TY  - JOUR
A1  - Loeffler-Wirth, Henry
A1  - Kreuz, Markus
A1  - Hopp, Lydia
A1  - Arakelyan, Arsen
A1  - Haake, Andrea
A1  - Cogliatti, Sergio B.
A1  - Feller, Alfred C.
A1  - Hansmann, Martin-Leo
A1  - Lenze, Dido
A1  - Möller, Peter
A1  - Müller-Hermelink, Hans Konrad
A1  - Fortenbacher, Erik
A1  - Willscher, Edith
A1  - Ott, German
A1  - Rosenwald, Andreas
A1  - Pott, Christiane
A1  - Schwaenen, Carsten
A1  - Trautmann, Heiko
A1  - Wessendorf, Swen
A1  - Stein, Harald
A1  - Szczepanowski, Monika
A1  - Trümper, Lorenz
A1  - Hummel, Michael
A1  - Klapper, Wolfram
A1  - Siebert, Reiner
A1  - Loeffler, Markus
A1  - Binder, Hans
T1  - A modular transcriptome map of mature B cell lymphomas
JF  - Genome Medicine
N2  - 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.
KW  - tumor heterogeneity
KW  - B cell malignancies
KW  - gene regulation
KW  - molecular subtypes
KW  - machine learning
Y1  - 2019
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-237262
VL  - 11
ER  -