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BACKGROUND: Deployment and access to state-of-the-art precision medicine technologies remains a fundamental challenge in providing equitable global cancer care in low-resource settings. The expansion of digital pathology in recent years and its potential interface with diagnostic artificial intelligence algorithms provides an opportunity to democratize access to personalized medicine. Current digital pathology workstations, however, cost thousands to hundreds of thousands of dollars. As cancer incidence rises in many low- and middle-income countries, the validation and implementation of low-cost automated diagnostic tools will be crucial to helping healthcare providers manage the growing burden of cancer. METHODS: Here we describe a low-cost ($230) workstation for digital slide capture and computational analysis composed of open-source components. We analyze the predictive performance of deep learning models when they are used to evaluate pathology images captured using this open-source workstation versus images captured using common, significantly more expensive hardware. Validation studies assessed model performance on three distinct datasets and predictive models: head and neck squamous cell carcinoma (HPV positive versus HPV negative), lung cancer (adenocarcinoma versus squamous cell carcinoma), and breast cancer (invasive ductal carcinoma versus invasive lobular carcinoma). FINDINGS: When compared to traditional pathology image capture methods, low-cost digital slide capture and analysis with the open-source workstation, including the low-cost microscope device, was associated with model performance of comparable accuracy for breast, lung, and HNSCC classification. At the patient level of analysis, AUROC was 0.84 for HNSCC HPV status prediction, 1.0 for lung cancer subtype prediction, and 0.80 for breast cancer classification. INTERPRETATION: Our ability to maintain model performance despite decreased image quality and low-power computational hardware demonstrates that it is feasible to massively reduce costs associated with deploying deep learning models for digital pathology applications. Improving access to cutting-edge diagnostic tools may provide an avenue for reducing disparities in cancer care between high- and low-income regions. FUNDING: Funding for this project including personnel support was provided via grants from NIH/NCIR25-CA240134, NIH/NCIU01-CA243075, NIH/NIDCRR56-DE030958, NIH/NCIR01-CA276652, NIH/NCIK08-CA283261, NIH/NCI-SOAR25CA240134, SU2C (Stand Up to Cancer) Fanconi Anemia Research Fund - Farrah Fawcett Foundation Head and Neck Cancer Research Team Grant, and the European UnionHorizon Program (I3LUNG).

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Technological development of microwave treatment and detection techniques for lung cancer requires accurate and comprehensive knowledge of the microwave dielectric properties of human lung tissue. We characterize the dielectric properties of room temperature human lung tissue from 0.5 to 10 GHz for three lung tissue groups: normal, fibroelastotic, and malignant. We fit a two-pole Debye model to the measured frequency-dependent complex permittivity and calculate the median Debye parameters for the three groups. We find that malignant lung tissue is approximately 10% higher in relative permittivity and conductivity compared to normal lung tissue; this trend matches previously reported normal versus malignant data for other biological tissues. There is little contrast between benign lung tissue with fibroelastosis and malignant lung tissue. We extrapolate our data from room temperature to 37 °C using a temperature-dependence model for animal lung tissue and use the Maxwell-Garnett dielectric mixing model to predict the dielectric properties of inflation-dynamic human lung tissue; both approximations correspond with previously reported dielectric data of bovine and porcine lung tissue.

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CONTEXT.­: Mesothelioma is an uncommon tumor that can be difficult to diagnose. OBJECTIVE.­: To provide updated, practical guidelines for the pathologic diagnosis of mesothelioma. DATA SOURCES.­: Pathologists involved in the International Mesothelioma Interest Group and others with expertise in mesothelioma contributed to this update. Reference material includes peer-reviewed publications and textbooks. CONCLUSIONS.­: There was consensus opinion regarding guidelines for (1) histomorphologic diagnosis of mesothelial tumors, including distinction of epithelioid, biphasic, and sarcomatoid mesothelioma; recognition of morphologic variants and patterns; and recognition of common morphologic pitfalls; (2) molecular pathogenesis of mesothelioma; (3) application of immunohistochemical markers to establish mesothelial lineage and distinguish mesothelioma from common morphologic differentials; (4) application of ancillary studies to distinguish benign from malignant mesothelial proliferations, including BAP1 and MTAP immunostains; novel immunomarkers such as Merlin and p53; fluorescence in situ hybridization (FISH) for homozygous deletion of CDKN2A; and novel molecular assays; (5) practical recommendations for routine reporting of mesothelioma, including grading epithelioid mesothelioma and other prognostic parameters; (6) diagnosis of mesothelioma in situ; (7) cytologic diagnosis of mesothelioma, including use of immunostains and molecular assays; and (8) features of nonmalignant peritoneal mesothelial lesions.

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Introduction. The identification of mitotic figures is essential for the diagnosis, grading, and classification of various different tumors. Despite its importance, there is a paucity of literature reporting the consistency in interpreting mitotic figures among pathologists. This study leverages publicly accessible datasets and social media to recruit an international group of pathologists to score an image database of more than 1000 mitotic figures collectively. Materials and Methods. Pathologists were instructed to randomly select a digital slide from The Cancer Genome Atlas (TCGA) datasets and annotate 10-20 mitotic figures within a 2 mm2 area. The first 1010 submitted mitotic figures were used to create an image dataset, with each figure transformed into an individual tile at 40x magnification. The dataset was redistributed to all pathologists to review and determine whether each tile constituted a mitotic figure. Results. Overall pathologists had a median agreement rate of 80.2% (range 42.0%-95.7%). Individual mitotic figure tiles had a median agreement rate of 87.1% and a fair inter-rater agreement across all tiles (kappa = 0.284). Mitotic figures in prometaphase had lower percentage agreement rates compared to other phases of mitosis. Conclusion. This dataset stands as the largest international consensus study for mitotic figures to date and can be utilized as a training set for future studies. The agreement range reflects a spectrum of criteria that pathologists use to decide what constitutes a mitotic figure, which may have potential implications in tumor diagnostics and clinical management.

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Mesothelioma is a rare disease with an historically poor prognosis. Over the past decade, a grading system has been developed that is a powerful prognostic tool in epithelioid mesothelioma. Grading of epithelioid mesothelioma is now required or strongly recommended by expert consensus, the College of American Pathologists, the World Health Organization, and the International Mesothelioma Interest Group. The original nuclear grading system for epithelioid mesothelioma, developed in the United States, split epithelioid mesotheliomas into three prognostic groups with marked differences in survival. Now, this three-tiered nuclear grading system has been combined with the presence or absence of necrosis to form the currently recommended two-tiered grading system of low- and high-grade epithelioid mesothelioma. This review will focus on the development of this grading system in mesothelioma, the grading system's shortcomings, and the application of the grading system to cytology specimens and other extra-pleural sites. Lastly, this review will briefly discuss alternative grading systems and future considerations.

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Artificial intelligence methods including deep neural networks (DNN) can provide rapid molecular classification of tumors from routine histology with accuracy that matches or exceeds human pathologists. Discerning how neural networks make their predictions remains a significant challenge, but explainability tools help provide insights into what models have learned when corresponding histologic features are poorly defined. Here, we present a method for improving explainability of DNN models using synthetic histology generated by a conditional generative adversarial network (cGAN). We show that cGANs generate high-quality synthetic histology images that can be leveraged for explaining DNN models trained to classify molecularly-subtyped tumors, exposing histologic features associated with molecular state. Fine-tuning synthetic histology through class and layer blending illustrates nuanced morphologic differences between tumor subtypes. Finally, we demonstrate the use of synthetic histology for augmenting pathologist-in-training education, showing that these intuitive visualizations can reinforce and improve understanding of histologic manifestations of tumor biology.

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OBJECTIVES: Mesothelioma is a lethal disease that arises from the serosal lining of organ cavities. Several recurrent alterations have been observed in pleural and peritoneal -mesotheliomas, including in BAP1, NF2, and CDKN2A. Although specific histopathologic parameters have been correlated with prognosis, it is not as well known whether genetic alterations correlate with histologic findings. METHODS: We reviewed 131 mesotheliomas that had undergone next-generation sequencing (NGS) at our institutions after pathologic diagnosis. There were 109 epithelioid mesotheliomas, 18 biphasic mesotheliomas, and 4 sarcomatoid mesotheliomas. All our biphasic and sarcomatoid cases arose in the pleura. Of the epithelioid mesotheliomas, 73 were from the pleura and 36 were from the peritoneum. On average, patients were 66 years of age (range, 26-90 years) and predominantly male (92 men, 39 women). RESULTS: The most common alterations identified were in BAP1, CDKN2A, NF2, and TP53. Twelve mesotheliomas did not show a pathogenic alteration on NGS. For epithelioid mesotheliomas in the pleura, the presence of an alteration in BAP1 correlated with low nuclear grade (P = .04), but no correlation was found in the peritoneum (P = .62). Similarly, there was no correlation between the amount of solid architecture in epithelioid mesotheliomas and any alterations in the pleura (P = .55) or peritoneum (P = .13). For biphasic mesotheliomas, cases with either no alteration detected or with an alteration in BAP1 were more likely to be epithelioid predominant (>50% of the tumor, P = .0001), and biphasic mesotheliomas with other alterations detected and no alteration in BAP1 were more likely to be sarcomatoid predominant (>50% of the tumor, P = .0001). CONCLUSIONS: This study demonstrates a significant association between morphologic features associated with a better prognosis and an alteration in BAP1.

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Subclonal loss of mismatch repair (MMR) proteins has been described in a small subset of endometrial carcinomas (ECs), but the genomic basis for this phenomenon has received limited attention. Herein, we retrospectively evaluated all ECs with MMR immunohistochemistry (n=285) for subclonal loss, and in those (n=6), performed a detailed clinicopathologic and genomic comparison of the MMR-deficient and MMR-proficient components. Three tumors were FIGO stage IA, and one each stage IB, II, and IIIC2. Patterns of subclonal loss were as follows: (1) 3 FIGO grade 1 endometrioid carcinomas with subclonal MLH1/PMS2, MLH1 promoter hypermethylation, and no MMR gene mutations; (2) POLE -mutated FIGO grade 3 endometrioid carcinoma with subclonal PMS2, and PMS2 and MSH6 mutations limited to the MMR-deficient component; (3) dedifferentiated carcinoma with subclonal MSH2/MSH6, as well as complete loss of MLH1/PMS2, MLH1 promoter hypermethylation, and PMS2 and MSH6 mutations in both components; (4) dedifferentiated carcinoma with subclonal MSH6, and somatic and germline MSH6 mutations in both components, but with a higher allele frequency in MMR-deficient foci. Recurrences occurred in 2 patients, one consisted of the MMR-proficient component from a FIGO 1 endometrioid carcinoma, while the other was from the MSH6 -mutated dedifferentiated endometrioid carcinoma. At the last follow-up (median: 44 mo), 4 patients were alive and disease-free and 2 were alive with disease. In summary, subclonal MMR loss reflects subclonal and often complex genomic and epigenetic alterations, which may have therapeutic implications and therefore must be reported when present. In addition, subclonal loss can occur in both POLE -mutated and Lynch syndrome-associated ECs.

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RATIONALE: Contribution of central lung tissues to pathogenesis of idiopathic pulmonary fibrosis (IPF) remains unknown. OBJECTIVE: To ascertain the relationship between cell types of IPF-central and IPF-peripheral lung explants using RNA sequencing (RNA-seq) transcriptome. METHODS: Biopsies of paired IPF-central and IPF-peripheral along with non-IPF lungs were selected by reviewing H&E data. Criteria for differentially expressed genes (DEG) were set at false discovery rate <5% and fold change >2. Computational cell composition deconvolution was performed. Signature scores were computed for each cell type. FINDINGS: Comparison of central IPF versus non-IPF identified 1723 DEG (1522 upregulated and 201 downregulated). Sixty-two per cent (938/1522) of the mutually upregulated genes in central IPF genes were also upregulated in peripheral IPF versus non-IPF. Moreover, 85 IPF central-associated genes (CAG) were upregulated in central IPF versus both peripheral IPF and central non-IPF. IPF single-cell RNA-seq analysis revealed the highest CAG signature score in myofibroblasts and significantly correlated with a previously published activated fibroblasts signature (r=0.88, p=1.6×10-4). CAG signature scores were significantly higher in IPF than in non-IPF myofibroblasts (p=0.013). Network analysis of central-IPF genes identified a module significantly correlated with the deconvoluted proportion of myofibroblasts in central IPF and anti-correlated with inflammation foci trait in peripheral IPF. The module genes were over-represented in idiopathic pulmonary fibrosis signalling pathways. INTERPRETATION: Gene expression in central IPF lung regions demonstrates active myofibroblast features that contributes to disease progression. Further elucidation of pathological transcriptomic state of cells in the central regions of the IPF lung that are relatively spared from morphological rearrangements may provide insights into molecular changes in the IPF progression.

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In the 3rd year of the SARS-CoV-2 pandemic, much has been learned about the long-term effects of COVID-19 pneumonia on the lungs. Approximately one-third of patients with moderate-to-severe pneumonia, especially those requiring intensive care therapy or mechanical ventilation, have residual abnormalities at chest CT 1 year after presentation. Abnormalities range from parenchymal bands to bronchial dilation to frank fibrosis. Less is known about the long-term pulmonary vascular sequelae, but there appears to be a persistent, increased risk of venothromboembolic events in a small cohort of patients. Finally, the associated histologic abnormalities resulting from SARS-CoV-2 infection are similar to those seen in patients with other causes of acute lung injury.

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A model's ability to express its own predictive uncertainty is an essential attribute for maintaining clinical user confidence as computational biomarkers are deployed into real-world medical settings. In the domain of cancer digital histopathology, we describe a clinically-oriented approach to uncertainty quantification for whole-slide images, estimating uncertainty using dropout and calculating thresholds on training data to establish cutoffs for low- and high-confidence predictions. We train models to identify lung adenocarcinoma vs. squamous cell carcinoma and show that high-confidence predictions outperform predictions without uncertainty, in both cross-validation and testing on two large external datasets spanning multiple institutions. Our testing strategy closely approximates real-world application, with predictions generated on unsupervised, unannotated slides using predetermined thresholds. Furthermore, we show that uncertainty thresholding remains reliable in the setting of domain shift, with accurate high-confidence predictions of adenocarcinoma vs. squamous cell carcinoma for out-of-distribution, non-lung cancer cohorts.

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PURPOSE: The lack of effective molecular biomarkers to monitor idiopathic pulmonary fibrosis (IPF) activity or treatment response remains an unmet clinical need. Herein, we determined the utility of fibroblast activation protein inhibitor for positron emission tomography (FAPI PET) imaging in a mouse model of pulmonary fibrosis. METHODS: Pulmonary fibrosis was induced by intratracheal administration of bleomycin (1 U/kg) while intratracheal saline was administered to control mice. Subgroups from each cohort (n = 3-5) underwent dynamic 1 h PET/CT after intravenously injecting FAPI-46 radiolabeled with gallium-68 ([68 Ga]Ga-FAPI-46) at 7 days and 14 days following disease induction. Animals were sacrificed following imaging for ex vivo gamma counting and histologic correlation. [68 Ga]Ga-FAPI-46 uptake was quantified and reported as percent injected activity per cc (%IA/cc) or percent injected activity (%IA). Lung CT density in Hounsfield units (HU) was also correlated with histologic examinations of lung fibrosis. RESULTS: CT only detected differences in the fibrotic response at 14 days post-bleomycin administration. [68 Ga]Ga-FAPI-46 lung uptake was significantly higher in the bleomycin group than in control subjects at 7 days and 14 days. Significantly (P = 0.0012) increased [68 Ga]Ga-FAPI-46 lung uptake in the bleomycin groups at 14 days (1.01 ± 0.12%IA/cc) vs. 7 days (0.33 ± 0.09%IA/cc) at 60 min post-injection of the tracer was observed. These findings were consistent with an increase in both fibrinogenesis and FAP expression as seen in histology. CONCLUSION: CT was unable to assess disease activity in a murine model of IPF. Conversely, FAPI PET detected both the presence and activity of lung fibrogenesis, making it a promising tool for assessing early disease activity and evaluating the efficacy of therapeutic interventions in lung fibrosis patients.

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Lung transplantation has been well described for patients with coronavirus disease 2019 (COVID-19) in the acute setting, but less so for the resulting pulmonary sequelae. This report describes a case of lung transplantation for post-COVID-19 pulmonary fibrosis. A 52-year-old woman contracted COVID-19 in July 2020 and mounted a partial recovery, but she went on to have declining function over the ensuing 3 months, with development of fibrocystic lung changes. She underwent bilateral lung transplantation and recovered rapidly, was discharged home on postoperative day 14, and has done well in follow-up. This case report demonstrates that lung transplantation is an acceptable therapy for post-COVID-19 pulmonary fibrosis.

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The Cancer Genome Atlas (TCGA) is one of the largest biorepositories of digital histology. Deep learning (DL) models have been trained on TCGA to predict numerous features directly from histology, including survival, gene expression patterns, and driver mutations. However, we demonstrate that these features vary substantially across tissue submitting sites in TCGA for over 3,000 patients with six cancer subtypes. Additionally, we show that histologic image differences between submitting sites can easily be identified with DL. Site detection remains possible despite commonly used color normalization and augmentation methods, and we quantify the image characteristics constituting this site-specific digital histology signature. We demonstrate that these site-specific signatures lead to biased accuracy for prediction of features including survival, genomic mutations, and tumor stage. Furthermore, ethnicity can also be inferred from site-specific signatures, which must be accounted for to ensure equitable application of DL. These site-specific signatures can lead to overoptimistic estimates of model performance, and we propose a quadratic programming method that abrogates this bias by ensuring models are not trained and validated on samples from the same site.

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OBJECTIVES: Numerous studies on malignant mesothelioma (MM) highlight the prognostic importance of histologic subtype, nuclear grade, and necrosis. This study compares these parameters in paired biopsy and resection specimens of pleural MM. METHODS: Histologic subtype, percentage of epithelioid morphology, nuclear grade, and the presence or absence of necrosis were compared in 429 paired biopsies and resection specimens of pleural MM from 19 institutions. RESULTS: Histologic subtype was concordant in 81% of cases (κ = 0.58). When compared with resection specimens, epithelioid morphology at biopsy had a positive predictive value (PPV) of 78.9% and a negative predictive value (NPV) of 93.5%; sarcomatoid morphology showed high PPV (92.9%) and NPV (99.3%), and biphasic morphology PPV was 89.7% and NPV was 79.7%. Agreement of the percentage of epithelioid morphology was fair (κ = 0.27). Nuclear grade and necrosis were concordant in 75% (κ = 0.59) and 81% (κ = 0.53) of cases, respectively. Nuclear grade showed moderate (κ = 0.53) and substantial (κ = 0.67) agreement from patients with and without neoadjuvant therapy, respectively, and necrosis showed moderate (κ = 0.47 and κ = 0.60) agreement, respectively, in the same subsets of paired specimens. CONCLUSIONS: Paired biopsy-resection specimens from pleural MM show overall moderate agreement in pathologic parameters. These findings may help guide postbiopsy management and triage of patients with MM.

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Parathyromatosis is displaced parathyroid tissue in the neck and mediastinum related to prior surgery. Parathyromatosis can be difficult to distinguish from atypical adenoma and parathyroid carcinoma. The aim of this study is to evaluate clinical and morphologic features that may differentiate parathyromatosis, atypical adenoma, and parathyroid carcinoma. Cases of parathyromatosis, atypical adenoma, and parathyroid carcinoma were identified. Index cases were reviewed by consensus for histologic features, including stromal, cytologic/architectural, and invasive features. Ki67 was performed on index cases and scored using the Adsay method. Clinical information was gathered from the electronic medical record. 4 parathyromatosis, 17 atypical adenoma, and 6 parathyroid carcinoma were included. Parathyroid carcinomas were more likely to display coarse chromatin with nucleoli (P = 0.04), infiltrative invasion (P < 0.01), and metastasis (P < 0.01). Only parathyromatosis showed circumscribed invasion. Infiltrative invasion was more common in cases with progression (P = 0.046) and metastasis (P < 0.001). Necrosis and perineural invasion were only present in cases with progression and were more frequent in cases with metastasis (P = 0.079 and P = 0.19, respectively). There were no differences in presence of a fibrous capsule, capsular invasion, intralesional fibrous bands, random endocrine atypia, solid growth, Ki67 index, gland size/weight, serum PTH/calcium levels, and locoregional recurrence rates. There is overlap in the histologic features in parathyromatosis, atypical adenoma, and parathyroid carcinoma. While perineural, vascular, and infiltrative soft tissue invasion should remain diagnostic of malignancy, other atypical features such as solid growth, coarse chromatin with nucleoli, and necrosis should raise concern for recurrence and/or metastasis, and can be present in parathyroid lesions with and without recurrence.

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Malignant peritoneal mesothelioma historically carried a grim prognosis, but outcomes have improved substantially in recent decades. The prognostic significance of clinical, morphologic, and immunophenotypic features remains ill-defined. This multi-institutional cohort comprises 225 malignant peritoneal mesotheliomas, which were assessed for 21 clinical, morphologic, and immunohistochemical parameters. For epithelioid mesotheliomas, combining nuclear pleomorphism and mitotic index yielded a composite nuclear grade, using a previously standardized grading system. Correlation of clinical, morphologic, and immunohistochemical parameters with overall and disease-free survival was examined by univariate and multivariate analyses. On univariate analysis, longer overall survival was significantly associated with diagnosis after 2000 (P = 0.0001), age <60 years (P = 0.0001), ECOG performance status 0 or 1 (P = 0.01), absence of radiographic lymph-node metastasis (P = 0.04), cytoreduction surgery (P < 0.0001), hyperthermic intraperitoneal chemotherapy (P = 0.0001), peritoneal carcinomatosis index <27 (P = 0.01), absence of necrosis (P = 0.007), and epithelioid histotype (P < 0.0001). Among epithelioid malignant mesotheliomas only, longer overall survival was further associated with female sex (P = 0.03), tubulopapillary architecture (P = 0.005), low nuclear pleomorphism (P < 0.0001), low mitotic index (P = 0.0007), and low composite nuclear grade (P < 0.0001). On multivariate analyses, the low composite nuclear grade was independently associated with longer overall and disease-free survival (P < 0.0001). Our data further clarify the interactions of clinical and pathologic features in peritoneal mesothelioma prognosis and validate the prognostic significance of a standardized nuclear-grading system in epithelioid malignant mesothelioma of the peritoneum.

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Programmed death-ligand 1 (PD-L1) expression has been described in patients with malignant peritoneal mesothelioma (MPM), but treatment strategies utilising immune checkpoint inhibition are yet to be defined. Here, we examine levels of PD-L1 expression in MPM patients treated with systemic and/or intraperitoneal chemotherapy using tissue from patient tumour biopsies or resections at multiple time points. We found the mean PD-L1 expression was higher in those with a germline mutation and/or those with a higher somatic mutation burden. Moreover, PD-L1 expression was lower in patients who had received prior chemotherapy as compared to the treatment-naive cohort. Twenty patients who received chemotherapy, either systemic and/or peritoneal, between PD-L1 measurements showed marked heterogeneity. Six (30%) patients demonstrated upregulation of PD-L1, while eight (40%) demonstrated downregulation. Heterogeneity in PD-L1 expression in MPM before and after cytotoxic therapies may present an additional consideration when initiating immune checkpoint inhibition in this rare and challenging disease.

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OBJECTIVES: To present an index case and review the histologic and electron microscopic findings in chloroquine (CQ) and hydroxychloroquine (HCQ) myopathy, focusing primarily on cardiomyopathy. CQ and HCQ are antimalarial drugs with disease-modifying activity in rheumatic diseases (DMARD) and now are among the most widely used DMARDs. Although they are rare, severe adverse effects caused mainly by deposition of intracellular metabolites in both cardiac and skeletal muscle have been described. Currently, both CQ and HCQ have been proposed to have efficacy for patients with coronavirus disease 2019, and several large centers in the United States and other countries have started clinical trials. METHODS: A case of HCQ cardiotoxicity diagnosed on an endomyocardial biopsy is presented. A review of the pathology archives was performed to identify additional cases of CQ or HCQ myopathy, and histologic changes were recorded. A brief literature review with an emphasis on pathologic findings in myopathies was performed. RESULTS: Including the index case, 4 cases of CQ or HCQ myopathy were identified. Light microscopic findings included vacuolated myopathy, and electron microscopic findings included myeloid bodies and curvilinear inclusion bodies. CONCLUSION: CQ and HCQ myopathy can present following long-term administration of the drug. The pathologic findings are nonspecific and overlap with other vacuolated myopathies, necessitating careful correlation of the histologic changes with the patient's medical history.

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Malignant mesothelioma is an uncommon tumor that may be difficult to diagnose. The International Mesothelioma Interest Group has been writing guidelines for pathological diagnosis that are periodically updated. The guidelines are being updated based on published literature in the last 3 years, and experience of more than 20 leading international pathologists in the field who will be co-authors. Updates were discussed by attendees of the Pulmonary Pathology Society Biennial Meeting (Dubrovnik, Croatia, June 2019). Areas with significant advancements/changes include utilization of immunohistochemistry (establishing mesothelial lineage and benign versus malignant), prognosis and nuclear grading, biphasic malignant mesothelioma, transitional pattern, malignant mesothelioma in situ, and therapeutic/molecular targets.