Charles Grenfell Mullighan

This study identifies SOX11 as a driver of γδ-like T-cell acute lymphoblastic leukemia, showing its cooperation with LMO2 and MYCN to promote leukemogenesis.

The paper identifies LDB1-dependent enhancer connectivity as critical for T-cell leukemia subtypes and reveals a metabolic vulnerability exploitable by statins.

The paper develops ALTitude, a machine learning model to predict ALT status from whole genome sequencing data, identifies SMARCAL1 as a therapeutic target in ALT-driven cancers.

The paper maps human DNA replication origins using whole-genome sequencing data, identifying a 16 bp motif and periodicity, and links replication activity to gene expression and genetic variation.

This study uses scRNA-seq to analyze B-ALL samples, revealing transcriptional heterogeneity and developmental origins, with specific subtypes associated with distinct cell populations and clinical outcomes.

This study identifies MOZ and HBO1 as molecular dependencies in NUP98-rearranged AML, showing their inhibition reduces leukemic burden and synergizes with Menin inhibitors.

The paper constructs a reference atlas of human hematopoiesis and maps AML differentiation patterns, revealing genetic and non-genetic factors driving aberrant differentiation in leukemia.

This study identifies IKAROS as a factor associated with antigen escape in B-ALL, showing that low IKAROS levels lead to reduced B-cell antigen expression and resistance to CD19- and CD22-targeted therapies.

This study demonstrates real-time genomic classification of pediatric acute leukemia using long-read sequencing with adaptive sampling, identifying key alterations faster than traditional methods.

This study identifies uridine metabolism as a therapeutic target for chemo-resistant B-ALL by linking active signaling to uridine dependency and demonstrating DHODH inhibition as a promising treatment.

This study shows KMT2A oncoproteins drive lineage-switching and epigenetic resistance in leukemia by dynamically binding chromatin and persisting as ENL-marked lesions despite therapy.

BEAM integrates multiple omics profiles with multiple clinical outcomes using bootstrap resampling to identify significant associations, outperforming existing methods in simulations and a pediatric leukemia application.

The paper maps chromatin accessibility in B-ALL subtypes using ATAC-seq, identifies TFs and genetic variants influencing chromatin architecture and gene regulation.