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
Prof Ulrich Sax
Department of Hematology and Medical Oncology
Prof. Annalen Bleckmann (now Münster University Hospital, UKM)
Dr. Raphael Koch
Current theses offers
Bachelor thesis (including practical course): Creating a drug ontology by automatic information retrieval from DrugBank and other sources for application in molecular tumor boards
At the department of Medical Bioinformatics in cooperation with the department of Medical Informatics and the department of Haematology and Oncology we offer a Bachelor thesis in the context of the MTB-Report Project.
In the MTB Report we aim at developing tools to support the information process to recommend treatment options based on the patient’s biomarkers. One important part here is the standardization and annotation of drugs. Drugs can be mentioned with a drug name, drug class or trade name. For an automatic processing a classification is needed. With additional information like the annotation of the target of the drug, the affected target of the drug and the involved genes up- and down streams open the options for further analysis. There is already a lot of information, however, a comprehensive information resource that will cover the needs of the MTB project.
Main tasks will be:
- Identifying valuable and usable external resources
- Automatic extraction and preparation of information of external resources and from the project tools
- Design of an ontology which covers the information required by the project in a semantic way
- Populate the ontology and link to external resources
- Validate the new resource in the scope of the project
Focus: Applied Computer Science, Medical Informatics
Supervisor: Dr. Jürgen Dönitz
Current Theses Offers by the Institute of Medical Informatics
In the context of the MTB project, two Bachleor-/Master- theses are currently offered by the Institute of Medical Informatics:
1. Topic: Support of the molecular tumor board with cBioPortal.
2. Topic: Comparison of current patient similarity searches using two example data sets
For more information, please see here: https://medizininformatik.umg.eu/karriere/stellenangebote-im-institut/ or contact Jonas Hügel: jonas.huegel@med.uni-goettingen.de
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: 24th of February 10.30 am
Speaker: Nicole Schmidt
Title: "Wetlab workflow - Drug screening"
Abstract: An evidence-driven reporting system developed for molecular tumor boards was utilized to detect relevant genetic alterations in primary T-cell lymphoma (TCL) samples and cell line models and identified potential therapeutics. In order to pre-clinically validate potential therapeutic targets and to assess novel therapeutic strategies in vitro we performed a cell viability drug screening using established TCL cell lines. This presentation will summarize the wetlab workflow and drug screen approach.
Location: https://meet.gwdg.de/b/jue-ywf-v93
Press releases
Press release from the Volkswagenstiftung:
Big Data: 18 Millionen Euro für 16 innovative Projekte in den Lebenswissenschaften
Press release from the UMG:
Big Data in den Lebenswissenschaften der Zukunft“: Förderung von drei Forschungsgruppen von Universitätsmedizin Göttingen und Universität
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. PubMed PMID: 29544535;
Contact data of the coordinator
contact information
- telephone: +49 551 3914912
- fax: +49 551 3914914
- e-mail address: tim.beissbarth(at)bioinf.med.uni-goettingen.de
- location: 2.107
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