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: 25th of May 10.30 am

Speaker: Jonas Hügel (PhD, Medizininformatik)

Topic: Enhancing an phenotyping approach for the usage of MTB data

Abstract: Pheno- and genotyping are important methods to detect patient similarities in precision medicine. In this talk I will present my planned approach to extend an existing phenotyping algorithm for the usage with MTB data. Therefore I will present the already developed phenotyping algorithm from Hostiri et al. [1,2], before I explain my planned three-folded approach to extend it during my stay in Boston and how the results could afterwards be applied at the UMG. Parts of the enhancement includes the integration of MTB-specific data, temporal weights, co-occurrences of clinical events as well as an efficient implementation of the modified dimensionality reduction algorithm [2].

Former and upcoming Talks

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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

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. 

Contact data of the coordinator


Prof. Dr. Tim Beißbarth

Prof. Dr. Tim Beißbarth

contact information


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