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- W4310576945 endingPage "e1010518" @default.
- W4310576945 startingPage "e1010518" @default.
- W4310576945 abstract "Cancer progression is associated with the evolutionary accumulation of genetic mutations that are biologically significant. Mutations of the androgen receptor (AR) are associated with the development of prostate cancer (PCa) by responding to non-androgenic hormones, and the lack of annotations in their responsiveness to hormone ligands remains a daunting challenge. Here, we have used a yeast reporter system to quickly evaluate the responsiveness of all fifty clinical AR mutations to a variety of steroidal ligands including dihydrotestosterone (DHT), 17β-estradiol (E2), progesterone (PROG), and cyproterone acetate (CPA). Based on an AR-driven reporter that synthesizes histidine, a basic amino acid required for yeast survival and propagation, the yeast reporter system enabling clonal selection was further empowered by combining with a random DNA mutagenesis library to simulate the natural evolution of AR gene under the selective pressures of steroidal ligands. In a time-frame of 1–2 weeks, 19 AR mutants were identified, in which 11 AR mutants were validated for activation by tested steroidal compounds. The high efficiency of our artificial evolution strategy was further evidenced by a sequential selection that enabled the discovery of multipoint AR mutations and evolution directions under the pressure of steroidal ligands. In summary, our designer yeast is a portable reporter module that can be readily adapted to streamline high-throughput AR-compound screening, used as a PCa clinical reference, and combined with additional bioassay systems to further extend its potential." @default.
- W4310576945 created "2022-12-12" @default.
- W4310576945 creator A5026886431 @default.
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- W4310576945 date "2022-12-02" @default.
- W4310576945 modified "2023-10-14" @default.
- W4310576945 title "Yeast-based evolutionary modeling of androgen receptor mutations and natural selection" @default.
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- W4310576945 doi "https://doi.org/10.1371/journal.pgen.1010518" @default.
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- W4310576945 hasPublicationYear "2022" @default.
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