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Updated: Jul 5, 2025
A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
Published on: May 27, 2021
A systematic analysis of the landscape of synthetic lethality-driven precision oncology
Alejandro A Schäffer1, Youngmin Chung2, Ashwin V Kammula1
1Cancer Data Science Laboratory, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Background:
Synthetic lethality (SL) denotes a genetic interaction between two genes whose co-inactivation is detrimental to cells. Because more than 25 years have passed since SL was proposed as a promising way to selectively target cancer vulnerabilities, it is timely to comprehensively assess its impact so far and discuss its future.
Methods:
We systematically analyzed the literature and clinical trial data from the PubMed and Trialtrove databases to portray the preclinical and clinical landscape of SL oncology.
Findings:
We identified 235 preclinically validated SL pairs and found 1,207 pertinent clinical trials, and the number keeps increasing over time. About one-third of these SL clinical trials go beyond the typically studied DNA damage response (DDR) pathway, testifying to the recently broadening scope of SL applications in clinical oncology. We find that SL oncology trials have a greater success rate than non-SL-based trials. However, about 75% of the preclinically validated SL interactions have not yet been tested in clinical trials.
Conclusions:
Dissecting the recent efforts harnessing SL to identify predictive biomarkers, novel therapeutic targets, and effective combination therapy, our systematic analysis reinforces the hope that SL may serve as a key driver of precision oncology going forward.
Funding:
Funded by the Samsung Research Funding & Incubation Center of Samsung Electronics, the Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Republic of Korea government (MSIT), the Kwanjeong Educational Foundation, the Intramural Research Program of the National Institutes of Health (NIH), National Cancer Institute (NCI), and Center for Cancer Research (CCR).
Insights
Synthetic lethality (SL) is a promising cancer therapy approach. While many SL interactions are validated preclinically, most haven't reached clinical trials, indicating significant future potential for cancer treatment.
Area of Science:
- Oncology
- Genetics
- Biotechnology
Background:
- Synthetic lethality (SL) is a genetic interaction where inactivating two genes harms cells.
- Over 25 years since its proposal, SL is a key strategy for targeting cancer vulnerabilities.
- SL research has expanded beyond DNA damage response (DDR) pathways.
Purpose of the Study:
- To comprehensively assess the impact and future potential of synthetic lethality in oncology.
- To analyze the preclinical and clinical landscape of SL applications in cancer treatment.
Main Methods:
- Systematic literature review of PubMed.
- Analysis of clinical trial data from Trialtrove.
- Identification of preclinical SL pairs and clinical trials.
Main Results:
- 235 preclinically validated SL pairs identified.
- 1,207 SL-related clinical trials found, with ongoing growth.
- SL trials show higher success rates than non-SL trials.
- 75% of validated SL interactions are not yet in clinical trials.
Conclusions:
- SL is a key driver for precision oncology.
- Harnessing SL aids in identifying predictive biomarkers and therapeutic targets.
- SL facilitates the development of effective combination therapies.
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