9 research outputs found
Epidemiology, Mortality and Healthcare Resource Utilization Associated With Systemic Sclerosis-Associated Interstitial Lung Disease in France
International audienceObjectives: To investigate the clinical characteristics, epidemiology, survival estimates and healthcare resource utilization and associated costs in patients with systemic sclerosis-associated interstitial lung disease (SSc-ILD) in France.</p> and nbsp;</p> Methods: The French national administrative healthcare database, the Systeme National des Donnees de Sante (SNDS), includes data on 98.8% of the French population, including data relating to ambulatory care, hospitalizations and death. In our study, claims data from the SNDS were used to identify adult patients with SSc-ILD between 2010 and 2017. We collected data on clinical features, incidence, prevalence, survival estimates, healthcare resource use and costs.</p> and nbsp;</p> Results: In total, 3,333 patients with SSc-ILD were identified, 76% of whom were female. Patients had a mean age [standard deviation (SD)] of 60.6 (14.4) years and a mean (SD) individual study duration of 3.9 (2.7) years. In 2016, the estimated overall incidence and prevalence were 0.69/100,000 individuals and 5.70/100,000 individuals, respectively. The overall survival estimates of patients using Kaplan-Meier estimation were 93, 82, and 55% at 1, 3, and 8 years, respectively. During the study, 98.7% of patients had and GE;1 hospitalization and 22.3% of patients were hospitalized in an intensive care unit. The total annual mean healthcare cost per patient with SSc-ILD was euro 25,753, of which euro 21,539 was related to hospitalizations.</p> and nbsp;</p> Conclusions: This large, real-world longitudinal study provides important insights into the epidemiology of SSc-ILD in France and shows that the disease is associated with high mortality, healthcare resource utilization and costs. SSc-ILD represents a high burden on both patients and healthcare services.</p> and nbsp;</p>
T-cadherin expression in cardiac allograft vasculopathy: Bench to bedside translational investigation
The Minasarc study: A case-control study measuring mineral exposome in sarcoidosis
International audienceIntroduction: it has been suggested that sarcoidosis could be associated with exposure to inorganic particles (Newman LS Curr Opin All Clin Immunol 2012; 12:145-50, Vincent M et al Am J Ind Med 2015; 58:S31-8).Objectives: in order to test this hypothesis the Minasarc study was designed to evaluate the mineral exposome by a specific questionnaire (SQ) and a mineralogical analysis performed on BALs by optical and electron microscopy in patients and healthy volunteers (HV). We present here the results obtained by the SQ which can be considered as a tool for global assessment of the “whole life” exposure to inorganic particles in occupational and environmental contexts.Methods: The study was performed on 20 patients with sarcoidosis and 20 HV. Every HV was matched to a patient by sex, age and smoking habit. The SQ was calibrated with a representative sample of the French population (n=825) in the ELIPSSilice survey (ANR-10-Eqpx-19-01) and the result was expressed as a “dust score”. Scores were compared by a Wilcoxon signed-rank test.Results: The “dust score” was found significantly higher in patients with sarcoidosis than in HV (p=0,036; Wilcoxon signed-rank test). Moreover we found a significant overrepresentation of people exposed to building activities among the cases. However this remains to be assessed on a larger series.Conclusion: The SQ demonstrated a significantly higher level of exposure to inorganic dusts in patients with sarcoidosis compared to HV. Such preliminary results encourage 1) to study the association between sarcoidosis and inorganic dust exposure and 2) to submit routinely this exposure questionnaire to every patient with a granulomatous disease
The Minasarc study: A case-control study measuring mineral exposome in sarcoidosis
International audienc
Comprehensive Molecular and Pathologic Evaluation of Transitional Mesothelioma Assisted by Deep Learning Approach: A Multi-Institutional Study of the International Mesothelioma Panel from the MESOPATH Reference Center
International audienceAbstractIntroductionHistologic subtypes of malignant pleural mesothelioma are a major prognostic indicator and decision denominator for all therapeutic strategies. In an ambiguous case, a rare transitional mesothelioma (TM) pattern may be diagnosed by pathologists either as epithelioid mesothelioma (EM), biphasic mesothelioma (BM), or sarcomatoid mesothelioma (SM). This study aimed to better characterize the TM subtype from a histological, immunohistochemical, and molecular standpoint. Deep learning of pathologic slides was applied to this cohort.MethodsA random selection of 49 representative digitalized sections from surgical biopsies of TM was reviewed by 16 panelists. We evaluated BAP1 expression and CDKN2A (p16) homozygous deletion. We conducted a comprehensive, integrated, transcriptomic analysis. An unsupervised deep learning algorithm was trained to classify tumors.ResultsThe 16 panelists recorded 784 diagnoses on the 49 cases. Even though a Kappa value of 0.42 is moderate, the presence of a TM component was diagnosed in 51%. In 49% of the histological evaluation, the reviewers classified the lesion as EM in 53%, SM in 33%, or BM in 14%. Median survival was 6.7 months. Loss of BAP1 observed in 44% was less frequent in TM than in EM and BM. p16 homozygous deletion was higher in TM (73%), followed by BM (63%) and SM (46%). RNA sequencing unsupervised clustering analysis revealed that TM grouped together and were closer to SM than to EM. Deep learning analysis achieved 94% accuracy for TM identification.ConclusionThese results revealed that the TM pattern should be classified as non-EM or at minimum as a subgroup of the SM type
SMARCA4 inactivation defines a group of undifferentiated thoracic malignancies transcriptionally related to BAF-deficient sarcomas
International audienceWhile investigating cohorts of unclassified sarcomas by RNA sequencing, we identified 19 cases with inactivation of SMARCA4, which encodes an ATPase subunit of BAF chromatin-remodeling complexes. Clinically, the cases were all strikingly similar, presenting as compressive mediastino-pulmonary masses in 30- to 35-year-old adults with a median survival time of 7 months. To help define the nosological relationships of these tumors, we compared their transcriptomic profiles with those of SMARCA4-mutated small-cell carcinomas of the ovary, hypercalcemic type (SCCOHTs), SMARCB1-inactivated malignant rhabdoid tumors (MRTs) and lung carcinomas (of which 10% display SMARCA4 mutations). Gene profiling analyses demonstrated that these tumors were distinct from lung carcinomas but related to MRTs and SCCOHTs. Transcriptome analyses, further validated by immunohistochemistry, highlighted strong expression of SOX2, a marker that supports the differential diagnosis of these tumors from SMARCA4-deficient lung carcinomas. The prospective recruitment of cases confirmed this new category of 'SMARCA4-deficient thoracic sarcomas' as readily recognizable in clinical practice, providing opportunities to tailor their therapeutic management
Disentangling heterogeneity of Malignant Pleural Mesothelioma through deep integrative omics analyses
Summary Malignant Pleural Mesothelioma (MPM) is an aggressive cancer with rising incidence and challenging clinical management. Using the largest series of whole-genome sequencing data integrated with transcriptomic and epigenomic data using multi-omic factor analysis, we demonstrate that MPM heterogeneity arises from four sources of variation: tumor cell morphology, ploidy, adaptive immune response, and CpG island methylator phenotype. Previous genomic studies focused on describing only the tumor cell morphology factor, although we robustly find the three other sources in all publicly available cohorts. We prove how these sources of variation explain the biological functions performed by the cancer cells, and how genomic events shape MPM molecular profiles. We show how these new sources of variation help understand the heterogeneity of the clinical behavior of MPM and drug responses measured in cell lines. These findings unearth the interplay between MPM functional biology and its genomic history, and ultimately, inform classification, prognostication and treatment. Graphical abstrac
Multiomic analysis of malignant pleural mesothelioma identifies molecular axes and specialized tumor profiles driving intertumor heterogeneity
International audienceAbstract Malignant pleural mesothelioma (MPM) is an aggressive cancer with rising incidence and challenging clinical management. Through a large series of whole-genome sequencing data, integrated with transcriptomic and epigenomic data using multiomics factor analysis, we demonstrate that the current World Health Organization classification only accounts for up to 10% of interpatient molecular differences. Instead, the MESOMICS project paves the way for a morphomolecular classification of MPM based on four dimensions: ploidy, tumor cell morphology, adaptive immune response and CpG island methylator profile. We show that these four dimensions are complementary, capture major interpatient molecular differences and are delimited by extreme phenotypes that—in the case of the interdependent tumor cell morphology and adapted immune response—reflect tumor specialization. These findings unearth the interplay between MPM functional biology and its genomic history, and provide insights into the variations observed in the clinical behavior of patients with MPM