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Updated: Sep 10, 2025

A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
Published on: May 27, 2021
Epigenetic synthetic lethality as a cancer therapeutic strategy: synergy of experimental and computational approaches
Maria Farina-Morillas1, Laia Ollé-Monràs1, Silvana Ce Maas1
1Cancer Computational Biology Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain.
Abstract:
Cancer treatment is an ongoing challenge, as directly targeting oncogenic drivers is often unfeasible in many patients due to the lack of druggable targets. This has led to the exploration of alternative strategies, such as exploiting synthetic lethality (SL) relationships between genes. SL facilitates the indirect targeting of oncogenic drivers, as exemplified by the clinical success of PARP inhibitors against BRCA-mutated tumors. Advances in high-throughput perturbation screens and multi-omics technologies have deepened our understanding of SL relationships, while computational models enhance SL predictions to better reflect biological complexity. However, while numerous experimental and computational methods have been developed to identify SL interactions, difficulties remain in translating these findings into clinical applications.This review combines recent progress on SL relationships in cancer with emerging insights into epigenetic regulation, highlighting how epigenetic drugs (epidrugs) can provide new opportunities for targeted interventions, offering a way to minimize off-target effects and enhance therapeutic precision. To advance SL-based therapies, efforts must focus not only on identifying new SL interactions but also on consolidating existing knowledge and integrating experimental and computational approaches to characterize the vulnerabilities of cancer cells. Strengthening this foundation will be critical for the effective development of SL-based cancer treatments.
Insights
Synthetic lethality (SL) offers a novel cancer therapy approach by indirectly targeting cancer drivers. Combining SL with epigenetic drugs enhances precision and minimizes side effects for better cancer treatment outcomes.
Area of Science:
- Cancer Biology
- Genetics
- Pharmacology
Background:
- Direct targeting of oncogenic drivers is often unfeasible in cancer due to a lack of druggable targets.
- Synthetic lethality (SL) provides an indirect strategy to target cancer drivers, as seen with PARP inhibitors in BRCA-mutated tumors.
- Existing methods for identifying SL interactions face challenges in clinical translation.
Purpose of the Study:
- To review recent advancements in synthetic lethality (SL) relationships in cancer.
- To explore the integration of epigenetic regulation and epigenetic drugs (epidrugs) with SL strategies.
- To highlight opportunities for developing more precise and effective targeted cancer interventions.
Main Methods:
- Review of high-throughput perturbation screens and multi-omics technologies for SL identification.
- Analysis of computational models for predicting SL interactions and biological complexity.
- Integration of experimental and computational approaches to characterize cancer cell vulnerabilities.
Main Results:
- Advances in screening and multi-omics have improved understanding of SL relationships.
- Computational models enhance the prediction of SL interactions.
- Epigenetic drugs offer potential for targeted cancer interventions with minimized off-target effects.
Conclusions:
- Integrating SL with epigenetic regulation and epidrugs presents a promising avenue for targeted cancer therapy.
- Future efforts should focus on identifying novel SL interactions and consolidating existing knowledge.
- Strengthening the foundation of SL research through integrated approaches is critical for clinical translation.
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