Panel-based RNA fusion sequencing improves diagnostics of pediatric acute myeloid leukemia.
Lina Marie HoffmeisterJulia SuttorpChristiane WalterEvangelia AntoniouYvonne Lisa BehrensGudrun GöhringAmani AwadaNils von NeuhoffDirk ReinhardtMarkus SchneiderPublished in: Leukemia (2023)
New methods like panel-based RNA fusion sequencing (RNA-FS) promise improved diagnostics in various malignancies. We here analyzed the impact of RNA-FS on the initial diagnostics of 241 cases with pediatric acute myeloid leukemia (AML). We show that, compared to classical cytogenetics (CCG), RNA-FS reliably detected risk-relevant fusion genes in pediatric AML. In addition, RNA-FS strongly improved the detection of cryptic fusion genes like NUP98::NSD1, KMT2A::MLLT10 and CBFA2T3::GLIS2 and thereby resulted in an improved risk stratification in 25 patients (10.4%). Validation of additionally detected non-risk-relevant high confidence fusion calls identified PIM3::BRD1, C22orf34::BRD1, PSPC1::ZMYM2 and ARHGAP26::NR3C1 as common genetic variants and MYB::GATA1 as recurrent aberration, which we here describe in AML subtypes M0 and M7 for the first time. However, it failed to detect rare cytogenetically confirmed fusion events like MNX1::ETV6 and other chromosome 12p-abnormalities. As add-on benefit, the proportion of patients for whom measurable residual disease (MRD) monitoring became possible was increased by RNA-FS from 44.4 to 75.5% as the information on the fusion transcripts' sequence allowed the design of new MRD assays.
Keyphrases
- acute myeloid leukemia
- end stage renal disease
- newly diagnosed
- ejection fraction
- nucleic acid
- chronic kidney disease
- allogeneic hematopoietic stem cell transplantation
- transcription factor
- prognostic factors
- peritoneal dialysis
- genome wide
- healthcare
- acute lymphoblastic leukemia
- gene expression
- young adults
- deep learning
- high throughput
- machine learning
- copy number
- genome wide identification
- loop mediated isothermal amplification