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Separation of mesothelioma from metastatic carcinoma requires immunohistochemical support, with small batteries of stains recommended as a starting-point, but these numbers commonly expand to 10, 12 or more stains, a process that is not only expensive but frequently generates anomalous or confounding results, leading to even more stains. Here we review data on HEG1 clone SKM9-2, a new (now commercially available) mesothelioma marker and claudin-4, a broad-spectrum carcinoma marker, to ask whether these two stains are sufficient, by themselves, to separate mesotheliomas from non-small-cell lung (NSCLC) as well as other carcinomas. Data for HEG1, derived from four laboratories, showed membrane staining in 393 of 434 (91%) epithelioid/biphasic mesotheliomas and one of 360 (0.3%) NSCLC (sensitivity 91%, specificity 99.7%). Reports from seven laboratories evaluating claudin-4 in NSCLC showed positivity in 469 of 502 (93%) carcinomas and weak positivity in five of 463 (1.0%) epithelioid/biphasic mesotheliomas (sensitivity 93%, specificity 98.9%). Comparable results were found with carcinomas from other sites, except for serous and thyroid carcinomas, some of which react with HEG1 but are also positive for claudin-4. For sarcomatoid mesotheliomas, HEG1 sensitivity is modest and staining sometimes difficult to interpret. We hypothesise that the combination of HEG1 and claudin-4 immunostaining will potentially allow the separation of epithelioid/biphasic mesotheliomas from NSCLC carcinomas with high accuracy using only two immunostains in most cases. This combination will probably also work for carcinomas from most other sites, but more reports on HEG1 SKM9-2 staining of carcinomas other than NSCLC are needed. This approach would greatly simplify the diagnosis of mesothelioma.

p53 immunohistochemistry has long been proposed for the separation of benign from malignant mesothelial proliferations, with the older literature suggesting that any degree of positivity supported a diagnosis of mesothelioma. However, using modern immunohistochemistry platforms in other organ systems, notably gynecologic tumors, it has become clear that p53 staining can represent wild-type protein, and only specific staining patterns (absent, overexpression, or cytoplasmic expression) are indicative of a TP53 mutation. We applied these principles to two tissue microarrays containing 94 mesotheliomas and 66 reactive mesothelial proliferations. Seven/65 (11%) epithelioid mesotheliomas showed aberrant staining (four absent and three overexpression patterns) as did 5/29 (17%) of sarcomatoid mesotheliomas (all overexpression patterns). We sequenced the TP53 gene (exons 2-11) in five of the epithelioid and three of the sarcomatoid cases with aberrant staining as well as 12 epithelioid and eight sarcomatoid mesotheliomas with wild-type staining. All three sarcomatoid cases with aberrant staining showed mutated TP53, as did three of the epithelioid cases; in two of the epithelioid cases no mutation was detected, most likely because of large deletions not detected by this assay. In contrast, none of the 20 mesotheliomas with wild-type staining contained mutated TP53. We conclude that absent or overexpression p53 staining patterns can be used as a marker of a malignant vs. a benign mesothelial proliferation. The sensitivity of p53 staining by itself is low, but here addition of p53 to BAP1/MTAP staining increased sensitivity from 72 to 81% for epithelioid and 38 to 50% for sarcomatoid mesotheliomas.

The color variation of hematoxylin and eosin (HE)-stained tissues has presented a challenge for applications of artificial intelligence (AI) in digital pathology. Many color normalization algorithms have been developed in recent years in order to reduce the color variation between HE images. However, previous efforts in benchmarking these algorithms have produced conflicting results and none have sufficiently assessed the efficacy of the various color normalization methods for improving diagnostic performance of AI systems. In this study, we systematically investigated eight color normalization algorithms for AI-based classification of HE-stained histopathology slides, in the context of using images both from one center and from multiple centers. Our results show that color normalization does not consistently improve classification performance when both training and testing data are from a single center. However, using four multi-center datasets of two cancer types (ovarian and pleural) and objective functions, we show that color normalization can significantly improve the classification accuracy of images from external datasets (ovarian cancer: 0.25 AUC increase, p = 1.6 e-05; pleural cancer: 0.21 AUC increase, p = 1.4 e-10). Furthermore, we introduce a novel augmentation strategy by mixing color-normalized images using three easily accessible algorithms that consistently improves the diagnosis of test images from external centers, even when the individual normalization methods had varied results. We anticipate our study to be a starting point for reliable use of color normalization to improve AI-based, digital pathology-empowered diagnosis of cancers sourced from multiple centers. © 2021 The Pathological Society of Great Britain and Ireland. Published by John WileySons, Ltd.

Sarcomatoid mesothelioma is an aggressive malignancy that can be challenging to distinguish from benign spindle cell mesothelial proliferations based on biopsy, and this distinction is crucial to patient treatment and prognosis. A novel deep learning based classifier may be able to aid pathologists in making this critical diagnostic distinction. SpindleMesoNET was trained on cases of malignant sarcomatoid mesothelioma and benign spindle cell mesothelial proliferations. Performance was assessed through cross-validation on the training set, on an independent set of challenging cases referred for expert opinion (‘referral’ test set), and on an externally stained set from outside institutions (‘externally stained’ test set). SpindleMesoNET predicted the benign or malignant status of cases with AUC’s of 0.932, 0.925, and 0.989 on the cross-validation, referral and external test sets, respectively. The accuracy of SpindleMesoNET on the referral set cases (92.5%) was comparable to the average accuracy of 3 experienced pathologists on the same slide set (91.7%). We conclude that SpindleMesoNET can accurately distinguish sarcomatoid mesothelioma from benign spindle cell mesothelial proliferations. A deep learning system of this type holds potential for future use as an ancillary test in diagnostic pathology.

The site of the gastrointestinal (GI) tract where biopsies are most likely to be diagnostic of graft-versus-host disease (GvHD) remains controversial. Recent reports have indicated that biopsies from the rectosigmoid have sufficient sensitivity and specificity for diagnosing GI GvHD and can be obtained via a less invasive flexible sigmoidoscopy procedure. While GvHD histologic grades 1–3 have little correlation with patients’ symptoms and overall clinical grade, histologic grade 4 GvHD does correlate with severe clinical presentation and a poor prognosis. We examined cases of lower GI biopsies obtained via a complete colonoscopy with ileal intubation for the evaluation of GvHD within a 2-year period from patients who underwent stem cell transplantation. In our study cohort, grade 4 GvHD was significantly more likely to be identified in a terminal ileum biopsy than in a biopsy from another site in the lower GI tract. Significantly, 5 of 6 patients with histologic grade 4 GvHD diagnosed on ileal biopsies died from complication of severe GI GvHD. Given the poor prognosis of histologic grade 4 GvHD in the terminal ileum, the detection of this finding may serve to inform clinicians that escalation or modification of treatment may need to be considered. Furthermore, our findings suggest that terminal ileal biopsies may help to increase sensitivity for identifying patients at high risk for poor outcome of GvHD.

The separation of malignant mesothelioma from non-small cell lung carcinomas can be a difficult problem. Sex-determining region Y box 6 (SOX6) and disabled homolog 2 (DAB2) have recently been proposed as sensitive/specific markers of mesothelial lineage, but have not yet been independently tested for utility in mesothelioma diagnosis. Using tissue microarrays containing mesotheliomas (epithelioid: n=40, sarcomatoid: n=23) and non-small cell lung carcinomas (adenocarcinoma: n=52, squamous cell carcinoma: n=57, large cell carcinoma: n=12) we evaluated the performance of SOX6 and DAB2 by themselves, in conjunction with other established mesothelioma markers (calretinin, WT1, D2-40, CK5/6, HEG1) and combined with 3 broad-spectrum established carcinoma markers: claudin-4, MOC31, and BerEP4. For epithelioid mesothelioma, SOX6 and DAB2 had sensitivities of 85% and 98%, respectively. For sarcomatoid mesothelioma, SOX6 had a sensitivity of 13% and DAB2 could not be assessed due to background stromal staining. For SOX6 alone, specificity for mesothelioma versus adenocarcinoma, squamous cell carcinoma, and large cell carcinoma was 94%, 79%, and 92%, respectively, while for DAB2 specificity was 77%, 86%, and 67%. Combinations of SOX6 and established mesothelioma markers produced sensitivities of 95% or greater. A combination of SOX6 positive/claudin-4 negative staining was 95% to 100% specific for mesothelioma versus carcinoma with a sensitivity of 85%. SOX6 is a promising marker for the diagnosis of mesothelioma and potentially could be combined with other mesothelial markers or a broad-spectrum carcinoma marker to reach an accurate diagnosis with relatively few immunostains, The relatively low specificity and difficulty of interpreting DAB2 staining limits its utility for mesothelioma diagnosis.

Deep learning-based computer vision methods have recently made remarkable breakthroughs in the analysis and classification of cancer pathology images. However, there has been relatively little investigation of the utility of deep neural networks to synthesize medical images. In this study, we evaluated the efficacy of generative adversarial networks to synthesize high-resolution pathology images of 10 histological types of cancer, including five cancer types from The Cancer Genome Atlas and the five major histological subtypes of ovarian carcinoma. The quality of these images was assessed using a comprehensive survey of board-certified pathologists (n = 9) and pathology trainees (n = 6). Our results show that the real and synthetic images are classified by histotype with comparable accuracies and the synthetic images are visually indistinguishable from real images. Furthermore, we trained deep convolutional neural networks to diagnose the different cancer types and determined that the synthetic images perform as well as additional real images when used to supplement a small training set. These findings have important applications in proficiency testing of medical practitioners and quality assurance in clinical laboratories. Furthermore, training of computer-aided diagnostic systems can benefit from synthetic images where labeled datasets are limited (e.g. rare cancers). We have created a publicly available website where clinicians and researchers can attempt questions from the image survey (http://gan.aimlab.ca/). © 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

The separation of benign from malignant mesothelial proliferations is an important clinical but often a difficult morphologic problem. Over the last roughly 10 years a variety of new markers that aid in this separation have been published and some older recommended markers reconsidered. Unlike previous, and largely unusable, empiric immunohistochemical (IHC) stains, these new markers, some using IHC and some using fluourescent in situ hybridization (FISH), are largely based on documented genomic abnormalities in malignant mesotheliomas. However, no marker works in all situations; rather, markers need to be chosen by the morphology of the process in question (epithelial vs. spindled) and the body cavity of interest (pleural vs. peritoneal). It is also important to be familiar with the exact pattern, for example nuclear versus cytoplasmic loss, that indicates a positive test. Furthermore, no single marker is 100% sensitive even with the optimal morphology/location, so that combinations of markers are essential. This review covers the various new markers in the literature, highlights their advantages and limitations, and suggests morphology/site specific combinations that can produce sensitivities in the 80% to 90% (and perhaps higher) range. At present only BRCA-1 related protein-1 and methylthioadenosine phosphorylase IHC, and cyclin-dependent kinase inhibitor 2A (p16) FISH have sufficient publications and reproducibility of results to be considered as established markers. 5-Hydroxymethyl cytosine, enhancer of zeste homolog 2, cyclin D1, and programmed death-ligand 1 IHC, and NF2 FISH are all potentially useful but need further study. The newly described entity of malignant mesothelioma in situ sits at the interface of benign and malignant mesothelial process; criteria for this diagnosis are reviewed.

The distinction of malignant mesothelioma from non-small-cell lung carcinoma (NSCLC) usually requires immunohistochemistry, but some broad-spectrum carcinoma markers stain mesotheliomas, and it remains unclear which broad-spectrum markers are most valuable for distinguishing these malignancies. Here, we directly compared the sensitivity and specificity of three broad-spectrum carcinoma markers, claudin-4, Ber-EP4, and MOC-31, for distinguishing NSCLC from mesothelioma. Immunohistochemistry was performed on tissue microarrays containing 68 epithelioid mesotheliomas, 31 sarcomatoid mesotheliomas, and 147 non-small-cell lung cancers (53 adenocarcinomas, 60 squamous cell carcinomas, 13 large-cell carcinomas, and 21 sarcomatoid carcinomas). For adenocarcinoma, squamous cell carcinoma, and large-cell carcinoma, claudin-4 staining was present in 103 of 126 cases (82%), MOC-31 staining was present in 112 of 126 cases (89%), and Ber-EP4 staining was present in 113 of 126 cases (90%); these values were not statistically different. Claudin-4 stained 0 of 68 (0%), MOC-31 stained 22 of 68 (32%), and Ber-EP4 stained 24 of 68 (35%) epithelioid mesotheliomas; thus, the specificities for NSCLC versus epithelioid mesothelioma were 100%, 68%, and 65%, respectively. Claudin-4 staining was present in 7 of 21 (33%), MOC-31 staining was present in 8 of 21 (38%), and Ber-EP4 staining was present in 5 of 21 (24%) sarcomatoid carcinomas. All three markers were negative in 12 of 21 (57%) sarcomatoid carcinomas. Sarcomatoid mesotheliomas were not stained with any of these markers. We conclude that claudin-4 has considerably greater specificity and comparable sensitivity to MOC-31 and Ber-EP4 for distinguishing NSCLC from epithelioid malignant mesothelioma. The use of all three markers may be necessary for sarcomatoid neoplasms, given their limited sensitivity.

Thymic carcinoma is an aggressive malignancy that can be challenging to distinguish from thymoma using histomorphology. We assessed two emerging markers for these entities, EZH2 and POU2F3, and compared them with conventional immunostains. Whole slide sections of 37 thymic carcinomas, 23 type A thymomas, 13 type B3 thymomas, and 8 micronodular thymomas with lymphoid stroma (MNTLS) were immunostained for EZH2, POU2F3, CD117, CD5, TdT, BAP1, and MTAP. POU2F3 (≥10% hotspot staining), CD117, and CD5 showed 100% specificity for thymic carcinoma versus thymoma with 51%, 86%, and 35% sensitivity, respectively, for thymic carcinoma. All POU2F3 positive cases were also positive for CD117. All thymic carcinomas showed >10% EZH2 staining. EZH2 (≥80% staining) had a sensitivity of 81% for thymic carcinoma and a specificity of 100% for thymic carcinoma versus type A thymoma and MNTLS but had poor specificity (46%) for thymic carcinoma versus B3 thymoma. Adding EZH2 to a panel of CD117, TdT, BAP1, and MTAP increased cases with informative results from 67/81 (83%) to 77/81 (95%). Overall, absent EZH2 staining may be useful for excluding thymic carcinoma, diffuse EZH2 staining may help to exclude type A thymoma and MNTLS, and ≥10% POU2F3 staining has excellent specificity for thymic carcinoma versus thymoma.

The separation of benign from malignant mesothelial proliferations is a morphologically difficult problem. Mutations/deletions of components of the Hippo pathway are frequent in malignant mesotheliomas, and one downstream effect of aberrant Hippo signaling is increased production of cyclin D1. We examined expression of cyclin D1 nuclear staining in two tissue microarrays containing 52 reactive epithelial mesothelial proliferations, 51 reactive spindle cell mesothelial proliferations, 54 epithelial mesotheliomas, and 22 sarcomatous/desmoplastic mesotheliomas. When present, cyclin D1 staining was always strong, hence the arrays were scored as 0, 1–25%, 26–50%, 51–75%, and 76–100% staining. Both arrays showed a similar pattern. Reactive epithelial proliferations generally showed no staining (42/52 cases) or 1–25% staining (10/52 cases) with no cases showing >25% staining. Overall for reactive epithelial proliferations the maximum staining was 14.8% and mean 1.1 ± 2.9%. For epithelial mesotheliomas 39/54 (72%) cases demonstrated >25% staining, with 8/54 in the 26–50% staining range, 9/54 in the 51–75% range, and 22/54 in the >75% range. Combinations of staining using cyclin D1 >50% plus BAP1 or MTAP loss in epithelial mesotheliomas produced about a 10% increase in sensitivity. Reactive spindle cell proliferations showed a broader range of staining with 27/51 in the 1–25% range, 5/51 in the 26–50% range, and 1/51 >50%. Eleven of 22 sarcomatous/desmoplastic mesotheliomas scored 50% or greater. We conclude that for epithelial mesothelial proliferations, the finding of >50% of tumor cells staining supports a diagnosis of epithelial mesothelioma with 100% specificity but only modest (57%) sensitivity.

Background Transbronchial needle aspiration (TBNA) of peripheral lung nodules can be difficult with conventional devices due to their limited flexibility. A promising new technology for accessing these lesions is the PeriView FLEX TBNA device, which has a flexible spiral-grooved needle. The present study reports the unique cytologic features, diagnostic value, and potential pitfalls of PeriView FLEX TBNA specimens. Methods This study retrospectively evaluates 113 consecutive cases of lung nodules sampled using the PeriView FLEX device with radial endobronchial ultrasound guidance. Results PeriView FLEX specimens were satisfactory for evaluation in 111 of 113 cases (98%). A diagnosis of malignancy was made on 64 specimens (57%), with 100% specificity and 70% sensitivity for malignancy. In 4 cases, the PeriView FLEX sample was the only specimen from bronchoscopy that was diagnostic of malignancy. Of the 64 PeriView FLEX specimens with malignant cells, 58 (91%) were adequate for immunohistochemistry and 44 (69%) were adequate for molecular genetic testing. Potential pitfalls were largely ameliorated through education regarding the unique features of PeriView FLEX samples, such as the expected abundance of anthracotic pigment and the paucity of lymphocytes. Conclusions TBNA using the PeriView FLEX device to sample pulmonary nodules contributed to the diagnostic value of bronchoscopy and tended to provide sufficient tissue for ancillary studies. Many of the possible pitfalls may be avoided through consideration of the unique cytologic features associated with this novel sampling method.

Sarcomatoid mesothelioma is an aggressive malignancy that can be challenging to distinguish from benign spindle cell mesothelial proliferations based on biopsy, and this distinction is crucial to patient treatment and prognosis. A novel deep learning based classifier may be able to aid pathologists in making this critical diagnostic distinction. SpindleMesoNET was trained on cases of malignant sarcomatoid mesothelioma and benign spindle cell mesothelial proliferations. Performance was assessed through cross-validation on the training set, on an independent set of challenging cases referred for expert opinion ('referral' test set), and on an externally stained set from outside institutions ('externally stained' test set). SpindleMesoNET predicted the benign or malignant status of cases with AUC's of 0.932, 0.925, and 0.989 on the cross-validation, referral and external test sets, respectively. The accuracy of SpindleMesoNET on the referral set cases (92.5%) was comparable to the average accuracy of 3 experienced pathologists on the same slide set (91.7%). We conclude that SpindleMesoNET can accurately distinguish sarcomatoid mesothelioma from benign spindle cell mesothelial proliferations. A deep learning system of this type holds potential for future use as an ancillary test in diagnostic pathology.

The separation of malignant mesothelioma from non-small cell lung carcinomas can be a difficult problem. Sex-determining region Y box 6 (SOX6) and disabled homolog 2 (DAB2) have recently been proposed as sensitive/specific markers of mesothelial lineage, but have not yet been independently tested for utility in mesothelioma diagnosis. Using tissue microarrays containing mesotheliomas (epithelioid: n=40, sarcomatoid: n=23) and non-small cell lung carcinomas (adenocarcinoma: n=52, squamous cell carcinoma: n=57, large cell carcinoma: n=12) we evaluated the performance of SOX6 and DAB2 by themselves, in conjunction with other established mesothelioma markers (calretinin, WT1, D2-40, CK5/6, HEG1) and combined with 3 broad-spectrum established carcinoma markers: claudin-4, MOC31, and BerEP4. For epithelioid mesothelioma, SOX6 and DAB2 had sensitivities of 85% and 98%, respectively. For sarcomatoid mesothelioma, SOX6 had a sensitivity of 13% and DAB2 could not be assessed due to background stromal staining. For SOX6 alone, specificity for mesothelioma versus adenocarcinoma, squamous cell carcinoma, and large cell carcinoma was 94%, 79%, and 92%, respectively, while for DAB2 specificity was 77%, 86%, and 67%. Combinations of SOX6 and established mesothelioma markers produced sensitivities of 95% or greater. A combination of SOX6 positive/claudin-4 negative staining was 95% to 100% specific for mesothelioma versus carcinoma with a sensitivity of 85%. SOX6 is a promising marker for the diagnosis of mesothelioma and potentially could be combined with other mesothelial markers or a broad-spectrum carcinoma marker to reach an accurate diagnosis with relatively few immunostains, The relatively low specificity and difficulty of interpreting DAB2 staining limits its utility for mesothelioma diagnosis.

Introduction: PD-L1 expression may be used as a biomarker predictive of non-small cell lung carcinoma (NSCLC) response to PD-L1 inhibitor treatment. Spatial and temporal heterogeneity in PD-L1 expression and variation in PD-L1 test interpretation may contribute to differences in PD-L1 test results between samples of the same patient's disease. Methods: Retrospective chart review identified 77 NSCLC patients with 22C3 PharmDx PD-L1 assays performed on two different tumor samples. Patients clinically suspected to have two separate primaries were excluded. PD-L1 test results in different score categories (

PD-L1 expression in non-small cell lung cancer (NSCLC) is predictive of response to immunotherapy, but scoring of PD-L1 immunohistochemistry shows considerable interobserver variability. Automated methods may allow more consistent and expedient PD-L1 scoring. We aimed to assess the technical concordance of PD-L1 scores produced using free open source QuPath software with the manual scores of three pathologists. A classifier for PD-L1 scoring was trained using 30 NSCLC image patches. A separate test set of 207 image patches from 69 NSCLC resection cases was used for comparison of automated and manual scores. Automated and average manual scores showed excellent correlation (concordance correlation coeffecient = 0.925), though automated scoring resulted in significantly more 1–49% scores than manual scoring (p = 0.012). At both 1% and 50% thresholds, automated scores showed a level of concordance with our ‘gold standard’ (the average of three pathologists’ manual scores) similar to that of individual pathologists. Automated scoring showed high sensitivity (95%) but lower specificity (84%) at a 1% threshold, and excellent specificity (100%) but lower sensitivity (71%) at a 50% threshold. We conclude that our automated PD-L1 scoring system for NSCLC has an accuracy similar to that of individual pathologists. The detailed protocol we provide for free open source scoring software and our discussion of the limitations of this technology may facilitate more effective integration of automated scoring into clinical workflows.

The site of the gastrointestinal (GI) tract where biopsies are most likely to be diagnostic of graft-versus-host disease (GvHD) remains controversial. Recent reports have indicated that biopsies from the rectosigmoid have sufficient sensitivity and specificity for diagnosing GI GvHD and can be obtained via a less invasive flexible sigmoidoscopy procedure. While GvHD histologic grades 1-3 have little correlation with patients' symptoms and overall clinical grade, histologic grade 4 GvHD does correlate with severe clinical presentation and a poor prognosis. We examined cases of lower GI biopsies obtained via a complete colonoscopy with ileal intubation for the evaluation of GvHD within a 2-year period from patients who underwent stem cell transplantation. In our study cohort, grade 4 GvHD was significantly more likely to be identified in a terminal ileum biopsy than in a biopsy from another site in the lower GI tract. Significantly, 5 of 6 patients with histologic grade 4 GvHD diagnosed on ileal biopsies died from complication of severe GI GvHD. Given the poor prognosis of histologic grade 4 GvHD in the terminal ileum, the detection of this finding may serve to inform clinicians that escalation or modification of treatment may need to be considered. Furthermore, our findings suggest that terminal ileal biopsies may help to increase sensitivity for identifying patients at high risk for poor outcome of GvHD.

Background RNA‐sequencing‐based classifiers can stratify pancreatic ductal adenocarcinoma (PDAC) into prognostically significant subgroups but are not practical for use in clinical workflows. Here, we assess whether histomorphological features may be used as surrogate markers for predicting molecular subgroup and overall survival in PDAC. Methods Ninety‐six tissue samples from 50 patients with non‐resectable PDAC were scored for gland formation, stromal maturity, mucin, necrosis, and neutrophil infiltration. Prognostic PDAC gene expression classifiers were run on all tumors using whole transcriptome sequencing data from the POG trial (NCT02155621). Findings were validated using digital TCGA slides (n = 50). Survival analysis used multivariate Cox proportional‐hazards tests and log‐rank tests. Results The combination of low gland formation and low neutrophil infiltration was significantly associated with the poor prognosis PDAC molecular subgroup (basal‐like or squamous) and was an independent predictor of shorter overall survival, in both frozen section (n = 47) and formalin‐fixed paraffin‐embedded (n = 49) tissue samples from POG patients, and in the TCGA samples. This finding held true in the subgroup analysis of primary (n = 17) and metastatic samples (n = 79). The combination of high gland formation and high neutrophils had low sensitivity but high specificity for favorable prognosis subgroups. Conclusions The assessment of gland formation and neutrophil infiltration on routine histological sections can aid in prognostication and allow inferences to be made about molecular subtype, which may help guide patient management decisions and contribute to our understanding of heterogeneity in treatment response., The combination of low gland formation and low neutrophils is significantly associated with poor prognosis molecular subgroups of pancreatic ductal adenocarcinoma, and is an independent predictor of shorter overall survival. These features can be readily assessed in archival tissue slides, allowing inferences regarding molecular subtype and prognosis to be made as part of routine patient care.

Benign spindle cell lesions of the breast include neoplastic and reactive entities that are diagnostically challenging given their rarity and similar histomorphology. Accurate diagnosis on percutaneous core biopsy within this category is essential as some lesions require excision and surveillance, whereas others may be observed. We present three cases of rare benign spindle cell lesions of the breast that reflect the diversity of this group: solitary fibrous tumour, nodular pseudoangiomatous stromal hyperplasia and nodular fasciitis. Through these cases, we discuss the associated differential diagnosis and demonstrate how emerging ancillary studies can be integrated into a diagnostic approach. We highlight distinctive clinical and histopathological features and summarise recent updates to the clinical management of these lesions. An organised approach to the broad differential of spindle cell lesions is essential for appropriate diagnosis and treatment.

Context.— Serosal involvement (pT4a category) and lymphovascular invasion have prognostic significance in colorectal carcinoma, but are subject to interobserver variation in assessment. Objectives.— To provide the first large-scale assessment of interobserver variability in pT4a category and lymphovascular invasion reporting in real-world practice and to explore the impact of information from guidelines on variability in reporting these features. Design.— Analysis of 1555 consecutive synoptic reports of colorectal carcinoma was performed using multivariate logistic regression. Interobserver variability before and after the presentation of guideline information was assessed using an image-based survey. Results.— Significant differences in the odds of reporting pT4a versus pT3 category, detecting lymphovascular invasion of any type, and detecting large vessel invasion were identified among hospital sites and for individual pathologists compared with the median pathologist at the same site. Consistent with these results, interobserver agreement was only moderate in the image-based survey regarding T4a staging and lymphovascular invasion (all κ ≤ 0.57). The provision of information from guidelines did not tend to increase interobserver agreement in the survey, though responses in favor of using an elastic stain increased following recommendations for their use. However, when observers were provided with elastic-stained images, interobserver agreement remained only moderate (κ = 0.55). Conclusions.— Real-world reporting of pT4a category and lymphovascular invasion shows substantial variability at both local and regional levels. Our study underscores the need to address these features in quality initiatives, and provides a novel method through which existing synoptic data can be harnessed to monitor reporting patterns and provide individualized feedback.

Malignant mesothelioma can be difficult to distinguish from other malignancies, particularly non-small cell lung carcinomas (NSCLCs), without immunohistochemistry. However, conventional markers of mesothelial lineage all have variable degrees of cross-reactivity with other neoplasms, including NSCLCs, necessitating the use of multiple mesothelioma and carcinoma markers in every case for accurate diagnosis. A recently described monoclonal HEG homolog 1 (HEG1) antibody was proposed to be a specific marker for mesothelioma. Here we performed a large scale assessment of the SKM9-2 HEG1 antibody using tissue microarrays containing 69 epithelioid mesotheliomas, 32 sarcomatoid mesotheliomas, 167 NSCLCs, and 17 ovarian high-grade serous carcinomas. Strong membrane staining, usually diffuse, for HEG1 was seen in 65/69 (94%) epithelioid mesotheliomas, 0/60 pulmonary squamous cell carcinomas, 0/73 pulmonary adenocarcinomas, and 0/13 pulmonary large cell carcinomas. HEG1 showed staining in 14/32 (44%) sarcomatoid mesotheliomas compared with 0/21 sarcomatoid pulmonary carcinomas. Three of 17 (18%) high-grade serous carcinomas demonstrated membrane staining. Ten B3 thymoma whole sections were negative. On the microarrays, the conventional mesothelial markers calretinin, WT1, D2-40, and CK5/6 had sensitivities for epithelioid mesothelioma of 94%, 90%, 96%, and 91%, respectively. We conclude that HEG1 SKM9-2 antibody offers sensitivity comparable to conventional markers for epithelioid mesotheliomas, but provides considerably better specificity, such that the diagnosis of epithelioid mesothelioma versus NSCLC potentially could be confirmed with a combination of HEG1 and a suitable broad spectrum carcinoma marker such as claudin-4. HEG1 is specific but insensitive for separating sarcomatoid mesotheliomas from sarcomatoid lung carcinomas.

Whipple's endocarditis is a rare but treatable infectious disease. We discuss the diagnostic work-up of a case lacking classic endocarditis features. Current challenges in diagnosis and treatment of this under-recognized infection are highlighted. This case underscores the necessity of considering Whipple's endocarditis in the differential diagnosis for chronic valvular disease. Keywords: Whipple's endocarditis, Whipple's disease, Tropheryma whipplei, Endocarditis, Culture-negative endocarditis

AIMS Accurate assessment of programmed death-ligand 1 (PD-L1) levels in non-small cell lung carcinoma (NSCLC) samples is complicated by intratumoral heterogeneity. We aimed to: (i) establish whether intratumoral PD-L1 variation is associated with differences in local histotype; (ii) identify histotypes associated with a tendency for there to be higher or lower PD-L1 scores; and (iii) estimate the frequency of clinically significant discordance in PD-L1 levels between intratumoral histotype areas. METHODS AND RESULTS We reviewed 166 NSCLC resection specimens clinically tested for PD-L1 with the 22C3 pharmDx assay. Multiple histotypes were present in 55% (68/123) of non-mucinous adenocarcinoma samples. Solid histotypes had significantly higher PD-L1 levels than other histotypes, both when samples were grouped by predominant histotype, and when histotype areas within a tumour were compared (P

PD-L1 expression in non-small cell lung cancer (NSCLC) is predictive of response to treatment with PD-1 and PD-L1 inhibitors. Different inhibitors have been developed with different PD-L1 assays, which use different PD-1 antibody clones on different immunohistochemistry platforms. Depending on instrument and reagent availability, laboratory-developed tests with cross-platform use of PD-L1 antibodies may have practical benefits over commercial assays. The 22C3 pharmDx Assay (referred to as 22C3 DAKO), the VENTANA PD-L1 SP263 Assay (referred to as SP263 VENTANA) and a lab-developed test using the 22C3 antibody on the VENTANA BenchMark ULTRA IHC/ISH system (referred to as 22C3 VENTANA) were performed on whole sections of 85 NSCLC surgical resections. All sections were independently scored by three pathologists using tumor proportion scores. Correlation coefficients for continuous scores in pairwise comparisons between assays ranged from 0.976 to 0.978. When using a 1% positivity threshold (dichotomous scores), the 22C3 DAKO assay and 22C3 VENTANA assays showed the greatest agreement (93% agreement, κ = 0.86, 95% CI 0.75–0.97), and the 22C3 DAKO and SP263 VENTANA assays tended to show slightly less agreement (84% agreement, κ = 0.66, 95% CI 0.50–0.82). When using a 50% positivity threshold (dichotomous scores), all pairwise comparisons showed similar agreement (96–99% agreement, κ = 0.89–0.97). Overall, there was no significant difference between assays at 1% or 50% thresholds (P = .77). These data are consistent with potential interchangeability of these assays, which may widen the scope of PD-L1 assays available to laboratories and reduce logistical barriers to testing.