Journal
NATURE GENETICS
Volume 52, Issue 4, Pages 408-+Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41588-020-0590-9
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Funding
- Duke University School of Medicine start-up funds
- Duke Cancer Institute
- NIH [R01CA207083, F30CA206348, F31CA195967]
- National Science Foundation Graduate Research Fellowship awards [DGE-1106401, DGF1106401]
- Duke Medical Scientist Training Program [T32 GM007171]
- Duke Undergraduate Research Support Office
- ATIP/AVENIR French research program
- EHA research grant for NonClinical Advanced Fellow
- ERC [758848]
- St Louis Association for leukemia research
- European Research Council (ERC) [758848] Funding Source: European Research Council (ERC)
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CRISPR-Cas9 knockout screens in chemotherapy-treated acute myeloid leukemia cells help map the drug-dependent genetic basis of fitness trade-offs (antagonistic pleiotropy) for the design of evolutionary traps that target drug resistance in cancer. Local adaptation directs populations towards environment-specific fitness maxima through acquisition of positively selected traits. However, rapid environmental changes can identify hidden fitness trade-offs that turn adaptation into maladaptation, resulting in evolutionary traps. Cancer, a disease that is prone to drug resistance, is in principle susceptible to such traps. We therefore performed pooled CRISPR-Cas9 knockout screens in acute myeloid leukemia (AML) cells treated with various chemotherapies to map the drug-dependent genetic basis of fitness trade-offs, a concept known as antagonistic pleiotropy (AP). We identified a PRC2-NSD2/3-mediated MYC regulatory axis as a drug-induced AP pathway whose ability to confer resistance to bromodomain inhibition and sensitivity to BCL-2 inhibition templates an evolutionary trap. Across diverse AML cell-line and patient-derived xenograft models, we find that acquisition of resistance to bromodomain inhibition through this pathway exposes coincident hypersensitivity to BCL-2 inhibition. Thus, drug-induced AP can be leveraged to design evolutionary traps that selectively target drug resistance in cancer.
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