Reproducibility of Histopathological Diagnosis in Poorly Differentiated NSCLC: An International Multiobserver Study

INTRODUCTION: The 2004 World Health Organization classification of lung cancer contained three major forms of non-small-cell lung cancer: squamous cell carcinoma (SqCC), adenocarcinoma (AdC), and large cell carcinoma. The goal of this study was first, to assess the reproducibility of a set of histopathological features for SqCC in relation to other poorly differentiated non-small-cell lung cancers and second, to assess the value of immunohistochemistry in improving the diagnosis. METHODS: Resection specimens (n = 37) with SqCC, large cell carcinoma, basaloid carcinoma, sarcomatoid carcinoma, lymphoepithelial-like carcinoma, and solid AdC, were contributed by the participating pathologists. Hematoxylin and eosin (H&E) stained slides were digitized. The diagnoses were evaluated in two ways. First, the histological criteria were evaluated and the (differential) diagnosis on H&E alone was scored. Second, the added value of additional stains to make an integrated diagnosis was examined. RESULTS: The histologic criteria defining SqCC were consistently used, but in poorly differentiated cases they were infrequently present, rendering the diagnosis more difficult. Kappa scores on H&E alone were for SqCC 0.46, large cell carcinoma 0.25, basaloid carcinoma 0.27, sarcomatoid carcinoma 0.52, lymphoepithelial-like carcinoma 0.56, and solid AdC 0.21. The κ score improved with the use of additional stains for SqCC (combined with basaloid carcinoma) to 0.57, for solid AdC to 0.63. CONCLUSION: The histologic criteria that may be used in the differential diagnosis of poorly differentiated lung cancer were more precisely refined. Furthermore, additional stains improved the reproducibility of histological diagnosis of SqCC and AdC, uncovering information that was not present in routine H&E stained slides

Guidelines for pathologic diagnosis of mesothelioma: 2023 update of the consensus statement from the International Mesothelioma Interest Group

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

The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article

Scanning Electron Microscopic Analysis of Mineral Fiber Content of Lung Tissue in the Evaluation of Diffuse Pulmonary Fibrosis

The mineral fiber content of lung parenchyma in 24 cases of diffuse pulmonary fibrosis of unknown cause was determined by scanning electron microscopy and compared with that of 36 autopsy cases of histologically confirmed asbestosis and 20 autopsy cases of patients with normal lungs . Fibers were isolated from the lung using a hypochlorite digestion technique and collected on the surface of a polycarbonate filter. In addition, the types of fibers present (asbestos vs. other mineral fibers) were determined by energy dispersive x - ray analysis (EDXA). When the histologic grade of fibrosis in the cases of asbestosis was compared with the uncoated fiber content by means of linear regression analysis , it was determined that the fiber content of the 24 cases of diffuse pulmonary fibrosis of unknown cause was below the 95 % confidence limit for asbestosis in every instance. Furthermore, the majority of fibers analyzed by EDXA were not asbestos in the cases with diffuse pulmonary fibrosis of unknown cause , whereas more than 90 % of the fibers from the asbestosis cases were commercial amphiboles (amosite or crocidolite). It was concluded that most patients with advanced pulmonary fibrosis whose tissue samples do not meet histologic criteria for asbestosis do not have asbestos-induced fibrosis, even though there may be some history of exposure to asbestos. In such cases, scanning electron microscopic analysis of mineral fiber content and EDXA of the types of fibers present often provide useful information with regard to the correct classification of these cases

Pathology of Asbestos-Associated Diseases

VI, 357 p. 132 illus., 71 illus. in color.online