MMML-MYC-SYS

Motivation:

With the knowledge achieved in this project new molecular classifiers will be identified to improve the diagnosis of this disease.

MMML-MYC-SYS is a interdisciplinary consortium where partners from clinical haemaoncological study groups, pathologists, geneticicts, cell biologists as well as mathematicians, statisticians and bioinformaticists have allied. The goal is to investigate the process of development of B-cell lymphoma under special consideration of mutation of MYC. MYC is known to support the development and growth of tumors. This consortium collected and evaluated comprehensive molecular-genetic data for this purpose. The formation and growth of the tumor is simulated and predicted through computer models.

Programme: This Project is not associated with a Programme

LHA ID: 7Q0CR2P54E-8

Funding codes:

BMBF
FKZ 031 6166

Public web page: http://www.mmmlmycsys.de/

Human Diseases: Non-hodgkin lymphoma

Health Atlas - Local Data Hub/Leipzig PALs: Markus Löffler

Project Coordinators: No Project coordinators for this Project

Project start date: 1st Jan 2013

Project Hierarchy

Country: Germany

City: Leipzig

Web page: https://www.imise.uni-leipzig.de/en/

Interdisciplinary Center for Bioinformatics (IZBI)

Country: Germany

City: Leipzig

Web page: https://www.izbi.uni-leipzig.de

A modular transcriptome map of mature B cell lymphomas.

GLA - German Lymphoma Alliance, MMML-MYC-SYS, oBIG - omics Bioinformatics for Health

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Abstract (Expand)

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.

Authors: H. Loeffler-Wirth, M. Kreuz, L. Hopp, A. Arakelyan, A. Haake, S. B. Cogliatti, A. C. Feller, M. L. Hansmann, D. Lenze, P. Moller, H. K. Muller-Hermelink, E. Fortenbacher, E. Willscher, G. Ott, A. Rosenwald, C. Pott, C. Schwaenen, H. Trautmann, S. Wessendorf, H. Stein, M. Szczepanowski, L. Trumper, M. Hummel, W. Klapper, R. Siebert, M. Loeffler, H. Binder

Date Published: 30th Apr 2019

Publication Type: Not specified

Human Diseases: B-cell lymphoma, diffuse large B-cell lymphoma, follicular lymphoma, Burkitt lymphoma

PubMed ID: 31039827

Citation: Genome Med. 2019 Apr 30;11(1):27. doi: 10.1186/s13073-019-0637-7.

Created: 16th May 2019 at 09:53, Last updated: 7th Dec 2021 at 17:58

Dysregulated Signal Propagation in a MYC-associated Boolean Gene Network in B-cell Lymphoma

MMML-MYC-SYS

Abstract (Expand)

By the modern molecular biological approaches that exploit the availability of high quality gene expression data, it is made clear that flexible and robust responses of cellular programs are encoded …

Authors: V. Cakir, H. Loeffler-Wirth, A. Arakelyan, H. Binder

Date Published: 17th May 2017

Publication Type: Not specified

Human Diseases: B-cell lymphoma

DOI: 10.15761/BEM.1000115

Citation:

Created: 13th May 2019 at 10:55, Last updated: 7th Dec 2021 at 17:58

Epigenetic Heterogeneity of B-Cell Lymphoma: Chromatin Modifiers.

MMML-MYC-SYS

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Abstract (Expand)

We systematically studied the expression of more than fifty histone and DNA (de)methylating enzymes in lymphoma and healthy controls. As a main result, we found that the expression levels of nearly all …

Authors: L. Hopp, L. Nersisyan, H. Loffler-Wirth, A. Arakelyan, H. Binder

Date Published: 21st Oct 2015

Publication Type: Not specified

Human Diseases: non-Hodgkin lymphoma

PubMed ID: 26506391

Citation: Genes (Basel). 2015 Oct 21;6(4):1076-112. doi: 10.3390/genes6041076.

Created: 10th May 2019 at 11:27, Last updated: 7th Dec 2021 at 17:58

Epigenetic Heterogeneity of B-Cell Lymphoma: DNA Methylation, Gene Expression and Chromatin States.

MMML-MYC-SYS

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Abstract (Expand)

Mature B-cell lymphoma is a clinically and biologically highly diverse disease. Its diagnosis and prognosis is a challenge due to its molecular heterogeneity and diverse regimes of biological dysfunctions, …

Authors: L. Hopp, H. Loffler-Wirth, H. Binder

Date Published: 7th Sep 2015

Publication Type: Not specified

Human Diseases: non-Hodgkin lymphoma, B-cell lymphoma

PubMed ID: 26371046

Citation: Genes (Basel). 2015 Sep 7;6(3):812-40. doi: 10.3390/genes6030812.

Created: 9th May 2019 at 14:53, Last updated: 7th Dec 2021 at 17:58

Portraying the Expression Landscapes of B-CellLymphoma-Intuitive Detection of Outlier Samples and of Molecular Subtypes.

MMML-MYC-SYS

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Abstract (Expand)

We present an analytic framework based on Self-Organizing Map (SOM) machine learning to study large scale patient data sets. The potency of the approach is demonstrated in a case study using gene …

Authors: L. Hopp, K. Lembcke, H. Binder, H. Wirth

Date Published: 2nd Dec 2013

Publication Type: Not specified

Human Diseases: non-Hodgkin lymphoma, B-cell lymphoma

PubMed ID: 24833231

Citation: Biology (Basel). 2013 Dec 2;2(4):1411-37. doi: 10.3390/biology2041411.

Created: 10th May 2019 at 11:32, Last updated: 7th Dec 2021 at 17:58

Expression Data from Malignant Lymphoma

MMML-MYC-SYS

We performed gene-expression profiling using Affymetrix U133A GeneChips with RNA from 220 mature aggressive B-cell lymphomas, including a core group of 8 Burkitt's lymphomas that met all World Health Organization (WHO) criteria. A molecular signature for Burkitt's lymphoma was generated, and chromosomal abnormalities were detected with interphase fluorescence in situ hybridization and array-based comparative genomic hybridization.

Creator: Michael Hummel

Submitter: Christoph Beger

Data file type: Genomic Data

Human Diseases: B-cell lymphoma

Investigations: No Investigations

Studies: No Studies

Resources: No Resources

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Created: 13th May 2019 at 13:46, Last updated: 26th Jul 2021 at 13:55

Expression Data from Mature Aggressive B-cell lymphomas and Burkitt's Lymphoma

MMML - Molecular mechanisms in malignant lymphoma, MMML-MYC-SYS

We performed gene-expression profiling using Affymetrix U133A GeneChips with RNA from 873 biopsy specimens including diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), Burkitt’s lymphoma (BL), mixed FL/DLBCL lymphomas, primary mediastinal large B-cell lymphoma (PMBL), multiple myeloma (MM), IRF4-rearranged large cell lymphoma, MYC-negative high-grade B-cell lymphomas with Chr. 11q aberration pattern (mnBLL-11q), and Mantle cell lymphoma (MCL).

Creator: Henry Löffler-Wirth

Submitter: Henry Löffler-Wirth

Data file type: Other OMICs Data

Investigations: No Investigations

Studies: No Studies

Resources: No Resources

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Created: 13th May 2019 at 13:55, Last updated: 26th Jul 2021 at 13:25

Massive Transcriptional Perturbation in Subgroups of Diffuse Large B-cell Lymphomas

MMML-MYC-SYS

Based on the assumption that molecular mechanisms involved in cancerogenesis are characterized by groups of coordinately expressed genes, we developed and validated a novel method for analyzing transcriptional data called Correlated Gene Set Analysis (CGSA). Using 50 extracted gene sets we identified three different profiles of tumors in a cohort of 364 Diffuse large B-cell (DLBCL) and related mature aggressive B-cell lymphomas other than Burkitt lymphoma. The first profile had high level of ...

Creator: Maciej Rosolowski

Submitter: Christoph Beger

Data file type: Transcriptomic Data

Human Diseases: diffuse large B-cell lymphoma

Investigations: No Investigations

Studies: No Studies

Resources: No Resources

External Link

Created: 13th May 2019 at 13:50, Last updated: 13th Jul 2020 at 09:36

SOM Analysis of 873 Malignant Lymphomas

MMML-MYC-SYS

We present a transcriptome map of mature B-cell lymphomas that was obtained by analyzing expression data of 873 biopsy specimens including diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), Burkitt’s lymphoma (BL), mixed FL/DLBCL lymphomas, primary mediastinal large B-cell lymphoma (PMBL), multiple myeloma (MM), IRF4-rearranged large cell lymphoma, MYC-negative high-grade B-cell lymphomas with Chr. 11q aberration pattern (mnBLL-11q), and Mantle cell lymphoma (MCL) to describe their ...

Creator: Henry Löffler-Wirth

Submitters: Christoph Beger, Henry Löffler-Wirth

Data file type: SOM Data

Investigations: No Investigations

Studies: No Studies

Resources: No Resources

External Link

Created: 20th May 2019 at 13:10, Last updated: 20th May 2019 at 13:10

SOM Analysis of 221 Malignant Lymphomas

MMML-MYC-SYS

We performed gene-expression analysis of 220 mature aggressive B-cell lymphomas, including a core group of 8 Burkitt's lymphomas that met all World Health Organization (WHO) criteria. A SOM was trained using molecular classification of specimen according to molecular Burkitt's Lymphoma score provided by Hummel et al.

Creator: Henry Löffler-Wirth

Submitters: Christoph Beger, Henry Löffler-Wirth

Data file type: SOM Data

Investigations: No Investigations

Studies: No Studies

Resources: No Resources

External Link

Created: 20th May 2019 at 13:08, Last updated: 20th May 2019 at 13:08

René Hänsel