A new genomic framework to categorize pediatric acute myeloid leukemia

Masayuki Umeda(St. Jude Children's Research Hospital), Jing Ma(St. Jude Children's Research Hospital), Tamara Westover(St. Jude Children's Research Hospital), Yonghui Ni(St. Jude Children's Research Hospital), Guangchun Song(St. Jude Children's Research Hospital), Jamie L. Maciaszek(St. Jude Children's Research Hospital), Michael Rusch(St. Jude Children's Research Hospital), Delaram Rahbarinia(St. Jude Children's Research Hospital), Scott G. Foy(St. Jude Children's Research Hospital), Benjamin J. Huang(University of California, San Francisco), Michael Walsh(St. Jude Children's Research Hospital), Priyadarshini Kumar(St. Jude Children's Research Hospital), Yanling Liu(St. Jude Children's Research Hospital), Wenjian Yang(St. Jude Children's Research Hospital), Yiping Fan(St. Jude Children's Research Hospital), Gang Wu(St. Jude Children's Research Hospital), Sharyn D. Baker(The Ohio State University), Xiaotu Ma(St. Jude Children's Research Hospital), Lu Wang(St. Jude Children's Research Hospital), Todd A. Alonzo(University of Southern California), Jeffrey E. Rubnitz(St. Jude Children's Research Hospital), Stanley Pounds(St. Jude Children's Research Hospital), Jeffery M. Klco(St. Jude Children's Research Hospital)
Nature Genetics
January 11, 2024
Cited by 99Open Access
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Abstract

Recent studies on pediatric acute myeloid leukemia (pAML) have revealed pediatric-specific driver alterations, many of which are underrepresented in the current classification schemas. To comprehensively define the genomic landscape of pAML, we systematically categorized 887 pAML into 23 mutually distinct molecular categories, including new major entities such as UBTF or BCL11B, covering 91.4% of the cohort. These molecular categories were associated with unique expression profiles and mutational patterns. For instance, molecular categories characterized by specific HOXA or HOXB expression signatures showed distinct mutation patterns of RAS pathway genes, FLT3 or WT1, suggesting shared biological mechanisms. We show that molecular categories were strongly associated with clinical outcomes using two independent cohorts, leading to the establishment of a new prognostic framework for pAML based on these updated molecular categories and minimal residual disease. Together, this comprehensive diagnostic and prognostic framework forms the basis for future classification of pAML and treatment strategies.


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