Title |
Somatic drivers of B-ALL in a model of ETV6-RUNX1; Pax5+/− leukemia
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Published in |
BMC Cancer, August 2015
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DOI | 10.1186/s12885-015-1586-1 |
Pubmed ID | |
Authors |
Louise van der Weyden, George Giotopoulos, Kim Wong, Alistair G. Rust, Carla Daniela Robles-Espinoza, Hikari Osaki, Brian J. Huntly, David J. Adams |
Abstract |
B-cell precursor acute lymphoblastic leukemia (B-ALL) is amongst the leading causes of childhood cancer-related mortality. Its most common chromosomal aberration is the ETV6-RUNX1 fusion gene, with ~25 % of ETV6-RUNX1 patients also carrying PAX5 alterations. We have recreated this mutation background by inter-crossing Etv6-RUNX1 (Etv6 (RUNX1-SB) ) and Pax5 (+/-) mice and performed an in vivo analysis to find driver genes using Sleeping Beauty transposon-mediated mutagenesis and also exome sequencing. Combination of Etv6-RUNX1 and Pax5 (+/-) alleles generated a transplantable B220 + CD19+ B-ALL with a significant disease incidence. RNA-seq analysis showed a gene expression pattern consistent with arrest at the pre-B stage. Analysis of the transposon common insertion sites identified genes involved in B-cell development (Zfp423) and the JAK/STAT signaling pathway (Jak1, Stat5 and Il2rb), while exome sequencing revealed somatic hotspot mutations in Jak1 and Jak3 at residues analogous to those mutated in human leukemias, and also mutation of Trp53. Powerful synergies exists in our model suggesting STAT pathway activation and mutation of Trp53 are potent drivers of B-ALL in the context of Etv6-RUNX1;Pax5 (+/-) . |
X Demographics
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Unknown | 2 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 50% |
Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 54 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Master | 11 | 20% |
Researcher | 9 | 17% |
Student > Ph. D. Student | 8 | 15% |
Student > Bachelor | 6 | 11% |
Student > Doctoral Student | 4 | 7% |
Other | 8 | 15% |
Unknown | 8 | 15% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 13 | 24% |
Biochemistry, Genetics and Molecular Biology | 12 | 22% |
Medicine and Dentistry | 7 | 13% |
Computer Science | 4 | 7% |
Immunology and Microbiology | 3 | 6% |
Other | 5 | 9% |
Unknown | 10 | 19% |