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 - TY - JOUR A1 - Kim, Mia A1 - Grimmig, Tanja A1 - Grimm, Martin A1 - Lazariotou, Maria A1 - Meier, Eva A1 - Rosenwald, Andreas A1 - Tsaur, Igor A1 - Blaheta, Roman A1 - Heemann, Uwe A1 - Germer, Christoph-Thomas A1 - Waaga-Gasser, Ana Maria A1 - Gasser, Martin T1 - Expression of Foxp3 in Colorectal Cancer but Not in Treg Cells Correlates with Disease Progression in Patients with Colorectal Cancer JF - PLoS ONE N2 - Background Measles virus (MV) causes T cell suppression by interference with phosphatidylinositol-3-kinase (PI3K) activation. We previously found that this interference affected the activity of splice regulatory proteins and a T cell inhibitory protein isoform was produced from an alternatively spliced pre-mRNA. Hypothesis Differentially regulated and alternatively splice variant transcripts accumulating in response to PI3K abrogation in T cells potentially encode proteins involved in T cell silencing. Methods To test this hypothesis at the cellular level, we performed a Human Exon 1.0 ST Array on RNAs isolated from T cells stimulated only or stimulated after PI3K inhibition. We developed a simple algorithm based on a splicing index to detect genes that undergo alternative splicing (AS) or are differentially regulated (RG) upon T cell suppression. Results Applying our algorithm to the data, 9% of the genes were assigned as AS, while only 3% were attributed to RG. Though there are overlaps, AS and RG genes differed with regard to functional regulation, and were found to be enriched in different functional groups. AS genes targeted extracellular matrix (ECM)-receptor interaction and focal adhesion pathways, while RG genes were mainly enriched in cytokine-receptor interaction and Jak-STAT. When combined, AS/RG dependent alterations targeted pathways essential for T cell receptor signaling, cytoskeletal dynamics and cell cycle entry. Conclusions PI3K abrogation interferes with key T cell activation processes through both differential expression and alternative splicing, which together actively contribute to T cell suppression. KW - T cells KW - gene regulation KW - alternative splicing KW - measles virus KW - T cell receptors KW - reverse transcriptase-polymerase chain reaction KW - TCR signaling cascade KW - cell cycle and cell division Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-130340 VL - 8 IS - 1 ER -