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A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
Published on: May 27, 2021
Complex synthetic lethality in cancer
Colm J Ryan1, Lovely Paul Solomon Devakumar2, Stephen J Pettitt3
1Conway Institute and School of Computer Science, University College Dublin, Dublin, Ireland. colm.ryan@ucd.ie.
Abstract:
The concept of synthetic lethality has been widely applied to identify therapeutic targets in cancer, with varying degrees of success. The standard approach normally involves identifying genetic interactions between two genes, a driver and a target. In reality, however, most cancer synthetic lethal effects are likely complex and also polygenic, being influenced by the environment in addition to involving contributions from multiple genes. By acknowledging and delineating this complexity, we describe in this article how the success rate in cancer drug discovery and development could be improved.
Insights
Synthetic lethality, a cancer target strategy, often involves simple gene pairs. Recognizing complex, polygenic interactions can improve cancer drug discovery success.
Area of Science:
- Oncology
- Genetics
- Pharmacology
Background:
- Synthetic lethality is a key strategy for identifying cancer therapeutic targets.
- Current approaches typically focus on pairwise genetic interactions between driver and target genes.
- However, real-world synthetic lethal interactions in cancer are often more complex and polygenic.
Purpose of the Study:
- To explore the limitations of standard synthetic lethality approaches in cancer drug discovery.
- To propose a framework for understanding and leveraging complex, polygenic synthetic lethality.
- To enhance the success rate of cancer drug discovery and development.
Main Methods:
- Review of existing synthetic lethality principles and applications in oncology.
- Analysis of genetic interaction complexity and polygenic influences.
- Conceptual framework development for complex synthetic lethality.
Main Results:
- Standard two-gene synthetic lethality models may oversimplify actual cancer biology.
- Environmental factors and multiple gene contributions significantly influence synthetic lethal effects.
- Acknowledging complexity is crucial for advancing therapeutic target identification.
Conclusions:
- Improving cancer drug discovery requires moving beyond simple genetic interactions.
- A more nuanced understanding of polygenic and environmentally influenced synthetic lethality is needed.
- This approach holds potential to increase the success of cancer therapeutics development.
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