Tuesday, April 23, 2024
4/23/2024
Project Summary A fundamental difficulty in cancer research is the complex and genetically diverse nature of human tumors emphasized by recent large-scale tumor genome sequencing efforts such as the Cancer Genome Atlas (TCGA). For instance, TCGA identified nearly 30 recurrently mutated genes as drivers of colorectal cancer leading to deregulation of five signaling pathways. Individual tumors can carry any number of combinations of these driver mutations. A systematic, large-scale functional interrogation of human cancer genomes is essential to understand how this genetic complexity and diversity influences drug response. Powerful genetic tools available in Drosophila make it an ideal platform to generate and study a large number of genome-based cancer models in a rapid and cost effective manner. Insights from these models can then be used to test more directed hypotheses in vertebrate models, a more costly and time consuming prospect. To this end, we have generated and characterized 32 multigenic models representing the TCGA colorectal cancer dataset. These models carry 2-5 transgenes expressing oncogenes or knocking down tumor suppressors. When targeted to the adult hindgut epithelium (i.e. the Drosophila colon), these models recapitulated key features of human tumors. More importantly, a survey of clinically relevant drugs revealed that intrinsic drug resistance is a key emergent feature of genetic complexity. Our models are among the most genetically complex and diverse animal cancer models to date. Still, even more sophisticated models are necessary to fully represent the genetic diversity of human tumors revealed by cancer genomes. Generating and maintaining such models using standard Drosophila methods is challenging. In order to generate more sophisticated cancer models, we devised a method that allows expression and knock-down of multiple genes from a single multigenic construct. Preliminary experiments show that 10 genes can be manipulated using this platform. Its flexible design provides the opportunity to target 18 or even more genes. This proposal aims at further validating and expanding upon this multigenic vector design and create the toolbox to generate a more personalized and diverse panel of genome-based colorectal cancer models.
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