bioRxivCancer BiologyPreprint
Integrative enhancer discovery identifies functional enhancer dependencies in pediatric acute myeloid leukemia
Leah SchüleriD, Robert E. WinkleriD, José Gonçalves-DiasiD, K SchuscheliD, Hasan IssaiD, Lonneke VerbooniD, Xiaoyan WeiiD, Ronay ÇetiniD, Yves MatthessiD, Manuel KaulichiD, Stefan HüttelmaieriD, Raj BhayadiaiD, Dirk HeckliD, Jan‐Henning KlusmanniD
Abstract
Pediatric acute myeloid leukemia (AML) is driven by aberrant transcriptional programs sustained by poorly defined cis-regulatory mechanisms. To systematically identify functional enhancer dependencies, we developed an integrative enhancer discovery strategy that combines H3K27ac CUT&Tag profiling, enhancer-associated transcription, and CRISPR interference (CRISPRi) screening. By leveraging enhancer-associated transcription to prioritize candidate regulatory elements, we identified 321 leukemia-associated enhancers for functional interrogation. This approach uncovered the hematopoietic MYB enhancer (H-ME) within the HBS1L-MYB-AHI1 locus as a critical regulator of leukemic growth. H-ME repression reduced chromatin accessibility and active histone marks at the MYB promoter, suppressed MYB expression, and induced differentiation-associated transcriptional programs. In contrast, selective depletion of the enhancer-associated transcript had no effect on MYB expression or leukemic proliferation, demonstrating that enhancer activity resides within the underlying regulatory DNA element rather than its mature RNA product. H-ME exhibited preferential activity in megakaryocytic leukemia, and its perturbation impaired leukemic growth in primary patient-derived models in vitro and in vivo. Together, our findings establish an integrative framework for the systematic discovery of functional enhancer dependencies and identified H-ME as an RNA-independent regulator of MYB in pediatric AML.
- organism: human
- assay: ChIP-seq
- assay: CRISPR screen
- research focus: cell type annotation
- research focus: differential expression
- approach: deep learning
- approach: statistical model
- Citations
- 0
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