Biology subjects

Yashar, W. M.

Publications and source records attributed to Yashar, W. M..

4 recordsLinked to original sources

bioRxiv2026

PU.1 inhibition sensitizes stem-monocytic AML to BCL2 blockade

Acute myeloid leukemia (AML) exhibits substantial transcriptional heterogeneity across differentiation states that influences therapeutic response to BCL2 inhibition with venetoclax. While hematopoietic stem cell (HSC)-like AMLs show high sensitivity to venetoclax and monocytic-like AMLs demonstrate resistance, the therapeutic behavior of leukemias harboring both transcriptional programs remains poorly defined. Analysis of a large AML cohort reveals a distinct patient population exhibiting concurrent HSC- and monocyte-like transcriptional signatures, which we term stem-monocytic AML. Ex vivo drug sensitivity profiling demonstrates that stem-monocytic AMLs exhibit venetoclax resistance comparable to pure monocytic disease, despite expressing HSC-like transcriptional features. Using a leukemia cell line model that recapitulates stem-monocytic AML characteristics, we show through immunophenotyping and single-cell lineage tracing that venetoclax preferentially depletes immature blasts while sparing differentiated monocytic populations. Single-cell transcriptomic and chromatin accessibility analyses identify enrichment of myeloid differentiation transcription factors, particularly PU.1, in resistant populations. A targeted CRISPR knockout screen confirms that PU.1 disruption induces differentiation arrest and enhances venetoclax sensitivity primarily in the immature immunophenotypic compartments. Pharmacologic PU.1 inhibition with the small molecule DB2313 synergizes with venetoclax in both cell line models and primary patient samples. These findings establish stem-monocytic AML as a transcriptionally and functionally distinct subtype and nominate combined PU.1 and BCL2 inhibition as a rational therapeutic strategy for improving venetoclax response in this patient population.

cancer biology↗

bioRxiv2022

Predicting transcription factor activity using prior biological information

Transcription factors are critical regulators of cellular gene expression programs. Disruption of normal transcription factor regulation is associated with a broad range of diseases. In order to understand the mechanisms that underly disease pathogenesis, it is critical to detect aberrant transcription factor activity. We have developed Priori, a computational method to predict transcription factor activity from RNA sequencing data. Priori has several key advantages over existing methods. Priori utilizes literature-supported regulatory relationship information to identify known transcription factor target genes. Using these transcriptional relationships, Priori uses linear models to determine the impact and direction of transcription factor regulation on the expression of its target genes. In our work, we evaluated the ability of Priori and 16 other methods to detect aberrant activity from 124 single-gene perturbation experiments. We show that Priori identifies perturbed transcription factors with greater sensitivity and specificity than other methods. Furthermore, our work demonstrates that Priori can be used to discover significant determinants of survival in breast cancer as well as identify mediators of drug response in leukemia from primary patient samples.

bioinformatics↗

bioRxiv2022

Dual Targeting of FLT3 and LSD1 Disrupts the MYC Super-Enhancer Complex in Acute Myeloid Leukemia

Mutations in Fms-like tyrosine kinase 3 (FLT3) are common drivers in acute myeloid leukemia (AML) yet FLT3 inhibitors only provide modest clinical benefit. Prior work has shown that inhibitors of lysine-specific demethylase 1 (LSD1) enhance kinase inhibitor activity in AML. Here we show that combined LSD1 and FLT3 inhibition induces synergistic cell death in FLT3-mutant AML. Multi-omic profiling revealed that the drug combination disrupts STAT5, LSD1, and GFI1 binding at the MYC blood super-enhancer, suppressing super-enhancer activation as well as MYC expression and activity. The drug combination simultaneously results in the accumulation of repressive H3K9me1 methylation, an LSD1 substrate, at MYC target genes. We validated these findings in 72 primary AML samples with the nearly every sample demonstrating synergistic responses to the drug combination. Collectively, these studies provide preclinical rationale for the investigation of dual FLT3/LSD1 inhibition in a clinical trial.

cancer biology↗

bioRxiv2022

GoPeaks: Histone Modification Peak Calling for CUT&Tag

Genome-wide mapping of the histone modification landscape is critical to understanding tran-scriptional regulation. Cleavage Under Targets and Tagmentation (CUT&Tag) is a new method for profiling the localization of covalent histone modifications, offering improved sensitivity and decreased cost compared with Chromatin Immunoprecipitation Sequencing (ChIP-seq). Here, we present GoPeaks, a peak calling method specifically designed for histone modification CUT&Tag data. GoPeaks implements a Binomial distribution and stringent read count cut-off to nominate candidate genomic regions. We compared the performance of GoPeaks against commonly used peak calling algorithms to detect H3K4me3, H3K4me1, and H3K27Ac peaks from CUT&Tag data. These histone modifications display a range of peak profiles and are frequently used in epigenetic studies. We found GoPeaks robustly detects genome-wide histone modifications and, notably, identifies H3K27Ac with improved sensitivity compared to other standard peak calling algorithms.

bioinformatics↗