 1.8, p = 0.02). Conclusions We propose that tumour arrangement in few large nests indicates a decreased metastatic potential. By contrast, organisation in numerous small nests provides the tumour with increased metastatic potential to regional lymph nodes. An outstretched pattern in small nests bestows tumours with a tendency for decreased breast cancer-specific survival. Although further validation studies are required before the argument for routine quantification of microarchitectural features is established, our approach is consistent with the demand for cost-effective methods for triaging breast cancer patients that are more likely to benefit from chemotherapy.

Breast cancer (BC) displays striking clinical, morphological, and behavioural diversity within a single tumour and between tumours. Currently, mounting evidence indicates that the morphological heterogeneity of BC reflects an underlying spectrum of genetic and epigenetic portraits that control BC behaviour. Further understanding of BC heterogeneity will have an impact, not only on the routine diagnostic practices but also on patients' management decisions. Phenomena like diagnostic inconsistencies and therapeutic resistance, both primary and acquired, could be attributed, at least in part, to tumour heterogeneity within the same cancer and between the primary disease and subsequent recurrences. From a practical standpoint, and to minimise the impact of BC intratumoral heterogeneity, pragmatic approaches for adequate tumour sampling have been suggested in translational biomarker discovery and validation research studies and in the clinical setting. Here, we provide a brief overview of BC heterogeneity, with an emphasis on the clinical consequences of intratumoral heterogeneity.

Macrophage-associated cytokines play an important role in cancer metastasis; however, the functions of interleukins (IL) 6 and 10 in breast cancer (BC) progression and metastasis are not clear. In this study the roles of IL-6/IL-10 in regulating vascular invasion and their prognostic significance in BC are investigated. MDA-MB-231 and MCF-7 migration (± IL-6 or IL-10) was assessed by scratch wound assay. Cancer cell adhesion to IL-6/IL-10 stimulated blood and lymphatic endothelial cells (EC) was investigated. Expression of IL-6 /IL-10 was assessed using immunohistochemistry in an annotated cohort of early stage BC (n = 1380) and associations with clinicopathological variables and clinical outcome evaluated. IL-6 did not alter BC cell migration however a dose-dependent inhibition in MDA-MB-231 migration with IL-10 treatment was observed (P = 0.03). BC cells were more adhesive to blood vs lymphatic EC, however, IL-6/IL-10 had no effect on adhesion patterns. High expression of IL-6/IL-10 was associated with clinicopathological criteria (e.g. hormone receptor status, all P

537 Background: The EndoPredict 12-gene prognostic assay is validated to predict distant recurrence-free survival (DRFS) and response to chemotherapy in post-menopausal women with ER+, HER2- breast cancer. This study evaluated the performance of EndoPredict in pre-menopausal women. Methods: Stored tumor samples from women with ER+, HER2- primary breast cancer who were pre-menopausal at the time of diagnosis and were systemically treated with endocrine therapy alone were obtained from two sites (University of Nottingham and University of Cyprus). These samples were tested with EndoPredict to produce a 12-gene molecular score (EP). Pathologic tumor size and nodal status were algorithmically combined with the EP score to produce the clinicomolecular EPclin score. Cases with tumors > pT3, which were treated with chemotherapy, or for whom the EPclin score was missing or invalid were excluded. Associations of EP and EPclin with 10-year DRFS were evaluated in terms of hazard ratios (HRs) from Cox proportional hazards models stratified by cohort. 10-year DRFS was estimated for EPclin high-risk and low-risk women by Kaplan-Meier analysis. Results: Out of 411 eligible cases, 385 had a valid EPclin score and were included in the analysis. Mean age at breast cancer diagnosis was 46.5 years (standard deviation 4.7). Most women (N = 239, 62.6%) had grade II tumors and 16.1% (N = 62) had node-positive disease. Over the observation period (median 9.7 years, interquartile range 6.6-13.9 years), 35 women had a distant recurrence within 10 years. Both the molecular EP score and the molecular-clinicopathologic EPclin score were associated with increased risk of distant recurrence [HR 1.3, 95% confidence interval (CI) 1.2-1.5; p < 0.001 and HR 3.6, 95% CI 2.3-5.7; p < 0.001, respectively]. Of these patients, 249 (64.7%) were categorized as low risk by EPclin score while the remaining 136 (35.3%) were categorized as high risk. Compared to EPclin low-risk women, EPclin high-risk patients were more likely to experience distant recurrence (HR 4.6, 95% CI 1.4-15.2; p = 0.004). At 10 years post-diagnosis, EPclin low-risk women who received endocrine therapy alone had a DRFS of 97% (95% CI 93-99%). Conversely, EPclin high-risk women had a DRFS of only 76% (95% CI 67-82%). Conclusions: The EPclin score is highly associated with DRFS in pre-menopausal women who received adjuvant endocrine therapy alone. Based on these data, pre-menopausal women with EPclin low-risk breast cancer may safely forgo adjuvant chemotherapy in addition to endocrine therapy.

Triple-negative breast cancer is viewed clinically as an aggressive subgroup of breast cancer. In fact, most triple-negative breast cancers are poor-prognosis tumors with a complex genomic landscape. However, triple-negative disease is vastly heterogeneous, encompassing multiple entities with marked genetic, transcriptional, histologic, and clinical differences, with neoplasms in this group ranging from low to high grade. Among the less common low-grade triple-negative lesions, two large subgroups, both with a rather indolent behavior, can be distinguished: a low-grade triple-negative breast neoplasia family, which includes nonobligate precursors of triple-negative breast cancer, and, despite being low-grade, harbors the complex genomic landscape of usual triple-negative breast cancer, and the salivary gland-like tumors of the breast, lacking all the cardinal molecular features of conventional triple-negative breast cancer and underpinned by specific fusion genes or hotspot mutations, which may be of diagnostic and possibly therapeutic utility. Progression to high-grade triple-negative breast cancer likely occurs in both subgroups but at different rates. In this review, we describe the heterogeneity of triple-negative disease, focusing on the histologic and molecular features of the low-grade lesions. Recognition that triple-negative breast cancer is an operational term and that triple-negative disease is heterogeneous and includes low-grade forms driven by distinct sets of genetic alterations is germane to the successful implementation of precision medicine.

Background:\ud The prognostic value of lymphovascular invasion (LVI) in breast cancer (BC) has been demonstrated in several independent studies. However, identification of driver molecules for LVI remains a challenging task. Large-scale transcriptomic profiling of histologically validated LVI can potentially identify genes that regulate LVI.\ud \ud Methods:\ud Integrative bio-informatics analyses of the METABRIC study were performed utilising a subset of strictly defined LVI using histological and immunohistochemical (IHC) criteria. ARHGAP18 was among the top differentially expressed genes between LVI+ and LVI− BC with a 1.8-fold change. The prognostic impact of ARHGAP18 gene expression was assessed in the METABRIC data set (n=1980) and externally validated using the online BC gene expression data sets utilising bc-GenExMiner v4.0 (n=2016). Subsequently, ARHGAP18 protein expression was assessed on a large cohort of invasive BC (n=959) with long-term follow-up using IHC.\ud \ud Results:\ud Pooled analysis of ARHGAP18 mRNA expression showed that overexpression was associated with better outcome (P

Some previous studies have reported that the chemokine (C-C motif) receptor 7 (CCR7) plays a role in breast cancer, is associated with lymph node metastasis and drives the site of distant metastasis. However, the impact of its expression on patient outcome and its association with tumour infiltrating inflammatory cells remain to be validated. We evaluated CCR7 protein expression by immunohistochemistry in a large well characterized cohort (n = 866) of early invasive primary breast cancers. CCR7 was expressed in the cytoplasm and membrane of tumour cells. We observed a weak positive association of high CCR7 expression when in either cellular component, but not both together, with axillary lymph node stage 3 tumours (p = 0.043). Logistic regression analysis of lymph node stage revealed no independent predictive value for CCR7 expression. CCR7 expression was higher in HER2 positive tumours (p = 0.03) and associated with positive CD68+ FOXP3+ tumour infiltrating cells. CCR7 staining was negatively associated with CD3+ cells. There was no significant association of CCR7 expression with breast cancer recurrence or survival. We conclude that while CCR7 is not a useful biomarker for predicting lymph node metastasis, it may reflect altered intra- and inter-cellular signalling related to the immune microenvironment. The subcellular localization of CCR7 appears to affect the nature of these interactions.