MTB-Report


An automated data integration platform for interpreting genomic data and reporting treatment options in molecular tumor boards

Aims of this collaborative project

With growing knowledge of biomarkers and resent developments in sequencing techniques, nowaday genomic data is considered as extremely valuable and indispensable for the diagnosis and therapy recommendation particularly of tumor patients. The complexity of interpreting genomic data is hindering its application in the routine clinical context.
In the MTB-Report project the consortium aims to develop a tool to support the decision finding in a molecular tumor board (MTB). Biomarkers and other omics data from the patient will be compared to a multitude of available data bases in order to find case studies with a  parameter set equivalent to the patient’s one. Based on tumor type and certainty of the study an evidence level is assigned and used to propose the most relevant to the MTB in form a short report.

For access to the clinical data and to ensure data privacy the tool will be embedded in the IT-infrastructure. Clinical experts will define use cases for an optimal usage of the reporting tool and will validate the results.

Project partners

Department of Medical Bioinformatics (UMG)

Prof. Tim Beißbart
Dr. Jürgen Dönitz

Department of Medical Informatics (UMG)

Prof. Ulrich Sax

Department of Hematology and Medical Oncology (UMG)

Prof. Annalen Bleckmann (now Münster University Hospital, UKM)
Dr. Raphael Koch 

MTB-Report Seminar

The MTB-Report Seminar Series is a joint event of all partners and members of the MTB-Report project. Monthly, members of the different groups as well as invited speakers present their projects.

Unless announced otherwise, the seminar takes place monthly on the fourth Wednesday at 10.30am . Due to the SARS-CoV-2 related measures, the seminar takes place via video conference .

Coordination/Contact: Dr. Jürgen Dönitz 

Date: 24 th of November 10.30 am

Speaker: Kevin Kornrumpf (PhD Department of Medical Bioinformatics)

Topic: Copy Number Variations - From medical analysis to a bioinformatics approach.

Abstract: CNVs have a major impact on the development of cancer. However, in
many medical publications, these are analyzed only in the context of individual
cancer entities. A generalized and automated approach to analyze these CNV is
still missing. In this presentation, I will present the current state-of-art
of analysis, our ideas to automate the search for potentially harmful
CNV genes and some existing databases and tools.

Location: meet.gwdg.de/b/jue-ywf-v93

Former and upcoming Talks

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Publications

Schlotzig V, Kornrumpf K, König A, Tucholski T, Hügel J, Overbeck TR, Beissbarth T, Koch R, Dönitz J.
Predicting the Effect of Variants of Unknown Significance in Molecular Tumor Boards with the VUS-Predict Pipeline.
Stud Health Technol Inform. 2021 Sep 21;283:209-216.
doi: 10.3233/SHTI210562

Borchert, F., Mock A., ...., Hügel J., et al.
Knowledge bases and software support for variant interpretation in precision oncology
Briefings in Bioinformatics, bbab134, 2021, 1–17
doi: https://doi.org/10.1093/bib/bbab134

Publications from preliminary work

Perera-Bel J., Leha A., Beißbarth T.
Bioinformatic Methods and  Resources for Biomarker Discovery, Validation, Development, and  Integration.
In: Badve S., Kumar G. (eds) Predictive Biomarkers in  Oncology. Springer, Cham. (2019)

Perera-Bel J, Hutter B, Heining C, Bleckmann A, Fröhlich M, Fröhling S, Glimm H, Brors B, Beißbarth T.
From somatic variants towards precision oncology: Evidence-driven reporting of treatment options in molecular tumor boards.
Genome  Med. 2018 Mar 15;10(1):18. 
doi:10.1186/s13073-018-0529-2.

Contact data of the coordinator

Director

Prof. Dr. Tim Beißbarth

contact information

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