Faculty Bibliography

Background/UNASSIGNED:Mammalian cells express a single functional heparanase, an endoglycosidase that cleaves heparan sulfate and thereby promotes tumor metastasis, angiogenesis, and inflammation. Malignant mesothelioma is highly aggressive and has a poor prognosis because of the lack of markers for early diagnosis and resistance to conventional therapies. The purpose of this study was to elucidate the mode of action and biological significance of heparanase in mesothelioma and test the efficacy of heparanase inhibitors in the treatment of this malignancy. Methods/UNASSIGNED:The involvement of heparanase in mesothelioma was investigated by applying mouse models of mesothelioma and testing the effect of heparanase gene silencing (n = 18 mice per experiment; two different models) and heparanase inhibitors (ie, PG545, defibrotide; n = 18 per experiment; six different models). Synchronous pleural effusion and plasma samples from patients with mesothelioma (n = 35), other malignancies (12 non-small cell lung cancer, two small cell lung carcinoma, four breast cancer, three gastrointestinal cancers, two lymphomas), and benign effusions (five patients) were collected and analyzed for heparanase content (enzyme-linked immunosorbent assay). Eighty-one mesothelioma biopsies were analyzed by H-Score for the prognostic impact of heparanase using immunohistochemistry. All statistical tests were two-sided. Results/UNASSIGNED:Mesothelioma tumor growth, measured by bioluminescence or tumor weight at termination, was markedly attenuated by heparanase gene silencing (P = .02) and by heparanase inhibitors (PG545 and defibrotide; P < .001 and P = .01, respectively). A marked increase in survival of the mesothelioma-bearing mice (P < .001) was recorded. Heparanase inhibitors were more potent in vivo than conventional chemotherapy. Clinically, heparanase levels in patients' pleural effusions could distinguish between malignant and benign effusions, and a heparanase H-score above 90 was associated with reduced patient survival (hazard ratio = 1.89, 95% confidence interval = 1.09 to 3.27, P = .03). Conclusions/UNASSIGNED:Our results imply that heparanase is clinically relevant in mesothelioma development. Given these preclinical and clinical data, heparanase appears to be an important mediator of mesothelioma, and heparanase inhibitors are worthy of investigation as a new therapeutic modality in mesothelioma clinical trials.

Visual inspection of histopathology slides is one of the main methods used by pathologists to assess the stage, type and subtype of lung tumors. Adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) are the most prevalent subtypes of lung cancer, and their distinction requires visual inspection by an experienced pathologist. In this study, we trained a deep convolutional neural network (inception v3) on whole-slide images obtained from The Cancer Genome Atlas to accurately and automatically classify them into LUAD, LUSC or normal lung tissue. The performance of our method is comparable to that of pathologists, with an average area under the curve (AUC) of 0.97. Our model was validated on independent datasets of frozen tissues, formalin-fixed paraffin-embedded tissues and biopsies. Furthermore, we trained the network to predict the ten most commonly mutated genes in LUAD. We found that six of them-STK11, EGFR, FAT1, SETBP1, KRAS and TP53-can be predicted from pathology images, with AUCs from 0.733 to 0.856 as measured on a held-out population. These findings suggest that deep-learning models can assist pathologists in the detection of cancer subtype or gene mutations. Our approach can be applied to any cancer type, and the code is available at https://github.com/ncoudray/DeepPATH .

The Papanicolaou Society of Cytopathology has developed a set of guidelines for pulmonary cytology including indications for bronchial brushings, washings, and endobronchial ultrasound guided transbronchial fine-needle aspiration (EBUS-TBNA), technical recommendations for cytological sampling, recommended terminology and classification schemes, recommendations for ancillary testing and recommendations for post-cytological management and follow-up. All recommendations are based on the expertise of the authors, an extensive literature review and feedback from presentations at national and international conferences. This document selectively presents the results of these discussions. The present document summarizes recommendations regarding techniques used to obtain cytological and small histologic specimens from the lung and mediastinal lymph nodes including rapid on-site evaluation (ROSE), and the triage of specimens for immunocytochemical and molecular studies.

Visual inspection of histopathology slides is one of the main methods used by pathologists to assess the stage, type and subtype of lung tumors. Adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) are the most prevalent subtypes of lung cancer, and their distinction requires visual inspection by an experienced pathologist. In this study, we trained a deep convolutional neural network (inception v3) on whole-slide images obtained from The Cancer Genome Atlas to accurately and automatically classify them into LUAD, LUSC or normal lung tissue. The performance of our method is comparable to that of pathologists, with an average area under the curve (AUC) of 0.97. Our model was validated on independent datasets of frozen tissues, formalin-fixed paraffin-embedded tissues and biopsies. Furthermore, we trained the network to predict the ten most commonly mutated genes in LUAD. We found that six of them-STK11, EGFR, FAT1, SETBP1, KRAS and TP53-can be predicted from pathology images, with AUCs from 0.733 to 0.856 as measured on a held-out population. These findings suggest that deep-learning models can assist pathologists in the detection of cancer subtype or gene mutations. Our approach can be applied to any cancer type, and the code is available at https://github.com/ncoudray/DeepPATH .

OBJECTIVES/OBJECTIVE:The Blueprint (BP) Programmed Death Ligand 1 (PD-L1) Immunohistochemistry Comparability Project is a pivotal academic/professional society and industrial collaboration to assess the feasibility of harmonizing the clinical use of five independently developed commercial PD-L1 immunohistochemistry assays. The goal of BP phase 2 (BP2) was to validate the results obtained in BP phase 1 by using real-world clinical lung cancer samples. METHODS:BP2 were conducted using 81 lung cancer specimens of various histological and sample types, stained with all five trial-validated PD-L1 assays (22C3, 28-8, SP142, SP263, and 73-10); the slides were evaluated by an international panel of pathologists. BP2 also assessed the reliability of PD-L1 scoring by using digital images, and samples prepared for cytological examination. PD-L1 expression was assessed for percentage (tumor proportional score) of tumor cell (TC) and immune cell areas showing PD-L1 staining, with TCs scored continuously or categorically with the cutoffs used in checkpoint inhibitor trials. RESULTS:The BP2 results showed highly comparable staining by the 22C3, 28-8 and SP263 assays; less sensitivity with the SP142 assay; and higher sensitivity with the 73-10 assay to detect PD-L1 expression on TCs. Glass slide and digital image scorings were highly concordant (Pearson correlation >0.96). There was very strong reliability among pathologists in TC PD-L1 scoring with all assays (overall intraclass correlation coefficient [ICC] = 0.86-0.93), poor reliability in IC PD-L1 scoring (overall ICC = 0.18-0.19), and good agreement in assessing PD-L1 status on cytological cell block materials (ICC = 0.78-0.85). CONCLUSION/CONCLUSIONS:BP2 consolidates the analytical evidence for interchangeability of the 22C3, 28-8, and SP263 assays and lower sensitivity of the SP142 assay for determining tumor proportion score on TCs and demonstrates greater sensitivity of the 73-10 assay compared with that of the other assays.

The landscape of care for early stage non-small cell lung cancer continues to evolve. While some of the developments do not seem as dramatic as what has occurred in advanced disease in recent years, there is a continuous improvement in our ability to diagnose disease earlier and more accurately. We have an increased understanding of the diversity of early stage disease and how to better tailor treatments to make them more tolerable without impacting efficacy. The International Association for the Study of Lung Cancer and the Journal of Thoracic Oncology publishes this annual update to help readers keep pace with these important developments. Experts in the care of early stage lung cancer patients have provided focused updates across multiple areas including screening, pathology, staging, surgical techniques and novel technologies, adjuvant therapy, radiotherapy, surveillance, disparities, and quality of life. The source for information includes large academic meetings, the published literature, or novel unpublished data from other international oncology assemblies.