Please use this identifier to cite or link to this item:
doi:10.22028/D291-35692
Title: | ClinOmicsTrailbc: a visual analytics tool for breast cancer treatment stratification |
Author(s): | Schneider, Lara Kehl, Tim Thedinga, Kristina Grammes, Nadja Liddy Backes, Christina Mohr, Christopher Schubert, Benjamin Lenhof, Kerstin Gerstner, Nico Hartkopf, Andreas Daniel Wallwiener, Markus Kohlbacher, Oliver Keller, Andreas Meese, Eckart Graf, Norbert Lenhof, Hans-Peter |
Language: | English |
Title: | Bioinformatics |
Volume: | 35 |
Issue: | 24 |
Pages: | 5171–5181 |
Publisher/Platform: | Oxford University Press |
Year of Publication: | 2019 |
DDC notations: | 610 Medicine and health |
Publikation type: | Journal Article |
Abstract: | Motivation: Breast 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. Results: Here, 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 cancerrelevant 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 implementation: ClinOmicsTrailbc can be freely accessed at https://clinomicstrail. bioinf.uni-sb.de. |
DOI of the first publication: | 10.1093/bioinformatics/btz302 |
Link to this record: | urn:nbn:de:bsz:291--ds-356927 hdl:20.500.11880/32551 http://dx.doi.org/10.22028/D291-35692 |
ISSN: | 1460-2059 1367-4803 |
Date of registration: | 8-Mar-2022 |
Description of the related object: | Supplementary data |
Related object: | https://oup.silverchair-cdn.com/oup/backfile/Content_public/Journal/bioinformatics/35/24/10.1093_bioinformatics_btz302/1/btz302_supplementary_data.zip?Expires=1649755875&Signature=kpfBir-jhSCGvdF-GgDVbxaqG~5D9f9qwHZ33LUc4oLWvK~Ik-5M3WieRiQ9AVY-6XKhSVtm1VmqRiyrdKDSSlhSH~1b4bvvQK0MNlLdZkBvvcS4801V0Fa0U9uIup6rn2XOtUMLdFHCDXE4kbDjgH7ixmYBPKC~5MbSfzveCO2u2hGYI2~Hx8tEqGn5VT-vO4GkFCzcMFCDjtS6RRCbAHzyWihStTAQ0Q5Ixyjh69r1FpnLffhxcraujGXT~bUpYIt6fZLxLeFotLqqV4nMOek6szY02c2ST7rLsy7VU~3l4QGIILBnf4yyFClpqsB2~azZARybk6n8OVjQGungLg__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA |
Faculty: | M - Medizinische Fakultät MI - Fakultät für Mathematik und Informatik |
Department: | M - Humangenetik M - Medizinische Biometrie, Epidemiologie und medizinische Informatik M - Pädiatrie MI - Informatik |
Professorship: | M - Prof. Dr. Norbert Graf M - Univ.-Prof. Dr. Andreas Keller M - Prof. Dr. Eckhart Meese MI - Prof. Dr. Hans-Peter Lenhof |
Collections: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
Files for this record:
File | Description | Size | Format | |
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btz302.pdf | 1,48 MB | Adobe PDF | View/Open |
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