A Network of Conserved Synthetic Lethal Interactions for Exploration of Precision Cancer Therapy

Area of Science:

• Oncology
• Genetics
• Pharmacology

Background:

• Cancer therapy increasingly targets tumor-specific vulnerabilities.
• Synthetic lethality, where mutations in two genes cause cell death, offers a promising therapeutic strategy.
• Identifying synthetic lethal interactions is crucial for developing targeted cancer treatments.

Purpose of the Study:

• To develop a comprehensive resource of synthetic lethal interactions relevant to cancer therapy.
• To identify novel drug targets and tumor suppressor gene (TSG) interactions for selective cancer treatment.
• To establish rules for predicting conserved synthetic lethal interactions in human cancer cells.

Main Methods:

• Screening approximately 169,000 potential interactions between human tumor suppressor gene orthologs and drug target genes in yeast across various genotoxic environments.
• Evaluating thousands of TSG-drug combinations in HeLa cells to identify conserved synthetic lethal interactions.
• Analyzing interaction stability and shared gene function to prioritize human TSG-drug combinations.

Main Results:

• Identified conserved networks of synthetic lethal interactions across species and environments.
• Determined that interaction stability and shared gene function are key indicators for synthetic lethality in human cancer cells.
• Prioritized approximately 10^5 human TSG-drug combinations for further investigation, validating interactions with patient survival data.

Conclusions:

• Developed a robust multi-species approach for discovering synthetic lethal interactions.
• Established predictive rules for identifying therapeutically relevant TSG-drug combinations.
• Validated key synthetic lethal interactions, including topoisomerases with RAD17 and checkpoint kinases with BLM, demonstrating potential for novel cancer therapies.