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Mutation and cell state compatibility is required and targetable in Ph+ acute lymphoblastic leukemia minimal residual disease.

Peter S WinterMichelle L RamseierAndrew W NaviaSachit D SaksenaHaley StroufNezha SenhajiAlan DenAdelMahnoor MirzaHyun Hwan AnLaura BilalPeter DennisCatharine S LeahyKay ShigemoriJennyfer Galves-ReyesYe ZhangFoster PowersNolawit MulugetaAlejandro J GuptaNicholas L CalistriAlexandria Van ScoykKristen JonesHuiyun LiuKristen E StevensonSiyang RenMarlise R LuskinCharles P CouturierAva P SoleimanySrivatsan RaghavanRobert J KimmerlingMark M StevensLorin CrawfordDavid M WeinstockScott R ManalisAlex K ShalekMark A Murakami
Published in: bioRxiv : the preprint server for biology (2024)
Efforts to cure BCR::ABL1 B cell acute lymphoblastic leukemia (Ph+ ALL) solely through inhibition of ABL1 kinase activity have thus far been insufficient despite the availability of tyrosine kinase inhibitors (TKIs) with broad activity against resistance mutants. The mechanisms that drive persistence within minimal residual disease (MRD) remain poorly understood and therefore untargeted. Utilizing 13 patient-derived xenograft (PDX) models and clinical trial specimens of Ph+ ALL, we examined how genetic and transcriptional features co-evolve to drive progression during prolonged TKI response. Our work reveals a landscape of cooperative mutational and transcriptional escape mechanisms that differ from those causing resistance to first generation TKIs. By analyzing MRD during remission, we show that the same resistance mutation can either increase or decrease cellular fitness depending on transcriptional state. We further demonstrate that directly targeting transcriptional state-associated vulnerabilities at MRD can overcome BCR::ABL1 independence, suggesting a new paradigm for rationally eradicating MRD prior to relapse. Finally, we illustrate how cell mass measurements of leukemia cells can be used to rapidly monitor dominant transcriptional features of Ph+ ALL to help rationally guide therapeutic selection from low-input samples.
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