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Peritoneal mesothelioma is a rare and sometimes lethal malignancy that presents a clinical challenge for both diagnosis and management. Recent studies have led to a better understanding of the molecular biology of peritoneal mesothelioma. Translation of the emerging data into better treatments and outcome is needed. From two patients with peritoneal mesothelioma, we derived whole genome sequences, RNA expression profiles, and targeted deep sequencing data. Molecular data were made available for translation into a clinical treatment plan. Treatment responses and outcomes were later examined in the context of molecular findings. Molecular studies presented here provide the first reported whole genome sequences of peritoneal mesothelioma. Mutations in known mesothelioma-related genes NF2, CDKN2A, LATS2, amongst others, were identified. Activation of MET-related signaling pathways was demonstrated in both cases. A hypermutated phenotype was observed in one case (434 vs. 18 single nucleotide variants) and was associated with a favourable outcome despite sarcomatoid histology and multifocal disease. This study represents the first report of whole genome analyses of peritoneal mesothelioma, a key step in the understanding and treatment of this disease.

Venous invasion (VI) is a powerful prognostic factor in colorectal cancer (CRC) that is widely underreported. The ability of elastin stains to improve VI detection is now recognized in several international CRC pathology protocols. However, concerns related to the cost and time required to perform and evaluate these stains in addition to routine hematoxylin and eosin (H&E) stains remains a barrier to their wider use. We therefore sought to determine whether an elastin trichrome (ET) stain could be used as a "stand-alone" stain in CRC resections, by comparing the sensitivity, accuracy, and reproducibility of detection of CAP-mandated prognostic factors using ET and H&E stains. Representative H&E- and ET-stained slides from 50 CRC resections, including a representative mix of stages and prognostic factors, were used to generate 2 study sets. Each case was represented by H&E slides in 1 study set and by corresponding ET slides from the same blocks in the other study set. Ten observers (3 academic gastrointestinal [GI] pathologists, 4 community pathologists, 3 fellows) evaluated each study set for CAP-mandated prognostic factors. ET outperformed H&E in the assessment of VI with respect to detection rates (50% vs. 28.6%; P<0.0001), accuracy (82% vs. 59%, P<0.0001), and reproducibility (k=0.554 vs. 0.394). No significant differences between ET and H&E were observed for other features evaluated. In a poststudy survey, most observers considered the ease and speed of assessment at least equivalent for ET and H&E for most prognostic factors, and felt that ET would be feasible as a stand-alone stain in practice. If validated by others, our findings support the use of ET, rather than H&E, as the primary stain for the evaluation of CRC resections., Competing Interests: Conflicts of Interest and Source of Funding: The authors have disclosed that they have no significant relationships with, or financial interest in, any commercial companies pertaining to this article., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Accurate subtyping of ovarian carcinomas is an increasingly critical and often challenging diagnostic process. This work focuses on the development of an automatic classification model for ovarian carcinoma subtyping. Specifically, we present a novel clinically inspired contextual model for histopathology image subtyping of ovarian carcinomas. A whole slide image is modelled using a collection of tissue patches extracted at multiple magnifications. An efficient and effective feature learning strategy is used for feature representation of a tissue patch. The locations of salient, discriminative tissue regions are treated as latent variables allowing the model to explicitly ignore portions of the large tissue section that are unimportant for classification. These latent variables are considered in a structured formulation to model the contextual information represented from the multi-magnification analysis of tissues. A novel, structured latent support vector machine formulation is defined and used to combine information from multiple magnifications while simultaneously operating within the latent variable framework. The structural and contextual nature of our method addresses the challenges of intra-class variation and pathologists' workload, which are prevalent in histopathology image classification. Extensive experiments on a dataset of 133 patients demonstrate the efficacy and accuracy of the proposed method against state-of-the-art approaches for histopathology image classification. We achieve an average multi-class classification accuracy of 90%, outperforming existing works while obtaining substantial agreement with six clinicians tested on the same dataset., (Copyright © 2017 Elsevier B.V. All rights reserved.)

We studied the whole-genome point mutation and structural variation patterns of 133 tumors (59 high-grade serous (HGSC), 35 clear cell (CCOC), 29 endometrioid (ENOC), and 10 adult granulosa cell (GCT)) as a substrate for class discovery in ovarian cancer. Ab initio clustering of integrated point mutation and structural variation signatures identified seven subgroups both between and within histotypes. Prevalence of foldback inversions identified a prognostically significant HGSC group associated with inferior survival. This finding was recapitulated in two independent cohorts (n = 576 cases), transcending BRCA1 and BRCA2 mutation and gene expression features of HGSC. CCOC cancers grouped according to APOBEC deamination (26%) and age-related mutational signatures (40%). ENOCs were divided by cases with microsatellite instability (28%), with a distinct mismatch-repair mutation signature. Taken together, our work establishes the potency of the somatic genome, reflective of diverse DNA repair deficiencies, to stratify ovarian cancers into distinct biological strata within the major histotypes.

Context: It has been shown that ovarian carcinoma subtypes are distinct pathologic entities with differing prognostic and therapeutic implications. Histotyping by pathologists has good reproducibility, but occasional cases are challenging and require immunohistochemistry and subspecialty consultation. Motivated by the need for more accurate and reproducible diagnoses and to facilitate pathologists' workflow, we propose an automatic framework for ovarian carcinoma classification., Materials and Methods: Our method is inspired by pathologists' workflow. We analyse imaged tissues at two magnification levels and extract clinically-inspired color, texture, and segmentation-based shape descriptors using image-processing methods. We propose a carefully designed machine learning technique composed of four modules: A dissimilarity matrix, dimensionality reduction, feature selection and a support vector machine classifier to separate the five ovarian carcinoma subtypes using the extracted features., Results: This paper presents the details of our implementation and its validation on a clinically derived dataset of eighty high-resolution histopathology images. The proposed system achieved a multiclass classification accuracy of 95.0% when classifying unseen tissues. Assessment of the classifier's confusion (confusion matrix) between the five different ovarian carcinoma subtypes agrees with clinician's confusion and reflects the difficulty in diagnosing endometrioid and serous carcinomas., Conclusions: Our results from this first study highlight the difficulty of ovarian carcinoma diagnosis which originate from the intrinsic class-imbalance observed among subtypes and suggest that the automatic analysis of ovarian carcinoma subtypes could be valuable to clinician's diagnostic procedure by providing a second opinion.

Many women with ovarian endometrioid carcinoma present with concurrent endometrial carcinoma. Organ-confined and low-grade synchronous endometrial and ovarian tumors (SEOs) clinically behave as independent primary tumors rather than a single advanced-stage carcinoma. We used 18 SEOs to investigate the ancestral relationship between the endometrial and ovarian components. Based on both targeted and exome sequencing, 17 of 18 patient cases of simultaneous cancer of the endometrium and ovary from our series showed evidence of a clonal relationship, ie, primary tumor and metastasis. Eleven patient cases fulfilled clinicopathological criteria that would lead to classification as independent endometrial and ovarian primary carcinomas, including being of FIGO stage T1a/1A, with organ-restricted growth and without surface involvement; 10 of 11 of these cases showed evidence of clonality. Our observations suggest that the disseminating cells amongst SEOs are restricted to physically accessible and microenvironment-compatible sites yet remain indolent, without the capacity for further dissemination., (© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Endometriosis is a significant risk factor for clear cell and endometrioid ovarian cancers and is often found contiguous with these cancers. Using whole-genome shotgun sequencing of seven clear cell ovarian carcinomas (CCC) and targeted sequencing in synchronous endometriosis, we have investigated how this carcinoma may evolve from endometriosis. In every case we observed multiple tumour-associated somatic mutations in at least one concurrent endometriotic lesion. ARID1A and PIK3CA mutations appeared consistently in concurrent endometriosis when present in the primary CCC. In several cases, one or more endometriotic lesions carried the near-complete complement of somatic mutations present in the index CCC tumour. Ancestral mutations were detected in both tumour-adjacent and -distant endometriotic lesions, regardless of any cytological atypia. These findings provide objective evidence that multifocal benign endometriotic lesions are clonally related and that CCCs arising in these patients progress from endometriotic lesions that may already carry sufficient cancer-associated mutations to be considered neoplasms themselves, albeit with low malignant potential. We speculate that genomically distinct classes of endometriosis exist and that ovarian endometriosis with high mutational burden represents one class at high risk for malignant transformation., (© 2015 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.)

Importance: E-cadherin (CDH1) is a cancer predisposition gene mutated in families meeting clinically defined hereditary diffuse gastric cancer (HDGC). Reliable estimates of cancer risk and spectrum in germline mutation carriers are essential for management. For families without CDH1 mutations, genetic-based risk stratification has not been possible, resulting in limited clinical options., Objectives: To derive accurate estimates of gastric and breast cancer risks in CDH1 mutation carriers and determine if germline mutations in other genes are associated with HDGC., Design, Setting, and Participants: Testing for CDH1 germline mutations was performed on 183 index cases meeting clinical criteria for HDGC. Penetrance was derived from 75 mutation-positive families from within this and other cohorts, comprising 3858 probands (353 with gastric cancer and 89 with breast cancer). Germline DNA from 144 HDGC probands lacking CDH1 mutations was screened using multiplexed targeted sequencing for 55 cancer-associated genes., Main Outcomes and Measures: Accurate estimates of gastric and breast cancer risks in CDH1 mutation carriers and the relative contribution of other cancer predisposition genes in familial gastric cancers., Results: Thirty-one distinct pathogenic CDH1 mutations (14 novel) were identified in 34 of 183 index cases (19%). By the age of 80 years, the cumulative incidence of gastric cancer was 70% (95% CI, 59%-80%) for males and 56% (95% CI, 44%-69%) for females, and the risk of breast cancer for females was 42% (95% CI, 23%-68%). In CDH1 mutation-negative index cases, candidate mutations were identified in 16 of 144 probands (11%), including mutations within genes of high and moderate penetrance: CTNNA1, BRCA2, STK11, SDHB, PRSS1, ATM, MSR1, and PALB2., Conclusions and Relevance: This is the largest reported series of CDH1 mutation carriers, providing more precise estimates of age-associated risks of gastric and breast cancer that will improve counseling of unaffected carriers. In HDGC families lacking CDH1 mutations, testing of CTNNA1 and other tumor suppressor genes should be considered. Clinically defined HDGC families can harbor mutations in genes (ie, BRCA2) with different clinical ramifications from CDH1. Therefore, we propose that HDGC syndrome may be best defined by mutations in CDH1 and closely related genes, rather than through clinical criteria that capture families with heterogeneous susceptibility profiles.

Aims: Following the introduction of colorectal cancer screening programmes throughout Canada, it became necessary to standardise the diagnosis of colorectal adenomas. Canadian guidelines for standardised reporting of adenomas were developed in 2011. The aims of the present study were (a) to assess interobserver variability in the classification of dysplasia and architecture in adenomas and (b) to determine if interobserver variability could be improved by the adoption of criteria specified in the national guidelines., Methods: An a priori power analysis was used to determine an adequate number of cases and participants. Twelve pathologists independently classified 40 whole-slide images of adenomas according to architecture and dysplasia grade. Following a wash-out period, participants were provided with the national guidelines and asked to reclassify the study set., Results: At baseline, there was moderate interobserver agreement for architecture (K=0.4700; 95% CI 0.4427 to 0.4972) and dysplasia grade (K=0.5680; 95% CI 0.5299 to 0.6062). Following distribution of the guidelines, there was improved interobserver agreement in assessing architecture (K=0.5403; 95% CI 0.5133 to 0.5674)). For dysplasia grade, overall interobserver agreement remained moderate but decreased significantly (K=0.4833; 95% CI 0.4452 to 0.5215). Half of the cases contained high-grade dysplasia (HGD). Two pathologists diagnosed HGD in ≥75% of cases., Conclusions: The improvement in interobserver agreement in classifying adenoma architecture suggests that national guidelines can be useful in disseminating knowledge, however, the variability in the diagnosis of HGD, even following guideline review suggests the need for ongoing knowledge-transfer exercises.

ARID1A/BAF250a has been recently implicated as a tumor suppressor in gastric cancer. We sought to clarify the clinical significance of BAF250a/ARID1A in relation to other clinical parameters and relevant biomarkers in gastric carcinoma. Cases from 2 separate cohorts of patients with gastric carcinoma from Vancouver (n = 173) and Toronto (n = 80) were selected for the construction of tissue microarrays, which were used to assess the immunohistochemical status of BAF250a (anti-ARID1A), mismatch repair proteins and p53, as well as in situ hybridization for HER2 amplification and Epstein-Barr virus infection. The Toronto cohort contained a higher proportion of early stage cases (P = .019) and a smaller proportion of cases from the proximal stomach (P < .001). Overall, immunohistochemical loss of BAF250a was observed in 22.5% of gastric adenocarcinomas from the Vancouver group and 20% from Toronto. In both cohorts, loss of BAF250a was positively associated with loss of mismatch repair protein expression (P < .0001 and P = .035, respectively). Loss of BAF250a expression was independently associated with poor overall survival in the Toronto cohort (P = .0015), whereas no significant association with survival was observed in the Vancouver cohort. BAF250a loss was not significantly associated with any additional clinical parameters in either cohort. HER2 amplification was confirmed as a negative prognostic factor in both cohorts. These findings suggest that ARID1A/BAF250a may be of prognostic significance in a subset of patients with early stage gastric cancer and that pathological assessment should increasingly use a multimarker approach., (Copyright © 2014 Elsevier Inc. All rights reserved.)