Author(s): ,
Lilit Ghukasyan
Laboratory of biological microchips,Engelhardt Institute of Molecular Biology, Russian Academy of Sciences,Moscow,Russian Federation
Georgii Krasnov
Laboratory of postgenomic studies,Engelhardt Institute of Molecular Biology, Russian Academy of Sciences,Moscow,Russian Federation
Liudmila Baidun
Laboratory of cytology,Russian Children's Clinical Hospital,Moscow,Russian Federation
Tatiana Nasedkina
Laboratory of biological microchips,Engelhardt Institute of Molecular Biology, Russian Academy of Sciences,Moscow,Russian Federation
EHA Library. Ghukasyan L. Jun 15, 2019; 266622; PS1005
Ms. Lilit Ghukasyan
Ms. Lilit Ghukasyan

Abstract: PS1005

Type: Poster Presentation

Presentation during EHA24: On Saturday, June 15, 2019 from 17:30 - 19:00

Location: Poster area

Cytogenetically normal acute myeloid leukemia (CN-AML) is a highly heterogenic group of AML, characterized by lack of cytogenetic aberration according to conventional karyotyping. CN-AML represents 20-25% of all pediatric AML cases and is classified mostly into intermediate risk subgroup, whereas the clinical outcomes may differ significantly. The heterogeneity of the CN-AML group might be explained by the presence of cryptic gene fusions or driver somatic mutations. The discovery of driver oncogenic events in CN-AML might help to improve the treatment stratification and prognosis. 

To evaluate the prognostic implication of RNA-seq analysis as a robust approach for identification of recurrent cryptic gene fusions and clinically significant mutations in pediatric CN-AML in one run.

The 11 pediatric CN-AML cases (median age - 8.5 years) were recruited into the study. RNA was isolated from bone marrow samples taken at diagnosis and sequencing libraries were prepared using TruSeq RNA Library Preparation Kit v2. The paired-end polyA RNA sequencing (150bpx2) was performed using Illumina NextSeq500. The identification of fusion transcripts was done by STAR-Fusion tool. The mutation profiling was performed using GATK HaplotypeCaller after marking duplicates and base quality score recalibration. Gene expression profiles were evaluated by featureCounts (subread package) and then analyzed by edgeR. The fusion transcripts were validated by RT-PCR and Sanger sequencing. 


In total, we have found 18 fusion events in the 11 CN-AML cases. Two recurrent in-frame fusions resulted into chimeric proteins were identified, namely, MYB-GATA1 (n=1) and NUP98-NSD1 (n=3). Other in-frame fusions AC005258.1-DAZAP1, ZNF292-PNRC1 and frameshift fusions EEF1A1-HBB, MALRD1-PLXDC2, ATP11A-ING1 may be considered as  chimeric RNA candidates. Besides, in five patients (45%) we found the chimeric transcript PCAT18-KCTD1. The long non-coding RNA PCAT18 is known to be overexpressed in other cancers, suggesting its involvement in tumorigenesis. The six of 11 samples harbored one of cancer-associated mutations KRAS p.G13D (n=2), NRAS p.G12D (n=1), NRAS p.G13D (n=1), PTPN11 p.Y63C (n=1), NOTCH1 p.R1287C (n=1). The sample with MYB-GATA1 harbored KRAS mutation. In each of three NUP98-NSD1-positive samples, at least one mutation in the KRAS, NRAS or NOTCH1 genes was found. The MYB-GATA1-positive sample revealed clearly distinct signature, characterized by overexpression of genes involved in IL-6-mediated signaling and cell differentiation. The samples with NUP98-NSD1 fusion also had similar gene expression patterns, but they did not form a cluster. The overexpression of genes involved in oxidative phosphorylation and glycolysis was noticed.


Whole-transcriptome sequencing in combination with gene expression and mutational profiling gives important information about the pathogenicity of oncogenic events occurred in CN-AML.

The work was supported by the Russian Science Foundation (grant # 18-15-00398).

Session topic: 3. Acute myeloid leukemia - Biology & Translational Research

Keyword(s): Acute myeloid leukemia, Somatic mutation

By clicking “Accept Terms & all Cookies” or by continuing to browse, you agree to the storing of third-party cookies on your device to enhance your user experience and agree to the user terms and conditions of this learning management system (LMS).

Cookie Settings
Accept Terms & all Cookies