GEO series
Clonal evolution of the 3D chromatin landscape of relapsed ALL [RNA-seq]
GSE222685
Homo sapiens
Expression profiling by high throughput sequencing
24 samples
2024/05/01
GPL24676
Summary
Relapsed pediatric B-cell acute lymphoblastic leukemia (B-ALL) remains one of the leading causes of cancer mortality in children. Up to 20% of children will suffer relapse and face a poor prognosis. Our recent work on the evolution of the epigenetic landscape from diagnosis to relapse demonstrates both substantial diversity in the chromatin landscape as well as shared relapse-specific superenhancer activation, highlighting the importance of chromatin changes in disease progression. However, there is a gap in our understanding of B-ALL progression through the lens of three-dimensional (3D) chromosome topology. To uncover 3D chromatin architecture-related mechanisms underlying drug resistance in B-ALL, we performed Hi-C, ATAC-seq, and RNA-seq on 12 matched primary pediatric leukemia specimens at diagnosis and relapse. Mapping of structural variations (SVs) using Hi-C data revealed previously unidentified stable, diagnosis-specific, and relapse-specific SVs providing further evidence for clonal evolution as a mechanism for drug resistance. Moreover, Hi-C analysis revealed genome wide chromatin remodeling specifically in terms of A/B compartments, TAD interactivity, and chromatin loops. Integration with ATAC-seq and RNA-seq datasets revealed strong correlation with both gene expression and chromatin accessibility. Additionally, we identified recurrent A/B compartments and TAD interactivity changes across the patient cohort for which we were able to demonstrate a crucial role in the clonal evolution of B-ALL. Shared changes in 3D genome organization drive the expression of genes/pathways previously implicated in drug resistance as well. Lastly, enrichment analysis revealed key upstream regulators of 3D genome architecture in B-ALL disease progression. These results extend the landscape of genetic alterations in relapsed B-ALL through the addition of the 3D genomic landscape and identify a breadth of novel therapeutic targets.
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Paper (PMID 39198446) ↗
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