ClinOmicsTrailbc: a visual analytics tool for breast cancer treatment stratification

Author:

Schneider Lara12ORCID,Kehl Tim12ORCID,Thedinga Kristina1,Grammes Nadja Liddy1,Backes Christina13ORCID,Mohr Christopher45,Schubert Benjamin678,Lenhof Kerstin12,Gerstner Nico12ORCID,Hartkopf Andreas Daniel9,Wallwiener Markus1011,Kohlbacher Oliver45121314ORCID,Keller Andreas13,Meese Eckart115,Graf Norbert116ORCID,Lenhof Hans-Peter1

Affiliation:

1. Center for Bioinformatics, Saarbrücken, Germany

2. Saarbrücken Graduate School of Computer Science, Saarbrücken, Germany

3. Chair for Clinical Bioinformatics, Saarland Informatics Campus, Saarland University, Saarbrücken, Germany

4. Quantitative Biology Center (QBiC), Tübingen, Germany

5. Institute for Translational Bioinformatics, University Hospital Tübingen, Tübingen, Germany

6. Department of Systems Biology, Boston, MA, USA

7. Department of Cell Biology, Harvard Medical School, Boston, MA, USA

8. cBio Center, Dana-Farber Cancer Institute, Boston, MA, USA

9. Department of Obstetrics and Gynecology, University of Tübingen, Tübingen, Germany

10. Department of Obstetrics and Gynecology, University of Heidelberg, Heidelberg, Germany

11. National Center for Tumor Diseases, University of Heidelberg, Heidelberg, Germany

12. Center for Bioinformatics, University of Tübingen, Tübingen, Germany

13. Applied Bioinformatics, Department of Computer Science, University of Tübingen, Tübingen, Germany

14. Biomolecular Interactions, Max Planck Institute for Developmental Biology, Tübingen, Germany

15. Human Genetics, Saarland University, Homburg, Germany

16. Department of Pediatric Oncology and Hematology, Medical School, Saarland University, Homburg, Germany

Abstract

AbstractMotivationBreast cancer is the second leading cause of cancer death among women. Tumors, even of the same histopathological subtype, exhibit a high genotypic diversity that impedes therapy stratification and that hence must be accounted for in the treatment decision-making process.ResultsHere, we present ClinOmicsTrailbc, a comprehensive visual analytics tool for breast cancer decision support that provides a holistic assessment of standard-of-care targeted drugs, candidates for drug repositioning and immunotherapeutic approaches. To this end, our tool analyzes and visualizes clinical markers and (epi-)genomics and transcriptomics datasets to identify and evaluate the tumor’s main driver mutations, the tumor mutational burden, activity patterns of core cancer-relevant pathways, drug-specific biomarkers, the status of molecular drug targets and pharmacogenomic influences. In order to demonstrate ClinOmicsTrailbc’s rich functionality, we present three case studies highlighting various ways in which ClinOmicsTrailbc can support breast cancer precision medicine. ClinOmicsTrailbc is a powerful integrated visual analytics tool for breast cancer research in general and for therapy stratification in particular, assisting oncologists to find the best possible treatment options for their breast cancer patients based on actionable, evidence-based results.Availability and implementationClinOmicsTrailbc can be freely accessed at https://clinomicstrail.bioinf.uni-sb.de.Supplementary informationSupplementary data are available at Bioinformatics online.

Funder

Deutsche Forschungsgemeinschaft

European Union Horizon 2020 Framework

APERIM

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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