Support for Molecular Tumor Boards
Precision medicine already plays a major role in the care of tumor patients. For many tumors, so-called “driver mutations” can now be identified by means of molecular biological characterization in order to treat them in a targeted manner if a suitable drug is available.
In Molecular Tumor Boards (MTB), clinical information and molecular/genetic test results converge for interdisciplinary decision-making. In order to support MTBs, the MIRACUM consortium aims to improve the complex processes of quality assurance, data preparation, data analysis, data integration and information retrieval between genetic high-throughput analysis and medical therapy decisions with innovative IT solutions. In addition, clinicians will be offered decision support through efficient data visualization.
Use Case 3 of the MIRACUM consortium aims to support MTBs with IT solutions. An MTB is an interdisciplinary, cross-organ conference where clinical-pathological data and molecular findings of selected cancer patients are discussed. An interdisciplinary team of physicians and scientists from the fields of medicine, bioinformatics, medical informatics and biology votes on which therapy options promise the best chances of fighting the tumor on the basis of the available data. The application aims to identify patients without conventional or promising therapy options or with rare tumor diseases and to offer them potentially effective treatment options with a targeted therapy within the framework of precision medicine – in the context of clinical studies or individual healing trials.
In the daily clinical routine of medical centers, more and more high-throughput data of patients with the diagnosis of an advanced tumor is generated. In order to be able to process this enormous amount of data, standardized bioinformatics tools must be developed. These tools should support physicians in interpreting these complex data. Within the scope of the use case, a bioinformatics process for the analysis of the individual tumor DNA sequence was developed – the so-called MIRACUM Pipe. The pipeline was successfully distributed and installed at all MIRACUM sites in the second half of 2019. This allows the analysis of sequencing data to be performed in a uniform and standardized manner, starting with raw data and ending with the determination and annotation of tumor-specific mutations.
The automated pipeline delivers reliable and reproducible results with a single click as a PDF report that serves as the basis for therapy recommendations. In addition, a file is generated which can be imported into the cBioPortal software platform of the Memorial Sloan Kettering Cancer Center, a private cancer clinic and research facility in New York. In cBioPortal the results are visualized, the clinical and molecular biological data of the patient are combined and presented in a reduced form. This facilitates the interpretation of the data. Furthermore, the data can be viewed in the context of other cases.
In order to enhance cBioPortal with additional functionalities and adapt it to different data requirements, detailed stakeholder analyses with all MIRACUM sites were conducted and published in 2018. Since 2019, the University of Lübeck officially cooperates within MIRACUM Use Case 3 and implements it at the University Hospital Schleswig-Holstein, a HiGHmed site. Based on the stakeholder analyses, the process for creating a therapy recommendation is currently being implemented organizationally and technically for the local MTB. The cooperation with the University of Lübeck is the first cross-consortium collaboration within the German medical informatics initiative (MII) as a proof of principle for interoperability between IT architectures of data integration centers of two MII consortia.
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Gruendner J, Wolf N, Tögel L, Haller F, Prokosch HU, Christoph J. Integrating Genomics and Clinical Data for Statistical Analysis by Using GEnome MINIng (GEMINI) and Fast Healthcare Interoperability Resources (FHIR): System Design and Implementation. JMIR 2020; 22:e19879. DOI: 10.2196/19879.
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Hinderer M, Boerries M, Boeker M, Neumaier M, Loubal FP, Acker T, Brunner M, Prokosch HU, Christoph J. Implementing Pharmacogenomic Clinical Decision Support into German Hospitals.
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