Primary mammary angiosarcomas harbor frequent mutations in KDR and PIK3CA and show evidence of distinct pathogenesis.

Angiosarcoma (AS) is the most frequent primary sarcoma of the breast but nevertheless remains uncommon, accounting for <0.05% of breast malignancies. Secondary mammary AS arise following radiation therapy for breast cancer, in contrast to primary AS which occur sporadically. Essentially all show aggressive clinical behavior independent of histologic grade and most are treated by mastectomy. MYC amplification is frequently identified in radiation-induced AS but only rarely in primary mammary AS (PMAS). As a heterogeneous group, AS from various anatomic sites have been shown to harbor recurrent alterations in TP53, MAP kinase pathway genes, and genes involved in angiogenic signaling including KDR (VEGFR2) and PTPRB. In part due to its rarity, the pathogenesis of PMAS has not been fully characterized. In this study, we examined the clinical, pathologic, and genomic features of ten cases of PMAS, including one patient with bilateral disease. Recurrent genomic alterations were identified in KDR (70%), PIK3CA/PIK3R1 (70%), and PTPRB (30%), each at higher frequencies than reported in AS across all sites. Six tumors harbored a KDR p.T771R hotspot mutation, and all seven KDR-mutant cases showed evidence suggestive of biallelism (four with loss of heterozygosity and three with two aberrations). Of the seven tumors with PI3K alterations, six harbored pathogenic mutations other than in the canonical PIK3CA residues which are most frequent in breast cancer. Three AS were hypermutated (≥10 mutations/megabase (Mb)); hypermutation was seen concurrent with KDR or PIK3CA mutations. The patient with bilateral disease demonstrated shared alterations, indicative of contralateral metastasis. No MYC or TP53 aberrations were detected in this series. Immunohistochemistry for VEGFR2 was unable to discriminate between KDR-mutant tumors and benign vascular lesions of the breast. These findings highlight the underrecognized frequency of KDR and PIK3CA mutation in PMAS, and a significant subset with hypermutation, suggesting a pathogenesis distinct from other AS.

Whole-exome analysis of metaplastic breast carcinomas with extensive osseous differentiation.

AIMS: Metaplastic breast carcinoma (MBC) is a rare type of triple-negative breast cancer that shows vast histological and genetic heterogeneity. Osseous differentiation can be found in different subtypes of MBC. Whether MBCs with osseous differentiation are underpinned by specific genetic alterations has yet to be defined. The aim of this study was to investigate the repertoire of somatic mutations and copy number alterations (CNAs) in three MBCs with extensive osseous differentiation. METHODS AND RESULTS: Tumour and normal DNA samples from three MBCs with extensive osseous differentiation were subjected to whole-exome sequencing. Somatic mutations, CNAs and mutational signatures were determined by use of a validated bioinformatics pipeline. Our analyses revealed clonal TP53 hotspot mutations associated with loss of heterozygosity of the wild-type allele coupled with mutations affecting genes related to the Wnt and/or the phosphoinositide 3-kinase-AKT-mammalian target of rapamycin pathways in all cases analysed. All cases showed a dominant mutational signature 1, with two cases showing a secondary signature 3 in addition to other features of homologous recombination DNA repair defects. The oncostatin M receptor gene, which plays a role in mesenchymal differentiation and bone formation, was found to be mutated in two MBCs with extensive osseous differentiation and in none of 35 previously published 35 MBCs. CONCLUSION: Our findings suggest that MBCs with osseous differentiation have somatic mutations similar to those of other forms of MBC.

Whole-exome sequencing and RNA sequencing analyses of acinic cell carcinomas of the breast.

AIMS: Acinic cell carcinoma (ACC) of the breast is a rare histological form of triple-negative breast cancer (TNBC). Despite its unique histology, targeted sequencing analysis has failed to identify recurrent genetic alterations other than those found in common forms of TNBC. Here we subjected three breast ACCs to whole-exome and RNA sequencing to determine whether they would harbour a pathognomonic genetic alteration. METHODS AND RESULTS: DNA and RNA samples from three breast ACCs were subjected to whole-exome sequencing and RNA-sequencing, respectively. Somatic mutations, copy number alterations, mutational signatures and fusion genes were determined with state-of-the-art bioinformatics methods. Our analyses revealed TP53 hotspot mutations associated with loss of heterozygosity of the wild-type allele in two cases. Mutations affecting homologous recombination DNA repair-related genes were found in two cases, and an MLH1 pathogenic germline variant was found in one case. In addition, copy number analysis revealed the presence of a somatic BRCA1 homozygous deletion and focal amplification of 12q14.3-12q21.1, encompassing MDM2, HMGA2, FRS2, and PTPRB. No oncogenic in-frame fusion transcript was identified in the three breast ACCs analysed. CONCLUSIONS: No pathognomonic genetic alterations were detected in the breast ACCs analysed. These tumours have somatic genetic alterations similar to those of common forms of TNBC, and may show homologous recombination deficiency or microsatellite instability. These findings provide further insights into why breast ACCs, which are usually clinically indolent, may evolve into or in parallel with high-grade TNBC.

EZH2 protein expression in normal breast epithelium and risk of breast cancer: results from the Nurses' Health Studies.

BACKGROUND: Enhancer of zeste homolog 2 (EZH2) is a polycomb-group protein that is involved in stem cell renewal and carcinogenesis. In breast cancer, increased EZH2 expression is associated with aggressiveness and has been suggested to identify normal breast epithelium at increased risk of breast cancer development. However, the association between EZH2 expression in benign breast tissue and breast cancer risk has not previously been evaluated in a large prospective cohort. METHODS: We examined the association between EZH2 protein expression and subsequent breast cancer risk using logistic regression in a nested case-control study of benign breast disease (BBD) and breast cancer within the Nurses' Health Studies. EZH2 immunohistochemical expression in normal breast epithelium and stroma was evaluated by computational image analysis and its association with breast cancer risk was analyzed after adjusting for matching factors between cases and controls, the concomitant BBD diagnosis, and the Ki67 proliferation index. RESULTS: Women with a breast biopsy in which more than 20% of normal epithelial cells expressed EZH2 had a significantly increased risk of developing breast cancer (odds ratio (OR) 2.95, 95% confidence interval (CI) 1.11-7.84) compared to women with less than 10% EZH2 epithelial expression. The risk of developing breast cancer increased for each 5% increase in EZH2 expression (OR 1.22, 95% CI 1.02-1.46, p value 0.026). Additionally, women with high EZH2 expression and low estrogen receptor (ER) expression had a 4-fold higher risk of breast cancer compared to women with low EZH2 and low ER expression (OR 4.02, 95% CI 1.29-12.59). CONCLUSIONS: These results provide further evidence that EZH2 expression in the normal breast epithelium is independently associated with breast cancer risk and might be used to assist in risk stratification for women with benign breast biopsies.

Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer.

Importance: Application of deep learning algorithms to whole-slide pathology images can potentially improve diagnostic accuracy and efficiency. Objective: Assess the performance of automated deep learning algorithms at detecting metastases in hematoxylin and eosin-stained tissue sections of lymph nodes of women with breast cancer and compare it with pathologists' diagnoses in a diagnostic setting. Design, Setting, and Participants: Researcher challenge competition (CAMELYON16) to develop automated solutions for detecting lymph node metastases (November 2015-November 2016). A training data set of whole-slide images from 2 centers in the Netherlands with (n = 110) and without (n = 160) nodal metastases verified by immunohistochemical staining were provided to challenge participants to build algorithms. Algorithm performance was evaluated in an independent test set of 129 whole-slide images (49 with and 80 without metastases). The same test set of corresponding glass slides was also evaluated by a panel of 11 pathologists with time constraint (WTC) from the Netherlands to ascertain likelihood of nodal metastases for each slide in a flexible 2-hour session, simulating routine pathology workflow, and by 1 pathologist without time constraint (WOTC). Exposures: Deep learning algorithms submitted as part of a challenge competition or pathologist interpretation. Main Outcomes and Measures: The presence of specific metastatic foci and the absence vs presence of lymph node metastasis in a slide or image using receiver operating characteristic curve analysis. The 11 pathologists participating in the simulation exercise rated their diagnostic confidence as definitely normal, probably normal, equivocal, probably tumor, or definitely tumor. Results: The area under the receiver operating characteristic curve (AUC) for the algorithms ranged from 0.556 to 0.994. The top-performing algorithm achieved a lesion-level, true-positive fraction comparable with that of the pathologist WOTC (72.4% [95% CI, 64.3%-80.4%]) at a mean of 0.0125 false-positives per normal whole-slide image. For the whole-slide image classification task, the best algorithm (AUC, 0.994 [95% CI, 0.983-0.999]) performed significantly better than the pathologists WTC in a diagnostic simulation (mean AUC, 0.810 [range, 0.738-0.884]; P < .001). The top 5 algorithms had a mean AUC that was comparable with the pathologist interpreting the slides in the absence of time constraints (mean AUC, 0.960 [range, 0.923-0.994] for the top 5 algorithms vs 0.966 [95% CI, 0.927-0.998] for the pathologist WOTC). Conclusions and Relevance: In the setting of a challenge competition, some deep learning algorithms achieved better diagnostic performance than a panel of 11 pathologists participating in a simulation exercise designed to mimic routine pathology workflow; algorithm performance was comparable with an expert pathologist interpreting whole-slide images without time constraints. Whether this approach has clinical utility will require evaluation in a clinical setting.

Precision Cancer Diagnostics: Tracking Genomic Evolution in Clinical Trials.

In a Perspective, Francisco Beca and Andrew Beck discuss Charles Swanton and colleagues' accompanying Research Article on somatic mutations in patients with inflammatory breast cancer treated in a Phase II clinical trial.

Intratumor Heterogeneity in Breast Cancer.

Intratumor heterogeneity is the main obstacle to effective cancer treatment and personalized medicine. Both genetic and epigenetic sources of intratumor heterogeneity are well recognized and several technologies have been developed for their characterization. With the technological advances in recent years, investigators are now elucidating intratumor heterogeneity at the single cell level and in situ. However, translating the accumulated knowledge about intratumor heterogeneity to clinical practice has been slow. We are certain that better understanding of the composition and evolution of tumors during disease progression and treatment will improve cancer diagnosis and the design of therapies. Here we review some of the most important considerations related to intratumor heterogeneity. We discuss both genetic and epigenetic sources of intratumor heterogeneity and review experimental approaches that are commonly used to quantify it. We also discuss the impact of intratumor heterogeneity on cancer diagnosis and treatment and share our perspectives on the future of this field.

Altered PPP2R2A and Cyclin D1 expression defines a subgroup of aggressive luminal-like breast cancer.

BACKGROUND: PPP2R2A deletions were recently linked to a subgroup of luminal breast carcinoma (BC) that exhibits poor survival. This subgroup also exhibited amplification of a chromosome region containing the Cyclin D1 coding gene, CCND1. Therefore, we aimed to investigate whether a combination of PPP2R2A (B55α) and Cyclin D1 expression statuses evaluated by immunohistochemistry (IHC) could define a subgroup of luminal BC that exhibits poor survival. METHODS: First we conducted a retrospective cohort study using sequencing data from The Cancer Genome Atlas initiative to correlate PPP2R2A copy number alteration (CNA) status with its expression level and the corresponding overall survival (OS). Next, also using a retrospective cohort study design, we evaluated the PPP2R2A (B55α) expression levels by IHC in a total of 807 BC patients from two independent cohorts (discovery cohort n = 349 and validation cohort n = 458). Cyclin D1 expression was also evaluated, and the PPP2R2A (B55α)(-/low)/Cyclin D1(high) phenotype was evaluated as a predictor of disease-free survival (DFS) and OS in luminal-like BC patients. RESULTS: Deletions in the PPP2R2A gene strongly correlate with lower mRNA expression and poorer OS. PPP2R2A (B55α)(-/low) carcinomas have significantly shorter DFS and OS. Furthermore, in univariate analysis, the PPP2R2A (B55α)(-/low)/Cyclin D1(high) phenotype is significantly associated with poorer DFS and OS. In a multivariate analysis, the PPP2R2A (B55α)(-/low)/Cyclin D1(high) phenotype is significantly associated with poor DFS, thus defining a group of luminal-like BC with higher risk of relapse. CONCLUSION: We demonstrate that BCs harboring PPP2R2A deletions are associated with worse OS. Moreover, this is the first study to demonstrate that the combination of altered PPP2R2A (B55α) and high Cyclin D1 expression by IHC defines a subgroup of luminal-like BC patients with a high risk of relapse and death.

Improved malignancy prediction by B3 breast lesions subclassification.

Core-needle biopsy (CNB) of breast lesions can be classified into 5 categories according to lesion type and associated risk of malignancy. B3 category (lesion of uncertain malignant potential) constitutes a challenging problem in clinical decision, with most ending in excisional biopsy. Therefore, the aim of this study was to establish the incidence of malignancy on excision biopsy of B3 lesions and assess if subclassification (in B3a and B3b categories) according to the presence of atypia in otherwise B3 lesions better predicts malignancy on excision. Forty-eight cases with diagnosis of B3 lesion on CNB and matched surgical excision specimen were included to evaluate the positive predictive value (PPV) and odds for malignancy in CNB. All cases were further subclassified into B3a and B3b categories. B3 category lesions had an overall PPV for malignancy of 12.5% and significant low odds of malignancy of 0.14. When subclassified, B3b (lesions with atypia) demonstrated a higher PPV for malignancy (36.36%) with a nonsignificant odds. Inversely, B3a (lesions without atypia) demonstrated a PPV for malignancy of only 5.41% and a significant low odds of malignancy of only 0.06. The described low rate of malignancy in some of B3 lesions additionally reinforces the practice of avoiding surgical excision in selected patients and provides data that additionally support B3 lesion subclassification according to the presence of atypia. Subclassification of B3 category can further refine the current classification of associated risk of malignancy with possible implications in clinical management.

Stromal MED12 exon 2 mutations in complex fibroadenomas of the breast.

AIMS: Here we explore the presence of mediator complex subunit 12 (MED12) exon 2 and telomerase reverse transcriptase (TERT) promoter hotspot mutations in complex fibroadenomas (CFAs) of the breast. METHODS: The stromal components from 18 CFAs were subjected to Sanger sequencing of MED12 exon 2 and the TERT promoter hotspot loci. The epithelial and stromal components of two MED12 mutated CFAs were subjected to laser capture microdissection, and Sanger sequencing of MED12 exon 2, TERT promoter and PIK3CA exons 9 and 20, separately. RESULTS: MED12 exon 2 mutations were identified in the stroma of 17% of CFAs. The analyses of epithelial and stromal components, microdissected separately, revealed that MED12 mutations were restricted to the stroma. No TERT promoter or PIK3CA mutations in exons 9 and 20 were detected in analysed CFAs. CONCLUSIONS: Like conventional fibroadenomas, MED12 exon 2 mutations appear to be restricted to the stromal component of CFAs, supporting the notion that CFAs are stromal neoplasms.

The impact of mammographic screening on the subsequent breast cancer risk associated with biopsy-proven benign breast disease.

Data on the risk of breast cancer following a benign breast disease (BBD) diagnosis were derived predominantly from populations of women biopsied before the widespread use of mammographic screening and in whom these lesions were mostly incidental findings. Whether or not similar risk associations are seen when these lesions are detected in mammographically screened populations is unknown. To address this, we examined the variation in BBD and breast cancer risk associations by the calendar time of BBD diagnosis (pre- vs. post-mammography era [before vs. 1985 and after]) in a nested case-control study within the Nurses' Health Study (NHS) and NHSII BBD subcohort (488 cases; 1908 controls). We performed logistic regression analysis, adjusting for matching factors and potential confounders, to estimate odds ratio (ORs) and 95% confidence interval (CI) for the association between BBD subtype (non-proliferative, proliferative without atypia, proliferative with atypical hyperplasia (AH)) and subsequent breast cancer risk. When compared with non-proliferative lesions, both proliferative lesions without atypia (PWA) and AHs were associated with similar levels of risk in the pre-mammographic (pre) and post-mammographic (post) time periods (PWA: OR [95% CI] = 1.73 [1.27, 2.36] pre vs. 1.12 [0.73, 1.74] post; AH: 4.41 [2.90, 6.70] pre vs. 3.69 [2.21, 6.15] post). The interaction by mammography era was not statistically significant (p-interaction = 0.47). These results suggest that the risk associations reported for BBD subtypes in the pre-mammography era remain valid for BBD detected after the widespread implementation of mammographic screening.

Molecular analysis of TCGA breast cancer histologic types.

Breast cancer is classified into multiple distinct histologic types, and many of the rarer types have limited characterization. Here, we extend The Cancer Genome Atlas Breast Cancer (TCGA-BRCA) dataset with additional histologic type annotations, in a total of 1063 breast cancers. We analyze this extended dataset to define transcriptomic and genomic profiles of six rare special histologic types: cribriform, micropapillary, mucinous, papillary, metaplastic, and invasive carcinoma with medullary pattern. We show the broader applicability of our constructed special histologic type gene signatures in the TCGA Pan-Cancer Atlas dataset with a predictive model that detects mucinous histologic type across cancers of other organ systems. Using a normal mammary cell differentiation score analysis, we order histologic types into a continuum from stem cell-like to luminal progenitor-like to mature luminal-like. Finally, we classify TCGA-BRCA into 12 consensus groups based on integrated genomic and histological features. We present a rich openly accessible resource of histologic and genomic characterization of TCGA-BRCA to enable studies of the range of breast cancers.

The genomic landscape of metastatic histologic special types of invasive breast cancer.

Histologic special types of breast cancer (BC) account for ~20% of BCs. Large sequencing studies of metastatic BC have focused on invasive ductal carcinomas of no special type (IDC-NSTs). We sought to define the repertoire of somatic genetic alterations of metastatic histologic special types of BC. We reanalyzed targeted capture sequencing data of 309 special types of BC, including metastatic and primary invasive lobular carcinomas (ILCs; n = 132 and n = 127, respectively), mixed mucinous (n = 5 metastatic and n = 14 primary), micropapillary (n = 12 metastatic and n = 8 primary), and metaplastic BCs (n = 6 metastatic and n = 5 primary), and compared metastatic histologic special types of BC to metastatic IDC-NSTs matched according to clinicopathologic characteristics and to primary special type BCs. The genomic profiles of metastatic and primary special types of BC were similar. Important differences, however, were noted: metastatic ILCs harbored a higher frequency of genetic alterations in TP53, ESR1, FAT1, RFWD2, and NF1 than primary ILCs, and in CDH1, PIK3CA, ERBB2, TBX3, NCOR1, and RFWD2 than metastatic IDC-NSTs. Metastatic ILCs displayed a higher mutational burden, and more frequently dominant APOBEC mutational signatures than primary ILCs and matched metastatic IDC-NSTs. ESR1 and NCOR mutations were frequently detected in metastatic mixed mucinous BCs, whereas PIK3CA and TP53 were the most frequently altered genes in metastatic micropapillary and metaplastic BCs, respectively. Taken together, primary and metastatic BCs histologic special types have remarkably similar repertoires of somatic genetic alterations. Metastatic ILCs more frequently harbor APOBEC mutational signatures than primary ILCs and metastatic IDC-NSTs.

Ancillary Tests in Breast Cytology: A Practical Guide.

Utilization of fine-needle aspiration biopsy (FNAB) cytology for the diagnosis of diseases of the breast has been met with both excitement and uncertainty during the last couple of decades. Presently, FNAB for the diagnosis of primary and metastatic breast lesions is on the rise again. This is probably due to its fast turnaround time, cost efficiency, and minimal invasiveness, characteristics of this sampling modality which are particularly crucial for patients requiring frequent repeat biopsy in the setting of metastatic lesions. In this article, we will briefly review the main modern applications of FNAB of the breast when coupled with contemporary ancillary techniques. Such contemporary ancillary techniques range from classic immunocytochemistry (ICC) to the most modern molecular techniques, particularly next-generation sequencing. Coupled with contemporary ICC and molecular methods, FNAB of the breast can be used for several applications. The applications reviewed in this article include the primary diagnosis of a breast lesion, the identification of the breast as a primary source of a metastatic lesion, the evaluation of breast prognostic/predictive markers, and the tracking of tumor evolution. In our opinion, FNAB of the breast is an ideal sampling method, sharing many of the advantages of truly liquid and of tissue biopsies. Ultimately, we aim at demystifying the complexity of many of the challenges traditionally associated with the application of ancillary techniques to FNAB of the breast and provide insights into some of the most cutting-edge and clinically useful application scenarios.

Outcome of radial scar/complex sclerosing lesion associated with epithelial proliferations with atypia diagnosed on breast core biopsy: results from a multicentric UK-based study.

AIMS: The clinical significance of radial scar (RS)/complex sclerosing lesion (CSL) with high-risk lesions (epithelial atypia) diagnosed on needle core biopsy is not well defined. We aimed at assessing the upgrade rate to ductal carcinoma in situ (DCIS) and invasive carcinoma on the surgical excision specimen in a large cohort with RS/CSL associated with atypia. METHODS: 157 women with a needle core biopsy diagnosis of a RS/CSL with atypia and follow-up histology were studied. Histological findings, including different forms of the atypical lesions and final histological outcome in the excision specimens, were retrieved and analysed, and the upgrade rates for malignancy and for invasive carcinoma were calculated. RESULTS: 69.43% of the cases were associated with atypical ductal hyperplasia (ADH) or atypia not otherwise classifiable, whereas lobular neoplasia was seen in 21.66%. On final histology, 39 cases were malignant (overall upgrade rate of 24.84%); 12 were invasive and 27 had DCIS. The upgrade differed according to the type of atypia and was highest for ADH (35%). When associated with lobular neoplasia, the upgrade rate was 11.76%. The upgrade rate's variability was also considerably lower when considering the upgrade to invasive carcinoma alone for any associated lesion. CONCLUSIONS: The upgrade rate for ADH diagnosed on needle core biopsy with RS is similar to that of ADH without RS and therefore should be managed similarly. RS associated with lobular neoplasia is less frequently associated with malignant outcome. Most lesions exhibiting some degree of atypia showed a similar upgrade rate to invasive carcinoma. Management of RS should be based on the concurrent atypical lesion.

SPOP Promotes Nanog Destruction to Suppress Stem Cell Traits and Prostate Cancer Progression.

Frequent SPOP mutation defines the molecular feature underlying one of seven sub-types of human prostate cancer (PrCa). However, it remains largely elusive how SPOP functions as a tumor suppressor in PrCa. Here, we report that SPOP suppresses stem cell traits of both embryonic stem cells and PrCa cells through promoting Nanog poly-ubiquitination and subsequent degradation. Mechanistically, Nanog, but not other pluripotency-determining factors including Oct4, Sox2, and Klf4, specifically interacts with SPOP via a conservative degron motif. Importantly, cancer-derived mutations in SPOP or at the Nanog-degron (S68Y) disrupt SPOP-mediated destruction of Nanog, leading to elevated cancer stem cell traits and PrCa progression. Notably, we identify the Pin1 oncoprotein as an upstream Nanog regulator that impairs its recognition by SPOP and thereby stabilizes Nanog. Thus, Pin1 inhibitors promote SPOP-mediated destruction of Nanog, which provides the molecular insight and rationale to use Pin1 inhibitor(s) for targeted therapies of PrCa patients with wild-type SPOP.

EN1 Is a Transcriptional Dependency in Triple-Negative Breast Cancer Associated with Brain Metastasis.

To define transcriptional dependencies of triple-negative breast cancer (TNBC), we identified transcription factors highly and specifically expressed in primary TNBCs and tested their requirement for cell growth in a panel of breast cancer cell lines. We found that EN1 (engrailed 1) is overexpressed in TNBCs and its downregulation preferentially and significantly reduced viability and tumorigenicity in TNBC cell lines. By integrating gene expression changes after EN1 downregulation with EN1 chromatin binding patterns, we identified genes involved in WNT and Hedgehog signaling, neurogenesis, and axonal guidance as direct EN1 transcriptional targets. Quantitative proteomic analyses of EN1-bound chromatin complexes revealed association with transcriptional repressors and coactivators including TLE3, TRIM24, TRIM28, and TRIM33. High expression of EN1 correlated with short overall survival and increased risk of developing brain metastases in patients with TNBC. Thus, EN1 is a prognostic marker and a potential therapeutic target in TNBC. SIGNIFICANCE: These findings show that the EN1 transcription factor regulates neurogenesis-related genes and is associated with brain metastasis in triple-negative breast cancer.

Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge.

Tumor proliferation is an important biomarker indicative of the prognosis of breast cancer patients. Assessment of tumor proliferation in a clinical setting is a highly subjective and labor-intensive task. Previous efforts to automate tumor proliferation assessment by image analysis only focused on mitosis detection in predefined tumor regions. However, in a real-world scenario, automatic mitosis detection should be performed in whole-slide images (WSIs) and an automatic method should be able to produce a tumor proliferation score given a WSI as input. To address this, we organized the TUmor Proliferation Assessment Challenge 2016 (TUPAC16) on prediction of tumor proliferation scores from WSIs. The challenge dataset consisted of 500 training and 321 testing breast cancer histopathology WSIs. In order to ensure fair and independent evaluation, only the ground truth for the training dataset was provided to the challenge participants. The first task of the challenge was to predict mitotic scores, i.e., to reproduce the manual method of assessing tumor proliferation by a pathologist. The second task was to predict the gene expression based PAM50 proliferation scores from the WSI. The best performing automatic method for the first task achieved a quadratic-weighted Cohen's kappa score of κ = 0.567, 95% CI [0.464, 0.671] between the predicted scores and the ground truth. For the second task, the predictions of the top method had a Spearman's correlation coefficient of r = 0.617, 95% CI [0.581 0.651] with the ground truth. This was the first comparison study that investigated tumor proliferation assessment from WSIs. The achieved results are promising given the difficulty of the tasks and weakly-labeled nature of the ground truth. However, further research is needed to improve the practical utility of image analysis methods for this task.

Androgen receptor expression in normal breast tissue and subsequent breast cancer risk.

Sex steroid hormone signaling is critical in the development of breast cancers, although the role of the androgen receptor remains unclear. This study evaluated androgen receptor (AR) expression in normal breast tissue as a potential marker of breast cancer risk. We conducted a nested case-control study of women with benign breast disease (BBD) within the Nurses' Health Studies. Epithelial AR expression was assessed by immunohistochemistry in normal tissue from the BBD biopsy and the percent of positive nuclei was estimated in ordinal categories of 10% for 78 breast cancer cases and 276 controls. Logistic regression models adjusting for the matching factors and BBD lesion type were used to calculate odds ratios (ORs) for the association between AR expression (tertiles: ≤10%, 11-30%, and >30%) and breast cancer risk. AR expression in normal breast tissue was not associated with subsequent breast cancer risk (ORT3vsT1 = 0.9, 95% CI = 0.4-1.8, p trend = 0.68). In comparison with low AR/low ER women, ORs of 0.4 (95% CI = 0.1-1.2) for high AR/high ER women, 1.8 (95% CI = 0.4-7.8) for low AR/high ER women, and 0.7 (95% CI = 0.3-1.6) for high AR/low ER women were observed (p interaction = 0.21). Ki67 did not modify the association between AR expression and breast cancer risk (p interaction = 0.75). There was little evidence for an overall association between AR expression in normal breast tissue and breast cancer risk. These findings did not show that the AR association varied by Ki67 expression in normal breast tissue, though there was suggestive heterogeneity by ER expression.