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Mechanisms of mammalian drug resistance acquired during long-term evolution

ORAL

Abstract

Drug resistance emerges through cellular evolution, where selection pressure during treatment enables the spreading of increasingly drug-resistant cell variants. Despite the generality of this process, its underlying biological mechanisms and events are diverse, complex, and improperly understood. Previously, we applied synthetic gene circuits integrated into Chinese hamster ovary (CHO) cells to reveal antagonistic roles of gene expression stochasticity in mammalian drug resistance. After long-term exposure to Puromycin, many replicate cell populations evolved to be stably drug resistant. Yet, the biological mechanisms underlying drug resistance were unknown. Here, through transcriptome profiling by bulk RNA sequencing, we observed high up-regulation of drug resistance and other genes in the synthetic constructs, together with other native transcriptome changes. We verified both experimentally and computationally DNA amplification of gene circuit components during cellular evolution as a major cause of drug resistance. We propose DNA amplification around resistance genes as one of the major causes of drug resistance in cancer and other diseases, and suggest corresponding measures to improve treatment efficiency.

Publication: planned paper: Mechanisms of mammalian drug resistance acquired during long-term evolution

Presenters

  • Yiming Wan

    Stony Brook University

Authors

  • Yiming Wan

    Stony Brook University

  • Quanhua Mu

    Hong Kong University of Science and Technology

  • Rafa? Krzyszto?

    Stony Brook University

  • Joseph Cohen

    Stony Brook University (SUNY)

  • Damiano Coraci

    Stony Brook University

  • Christopher Helenek

    Stony Brook University

  • Annie Lin

    Stony Brook University

  • Kevin Farquhar

    PONCE Therapeutics

  • Jiguang Wang

    Hong Kong University of Science and Technology

  • Gabor Balazsi

    Stony Brook University (SUNY), Laufer Center for Physical and Quantitative Biology, Stony Brook University