vulcanSpot
vulcanSpot prioritizes therapeutic vulnerabilities in cancer by integrating genome-wide screening experiments and applying a weighted scoring system to drug-gene relationships to identify candidate targets, cancer-specific gene dependencies, and drug repositioning opportunities, including genes considered undruggable.
Key Features:
- Integration of Genome-Wide Data: Integrates genome-wide screening experiments to map genetic alterations and tumor-specific gene dependencies.
- Prioritization of Therapeutic Options: Applies a weighted scoring system to prioritize drugs based on known drug-gene relationships and to support drug repositioning strategies.
- Exploitation of Cancer-Specific Vulnerabilities: Identifies cancer-specific gene dependencies, including targets often considered undruggable, to expand potential therapeutic options.
Scientific Applications:
- Oncology research: Identification and prioritization of novel therapeutic targets from genome-wide dependency data.
- Precision/personalized medicine: Informing patient-stratified treatment strategies based on tumor-specific vulnerabilities.
- Drug repositioning: Recommending existing drugs for new cancer indications by prioritizing drug-gene interactions.
Methodology:
Integrates data from genome-wide screening experiments, applies a weighted scoring system to known drug-gene interactions for prioritization, and identifies cancer-specific gene dependencies as candidate therapeutic targets.
Topics
Collections
Details
- License:
- APL-1.0
- Maturity:
- Mature
- Cost:
- Free of charge (with restrictions)
- Tool Type:
- api, web application
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- R, Python
- Added:
- 7/4/2019
- Last Updated:
- 11/24/2024
Operations
Data Inputs & Outputs
Enrichment analysis
Publications
Perales-Patón J, Di Domenico T, Fustero-Torre C, Piñeiro-Yáñez E, Carretero-Puche C, Tejero H, Valencia A, Gómez-López G, Al-Shahrour F. vulcanSpot: a tool to prioritize therapeutic vulnerabilities in cancer. Bioinformatics. 2019;35(22):4846-4848. doi:10.1093/bioinformatics/btz465. PMID:31173067. PMCID:PMC6853644.