Back

Non-coding germline GATA3 variants alter chromatin topology and contribute to pathogenesis of acute lymphoblastic leukemia

Yang, H.; Zhang, H.; Luan, Y.; Liu, T.; Roberts, K. G.; Qian, M.-x.; Zhang, B.; Yang, W.; Perez-Andreu, V.; Xu, J.; Iyyanki, S.; Kuang, D.; Reshmi, S. C.; Gastier-Foster, J.; Smith, C.; Pui, C.-H.; Evans, W. E.; Hunger, S. P.; Platanias, L. C.; Relling, M. V.; Mullighan, C. G.; Loh, M. L.; Yue, F.; Yang, J. J.

2020-02-25 cancer biology
10.1101/2020.02.23.961672 bioRxiv
Show abstract

Inherited non-coding genetic variants confer significant disease susceptibility in many cancers. However, the molecular processes of by which germline variants contribute to somatic lesions are poorly understood. We performed targeted sequencing in 5,008 patients and identified a key regulatory germline variant in GATA3 strongly associated with Philadelphia chromosome-like acute lymphoblastic leukemia (Ph-like ALL). By creating an isogenic cellular model with CRISPR-Cas9 system, we showed that this variant activated a strong enhancer that significantly upregulated GATA3 transcription, which in turn reshaped the global chromatin accessibility and 3D genome organization. Remarkably, this genotype switch induced a chromatin loop between the CRLF2 oncogene and a distal enhancer, similar to the somatically acquired super-enhancer hijacking event in patients. GATA3 genotype-related alterations in transcriptional control and 3D chromatin organization were further validated in Ph-like ALL patients. Finally, we showed that GATA3 directly regulates CRLF2 and potentiates the oncogenic effects of JAK-STAT signaling in leukemogenesis. Altogether, our results provide evidence for a novel mechanism by which a germline non-coding variant contributes to oncogene activation epigenetic regulation and 3D genome reprogramming.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.