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 


The MT-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 10.30 am . 

Coordination/Contact: Dr. Jürgen Dönitz 

Date:Wednesday:  22.05.2024 at 10.30pm

Location: online,

Speaker: Dominik Böhm (Friedrich-Alexander-University of Erlangen-Neuberg, AG Prof. Dr. Philipp Unberath; Research Fellow at the Data Integration Centre of the University Hospital Erlangen)

Topic: MTB-cBioPortal -- cBioPortal Extensions for Enhanced Molecular Tumor Board Support

Abstract: The seminar focuses on cBioPortal extensions supporting Molecular Tumor Boards, developed through a user-centered approach. Collaborative design processes involving oncologists, bioinformaticians, pathologists, and other medical professionals ensure that the platform meets the specific needs of MTB workflows. By incorporating user feedback, iterative prototyping, and usability testing we were able to expand cBioPortal's toolkit while maintaining its usability and uncovered a variety of future requirements. This includes features for data visualization, documentation capabilities, the integration of existing clinical and genomic data, as well as providing additional decision support. Through these enhancements, we aim to improve the preparation as well as the execution of MTBs, leading to more personalized and precise cancer treatment options.

Former and upcoming Talks

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Yang J, Beißbarth T, Dönitz J.
Onkopipe: A Snakemake Based DNA-Sequencing Pipeline for Clinical Variant Analysis in Precision Medicine.
Stud Health Technol Inform. 2023 Sep 12;307:60-68. doi: 10.3233/SHTI230694. PMID: 37697838.

Kurz NS, Perera-Bel J, Höltermann C, Tucholski T, Yang J, Beissbarth T, Dönitz J: 
Identifying Actionable Variants in Cancer – The Dual Web and Batch Processing Tool MTB-Report
Volume 296: German Medical Data Sciences 2022 – Future Medicine: More Precise, More Integrative, More Sustainable

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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