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Updated: Jun 30, 2026
Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
Published on: December 11, 2016
Drug repositioning and ovarian cancer, a study based on Mendelian randomisation analysis
Lin Zhu1, Hairong Zhang2, Xiaoyu Zhang1
1School of Chinese Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China.
Background:
The role of drug repositioning in the treatment of ovarian cancer has received increasing attention. Although promising results have been achieved, there are also major controversies.
Methods:
In this study, we conducted a drug-target Mendelian randomisation (MR) analysis to systematically investigate the reported effects and relevance of traditional drugs in the treatment of ovarian cancer. The inverse-variance weighted (IVW) method was used in the main analysis to estimate the causal effect. Several MR methods were used simultaneously to test the robustness of the results.
Results:
By screening 31 drugs with 110 targets, FNTA, HSPA5, NEU1, CCND1, CASP1, CASP3 were negatively correlated with ovarian cancer, and HMGCR, PLA2G4A, ITGAL, PTGS1, FNTB were positively correlated with ovarian cancer.
Conclusion:
Statins (HMGCR blockers), lonafarnib (farnesyltransferase inhibitors), the anti-inflammatory drug aspirin, and the anti-malarial drug adiponectin all have potential therapeutic roles in ovarian cancer treatment.
Insights
Drug repositioning shows promise for ovarian cancer treatment. Mendelian randomization identified statins, lonafarnib, aspirin, and adiponectin as potential therapies, warranting further investigation.
Area of Science:
- Oncology
- Pharmacogenomics
- Drug Discovery
Background:
- Drug repositioning is gaining traction for ovarian cancer therapy.
- Despite promising outcomes, significant controversies surround its application.
Purpose of the Study:
- To systematically investigate the efficacy of existing drugs for ovarian cancer treatment using drug-target Mendelian randomization (MR).
- To identify potential therapeutic roles for traditional drugs in managing ovarian cancer.
Main Methods:
- A drug-target Mendelian randomization (MR) analysis was performed.
- The inverse-variance weighted (IVW) method was employed for causal effect estimation.
- Multiple MR methods were used to ensure result robustness.
Main Results:
- Screening of 31 drugs and 110 targets revealed correlations with ovarian cancer.
- Negative correlations were observed for FNTA, HSPA5, NEU1, CCND1, CASP1, and CASP3.
- Positive correlations were found for HMGCR, PLA2G4A, ITGAL, PTGS1, and FNTB.
Conclusions:
- Statins (HMGCR inhibitors) show potential for ovarian cancer treatment.
- Lonafarnib (farnesyltransferase inhibitors) may offer therapeutic benefits.
- Aspirin and adiponectin also present potential roles in ovarian cancer therapy.
