Mapping the Landscape of Synthetic Lethal Interactions in Liver Cancer

Background: Current therapies against liver cancer all follow the “one fits all” principle, without the capacity to provide individualized treatment regimens, which may be responsible for the fact that almost all of them fail to bring about satisfactory survival benefit to liver cancer patients. Synthetic lethality, a concept that simultaneous losses of two genes is lethal to a cell while a single loss is non-lethal, can be utilized to selectively eliminate tumors with genetic aberrations through targeting synthetic lethal (SL) partners of those aberrations, offering an alternate route towards precision therapy. Methods: To infer liver cancer-specific SL interactions, we proposed a computational pipeline, termed SiLi (statistical inference-based synthetic lethality identification), that incorporated four inference procedures. Four sequencing datasets of liver cancer with both expression and mutation profiles available were integrated into a large-scale metadata set that was then taken as the basis for the identification of liver cancer-specific SL interactions. Findings: Through SiLi analysis, a total of 272 SL pairs were discovered, which included 209 unique target candidates. Among these, PLK1 was considered to have considerable therapeutic potential. Further computational and experimental validation of the corresponding SL pair, TP53-PLK1, demonstrated that inhibiting PLK1 could be a novel therapeutic strategy selectively targeting those patients with TP53-mutant liver tumors. Interpretation: Generally, our findings in this study may open new possibilities as well as provide a potential treasure trove for patient-tailored therapeutic interventions in liver cancer. Funding Statement: National Key Sci-Tech Special Projects of Infectious Diseases of China (2018ZX10732202- 002-003); the National Natural Science Foundation of China (81874229); Shanghai Natural Science Foundation (19ZR1452700). Declaration of Interests: The authors declare no conflict of interest.