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Integrative Genomic Analysis of Pediatric Myeloid-Related Acute Leukemias Identifies Novel Subtypes and Prognostic Indicators

  • for the Berlin-Frankfurt-Munster Study Group (BFM)
  • , for the Dutch Children’s Oncology Group (DCOG)
  • , for the Associazione Italiana di Ematologia e Oncologia Pediatrica (AIEOP);
  • , for the Nordic Society for Pediatric Hematology and Oncology (NOPHO)
  • , for the Dutch Children’s Oncology Group (DCOG);
  • , for St. Jude Children’s Research Hospital Study Group (SJCRH)
  • Erasmus University Rotterdam
  • St. Jude Children Research Hospital
  • Shanghai Jiao Tong University
  • Stanford University
  • University of Padua
  • University of Rome La Sapienza
  • Masaryk University
  • Aghia Sophia Children's Hospital
  • University of Florida
  • Ohio State University
  • University of Duisburg-Essen
  • Princess Máxima Center for Pediatric Oncology
  • Aarhus University

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

Genomic characterization of pediatric patients with acute myeloid leukemia (AML) has led to the discovery of somatic mutations with prognostic implications. Although gene-expression profiling can differentiate subsets of pediatric AML, its clinical utility in risk stratification remains limited. Here, we evaluate gene expression, pathogenic somatic mutations, and outcome in a cohort of 435 pediatric patients with a spectrum of pediatric myeloid-related acute leukemias for biological subtype discovery. This analysis revealed 63 patients with varying immunophenotypes that span a T-lineage and myeloid continuum designated as acute myeloid/T-lymphoblastic leukemia (AMTL). Within AMTL, two patient subgroups distinguished by FLT3-ITD and PRC2 mutations have different outcomes, demonstrating the impact of mutational composition on survival. Across the cohort, variability in outcomes of patients within isomutational subsets is influenced by transcriptional identity and the presence of a stem cell–like gene-expression signature. Integration of gene expression and somatic mutations leads to improved risk stratification.

Original languageEnglish
Pages (from-to)586-599
Number of pages14
JournalBlood Cancer Discovery
Volume2
Issue number6
DOIs
StatePublished - Nov 1 2021

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