Ramos, A. R. | bioRxiv Science

bioRxiv2020

Chemical inhibition of ENL/AF9 YEATS domains in acute leukemia

Transcriptional co-regulators, which mediate chromatin-dependent transcriptional signaling, represent tractable targets to modulate tumorigenic gene expression programs with small molecules. Genetic loss-of-function studies have recently implicated the transcriptional co-activator, ENL, as a selective requirement for the survival of acute leukemia and highlighted an essential role for its chromatin reader YEATS domain. Motivated by these discoveries, we executed a screen of nearly 300,000 small molecules and identified an amido-imidazopyridine inhibitor of the ENL YEATS domain (IC50 = 7 {micro}M). Leveraging a SuFEx-based high-throughput approach to medicinal chemistry optimization, we discovered SR-0813 (IC50 = 25 nM), a potent and selective ENL/AF9 YEATS domain inhibitor that exclusively inhibits the growth of ENL-dependent leukemia cell lines. Armed with this tool and a first-in-class ENL PROTAC, SR-1114, we detailed the response of AML cells to pharmacological ENL disruption for the first time. Most notably, displacement of ENL from chromatin by SR-0813 elicited a strikingly selective suppression of ENL target genes, including HOXA9/10, MYB, MYC and a number of other leukemia proto-oncogenes. Our study reproduces a number of key observations previously made by CRISPR/Cas9 loss of function and dTAG-mediated degradation, and therefore, both reinforces ENL as an emerging leukemia target and validates SR-0813 as a high-quality chemical probe.

cancer biology↗

bioRxiv2020

The Aging Slow Wave: A Shifting Amalgam of Distinct Slow Wave and Spindle Coupling Subtypes Define Slow Wave Sleep Across the Human Lifespan

Study ObjectivesSlow wave and spindle coupling supports memory consolidation, and loss of coupling is linked with cognitive decline and neurodegeneration. Coupling is proposed to be a possible biomarker of neurological disease, yet little is known about the different subtypes of coupling that normally occur throughout human development and aging. Here we identify distinct subtypes of spindles within slow wave upstates and describe their relationships with sleep stage across the human lifespan. MethodsCoupling within a cross-sectional cohort of 582 subjects was quantified from stages N2 and N3 sleep across ages 6-88 years old. Results were analyzed across the study population via mixed model regression. Within a subset of subjects, we further utilized coupling to identify discrete subtypes of slow waves by their coupled spindles. ResultsTwo different subtypes of spindles were identified during the upstates of (distinct) slow waves: an "early-fast" spindle, more common in stage N2 sleep, and a "late-fast" spindle, more common in stage N3. We further found stages N2 and N3 sleep are composed of two discrete subtypes of slow waves, each identified by their unique coupled-spindle timing and frequency. The relative contribution of coupling subtypes shifts across the human lifespan, and a deeper sleep phenotype prevails during old age. ConclusionsDistinct subtypes of slow waves and coupled spindles form the composite of slow wave sleep. Our findings support a model of sleep-dependent synaptic regulation via discrete slow wave/spindle coupling subtypes and advance a conceptual framework for the development of coupling-based biomarkers in age-associated neurological disease. Statement of SignificanceSlow waves of nonrapid eye movement sleep couple with sleep spindles in a process hypothesized to support memory functions. This coupling has recently gained interest as a possible biomarker of cognitive aging and onset of Alzheimers disease. Most studies have been limited by an assumption that all slow waves (and coupled spindles) are fundamentally the same physiological events. Here we demonstrate that distinct subtypes of slow waves and their coupled spindles can be identified in human sleep. A mixture of different slow wave and spindle subtypes shifts in composition during lighter versus deeper sleep, and aging favors the deep sleep subtypes. These data should inform any future attempts to use slow wave sleep as a biomarker or clinical interventional target.

neuroscience↗