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A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
Published on: May 27, 2021
Genetic landscape of T cells identifies synthetic lethality for T-ALL
Connor P O'Meara1, Lucia Guerri1,2, Divine-Fondzenyuy Lawir1,3
1Department of Developmental Immunology, Max Planck Institute of Immunobiology and Epigenetics, 79108, Freiburg, Germany.
Abstract:
To capture the global gene network regulating the differentiation of immature T cells in an unbiased manner, large-scale forward genetic screens in zebrafish were conducted and combined with genetic interaction analysis. After ENU mutagenesis, genetic lesions associated with failure of T cell development were identified by meiotic recombination mapping, positional cloning, and whole genome sequencing. Recessive genetic variants in 33 genes were identified and confirmed as causative by additional experiments. The mutations affected T cell development but did not perturb the development of an unrelated cell type, growth hormone-expressing somatotrophs, providing an important measure of cell-type specificity of the genetic variants. The structure of the genetic network encompassing the identified components was established by a subsequent genetic interaction analysis, which identified many instances of positive (alleviating) and negative (synthetic) genetic interactions. Several examples of synthetic lethality were subsequently phenocopied using combinations of small molecule inhibitors. These drugs not only interfered with normal T cell development, but also elicited remission in a model of T cell acute lymphoblastic leukaemia. Our findings illustrate how genetic interaction data obtained in the context of entire organisms can be exploited for targeted interference with specific cell types and their malignant derivatives.
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