Hypertension and risk of endometrial cancer: a pooled analysis in the Epidemiology of Endometrial Cancer Consortium (E2C2).

BACKGROUND: The incidence rates of endometrial cancer (EC) are increasing, which may partly be explained by the rising prevalence of obesity, an established risk factor for EC. Hypertension, another component of metabolic syndrome, is also increasing in prevalence, and emerging evidence suggests that it may be associated with the development of certain cancers. The role of hypertension independent of other components of metabolic syndrome in the etiology of EC remains unclear. In this study we evaluated hypertension as an independent risk factor for EC and whether this association is modified by other established risk factors. METHODS: We included 15,631 EC cases and 42,239 controls matched on age, race, and study-specific factors from 29 studies in the Epidemiology of Endometrial Cancer Consortium. We used multivariable unconditional logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (CIs) to evaluate the association between hypertension and EC and whether this association differed by study design, race/ethnicity, body mass index, diabetes status, smoking status, or reproductive factors. RESULTS: Hypertension was associated with an increased risk of EC (OR=1.14, 95% CI:1.09-1.19). There was significant heterogeneity by study design (Phet<0.01), with a stronger magnitude of association observed among case-control vs. cohort studies. Stronger associations were also noted for pre-/peri-menopausal women and never users of postmenopausal hormone therapy. CONCLUSIONS: Hypertension is associated with EC risk independently from known risk factors. Future research should focus on biologic mechanisms underlying this association. IMPACT: This study provides evidence that hypertension may be an independent risk factor for EC.

Localized Endometrial Proliferations of Pregnancy are Clonal Glandular Outgrowths Characterized by PTEN Loss and PIK3CA Pathogenic Variants.

Gestational endometrium can demonstrate a spectrum of atypical but benign changes. One such lesion is localized endometrial proliferation of pregnancy (LEPP), first described in a series of 11 cases. To understand its biological and clinical importance, we explore the pathologic, immunophenotypic, and molecular features of this entity. Nine cases of LEPP identified in 15 years were retrieved from departmental archives and reviewed. Immunohistochemistry and next-generation sequencing using a comprehensive 446-gene panel were performed when the material was available. Eight cases were identified in curettage specimens performed after first-trimester pregnancy loss, and 1 in the basal plate of a mature placenta. The mean patient age was 35 (range 27-41) years. The mean lesion size was 6.3 (range 2-12) mm. Architectural patterns, often coexisting in the same case, included cribriform (n = 7), solid (n = 5), villoglandular (n = 2), papillary (n = 2), and micropapillary (n = 1). Cytologic atypia was mild in 7 cases and moderate in 2. Mitotic activity was low (up to 3 per 2.4 mm2). All lesions were associated with neutrophils. Background Arias-Stella phenomenon was present in 4 cases. Immunohistochemistry was performed in 7 LEPP, all of which demonstrated wildtype p53, retained MSH6 and PMS2, membranous beta-catenin, and positive estrogen receptor (mean 71%) and progesterone receptor (mean 74%). All were negative for p40 except 1 case (focal weak positivity). PTEN was markedly reduced in background secretory glands in all cases; in 5/7, LEPP foci showed a complete absence of PTEN expression. PIK3CA pathogenic variants were identified in 4/4 cases sequenced; 3/4 had inactivating PTEN mutations. Follow-up, available in 8 patients (mean length = 51 months, range 7-161), was conservative with observation only and showed no persistence or adverse outcomes. LEPP is characterized by intraglandular cribriform/solid architecture, positive estrogen receptor/progesterone receptor, PTEN loss, and PIK3CA and PTEN mutations. Although our findings indicate that LEPP is neoplastic, for now, we advise against diagnosing LEPP as endometrial carcinoma or hyperplasia because LEPP has a particular clinicopathologic context (concurrent gestation), distinct morphology (purely intraepithelial complex growth), and indolent outcome. Thus, it should be distinguished from endometrial intraepithelial neoplasia and carcinoma for which therapeutic interventions are indicated.

Measuring Digital Pathology Throughput and Tissue Dropouts.

BACKGROUND: Digital pathology operations that precede viewing by a pathologist have a substantial impact on costs and fidelity of the digital image. Scan time and file size determine throughput and storage costs, whereas tissue omission during digital capture ("dropouts") compromises downstream interpretation. We compared how these variables differ across scanners. METHODS: A 212 slide set randomly selected from a gynecologic-gestational pathology practice was used to benchmark scan time, file size, and image completeness. Workflows included the Hamamatsu S210 scanner (operated under default and optimized profiles) and the Leica GT450. Digital tissue dropouts were detected by the aligned overlay of macroscopic glass slide camera images (reference) with images created by the slide scanners whole slide images. RESULTS: File size and scan time were highly correlated within each platform. Differences in GT450, default S210, and optimized S210 performance were seen in average file size (1.4 vs. 2.5 vs. 3.4 GB) and scan time (93 vs. 376 vs. 721 s). Dropouts were seen in 29.5% (186/631) of successful scans overall: from a low of 13.7% (29/212) for the optimized S210 profile, followed by 34.6% (73/211) for the GT450 and 40.4% (84/208) for the default profile S210 profile. Small dislodged fragments, "shards," were dropped in 22.2% (140/631) of slides, followed by tissue marginalized at the glass slide edges, 6.2% (39/631). "Unique dropouts," those for which no equivalent appeared elsewhere in the scan, occurred in only three slides. Of these, 67% (2/3) were "floaters" or contaminants from other cases. CONCLUSIONS: Scanning speed and resultant file size vary greatly by scanner type, scanner operation settings, and clinical specimen mix (tissue type, tissue area). Digital image fidelity as measured by tissue dropout frequency and dropout type also varies according to the tissue type and scanner. Dropped tissues very rarely (1/631) represent actual specimen tissues that are not represented elsewhere in the scan, so in most cases cannot alter the diagnosis. Digital pathology platforms vary in their output efficiency and image fidelity to the glass original and should be matched to the intended application.

Endometrial Tumor Classification by Histomorphology and Biomarkers in the Nurses' Health Study.

OBJECTIVE: Endometrial cancers have historically been classified by histomorphologic appearance, which is subject to interobserver disagreement. As molecular and biomarker testing has become increasingly available, the prognostic significance and accuracy of histomorphologic diagnoses have been questioned. To address these issues for a large, prospective cohort study, we provide the results of a centralized pathology review and biomarker analysis of all incidental endometrial carcinomas occurring between 1976 and 2012 in the Nurses' Health Study. METHODS: Routine histology of all (n = 360) cases was reviewed for histomorphologic diagnosis. Cases were subsequently planted in a tissue microarray to explore expression of a variety of biomarkers (e.g., ER, PR, p53, PTEN, PAX2, AMACR, HNF1ß, Napsin A, p16, PAX8, and GATA3). RESULTS: Histologic subtypes included endometrioid (87.2%), serous (5.6%), carcinosarcoma (3.9%), clear cell (1.7%), and mixed type (1.7%). Biomarker results within histologic subtypes were consistent with existing literature: abnormal p53 was frequent in serous cases (74%), and HNF1ß (67%), Napsin A (67%), and AMACR (83%) expression was frequent in clear cell carcinomas. Our dataset also allowed for examination of biomarker expression across non-preselected histologies. The results demonstrated that (1) HNF1ß was not specific for clear cell carcinoma, (2) TP53 mutations occurred across many histologies, and (3) GATA3 was expressed across multiple histotypes, with 75% of positive cases demonstrating high-grade features. CONCLUSIONS: Our findings establish the subtypes of endometrial cancer occurring in the Nurses' Health Study, corroborate the sensitivity of certain well-established biomarkers, and call into question previously identified associations between certain biomarkers (e.g., HNF1B) and particular histotypes.

Computational augmentation of neoplastic endometrial glands in digital pathology displays.

The pathologic diagnosis of neoplasia requires localization and classification of lesional tissue, a process that depends on the recognition of an abnormal spatial distribution of neoplastic elements relative to admixed normal background tissue. In endometrial intraepithelial neoplasia (EIN), a pre-cancer usually managed by hysterectomy, a clonally mutated proliferation of cytologically altered glands ('neoplastic-EIN') aggregates in clusters that also contain background non-neoplastic glands ('background-NL'). Here, we used image analysis to classify individual glands within endometrial tissue fragments as neoplastic-EIN or background-NL, and we used the distribution of predictions to localize foci diagnostic of EIN. Nuclear coordinates were automatically assigned and were used as vertices to generate Delaunay triangulations for each gland. Graph statistical variables were used to develop random forest algorithms to classify glands as neoplastic-EIN or background-NL. Individual glands in an independent validation set were scored by a 'ground truth' biomarker (PAX2 immunohistochemistry). We found that exclusion of small glands led to improvement in classification accuracy. Using an inclusion threshold of 200 nuclei per gland, our final model classification accuracy was 77.5% in the validation set, with a positive predictive value of 0.81. We leveraged this high positive predictive value in a point cloud overlay display to assist end-user identification of EIN foci. This study demonstrates that graph theory approaches applied to small-scale anatomic elements in the endometrium allow biologic classification by machine learning, and that spatial superimposition over large-scale tissue expanses can have practical diagnostic utility. We expect this augmented diagnostic approach to be generalizable to commonly encountered problems in other organ systems. © 2020 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Deciphering serous ovarian carcinoma histopathology and platinum response by convolutional neural networks.

BACKGROUND: Ovarian cancer causes 151,900 deaths per year worldwide. Treatment and prognosis are primarily determined by the histopathologic interpretation in combination with molecular diagnosis. However, the relationship between histopathology patterns and molecular alterations is not fully understood, and it is difficult to predict patients' chemotherapy response using the known clinical and histological variables. METHODS: We analyzed the whole-slide histopathology images, RNA-Seq, and proteomics data from 587 primary serous ovarian adenocarcinoma patients and developed a systematic algorithm to integrate histopathology and functional omics findings and to predict patients' response to platinum-based chemotherapy. RESULTS: Our convolutional neural networks identified the cancerous regions with areas under the receiver operating characteristic curve (AUCs) > 0.95 and classified tumor grade with AUCs > 0.80. Functional omics analysis revealed that expression levels of proteins participated in innate immune responses and catabolic pathways are associated with tumor grade. Quantitative histopathology analysis successfully stratified patients with different response to platinum-based chemotherapy (P = 0.003). CONCLUSIONS: These results indicated the potential clinical utility of quantitative histopathology evaluation in tumor cell detection and chemotherapy response prediction. The developed algorithm is easily extensible to other tumor types and treatment modalities.

A New Classification of Benign, Premalignant, and Malignant Endometrial Tissues Using Machine Learning Applied to 1413 Candidate Variables.

Benign normal (NL), premalignant (endometrial intraepithelial neoplasia, EIN) and malignant (cancer, EMCA) endometria must be precisely distinguished for optimal management. EIN was objectively defined previously as a regression model incorporating manually traced histologic variables to predict clonal growth and cancer outcomes. Results from this early computational study were used to revise subjective endometrial precancer diagnostic criteria currently in use. We here use automated feature segmentation and updated machine learning algorithms to develop a new classification algorithm. Endometrial tissue from 148 patients was randomly separated into 72-patient training and 76-patient validation cohorts encompassing all 3 diagnostic classes. We applied image analysis software to keratin stained endometrial tissues to automatically segment whole-slide digital images into epithelium, cells, and nuclei and extract corresponding variables. A total of 1413 variables were culled to 75 based on random forest classification performance in a 3-group (NL, EIN, EMCA) model. This algorithm correctly classifies cases with 3-class error rates of 0.04 (training set) and 0.058 (validation set); and 2-class (NL vs. EIN+EMCA) error rate of 0.016 (training set) and 0 (validation set). The 4 most heavily weighted variables are surrogates of those previously identified in manual-segmentation machine learning studies (stromal and epithelial area percentages, and normalized epithelial surface lengths). Lesser weighted predictors include gland and lumen axis lengths and ratios, and individual cell measures. Automated image analysis and random forest classification algorithms can classify normal, premalignant, and malignant endometrial tissues. Highest predictive variables overlap with those discovered independently in early models based on manual segmentation.

Assessment of a Chemotherapy Response Score (CRS) System for Tubo-Ovarian High-Grade Serous Carcinoma (HGSC).

A chemotherapy response score (CRS) system was recently described to assess the histopathologic response and prognosis of patients with tubo-ovarian high-grade serous carcinoma (HGSC) receiving neoadjuvant chemotherapy. The current study was performed as an independent assessment of this CRS system. We retrospectively identified advanced stage HGSC patients who received neoadjuvant chemotherapy and underwent interval debulking. If available, a hemotoxylin and eosin slide from the omentum and the adnexa was selected for the study. Slides were independently scored by 13 pathologists using the 3-tiered CRS system. Reviewers then received web-based training and rescored the slides. Overall survival and progression-free survival were estimated using the Kaplan-Meier method and compared using the log-rank test. A total of 68 patients with omental (n=65) and/or adnexal (n=59) slides were included in the study. Interobserver reproducibility was moderate for omentum (κ, 0.48) and poor for adnexa (κ, 0.40), which improved for omentum (κ, 0.62) but not for adnexa (κ, 0.38) after online training. For omental slides, a consensus CRS of 1/2 was associated with a shorter median progression-free survival (10.9 mo; 95% confidence interval, 9-14) than a CRS of 3 (18.9 mo; 95% CI, 18-24; P=0.020). In summary, a 3-tiered CRS system of hemotoxylin and eosin-stained omental deposits can yield prognostic information for HGSC patients receiving neoadjuvant chemotherapy, and web-based training improved reproducibility but did not alter determination of clinical outcomes. The CRS system may allow oncologists to identify potential nonresponders and triage HGSC patients for heightened observation and/or clinical trials.

Issues in the Differential Diagnosis of Uterine Low-grade Endometrioid Carcinoma, Including Mixed Endometrial Carcinomas: Recommendations from the International Society of Gynecological Pathologists.

This article provides practical recommendations developed from the International Society of Gynecological Pathologists Endometrial Carcinoma Project to address 4 issues that may arise in the diagnosis of uterine corpus low-grade endometrioid carcinoma: (1) The distinction between atypical hyperplasia and low-grade endometrioid carcinoma. (2) The distinction between low-grade endometrioid carcinoma and serous carcinoma. (3) The distinction between corded and hyalinized or spindle cell variants of low-grade endometrioid carcinoma and carcinosarcoma. (4) The diagnostic criteria for mixed endometrial carcinomas, a rare entity that should be diagnosed only after exclusion of a spectrum of tumors including morphologic variants of endometrioid carcinoma, dedifferentiated endometrial carcinoma, carcinosarcoma, and endometrial carcinomas with ambiguous morphology.

Implementing the DICOM Standard for Digital Pathology.

BACKGROUND: Digital Imaging and Communications in Medicine (DICOM®) is the standard for the representation, storage, and communication of medical images and related information. A DICOM file format and communication protocol for pathology have been defined; however, adoption by vendors and in the field is pending. Here, we implemented the essential aspects of the standard and assessed its capabilities and limitations in a multisite, multivendor healthcare network. METHODS: We selected relevant DICOM attributes, developed a program that extracts pixel data and pixel-related metadata, integrated patient and specimen-related metadata, populated and encoded DICOM attributes, and stored DICOM files. We generated the files using image data from four vendor-specific image file formats and clinical metadata from two departments with different laboratory information systems. We validated the generated DICOM files using recognized DICOM validation tools and measured encoding, storage, and access efficiency for three image compression methods. Finally, we evaluated storing, querying, and retrieving data over the web using existing DICOM archive software. RESULTS: Whole slide image data can be encoded together with relevant patient and specimen-related metadata as DICOM objects. These objects can be accessed efficiently from files or through RESTful web services using existing software implementations. Performance measurements show that the choice of image compression method has a major impact on data access efficiency. For lossy compression, JPEG achieves the fastest compression/decompression rates. For lossless compression, JPEG-LS significantly outperforms JPEG 2000 with respect to data encoding and decoding speed. CONCLUSION: Implementation of DICOM allows efficient access to image data as well as associated metadata. By leveraging a wealth of existing infrastructure solutions, the use of DICOM facilitates enterprise integration and data exchange for digital pathology.

Computational morphogenesis - Embryogenesis, cancer research and digital pathology.

Overall survival benefits of cancer therapies have, in general, fallen short of what was expected from them. By examining the many parallels that exist between embryogenesis and carcinogenesis, we discuss how clinical and fundamental cancer research can benefit from computational morphogenesis (CM) insofar as carcinogenesis is causally related to altered mechanisms underlying embryogenesis and post-embryonic tissue homeostasis. We also discuss about the critical role played by digital pathology (DP) since it constitutes the main source of data for the model-fitting and validation of CM-generated virtual tissues. Conversely, we outline how CM can provide support to DP by generating annotated synthetic 2D and 3D data that can be fed into machine-learning methods dedicated to the automated diagnosis of DP slides.

Adiponectin, Leptin, and Insulin-Pathway Receptors as Endometrial Cancer Subtyping Markers.

Developing a system of molecular subtyping for endometrial tumors might improve insight into disease etiology and clinical prediction of patient outcomes. High body mass index (BMI) has been implicated in development of endometrial cancer through hormonal pathways and might influence tumor expression of biomarkers involved in BMI-sensitive pathways. We evaluated whether endometrial tumor expression of 7 markers from BMI-sensitive pathways of insulin resistance could effectively characterize molecular subtypes: adiponectin receptor 1, adiponectin receptor 2, leptin receptor, insulin receptor (beta subunit), insulin receptor substrate 1, insulin-like growth factor 1 receptor, and insulin-like growth factor 2 receptor. Using endometrial carcinoma tissue specimens from a case-only prospective sample of 360 women from the Nurses' Health Study, we scored categorical immunohistochemical measurements of protein expression for each marker. Logistic regression was used to estimate associations between endometrial cancer risk factors, especially BMI, and tumor marker expression. Proportional hazard modeling was performed to estimate associations between marker expression and time to all-cause mortality as well as time to endometrial cancer-specific mortality. No association was observed between BMI and tumor expression of any marker. No marker was associated with time to either all-cause mortality or endometrial cancer-specific mortality in models with or without standard clinical predictors of patient mortality (tumor stage, grade, and histologic type). It did not appear that any of the markers evaluated here could be used effectively to define molecular subtypes of endometrial cancer.

Diagnostic and Treatment Reproducibility of Cervical Intraepithelial Neoplasia / Squamous Intraepithelial Lesion and Factors Affecting the Diagnosis.

OBJECTIVE: Inter-observer differences in the diagnosis of HPV related cervical lesions are problematic and response of gynecologists to these diagnostic entities is non-standardized. This study evaluated the diagnostic reproducibility of "cervical intraepithelial neoplasia" (CIN) and "squamous intraepithelial lesion" (SIL) diagnoses. MATERIAL AND METHOD: 19 pathologists evaluated 66 cases once using H&E slides and once with immunohistochemical studies (p16, Ki-67 and Pro-ExC). Management response to diagnoses was evaluated amongst 12 gynecologists. Pathologists and gynecologists were also given a questionnaire about how additional information like smear results and age modify diagnosis and management. RESULTS: We show moderate interobserver diagnostic reproducibility amongst pathologists. The overall kappa value was 0.50 and 0.59 using the CIN and SIL classifications respectively. Impact of immunohistochemical evaluation on interpretation of cases differed and there was lack of statistically significant improvement of interobserver diagnostic reproducibility with the addition of immunohistochemistry. We saw that choice of treatment methods amongst gynecologists varied and overall concordance was only fair to moderate. The CIN2 diagnostic category was seen to have the lowest percentage agreement amongst both pathologists and gynecologists. We showed that pathologists had diagnostic "styles" and gynecologists had management "styles". CONCLUSION: In summary each pathologist had different diagnostic tendencies which were affected not only by histopathology and marker studies, but also by the patient management tendencies of the gynecologist that the pathologist worked with. The two-tiered modified Bethesda system improved diagnostic agreement. We concluded that immunohistochemistry should be used only to resolve problems in select cases and not for every case.

Endometrial Cancer Risk Factors, Hormone Receptors, and Mortality Prediction.

Background: Endometrial tumors arise from a hormonally responsive tissue. Defining subtypes by hormone receptor expression might better inform etiology and prediction of patient outcomes. We evaluated the potential role of tumor estrogen receptor (ER) and progesterone receptor (PR) expression to define endometrial cancer subtypes.Methods: We measured semi-continuous ER and PR protein expression in tissue specimens from 360 endometrial primary tumors from the Nurses' Health Study. To explore the impact of different definitions of marker positivity, we dichotomized ER and PR expression at different cut points in increments of 5% positive cells. Logistic regression was used to estimate associations between endometrial cancer risk factors, such as body mass index, with dichotomous ER or PR status. Reclassification statistics were used to assess whether adding dichotomous ER or PR status to standard prognostic factors of stage, grade, and histologic type would improve endometrial cancer-specific mortality prediction.Results: Compared with not being obese, obesity increased the odds of having an ER-positive tumor at cut points of 0% to 20% [maximum OR, 2.92; 95% confidence interval (CI), 1.34-6.33] as well as the odds of having a PR-positive tumor at cut points of 70% to 90% (maximum OR, 2.53; 95% CI, 1.36-4.68). Adding dichotomous tumor ER or PR status to the panel of standard predictors did not improve both model discrimination and calibration.Conclusions: Obesity may be associated with greater endometrial tumor expression of ER and PR. Adding either marker does not appear to improve mortality prediction beyond the standard predictors.Impact: Body mass index might explain some of the biological variation among endometrial tumors. Cancer Epidemiol Biomarkers Prev; 26(5); 727-35. ©2017 AACR.

Toxicology Study of Single-walled Carbon Nanotubes and Reduced Graphene Oxide in Human Sperm.

Carbon-based nanomaterials such as single-walled carbon nanotubes and reduced graphene oxide are currently being evaluated for biomedical applications including in vivo drug delivery and tumor imaging. Several reports have studied the toxicity of carbon nanomaterials, but their effects on human male reproduction have not been fully examined. Additionally, it is not clear whether the nanomaterial exposure has any effect on sperm sorting procedures used in clinical settings. Here, we show that the presence of functionalized single walled carbon nanotubes (SWCNT-COOH) and reduced graphene oxide at concentrations of 1-25 µg/mL do not affect sperm viability. However, SWCNT-COOH generate significant reactive superoxide species at a higher concentration (25 µg/mL), while reduced graphene oxide does not initiate reactive species in human sperm. Further, we demonstrate that exposure to these nanomaterials does not hinder the sperm sorting process, and microfluidic sorting systems can select the sperm that show low oxidative stress post-exposure.

Sperm processing for advanced reproductive technologies: Where are we today?

Assisted reproductive technologies (ARTs) utilize sperm sorting methods to select viable sperm from the semen samples. Conventional sperm sorting techniques in current use are density gradient centrifugation, direct swim-up, and conventional swim-up. These methods use multiple centrifugation steps, which have been shown to generate reactive oxygen species (ROS) that decrease DNA integrity and damage sperm. Newer technologies, such as microfluidics, electrophoresis, motile sperm organelle morphology examination (MSOME), and birefringence eliminate the centrifugation steps and can improve the selection of sperm with higher DNA integrity, normal morphology, and motility as well as improved artificial insemination outcomes. In this review, we discuss some recent research in centrifugation and non-centrifugation based techniques and their effect on sperm quality and ART outcomes.

Dyssynchronous secretory endometrial glands often show sporadically acquired progesterone nonresponsiveness.

Primary sporadic gene-inactivating events within the progesterone response cascade might explain the presence of individual dyssynchronous (outlier) glands commonly observed in a secretory background. We queried morphologically dyssynchronous glands in mid-secretory endometrium with a series of markers normally downregulated by progesterone. Seventy-nine mid-secretory endometrial biopsies were stained with hematoxylin and eosin, MIB-1, PAX2, estrogen and progesterone receptors, and PTEN. Aberrant staining of glands was independently scored for each marker. Outlier glands overlapping between stains were enumerated. A total of 63% of cases had hematoxylin and eosin stained outlier glands (average 9), which often demonstrated failed progesterone-mediated downregulation of PAX2 (43%), estrogen (40%), and/or progesterone receptors (28%). Aberrations of progesterone response was seen in 70% to 85% of cases overall, averaging 10 to 30 glands/affected case. The frequency and burden of affected glands was similar to that seen for primary inactivating events of the PAX2 and PTEN genes (35% and 41% of cases, respectively, averaging 32 and 38 glands per affected patient). Sporadic gene-inactivating events are common during endometrial regeneration, and may cause morphologic changes unmasked by the hormonal context. Some of these dyssynchronous "outlier" glands, whether evident on hematoxylin and eosin stain or not, have an interrupted progesterone response.

Biomarker resolution of uterine smooth muscle tumor necrosis as benign vs malignant.

Uterine leiomyosarcomas are rare malignant tumors with a poor prognosis while leiomyomas are common benign tumors unrelated to their malignant counterparts. Diagnostic features commonly present in leiomyosarcoma include cytologic atypia, high mitotic index, and a sarcoma-specific geographic cell death designated 'tumor cell necrosis (TCN)'. TCN has a sharp viable-nonviable boundary lacking inflammation, fibrosis or granulation tissue seen in nonspecific infarction. These characteristics are sometimes difficult to interpret on routine hematoxylin and eosin slides, and can lead to diagnostic errors. In this study, we used extracellular matrix stains to test the hypothesis that the host response which characterizes nonspecific infarction may degrade the matrix in infarcted tumor more than in TCN. A 'honeycomb' pattern of reticulin highlighted individual tumor cells in viable regions of all cases. Nonviable area of reticulin patterns differed significantly by diagnosis (P<0.001), with a honeycomb pattern maintained (91%, 20/22) in leiomyosarcoma and lost (61%, 11/18) in leiomyomas. Retention of honeycomb reticulin in nonviable areas of leiomyosarcoma occurred irrespective of the presence of inflammation, hemorrhage, fibrosis, or diffuse hyalinization. Fibrosis/hyalinization as evidenced by trichrome stain was significantly (P<0.001) more common in nonviable areas of benign leiomyomas (100%, 18/18) compared with leiomyosarcomas (36%, 8/22). In those occasions where viable tissues contained discernable polarization of mitotic activity, these decreased toward the nonviable interface in leiomyosarcoma, and had an opposite pattern in leiomyomas, increasing toward the interface. There is a significant difference in the reticulin and collagen networks of nonviable areas of leiomyosarcoma compared with leiomyoma. At the time of early injury, both retain reticulin; however, this is cleared over time in benign, but not malignant, areas of necrosis. We conclude that proliferative repair of leiomyomas at the viable-nonviable interface includes remodeling of the extracellular matrix, in contrast to the static preservation of extracellular matrix ('mummification') in nonviable areas of leiomyosarcomas.

ARID1A is a useful marker of malignancy in peritoneal washings for endometrial carcinoma.

BACKGROUND: ARID1A (AT-rich interactive domain 1A gene) has recently been identified as a novel tumor suppressor gene and one of the driver genes in endometrial carcinogenesis. Approximately 30% to 40% of endometrial carcinomas harbor mutations in the ARID1A gene, which results in complete loss of ARID1A protein expression. Although ARID1A aberrations are not restricted to endometrial cancer, the authors hypothesized that it might be a useful marker of malignancy in peritoneal washings for patients with endometrial cancer. METHODS: The cytology archive of Brigham and Women's Hospital was searched to identify cell blocks from peritoneal washings that contained malignant or benign endometrial epithelium. From 2006 through 2013, 17 cases of endometrial carcinoma (EMCA) and 16 cases of endometriosis were identified. Surgical pathology reports and follow-up data were used to confirm the diagnoses. Immunohistochemistry for ARID1A was performed, and slides were scored as 0 (complete loss of staining) or 1 (retained staining) by 2 independent pathologists. The discordant cases were resolved by consensus. The two-tailed Fisher exact probability test was used to calculate statistical significance. RESULTS: Complete loss of ARID1A expression was found in 8 of 17 EMCA cases (47%) and none of the 16 endometriosis cases (0%) (P = .024). The concordance among the pathologists on first review was high (96.7%). CONCLUSIONS: The results of the current study demonstrated that ARID1A can be used in peritoneal washings to confirm malignancy in patients with EMCA. Complete loss of ARID1A expression by immunohistochemistry is highly specific for carcinoma, but retained expression is not informative.