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Published on: December 26, 2016
Computational Cell Cycle Profiling of Cancer Cells for Prioritizing FDA-Approved Drugs with Repurposing Potential
Yu-Chen Lo1,2, Silvia Senese1, Bryan France3,4
1Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA.
Abstract:
Discovery of first-in-class medicines for treating cancer is limited by concerns with their toxicity and safety profiles, while repurposing known drugs for new anticancer indications has become a viable alternative. Here, we have developed a new approach that utilizes cell cycle arresting patterns as unique molecular signatures for prioritizing FDA-approved drugs with repurposing potential. As proof-of-principle, we conducted large-scale cell cycle profiling of 884 FDA-approved drugs. Using cell cycle indexes that measure changes in cell cycle profile patterns upon chemical perturbation, we identified 36 compounds that inhibited cancer cell viability including 6 compounds that were previously undescribed. Further cell cycle fingerprint analysis and 3D chemical structural similarity clustering identified unexpected FDA-approved drugs that induced DNA damage, including clinically relevant microtubule destabilizers, which was confirmed experimentally via cell-based assays. Our study shows that computational cell cycle profiling can be used as an approach for prioritizing FDA-approved drugs with repurposing potential, which could aid the development of cancer therapeutics.
Insights
Repurposing FDA-approved drugs for cancer treatment is possible using cell cycle profiles as molecular signatures. This computational approach identifies potential new cancer therapeutics by analyzing drug-induced cell cycle changes.
Area of Science:
- Oncology
- Pharmacology
- Computational Biology
Background:
- Drug discovery for novel cancer therapeutics faces challenges due to toxicity and safety concerns.
- Repurposing existing Food and Drug Administration (FDA)-approved drugs offers a viable alternative for developing new anticancer treatments.
- Identifying effective repurposed drugs requires innovative screening and prioritization strategies.
Purpose of the Study:
- To develop and validate a computational method for prioritizing FDA-approved drugs for anticancer repurposing.
- To utilize cell cycle arresting patterns as unique molecular signatures for drug prioritization.
- To identify novel FDA-approved drugs with potential anticancer activity through large-scale cell cycle profiling.
Main Methods:
- Conducted large-scale cell cycle profiling of 884 FDA-approved drugs.
- Utilized cell cycle indexes to quantify changes in cell cycle profiles after drug treatment.
- Performed cell cycle fingerprint analysis and 3D chemical structural similarity clustering.
Main Results:
- Identified 36 compounds that inhibited cancer cell viability, including 6 previously undescribed compounds.
- Discovered unexpected FDA-approved drugs that induced DNA damage.
- Confirmed the anticancer potential of identified drugs, including microtubule destabilizers, via experimental assays.
Conclusions:
- Computational cell cycle profiling is an effective approach for prioritizing FDA-approved drugs for cancer repurposing.
- This method can accelerate the identification of novel cancer therapeutics.
- The findings support the use of cell cycle signatures in drug discovery and development for oncology.
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