bioRxivCancer BiologyPreprint
IKAROS Gene Regulatory Network Reveal ERG as a Vulnerability in B-cell Acute Lymphoblastic Leukemia
Hana PaculováiD, Alyssa R. RichmaniD, Joseph BoydiD, Joshua Carlos BerniliD, Princess RodrigueziD, Etapong Fonabei AyongabaiD, Prachi N. GhuleiD, Elsa DrivetiD, Amrita PalariaiD, Mariam Dajani, Els VerhoeyeniD, Anthony J. SaviolaiD, Gary S. SteiniD, Hilde SchjerveniD, Seth E. FrietzeiD
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Abstract
B-cell acute lymphoblastic leukemia (B-ALL) is driven by transcriptional dysregulation that impairs B-cell differentiation and sustains leukemic growth. A defining feature of high-risk B-ALL is mutations in IKZF1, which encodes the tumor suppressor IKAROS. Here, we map IKAROS gene regulatory networks in IKZF1-mutated Ph B-ALL using an inducible IKAROS system and multi-omic profiling. IKAROS restoration reprograms chromatin accessibility and transcriptional control, shifting regulation from an ETS-dominated state to one enriched for B-cell lineage factors. Among repressed transcription factors, we identify ERG as a key regulatory node directly bound and antagonized by IKAROS. IKAROS binds regulatory elements near ERG and other progenitor-associated genes, coinciding with reduced ERG expression and repression of transcriptional programs linked to early B-cell developmental stages. Analysis of single-cell multiome data from human B-cell progenitors shows that ERG and IKAROS have opposing stage-specific activities and identifies a developmental stage-specific regulatory region in ERG intron 3 which is bound by IKAROS, and functionally important for ERG gene expression. Functional assays using CRISPRi and ETS inhibitors, along with gene dependency data from DepMap, confirm ERG dependency in IKZF1-deficient B-ALL. Our findings identify ERG as a context-specific dependency in IKZF1-deficient B-ALL, providing a mechanistic basis for the observed mitigation of poor prognosis for IKZF1-mutation in patients with co-occurring ERG deletions.
- organism: human
- assay: scRNA-seq
- assay: ATAC-seq
- assay: multiome
- research focus: gene regulatory network inference
- research focus: cell type annotation
- research focus: differential expression
- approach: deep learning
- approach: statistical model
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