A modular transcriptome map of mature B cell lymphomas
Autor: | Henry Loeffler-Wirth, Markus Kreuz, Lydia Hopp, Arsen Arakelyan, Andrea Haake, Sergio B. Cogliatti, Alfred C. Feller, Martin-Leo Hansmann, Dido Lenze, Peter Möller, Hans Konrad Müller-Hermelink, Erik Fortenbacher, Edith Willscher, German Ott, Andreas Rosenwald, Christiane Pott, Carsten Schwaenen, Heiko Trautmann, Swen Wessendorf, Harald Stein, Monika Szczepanowski, Lorenz Trümper, Michael Hummel, Wolfram Klapper, Reiner Siebert, Markus Loeffler, Hans Binder, for the German Cancer Aid consortium Molecular Mechanisms for Malignant Lymphoma |
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Přispěvatelé: | German Cancer Aid consortium Molecular Mechanisms for Malignant Lymphoma |
Rok vydání: | 2018 |
Předmět: |
Tumor heterogeneity
B cell malignancies Gene regulation Molecular subtypes Machine learning 0301 basic medicine Lymphoma B-Cell lcsh:QH426-470 Molecular subtypes Follicular lymphoma lcsh:Medicine Biology Plasma cell Transcriptome Machine Learning 03 medical and health sciences 0302 clinical medicine immune system diseases hemic and lymphatic diseases Genetics medicine Humans ddc:610 Molecular Biology Genetics (clinical) B cell Research lcsh:R Large-cell lymphoma medicine.disease 3. Good health Lymphoma Gene regulation Gene Expression Regulation Neoplastic lcsh:Genetics 030104 developmental biology medicine.anatomical_structure 030220 oncology & carcinogenesis Cancer research Molecular Medicine Mantle cell lymphoma Diffuse large B-cell lymphoma |
Zdroj: | Genome Medicine Genome Medicine, Vol 11, Iss 1, Pp 1-20 (2019) |
ISSN: | 1756-994X |
Popis: | Background Germinal center-derived B cell lymphomas are tumors of the lymphoid tissues representing one of the most heterogeneous malignancies. Here we characterize the variety of transcriptomic phenotypes of this disease based on 873 biopsy specimens collected in the German Cancer Aid MMML (Molecular Mechanisms in Malignant Lymphoma) consortium. They include diffuse large B cell lymphoma (DLBCL), follicular lymphoma (FL), Burkitt’s lymphoma, mixed FL/DLBCL lymphomas, primary mediastinal large B cell lymphoma, multiple myeloma, IRF4-rearranged large cell lymphoma, MYC-negative Burkitt-like lymphoma with chr. 11q aberration and mantle cell lymphoma. Methods We apply self-organizing map (SOM) machine learning to microarray-derived expression data to generate a holistic view on the transcriptome landscape of lymphomas, to describe the multidimensional nature of gene regulation and to pursue a modular view on co-expression. Expression data were complemented by pathological, genetic and clinical characteristics. Results We present a transcriptome map of B cell lymphomas that allows visual comparison between the SOM portraits of different lymphoma strata and individual cases. It decomposes into one dozen modules of co-expressed genes related to different functional categories, to genetic defects and to the pathogenesis of lymphomas. On a molecular level, this disease rather forms a continuum of expression states than clearly separated phenotypes. We introduced the concept of combinatorial pattern types (PATs) that stratifies the lymphomas into nine PAT groups and, on a coarser level, into five prominent cancer hallmark types with proliferation, inflammation and stroma signatures. Inflammation signatures in combination with healthy B cell and tonsil characteristics associate with better overall survival rates, while proliferation in combination with inflammation and plasma cell characteristics worsens it. A phenotypic similarity tree is presented that reveals possible progression paths along the transcriptional dimensions. Our analysis provided a novel look on the transition range between FL and DLBCL, on DLBCL with poor prognosis showing expression patterns resembling that of Burkitt’s lymphoma and particularly on ‘double-hit’ MYC and BCL2 transformed lymphomas. Conclusions The transcriptome map provides a tool that aggregates, refines and visualizes the data collected in the MMML study and interprets them in the light of previous knowledge to provide orientation and support in current and future studies on lymphomas and on other cancer entities. Electronic supplementary material The online version of this article (10.1186/s13073-019-0637-7) contains supplementary material, which is available to authorized users. |
Databáze: | OpenAIRE |
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