PROJECT ABSTRACT Over 93% of cancer patients do not receive therapeutic benefit from oncology precision medicine. This can be partly attributed to 1) not understanding the genetic targets and modes-of-action of putative targeted therapies, and 2) lack of a well-characterized comprehensive drug compound library. To address these challenges, a shift in the drug discovery paradigm from “target-centric” to “chemical-centric” approaches is necessary. One such approach is chemical genomics, which involves screening drug compounds against a collection of defined gene mutants to identify mutations that sensitize or suppress a drug’s effect. These chemical-genetic interactions can be quantified by measuring mutants’ cell viability in the presence of compounds of interest. The entire set of mutant viability measurements for a given compound, called a “profile”, can then be used as a “fingerprint” to understand a drug’s modes-of-action. These screens can be performed in human cell lines using a pooled lentiviral CRISPR-Cas9 approach. While current genome-wide screens (~70,000 sgRNAs targeting ~18,000 genes) can inform candidate chemical compounds for drug development, many labs do not have the resources to perform these large-scale screens for more than a small number of compounds. Recent preliminary data from our labs show that screens with a small targeted CRISPR library (~3,000 sgRNAs targeting ~1,000 genes) can 1) recover similar biological information in a compressed library compared to genome-wide screens, and 2) reduce resource costs to allow for higher-throughput drug screening. TP53-mutant acute myeloid leukemia (AML) patients currently have very poor prognosis (1-2 year survival rates of 0-10%). There are currently no effective therapeutics for this patient subpopulation. However, a recent study showed that a TP53 KO AML cell line showed increased sensitivity to a panel of small-molecule inhibitors. The targeted chemical-genetic screen approach we develop here can reveal the genetic targets of these putative drugs to help with prioritizing lead compounds for drug development. The overall goal of this proposal is to develop a targeted CRISPR-Cas9 chemical-genetic screen approach and to develop a computational method to predict drug mode-of-action from chemical-genetic interaction data. I will pursue the following aims: (1a) develop and validate targeted screens in human cell lines, (1b) develop a computational method to score chemical-genetic interactions, rank candidate drug targets, and predict drug mode-of-action, and (2) elucidate mechanism-of-action of putative drug inhibitors for TP53-mutant AML using this targeted chemical-genetic screen approach. Completion of this study will result in a method for efficient discovery of drug mode-of-action and has implications for better understanding of how cancer (AML) therapeutics work. This work will also advance my understanding of computational tool development and application in clinical oncology, a...