| Summary: | 碩士 === 國立陽明大學 === 生物醫學資訊研究所 === 105 === Synthetic interactions (SI) are composed of synthetic lethality (SL) and synthetic viability (SV). SL is defined as the co-occurrence of two genetic perturbations results in cellular death, while single perturbations don’t. SV has been described as the second perturbation buffers the lethal effect of the first one. SIs have been reported as a promising strategy for identifying cancer therapeutic targets. Whole genome screening of SIs has succeeded in model organisms, such as S. cerevisiae and E. coli. However, it is time-consuming and expensive to perform experimental whole genome screening upon human genomes. Current computational approaches predicted SL by exploring homologous genes of experimentally validated SL and mutually exclusive somatic mutations in cancer genomes. By extending the concept of SIs toward organismal levels, we proposed a survival analysis-based model to identify SIs in human cancer genomes. This model applied the mRNA expression profiles of The Cancer Genome Atlas (TCGA) to clarify the relationships between the hazard of patients and gene expression levels. In the SI networks, we observed that SIs are cancer-specific. Moreover, cancer essential genes were under-represented in protective genes and the SI networks, emphasizing the reliability of the survival model. Functional enrichment analysis showed that SV genes are related to cell cycle and DNA repair; SL genes are related to signal transduction and metabolic process. Briefly, our model is useful for identifying novel therapeutic targets in cancer treatment and characterizing under-investigated genetic interactions.
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