Synthetic_lethality_of_TSG_in_hiPSC-sc-4402
Synthetic_lethality_of_TSG_in_hiPSC
We are performing CRISPR drop-out screenings using Yusa's KO library in human induced pluripotent stem cell lines knock out for a list of tumor suppressor genes. We collect cell pellets at multiple time points along the screening.
Tumor suppressor genes account for the majority of cancer drivers, while most approved molecular targeted therapies are directed against a small subset of the known oncogenes. Thus, there is a large uncovered space of targets that are not being exploited therapeutically and this currently remains as one of the critical challenges in genomic medicine. Importantly, drugs will rarely be able to directly re-activate a damaged gene, what makes targeting TSGs a specifically complex matter. To overcome this, targeted therapies will need to exploit the consequences of TSG loss-of function mutations and compensate them in an indirect manner. In order to achieve this, we will need a better understanding of the TSGs pathways and downstream effects of their loss.   For this purpose we have collected a panel of 30 isogenic human induced pluripotent stem (hiPS) cell lines with loss-of-function mutations in a single TSG each. First, we will perform a whole proteome analysis to identify the direct effects of TSG loss and deeply characterize its molecular consequences. Enrichment analysis using pathway and protein complexes databases will reveal which are the most significantly altered networks. Both downregulated and upregulated proteins can provide relevant insights, but the latter will already highlight potential therapeutical targets.   Then, we propose to perform a whole genome CRISPR screening to identify synthetic lethal pairs of the TSGs mutated in our panel of lines. The CRISPR screening will be performed in the parental cells as well as each of the targeted hiPS cell lines. The list of drop-out hits (i.e. guide RNAs lost in TSGs mutated cells but not in the parental line) will uncover candidate synthetic lethal pairs of the TSGs studied. At this point, integration with baseline proteomic data will help identify the most robust candidates and provide a way to filter the results based on specific hypotheses. This will enhance the probability of successful validation. Finally, the most interesting hits will be validated in independent clones and cancer cell lines. If there are drugs available we will try to reproduce the synthetic lethality events observed.