Enhancer hijacking discovery in acute myeloid leukemia by pyjacker identifies MNX1 activation via deletion 7q.

IF 11.5 Q1 HEMATOLOGY
Etienne Sollier, Anna Riedel, Umut H Toprak, Justyna A Wierzbinska, Dieter Weichenhan, Jan Philipp Schmid, Mariam Hakobyan, Aurore Touzart, Ekaterina Jahn, Binje Vick, Fiona Brown-Burke, Katherine Kelly, Simge Kelekci, Anastasija Pejkovska, Ashish Goyal, Marion Bähr, Kersten Breuer, Mei-Ju May Chen, Maria Llamazares-Prada, Mark Hartmann, Maximilian Schönung, Nadia Correia, Andreas Trumpp, Yomn Abdullah, Ursula Klingmüller, Sadaf S Mughal, Benedikt Brors, Frank Westermann, Elias Ulrich, Robert J Autry, Matthias Schlesner, Sebastian Vosberg, Tobias Herold, Philipp A Greif, Dietmar Pfeifer, Michael Lübbert, Thomas Fischer, Florian H Heidel, Gebhard Gebhard, Wencke Walter, Torsten Haferlach, Ann-Kathrin Eisfeld, Krzysztof Mrózek, Deedra Nicolet, Lars Bullinger, Leonie Smeenk, Claudia Erpelinck-Verschueren, Roger Mulet-Lazaro, Ruud Delwel, Aurélie Ernst, Michael Scherer, Pavlo Lutsik, Irmela Jeremias, Konstanze Döhner, Hartmut Döhner, Daniel B Lipka, Christoph Plass
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引用次数: 0

Abstract

Acute myeloid leukemia with complex karyotype (ckAML) is characterized by high genomic complexity, including frequent TP53 mutations and chromothripsis. Genomic rearrangements that reposition active enhancers near proto-oncogenes, leading to their aberrant expression, have not been systematically investigated in AML. To facilitate the discovery of such "enhancer hijacking" events, we developed pyjacker, a computational tool, and applied it to 39 ckAML samples. Pyjacker identified several enhancer hijacking events in AML patient samples, including aberrant expression of motor neuron and pancreas homeobox 1 (MNX1), which can result from del(7)(q22q36) and is associated with hijacking of a CDK6 enhancer. MNX1 activation occurs in 1.4% of AML patients and shows significant co-occurrence with BCOR mutations. Through a xenograft mouse model, we demonstrated that MNX1 is required for leukemia cell fitness. Pyjacker is an easy-to-use, accurate, and broadly applicable tool for identifying consequences of genomic events driving tumorigenesis, especially when germline genomic data is missing.

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来源期刊
CiteScore
12.70
自引率
1.80%
发文量
139
期刊介绍: The journal Blood Cancer Discovery publishes high-quality Research Articles and Briefs that focus on major advances in basic, translational, and clinical research of leukemia, lymphoma, myeloma, and associated diseases. The topics covered include molecular and cellular features of pathogenesis, therapy response and relapse, transcriptional circuits, stem cells, differentiation, microenvironment, metabolism, immunity, mutagenesis, and clonal evolution. These subjects are investigated in both animal disease models and high-dimensional clinical data landscapes. The journal also welcomes submissions on new pharmacological, biological, and living cell therapies, as well as new diagnostic tools. They are interested in prognostic, diagnostic, and pharmacodynamic biomarkers, and computational and machine learning approaches to personalized medicine. The scope of submissions ranges from preclinical proof of concept to clinical trials and real-world evidence. Blood Cancer Discovery serves as a forum for diverse ideas that shape future research directions in hematooncology. In addition to Research Articles and Briefs, the journal also publishes Reviews, Perspectives, and Commentaries on topics of broad interest in the field.
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