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Cell blocks are an integral part of cytology, but their utility is recognized probably more now than ever before, largely owing to the significant role they play in ancillary testing, particularly molecular diagnostics. Modifications to improve the cell block method initially introduced more than a century ago have been made over the years. Though their value is acknowledged and they are widely used across laboratories, cell block preparations are not standardized and results of ancillary testing performed on them are inconsistent. This article reviews the state of cell blocks—summarizes the more common, currently available and used methods and their corresponding advantages and shortcomings, outlines the role of alternative techniques (eg, smears), and proposes methods to optimize results.

The novel coronavirus SARS-CoV-2 (coronavirus disease 19, or COVID-19) primarily causes pulmonary injury, but has been implicated to cause hepatic injury, both by serum markers and histologic evaluation. The histologic pattern of injury has not been completely described. Studies quantifying viral load in the liver are lacking. Here we report the clinical and histologic findings related to the liver in 40 patients who died of complications of COVID-19. A subset of liver tissue blocks were subjected to polymerase chain reaction (PCR) for viral ribonucleic acid (RNA). Peak levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were elevated; median ALT peak 68 U/l (normal up to 46 U/l) and median AST peak 102 U/l (normal up to 37 U/l). Macrovesicular steatosis was the most common finding, involving 30 patients (75%). Mild lobular necroinflammation and portal inflammation were present in 20 cases each (50%). Vascular pathology, including sinusoidal microthrombi, was infrequent, seen in six cases (15%). PCR of liver tissue was positive in 11 of 20 patients tested (55%). In conclusion, we found patients dying of COVID-19 had biochemical evidence of hepatitis (of variable severity) and demonstrated histologic findings of macrovesicular steatosis and mild acute hepatitis (lobular necroinflammation) and mild portal inflammation. We also identified viral RNA in a sizeable subset of liver tissue samples.

Approximately 25% of all patients with non-small-cell lung cancer present with resectable stage IB–IIIA disease, and although perioperative chemotherapy is the standard of care, this treatment strategy provides only modest survival benefits. On the basis of the activity of immune checkpoint inhibitors in metastatic non-small-cell lung cancer, we designed a trial to test the activity of the PD-L1 inhibitor, atezolizumab, with carboplatin and nab-paclitaxel given as neoadjuvant treatment before surgical resection. This open-label, multicentre, single-arm, phase 2 trial was done at three hospitals in the USA. Eligible patients were aged 18 years or older and had resectable American Joint Committee on Cancer-defined stage IB–IIIA non-small-cell lung cancer, an Eastern Cooperative Oncology Group performance status of 0–1, and a history of smoking exposure. Patients received neoadjuvant treatment with intravenous atezolizumab (1200 mg) on day 1, nab-paclitaxel (100 mg/m2) on days 1, 8, and 15, and carboplatin (area under the curve 5; 5 mg/mL per min) on day 1, of each 21-day cycle. Patients without disease progression after two cycles proceeded to receive two further cycles, which were then followed by surgical resection. The primary endpoint was major pathological response, defined as the presence of 10% or less residual viable tumour at the time of surgery. All analyses were intention to treat. This study is registered with ClinicalTrials.gov, NCT02716038, and is ongoing but no longer recruiting participants. Between May 26, 2016, and March 1, 2019, we assessed 39 patients for eligibility, of whom 30 patients were enrolled. 23 (77%) of these patients had stage IIIA disease. 29 (97%) patients were taken into the operating theatre, and 26 (87%) underwent successful R0 resection. At the data cutoff (Aug 7, 2019), the median follow-up period was 12·9 months (IQR 6·2–22·9). 17 (57%; 95% CI 37–75) of 30 patients had a major pathological response. The most common treatment-related grade 3–4 adverse events were neutropenia (15 [50%] of 30 patients), increased alanine aminotransferase concentrations (two [7%] patients), increased aspartate aminotransferase concentration (two [7%] patients), and thrombocytopenia (two [7%] patients). Serious treatment-related adverse events included one (3%) patient with grade 3 febrile neutropenia, one (3%) patient with grade 4 hyperglycaemia, and one (3%) patient with grade 2 bronchopulmonary haemorrhage. There were no treatment-related deaths. Atezolizumab plus carboplatin and nab-paclitaxel could be a potential neoadjuvant regimen for resectable non-small-cell lung cancer, with a high proportion of patients achieving a major pathological response, and manageable treatment-related toxic effects, which did not compromise surgical resection. Genentech and Celgene.

Background Chest Computed tomography (CT) scans detect lung nodules and assess pulmonary fibrosis. While pulmonary fibrosis indicates increased lung cancer risk, current clinical practice characterizes nodule risk of malignancy based on nodule size and smoking history; little consideration is given to the fibrotic microenvironment. Purpose To evaluate the effect of incorporating fibrotic microenvironment into classifying malignancy of lung nodules in chest CT images using deep learning techniques. Materials and methods We developed a visualizable 3D classification model trained with in-house CT dataset for the nodule malignancy classification task. Three slightly-modified datasets were created: (1) nodule alone (microenvironment removed); (2) nodule with surrounding lung microenvironment; and (3) nodule in microenvironment with semantic fibrosis metadata. For each of the models, tenfold cross-validation was performed. Results were evaluated using quantitative measures, such as accuracy, sensitivity, specificity, and area-under-curve (AUC), as well as qualitative assessments, such as attention maps and class activation maps (CAM). Results The classification model trained with nodule alone achieved 75.61% accuracy, 50.00% sensitivity, 88.46% specificity, and 0.78 AUC; the model trained with nodule and microenvironment achieved 79.03% accuracy, 65.46% sensitivity, 85.86% specificity, and 0.84 AUC. The model trained with additional semantic fibrosis metadata achieved 80.84% accuracy, 74.67% sensitivity, 84.95% specificity, and 0.89 AUC. Our visual evaluation of attention maps and CAM suggested that both the nodules and the microenvironment contributed to the task. Conclusion The nodule malignancy classification performance was found to be improving with microenvironment data. Further improvement was found when incorporating semantic fibrosis information.

Background The tumor microenvironment (TME) plays a key role in lung cancer initiation, proliferation, invasion, and metastasis. Artificial intelligence (AI) methods could potentially accelerate TME analysis. The aims of this study were to (1) assess the feasibility of using hematoxylin and eosin (H&E)-stained whole slide images (WSI) to develop an AI model for evaluating the TME and (2) to characterize the TME of adenocarcinoma (ADCA) and squamous cell carcinoma (SCCA) in fibrotic and non-fibrotic lung. Methods The cohort was derived from chest CT scans of patients presenting with lung neoplasms, with and without background fibrosis. WSI images were generated from slides of all 76 available pathology cases with ADCA ( n  = 53) or SCCA ( n  = 23) in fibrotic ( n  = 47) or non-fibrotic ( n  = 29) lung. Detailed ground-truth annotations, including of stroma (i.e., fibrosis, vessels, inflammation), necrosis and background, were performed on WSI and optimized via an expert-in-the-loop (EITL) iterative procedure using a lightweight [random forest (RF)] classifier. A convolution neural network (CNN)-based model was used to achieve tissue-level multiclass segmentation. The model was trained on 25 annotated WSI from 13 cases of ADCA and SCCA within and without fibrosis and then applied to the 76-case cohort. The TME analysis included tumor stroma ratio (TSR), tumor fibrosis ratio (TFR), tumor inflammation ratio (TIR), tumor vessel ratio (TVR), tumor necrosis ratio (TNR), and tumor background ratio (TBR). Results The model’s overall classification for precision, sensitivity, and F1-score were 94%, 90%, and 91%, respectively. Statistically significant differences were noted in TSR ( p  = 0.041) and TFR ( p  = 0.001) between fibrotic and non-fibrotic ADCA. Within fibrotic lung, statistically significant differences were present in TFR ( p  = 0.039), TIR ( p  = 0.003), TVR ( p  = 0.041), TNR ( p  = 0.0003), and TBR ( p  = 0.020) between ADCA and SCCA. Conclusion The combined EITL—RF CNN model using only H&E WSI can facilitate multiclass evaluation and quantification of the TME. There are significant differences in the TME of ADCA and SCCA present within or without background fibrosis. Future studies are needed to determine the significance of TME on prognosis and treatment.

Abstract Objectives Although diffuse alveolar damage, a subtype of acute lung injury (ALI), is the most common microscopic pattern in coronavirus disease 2019 (COVID-19), other pathologic patterns have been described. The aim of the study was to review autopsies from COVID-19 decedents to evaluate the spectrum of pathology and correlate the results with clinical, laboratory, and radiologic findings. Methods A comprehensive and quantitative review from 40 postmortem examinations was performed. The microscopic patterns were categorized as follows: “major” when present in more than 50% of cases and “novel” if rarely or not previously described and unexpected clinically. Results Three major pulmonary patterns were identified: ALI in 29 (73%) of 40, intravascular fibrin or platelet-rich aggregates (IFPAs) in 36 (90%) of 40, and vascular congestion and hemangiomatosis-like change (VCHL) in 20 (50%) of 40. The absence of ALI (non-ALI) was novel and seen in 11 (27%) of 40. Compared with ALI decedents, those with non-ALI had a shorter hospitalization course (P = .02), chest radiographs with no or minimal consolidation (P = .01), and no pathologically confirmed cause of death (9/11). All non-ALI had VCHL and IFPAs, and clinically most had cardiac arrest. Conclusions Two distinct pulmonary phenotypic patterns—ALI and non-ALI—were noted. Non-ALI represents a rarely described phenotype. The cause of death in non-ALI is most likely COVID-19 related but requires additional corroboration.

Amphiregulin (Areg), a growth factor produced by regulatory T (Treg) cells to facilitate tissue repair, contains a heparan sulfate (HS) binding domain. How HS, a highly sulfated glycan subtype that alters growth factor signaling, influences Areg repair functions is unclear. Here we report that inhibition of HS in various cell lines and primary lung mesenchymal cells (LMC) qualitatively alters Areg downstream signaling. Utilization of a panel of cell lines with targeted deletions in HS synthesis–related genes identifies the glypican family of HS proteoglycans as critical for Areg signaling. In the context of influenza A virus (IAV) infection in vivo, an Areg-responsive subset of reparative LMC upregulate glypican-4 and HS; conditional deletion of HS primarily within this LMC subset results in reduced repair characteristics following IAV infection. This study demonstrates that HS on a specific lung mesenchymal population is a mediator of Treg cell–derived Areg reparative signaling. Amphiregulin is produced by regulatory T cells to promote tissue repair and regeneration. Here the authors characterise the function of a heparan sulphate binding region in amphiregulin and show the function of this in signalling via lung mesenchymal cells to promote lung repair after influenza infection in mouse models.

Viral infection often causes severe damage to the lungs, leading to the appearance of ectopic basal cells (EBCs) and tuft cells in the lung parenchyma. Thus far, the roles of these ectopic epithelial cells in alveolar regeneration remain controversial. Here, we confirm that the ectopic tuft cells are originated from EBCs in mouse models and COVID-19 lungs. The differentiation of tuft cells from EBCs is promoted by Wnt inhibition while suppressed by Notch inhibition. Although progenitor functions have been suggested in other organs, pulmonary tuft cells don’t proliferate or give rise to other cell lineages. Consistent with previous reports, Trp63 CreERT2 and KRT5-CreERT2 -labeled ectopic EBCs do not exhibit alveolar regeneration potential. Intriguingly, when tamoxifen was administrated post-viral infection, Trp63 CreERT2 but not KRT5-CreERT2 labels islands of alveolar epithelial cells that are negative for EBC biomarkers. Furthermore, germline deletion of Trpm5 significantly increases the contribution of Trp63 CreERT2 -labeled cells to the alveolar epithelium. Although Trpm5 is known to regulate tuft cell development, complete ablation of tuft cell production fails to improve alveolar regeneration in Pou2f3 -/- mice, implying that Trpm5 promotes alveolar epithelial regeneration through a mechanism independent of tuft cells.

Abstract Recent advances in therapy for non–small cell lung carcinoma have shown that a personalized approach to treatment has the potential to significantly reduce lung cancer mortality. Concurrently, endoscopic ultrasound transbronchial needle aspiration has emerged as an accurate and sensitive tool for the diagnosis and staging of this disease. As knowledge of the molecular mechanisms that drive lung cancer progression increases, the amount of information that must be derived from a tumor specimen will also increase. Recent clinical studies have demonstrated that small specimens acquired by endoscopic ultrasound transbronchial needle aspiration are sufficient for molecular testing if specimen acquisition and processing are done with these needs in mind. Optimum use of this procedure requires a coordinated effort between the bronchoscopist and the cytopathologist to collect and triage specimens for diagnostic testing. When feasible, rapid onsite evaluation should be performed to assess the specimen for both diagnostic quality and quantity and to allocate the specimen for cell-block and possible immunohistochemistry and molecular studies. It is necessary for pulmonologists and bronchoscopists to understand the rationale for histologic and molecular testing of lung cancer diagnostic specimens and to ensure that specimens are acquired and processed in a fashion that provides information from small cytologic specimens that is sufficient to guide treatment in this era of targeted therapy.