1. Refining diffuse large B-cell lymphoma subgroups using integrated analysis of molecular profiles
- Author
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Bettina Fabiani, Sylvain Mareschal, Pascaline Etancelin, Tony Petrella, Fabrice Jardin, Bruno Tesson, Sydney Dubois, Jean-Philippe Jais, Christiane Copie-Bergman, Gilles Salles, Elodie Bohers, Corinne Haioun, Pierre-Julien Viailly, Thierry Jo Molina, Philippe Ruminy, Karen Leroy, Hervé Tilly, Pauline Peyrouze, Génomique et Médecine Personnalisée du Cancer et des Maladies Neuropsychiatriques (GPMCND), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Carnot CALYM [Pierre-Benite], Synergie Lyon Cancer-Platform of Bioinformatics-Gilles Thomas, Centre de Recherche en Cancérologie de Lyon (UNICANCER/CRCL), Centre Léon Bérard [Lyon]-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre Léon Bérard [Lyon]-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre de Lutte Contre le Cancer Henri Becquerel Normandie Rouen (CLCC Henri Becquerel), Université Lille 2 - Faculté de Médecine, INSERM U955, équipe 9, Département de pathologie [Mondor], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Henri Mondor-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Henri Mondor-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-IFR10-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-IFR10, Service de Pathologie [CHU Saint-Antoine], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Saint-Antoine [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Centre de pathologie, Service d'informatique médicale et biostatistiques [CHU Necker], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Necker - Enfants Malades [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Université Paris-Est Créteil Val-de-Marne - Faculté de médecine (UPEC Médecine), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Service d'hématologie [Hôpital Edouard Herriot - HCL], Hôpital Edouard Herriot [CHU - HCL], Hospices Civils de Lyon (HCL)-Hospices Civils de Lyon (HCL), Service d'anatomie pathologique [CHU Necker], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Henri Mondor-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Département d'Hématologie, Institut Carnot Lymphome (CALYM), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre Léon Bérard [Lyon]-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Faculté de Médecine Henri Warembourg - Université de Lille, Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), and Centre de pathologie [Dijon]
- Subjects
0301 basic medicine ,Male ,Research paper ,Key genes ,Transcriptomic variability ,DNA Copy Number Variations ,lcsh:Medicine ,[SDV.CAN]Life Sciences [q-bio]/Cancer ,Locus (genetics) ,Computational biology ,Independent component analysis ,Biology ,General Biochemistry, Genetics and Molecular Biology ,Transcriptome ,03 medical and health sciences ,0302 clinical medicine ,[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN] ,hemic and lymphatic diseases ,medicine ,Biomarkers, Tumor ,Humans ,Genetic Predisposition to Disease ,Copy-number variation ,Gene signatures, prognosis ,Genetic Association Studies ,lcsh:R5-920 ,Gene Expression Profiling ,lcsh:R ,Gene signatures ,Chromosome Mapping ,Computational Biology ,[SDV.MHEP.HEM]Life Sciences [q-bio]/Human health and pathology/Hematology ,Molecular Sequence Annotation ,General Medicine ,Diffuse large B-cell lymphoma ,Gene signature ,medicine.disease ,Immunohistochemistry ,Gene expression profiling ,030104 developmental biology ,030220 oncology & carcinogenesis ,Affymetrix genechip ,Female ,prognosis ,Lymphoma, Large B-Cell, Diffuse ,lcsh:Medicine (General) - Abstract
Background: Gene expression profiling (GEP), next-generation sequencing (NGS) and copy number variation (CNV) analysis have led to an increasingly detailed characterization of the genomic profiles of DLBCL. The aim of this study was to perform a fully integrated analysis of mutational, genomic, and expression profiles to refine DLBCL subtypes. A comparison of our model with two recently published integrative DLBCL classifiers was carried out, in order to best reflect the current state of genomic subtypes. Methods: 223 patients with de novo DLBCL from the prospective, multicenter and randomized LNH-03B LYSA clinical trials were included. GEP data was obtained using Affymetrix GeneChip arrays, mutational profiles were established by Lymphopanel NGS targeting 34 key genes, CNV analysis was obtained by array CGH, and FISH and IHC were performed. Unsupervised independent component analysis (ICA) was applied to GEP data and integrated analysis of multi-level molecular data associated with each component (gene signature) was performed. Findings: ICA identified 38 components reflecting transcriptomic variability across our DLBCL cohort. Many of the components were closely related to well-known DLBCL features such as cell-of-origin, stromal and MYC signatures. A component linked to gain of 19q13 locus, among other genomic alterations, was significantly correlated with poor OS and PFS. Through this integrated analysis, a high degree of heterogeneity was highlighted among previously described DLBCL subtypes. Interpretation: The results of this integrated analysis enable a global and multi-level view of DLBCL, as well as improve our understanding of DLBCL subgroups. Keywords: Diffuse large B-cell lymphoma, Independent component analysis, Transcriptomic variability, Gene signatures, prognosis
- Published
- 2019