Florian Borchert, Andreas Mock, Aurelie Tomczak, Jonas Hügel, Samer Alkarkoukly, Alexander Knurr, Anna-Lena Volckmar, Albrecht Stenzinger, Peter Schirmacher, Jürgen Debus, Dirk Jäger, Thomas Longerich, Stefan Fröhling, Roland Eils, Nina Bougatf, Ulrich Sax, Matthieu-Patrick Schapranow
- Precision oncology is a rapidly evolving interdisciplinary medical specialty. Comprehensive cancer panels are becoming increasingly available at pathology departments worldwide, creating the urgent need for scalable cancer variant annotation and molecularly informed treatment recommendations. A wealth of mainly academia-driven knowledge bases calls for software tools supporting the multi-step diagnostic process. We derive a comprehensive list of knowledge bases relevant for variant interpretation by a review of existing literature followed by a survey among medical experts from university hospitals in Germany. In addition, we review cancer variant interpretation tools, which integrate multiple knowledge bases. We categorize the knowledge bases along the diagnostic process in precision oncology and analyze programmatic access options as well as the integration of knowledge bases into software tools. The most commonly used knowledge bases provide good programmatic access options and have been integrated into a range of software tools.Precision oncology is a rapidly evolving interdisciplinary medical specialty. Comprehensive cancer panels are becoming increasingly available at pathology departments worldwide, creating the urgent need for scalable cancer variant annotation and molecularly informed treatment recommendations. A wealth of mainly academia-driven knowledge bases calls for software tools supporting the multi-step diagnostic process. We derive a comprehensive list of knowledge bases relevant for variant interpretation by a review of existing literature followed by a survey among medical experts from university hospitals in Germany. In addition, we review cancer variant interpretation tools, which integrate multiple knowledge bases. We categorize the knowledge bases along the diagnostic process in precision oncology and analyze programmatic access options as well as the integration of knowledge bases into software tools. The most commonly used knowledge bases provide good programmatic access options and have been integrated into a range of software tools. For the wider set of knowledge bases, access options vary across different parts of the diagnostic process. Programmatic access is limited for information regarding clinical classifications of variants and for therapy recommendations. The main issue for databases used for biological classification of pathogenic variants and pathway context information is the lack of standardized interfaces. There is no single cancer variant interpretation tool that integrates all identified knowledge bases. Specialized tools are available and need to be further developed for different steps in the diagnostic process.…
MetadatenAuthor details: | Florian BorchertGND, Andreas MockORCiDGND, Aurelie TomczakGND, Jonas HügelORCiD, Samer AlkarkouklyORCiD, Alexander KnurrGND, Anna-Lena VolckmarORCiDGND, Albrecht StenzingerORCiDGND, Peter SchirmacherORCiDGND, Jürgen DebusORCiDGND, Dirk Jäger, Thomas LongerichORCiDGND, Stefan FröhlingORCiDGND, Roland EilsORCiDGND, Nina BougatfORCiDGND, Ulrich SaxORCiDGND, Matthieu-Patrick SchapranowORCiDGND |
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DOI: | https://doi.org/10.1093/bib/bbab134 |
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ISSN: | 1467-5463 |
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ISSN: | 1477-4054 |
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Pubmed ID: | https://pubmed.ncbi.nlm.nih.gov/33971666 |
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Title of parent work (English): | Briefings in bioinformatics |
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Publisher: | Oxford Univ. Press |
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Place of publishing: | Oxford |
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Publication type: | Article |
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Language: | English |
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Date of first publication: | 2021/05/10 |
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Publication year: | 2021 |
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Release date: | 2024/01/18 |
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Tag: | HiGHmed; cancer therapy; data integration; molecular tumor board; personalized medicine |
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Volume: | 22 |
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Issue: | 6 |
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Article number: | bbab134 |
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Number of pages: | 17 |
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Funding institution: | German Federal Ministry of Research and Education [01ZZ1802]; Physician-Scientist Program of the University of Heidelberg, Faculty of Medicine, DKTK (German Cancer Consortium) School of Oncology; Cancer Core Europe TRYTRAC program; MTB-Report project (VolkswagenStiftung) [ZN3424] |
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Organizational units: | An-Institute / Hasso-Plattner-Institut für Digital Engineering gGmbH |
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DDC classification: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
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| 5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie |
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Peer review: | Referiert |
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Publishing method: | Open Access / Hybrid Open-Access |
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License (German): | CC-BY - Namensnennung 4.0 International |
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External remark: | Correction: https://doi.org/10.1093/bib/bbab246 |
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