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

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posted on 2023-04-04, 01:05 authored by Maarten Fornerod, Jing Ma, Sanne Noort, Yu Liu, Michael P. Walsh, Lei Shi, Stephanie Nance, Yanling Liu, Yuanyuan Wang, Guangchun Song, Tamara Lamprecht, John Easton, Heather L. Mulder, Donald Yergeau, Jacquelyn Myers, Jennifer L. Kamens, Esther A. Obeng, Martina Pigazzi, Marie Jarosova, Charikleia Kelaidi, Sophia Polychronopoulou, Jatinder K. Lamba, Sharyn D. Baker, Jeffrey E. Rubnitz, Dirk Reinhardt, Marry M. van den Heuvel-Eibrink, Franco Locatelli, Henrik Hasle, Jeffery M. Klco, James R. Downing, Jinghui Zhang, Stanley Pounds, C. Michel Zwaan, Tanja A. Gruber

Supplementary Excel Tables

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American Cancer Society

Associazione Italiana Ricerca sul Cancro

CARIPARO

NIH

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ARTICLE 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. Immunophenotype and somatic mutations play a significant role in treatment approach and risk stratification of acute leukemia. We conducted an integrated genomic analysis of pediatric myeloid malignancies and found that a combination of genetic and transcriptional readouts was superior to immunophenotype and genomic mutations in identifying biological subtypes and predicting outcomes.This article is highlighted in the In This Issue feature, p. 549

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    Blood Cancer Discovery

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    Keywords

    Genome BiologyHematological CancersLeukemiasTranslational Research

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