ClinOmicsTrailbc

ClinOmicsTrailbc integrates clinical, (epi-)genomic, and transcriptomic data to stratify breast cancer treatments by evaluating driver mutations, tumor mutational burden, pathway activities, drug-specific biomarkers, molecular targets, pharmacogenomics, drug repositioning candidates, and immunotherapeutic options.


Key Features:

  • Holistic treatment assessment: Evaluates standard-of-care targeted drugs, candidates for drug repositioning, and immunotherapeutic approaches for breast cancer.
  • Multi-omics integration: Integrates clinical markers with (epi-)genomics and transcriptomics to identify driver mutations, tumor mutational burden, and core cancer-relevant pathway activity patterns.
  • Biomarker and target analysis: Assesses drug-specific biomarkers, molecular drug target status, and pharmacogenomic influences to inform therapeutic selection.

Scientific Applications:

  • Therapy stratification: Supports selection of personalized treatment options for breast cancer patients based on genomic and transcriptomic profiles.
  • Biomarker and target discovery: Facilitates identification and evaluation of actionable driver mutations, biomarkers, and molecular drug targets.
  • Translational research: Enables comparative analyses across cases to support research initiatives in breast cancer precision medicine.

Methodology:

Integration and visualization of clinical, genomic, and transcriptomic data combined with analyses of driver mutations, tumor mutational burden, pathway activities, and pharmacogenomics.

Topics

Details

License:
Unlicense
Maturity:
Mature
Cost:
Free of charge
Tool Type:
api, web application
Operating Systems:
Linux, Windows, Mac
Added:
8/9/2019
Last Updated:
11/24/2024

Operations

Publications

Schneider L, Kehl T, Thedinga K, Grammes NL, Backes C, Mohr C, Schubert B, Lenhof K, Gerstner N, Hartkopf AD, Wallwiener M, Kohlbacher O, Keller A, Meese E, Graf N, Lenhof H. ClinOmicsTrailbc: a visual analytics tool for breast cancer treatment stratification. Bioinformatics. 2019;35(24):5171-5181. doi:10.1093/bioinformatics/btz302. PMID:31038669. PMCID:PMC6954665.

PMID: 31038669
PMCID: PMC6954665
Funding: - Deutsche Forschungsgemeinschaft: LE952/3-2 - APERIM: 633592

Documentation