Genomic characterization of relapsed acute myeloid leukemia reveals novel putative therapeutic targets.

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Stratmann S, Yones SA, Mayrhofer M, Norgren N, Skaftason A, Sun J, Smolinska K, Komorowski J, Herlin MK, Sundström C, Eriksson A, Höglund M, Palle J, Abrahamsson J, Jahnukainen K, Munthe-Kaas MC, Zeller B, Tamm KP, Cavelier L, Holmfeldt L

Blood Adv 5 (3) 900-912 [2021-02-09; online 2021-02-10]

Relapse is the leading cause of death of adult and pediatric patients with acute myeloid leukemia (AML). Numerous studies have helped to elucidate the complex mutational landscape at diagnosis of AML, leading to improved risk stratification and new therapeutic options. However, multi-whole-genome studies of adult and pediatric AML at relapse are necessary for further advances. To this end, we performed whole-genome and whole-exome sequencing analyses of longitudinal diagnosis, relapse, and/or primary resistant specimens from 48 adult and 25 pediatric patients with AML. We identified mutations recurrently gained at relapse in ARID1A and CSF1R, both of which represent potentially actionable therapeutic alternatives. Further, we report specific differences in the mutational spectrum between adult vs pediatric relapsed AML, with MGA and H3F3A p.Lys28Met mutations recurrently found at relapse in adults, whereas internal tandem duplications in UBTF were identified solely in children. Finally, our study revealed recurrent mutations in IKZF1, KANSL1, and NIPBL at relapse. All of the mentioned genes have either never been reported at diagnosis in de novo AML or have been reported at low frequency, suggesting important roles for these alterations predominantly in disease progression and/or resistance to therapy. Our findings shed further light on the complexity of relapsed AML and identified previously unappreciated alterations that may lead to improved outcomes through personalized medicine.

Bioinformatics Compute and Storage [Service]

Bioinformatics Long-term Support WABI [Collaborative]

Bioinformatics Support, Infrastructure and Training [Collaborative]

Clinical Genomics Uppsala [Service]

NGI Uppsala (SNP&SEQ Technology Platform) [Service]

NGI Uppsala (Uppsala Genome Center) [Service]

National Genomics Infrastructure [Service]

PubMed 33560403

DOI 10.1182/bloodadvances.2020003709

Crossref 10.1182/bloodadvances.2020003709

pii: S2473-9529(21)00115-4
pmc: PMC7876890