RNA-Sequencing Unveils Cryptic Fusions in Patients with Acute Myeloid Leukemia

Abstract Abstract 1278 Introduction: Acute myeloid leukemia (AML) represents a heterogeneous group of malignancies with great variability in response to therapy. In recent years, an increasing list of molecular markers with prognostic significance in AML has been identified; nonetheless, new prognostic markers and therapeutic targets are still needed. The aim of this study was to identify and verify fusion transcripts using RNA-Sequencing (RNA-Seq) that would be otherwise undetectable by conventional karyotyping. Methods: Transcriptome Sequence data is generated by high-throughput short-read RNA-Seq performed for each AML sample on the Illumina HiSeq. Poly(A) RNA is captured with poly(T) magnetic beads, fragmented, copied to cDNA libraries with reverse transcriptase and random primers. Each library is subjected to 50-cycle paired-end sequencing on the Illumina HiSeq at Hudson Alpha. Filtered Fastq files are processed with TopHat-Fusion [Kim2011,Trapnell2009] alignment software to discover cryptic fusions in RNA-Seq data without relying on known, annotated models. This process yielded an average of 20 million alignable reads per sample. Cord blood blast cell transcripts are also processed and serve as normal controls. A series of filtering steps eliminate junctions commonly found to be in error. Filtered junctions found in at least 3 AML samples and no normal controls are retained as AML-associated candidate junctions. Visual curation of candidates is performed using Integrative Genomics Viewer. Candidate fusions were verified by RT-PCR amplification of the AML-associated fusions in the index cases. Fusion transcript product, as well as the break point junction was verified by Sanger sequencing Results: Diagnostic specimens from 70 patients with de novo AML that included patients with normal karyotype (NK, N=31), core-binding factor (CBF) AML (N=33) and other (N=6) were sequenced. Age at diagnosis varied from 10 months to 69 years (Median 12 years). White blood cell count (WBC) and blast percentage were 49×109/L (range, 2.4 to 496×109/L) and 78% (40% to 100%), respectively. Bioinformatic evaluation of the RNA-Seq data revealed 67 high-value novel fusions that were not detected by conventional karyotyping: 54 (80.6%) were intra- and 13 (19.4%) inter-chromosomal junctions. The number of novel translocations varied in different cytogenetic groups, with 22 novel fusions detected in those with NK (16 intra and 6 inter-chromosomal junctions), 37 CBF (32 intra and 5 inter-chromosomal junctions) and 8 in “other” (6 intra and 2 inter-chromosomal junctions). Thirteen novel fusions (19.4%) were found in at least 2 or more screened-patients: two (15.4%) inter- and 11 (84.6%) intra-chromosomal junctions. Median number of fusions identified per patient was 2 (range, 1 to 6). Novel fusions involving PDGFR-β gene were identified in two patients, each with a different translocation partner (G3BP1 and ETV6, which was an intra and inter-chromosomal fusions, respectively). Sequencing of the fusion transcript junctions verified the fusion junctions and demonstrated in frame fusions of G3BP1 and ETV6 to the kinase domain coding region of PDGFR-β, identical junction to that seen in cases of imatinib sensitive idiopathic hypereosinophilic syndrome (IHES). Frequency validation in 100 adult and 100 pediatric cases identified one additional patient with G3BP1-PDGFR-β. Cryptic NUP98/NSD1 was identified and verified in two patients with normal karyotype as well as NUP98/HOXD13 translocation in one patient. Frequency determination of NUP98/NSD1 demonstrated prevalence of 7.8% in patients with NK, and that of 13% in patients with FLT3/ITD. Patients who harbored both NUP98/NSD1 fusion and FLT3/ITD had a dismal remission induction rate (CR rate in FLT3/ITD with and without NUP98/NSD1 was 28% vs. 73%; p=0.002). Conclusion: Our data show the applicability of RNA-Seq as a tool to discover cryptic fusion transcripts in AML. These novel fusions may define new independent prognostic markers and potential therapeutic targets for patients with this highly treatment-resistant disease. Disclosures: No relevant conflicts of interest to declare.

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Comprehensive study on ERG gene expression in normal karyotype acute myeloid leukemia: ERG expression is of limited prognostic value, whereas the accumulation of adverse prognostic markers stepwise worsens the prognosis

Blood Cancer Journal ◽

10.1038/bcj.2016.120 ◽

2016 ◽

Vol 6 (12) ◽

pp. e507-e507 ◽

Cited By ~ 3

Author(s):

S Weber ◽

T Haferlach ◽

C Haferlach ◽

W Kern

Keyword(s):

Gene Expression ◽

Acute Myeloid Leukemia ◽

Myeloid Leukemia ◽

Prognostic Value ◽

Prognostic Markers ◽

Normal Karyotype ◽

Acute Myeloid ◽

Comprehensive Study

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RNA Sequencing Reveals Novel and Rare Fusion Transcripts in Acute Myeloid Leukemia

Blood ◽

10.1182/blood.v126.23.3627.3627 ◽

2015 ◽

Vol 126 (23) ◽

pp. 3627-3627 ◽

Cited By ~ 1

Author(s):

Antonella Padella ◽

Giorgia Simonetti ◽

Giulia Paciello ◽

Anna Ferrari ◽

Elisa Zago ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Rna Sequencing ◽

Cytogenetic Analysis ◽

Myeloid Leukemia ◽

Fusion Transcript ◽

Gene Fusions ◽

Fusion Genes ◽

Exon 2 ◽

Frame Fusion ◽

Acute Myeloid

Abstract Acute Myeloid Leukemia (AML) is a highly heterogeneous disease and a complex network of events contribute to its pathogenesis. Chromosomal rearrangements and fusion genes have a crucial diagnostic, prognostic and therapeutic role in AML. A recent RNA sequencing (RNAseq) study on 179 AML revealed that fusion events occur in 45% of patients. However, the leukemogenic potential of these fusions and their prognostic role are still unknown. To identify novel rare gene fusions having a causative role in leukemogenesis and to identify potential targets for personalized therapies, transcriptome profiling was performed on AML cases with rare and poorly described chromosomal translocations. Bone marrow samples were collected from 5 AML patients (#59810, #20 and #84 at diagnosis and #21 and #32 at relapse). RNAseq was performed using the Illumina Hiseq2000 platform. The presence of gene fusions was assessed with deFuse and Chimerascan. Putative fusion genes were prioritized using Pegasus and Oncofuse, in order to select biologically relevant fusions. Chimeras not supported by split reads, occurring in reactive samples, involving not annotated or conjoined genes were removed. The remaining fusions were prioritized according to mapping of partner genes to chromosomes involved in the translocation or to Chimerascan and deFuse concordance. The CBFβ-MYH11 chimera was identified in sample #84, carrying inv(16) aberration, thus confirming the reliability of our analysis. Sample #59810 carried the fusion transcript ZEB2-BCL11B (Driver Score, DS=0.7), which is an in-frame fusion and a rare event in AML associated with t(2;14)(q21;q32). The breakpoint of the fusion mapped in exon 2 of ZEB2 (ENST00000558170) and exon 2 of BCL11B (ENST00000357195). Differently from previous data, this fusion transcript showed 3 splicing isoforms. Type 1 isoform is the full-length chimera and it retains all exons of both genes involved in the translocation. Type 2 isoform was characterized by the junction of exon 2 of ZEB2 and exon 3 of BCL11B. In type 3 isoform, exon 2 and 3 of BCL11B were removed, resulting in an mRNA composed by exon 2 of ZEB2 and exon 4 of BCL11B. Gene expression profiling showed an upregulation of ZEB2 and BCL11B transcripts in the patient's blasts, compared to 53 AML samples with no chromosomal aberrations in the 14q32 region. The same samples showed the WT1-CNOT2 chimera, which is a novel out-of-frame fusion (DS= 0.008) related to t(11;12) translocation, identified by cytogenetic analysis. Two new in-frame fusion genes were identified in sample #20: CPD-PXT1 (DS=0.07), which appeared as the reciprocal fusion product of t(6;17) translocation, and SAV1-GYPB, which remained cryptic at cytogenetic analysis (DS=0.8, alternative splicing events are being investigated). SAV1 was downregulated in sample #20 compared to our AML cohort, suggesting the putative loss of a tumour-suppressor gene. Sample #21 carried a t(3;12) translocation and RNAseq identified a novel fusion event between chromosomes 19 and 7, involving the genes OAZ and MAFK (DS=0.9). Finally, no chimeras were confirmed in sample #32 having a t(12;18) translocation. Our data suggest that fusion events are frequent in AML and a number of them cannot be detected by current cytogenetic analyses. Gene fusions cooperate to AML pathogenesis and heterogeneity and we are further investigating the oncogenic potential of the identified translocations. Moreover, the results firmly indicate that different approaches, including G-banding, molecular biology, bioinformatics and statistics, need to be integrated in order to better understand AML pathogenesis and improve patients' stratification, High-resolution sequencing analysis currently represent the most informative strategy to tailor personalized therapies. Acknowledgments: ELN, AIL, AIRC, progetto Regione-Università 2010-12 (L. Bolondi), Fondazione del Monte di Bologna e Ravenna, FP7 NGS-PTL project. Disclosures Soverini: Novartis, Briston-Myers Squibb, ARIAD: Consultancy. Martinelli:BMS: Speakers Bureau; MSD: Consultancy; Roche: Consultancy; ARIAD: Consultancy; Novartis: Speakers Bureau; Pfizer: Consultancy.

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New chimeric RNAs in acute myeloid leukemia

F1000Research ◽

10.12688/f1000research.11352.1 ◽

2017 ◽

Vol 6 ◽

pp. 1302 ◽

Cited By ~ 2

Author(s):

Florence Rufflé ◽

Jerome Audoux ◽

Anthony Boureux ◽

Sacha Beaumeunier ◽

Jean-Baptiste Gaillard ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Myeloid Leukemia ◽

Normal Karyotype ◽

Rna Seq ◽

Specific Expression ◽

Splice Isoforms ◽

Fusion Transcripts ◽

Link Type ◽

Chimeric Rnas ◽

Acute Myeloid

Background: High-throughput next generation sequencing (NGS) technologies enable the detection of biomarkers used for tumor classification, disease monitoring and cancer therapy. Whole-transcriptome analysis using RNA-seq is important, not only as a means of understanding the mechanisms responsible for complex diseases but also to efficiently identify novel genes/exons, splice isoforms, RNA editing, allele-specific mutations, differential gene expression and fusion-transcripts or chimeric RNA (chRNA). Methods: We used Crac, a tool that uses genomic locations and local coverage to classify biological events and directly infer splice and chimeric junctions within a single read. Crac’s algorithm extracts transcriptional chimeric events irrespective of annotation with a high sensitivity, and CracTools was used to aggregate, annotate and filter the chRNA reads. The selected chRNA candidates were validated by real time PCR and sequencing. In order to check the tumor specific expression of chRNA, we analyzed a publicly available dataset using a new tag search approach. Results: We present data related to acute myeloid leukemia (AML) RNA-seq analysis. We highlight novel biological cases of chRNA, in addition to previously well characterized leukemia chRNA. We have identified and validated 17 chRNAs among 3 AML patients: 10 from an AML patient with a translocation between chromosomes 15 and 17 (AML-t(15;17), 4 from patient with normal karyotype (AML-NK) 3 from a patient with chromosomal 16 inversion (AML-inv16). The new fusion transcripts can be classified into four groups according to the exon organization. Conclusions: All groups suggest complex but distinct synthesis mechanisms involving either collinear exons of different genes, non-collinear exons, or exons of different chromosomes. Finally, we check tumor-specific expression in a larger RNA-seq AML cohort and identify new AML biomarkers that could improve diagnosis and prognosis of AML.

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New chimeric RNAs in acute myeloid leukemia

F1000Research ◽

10.12688/f1000research.11352.2 ◽

2017 ◽

Vol 6 ◽

pp. 1302 ◽

Cited By ~ 2

Author(s):

Florence Rufflé ◽

Jerome Audoux ◽

Anthony Boureux ◽

Sacha Beaumeunier ◽

Jean-Baptiste Gaillard ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Myeloid Leukemia ◽

Normal Karyotype ◽

Rna Seq ◽

Specific Expression ◽

Splice Isoforms ◽

Fusion Transcripts ◽

Link Type ◽

Chimeric Rnas ◽

Acute Myeloid

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Mutation detection in thousands of acute myeloid leukemia cells using single cell RNA-sequencing

10.1101/434746 ◽

2018 ◽

Cited By ~ 3

Author(s):

Allegra A. Petti ◽

Stephen R. Williams ◽

Christopher A. Miller ◽

Ian T. Fiddes ◽

Sridhar N. Srivatsan ◽

...

Keyword(s):

Gene Expression ◽

Bone Marrow ◽

Acute Myeloid Leukemia ◽

Single Cell ◽

Rna Sequencing ◽

Myeloid Leukemia ◽

Normal Karyotype ◽

Integrative Approach ◽

Single Cell Rna Sequencing ◽

Acute Myeloid

AbstractVirtually all tumors are genetically heterogeneous, containing subclonal populations of cells that are defined by distinct mutations1. Subclones can have unique phenotypes that influence disease progression2, but these phenotypes are difficult to characterize: subclones usually cannot be physically purified, and bulk gene expression measurements obscure interclonal differences. Single-cell RNA-sequencing has revealed transcriptional heterogeneity within a variety of tumor types, but it is unclear how this expression heterogeneity relates to subclonal genetic events – for example, whether particular expression clusters correspond to mutationally defined subclones3,4,5,6-9. To address this question, we developed an approach that integrates enhanced whole genome sequencing (eWGS) with the 10x Genomics Chromium Single Cell 5’ Gene Expression workflow (scRNA-seq) to directly link expressed mutations with transcriptional profiles at single cell resolution. Using bone marrow samples from five cases of primary human Acute Myeloid Leukemia (AML), we generated WGS and scRNA-seq data for each case. Duplicate single cell libraries representing a median of 20,474 cells per case were generated from the bone marrow of each patient. Although the libraries were 5’ biased, we detected expressed mutations in cDNAs at distances up to 10 kbp from the 5’ ends of well-expressed genes, allowing us to identify hundreds to thousands of cells with AML-specific somatic mutations in every case. This data made it possible to distinguish AML cells (including normal-karyotype AML cells) from surrounding normal cells, to study tumor differentiation and intratumoral expression heterogeneity, to identify expression signatures associated with subclonal mutations, and to find cell surface markers that could be used to purify subclones for further study. The data also revealed transcriptional heterogeneity that occurred independently of subclonal mutations, suggesting that additional factors drive epigenetic heterogeneity. This integrative approach for connecting genotype to phenotype in AML cells is broadly applicable for analysis of any sample that is phenotypically and genetically heterogeneous.

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NPM1 Mutated AML Is Associated With Lower Expression Of Poor Prognostic Markers BAALC, ERG and MN1 In Adult Patients With Acute Myeloid Leukaemia

Blood ◽

10.1182/blood.v122.21.4945.4945 ◽

2013 ◽

Vol 122 (21) ◽

pp. 4945-4945 ◽

Cited By ~ 1

Author(s):

Poonkuzhali Balasubramanian ◽

Ashok kumar Jayavelu ◽

Ajay Abraham ◽

Savitha Varatharajan ◽

Sreeja Karathedath ◽

...

Keyword(s):

Gene Expression ◽

Bone Marrow ◽

Acute Myeloid Leukemia ◽

Myeloid Leukemia ◽

Prognostic Markers ◽

Normal Karyotype ◽

Adult Patients ◽

Rna Expression ◽

Flt3 Mutations ◽

Acute Myeloid

Abstract Acute myeloid leukemia (AML) is a clinically and biologically complex and heterogeneous hematopoietic neoplasm. Recent advances in acute myeloid leukemia (AML) biology have lead to prognosticate and predict treatment outcome in AML based on molecular markers. Mutations in NPM1, CEBPA are considered good prognosis and High BAALC, ERG & MN1 expression associate with worse outcome in AML patients treated with standard chemotherapy. Although many efforts have been made to identify genetic mutations and modulated gene expression levels that can be used to predict outcomes in patients with AML, the association between these prognostic markers has not been evaluated. We have reported previously that the NPM1 mutated patients have significantly high dCK and hENT1 gene expression (involved in cytarabine metabolism) and low ABCG2 and ABCB1transporter expression (Abraham et al, ASH abstracts; Nov 2011; 118: 3481 and Nov 2012; 120: 143), suggesting that the good prognostic nature of this mutation is possibly due to the better metabolism and transport of the chemotherapeutic drugs used in induction therapy. We extended this study to look for association between NPM1/FLT3 mutation status and the RNA expression of other good or poor prognostic markers in patients with AML. We prospectively included 274 adult patients with AML in this study. The median age was 42 years (range 16-74y). AML was diagnosed according to the FAB and WHO classifications. There were 238 patients with de novo AML; Secondary AML -6; Therapy related AML- 2 and Relapsed AML-28. Bone marrow cytogenetics and immunophenotyping analysis was available for all patients at diagnosis and/or relapse. Diagnostic bone marrow MNCs were isolated by ficoll- density gradient centrifugation and stored in trizol reagent for RNA expression and mutation detection. RT-PCR was used to screen AML-ETO and Inv 16, and the expression of BAALC, ERG1, MN1, CXCR4 and WT1were analyzed using RQ-PCR. NPM1-c, FLT3 ITD and TKD were screened using DNA PCR followed by gene-scan, sequencing or RFLP methods. The basic demographics and the frequency of the markers are listed in Table 1. When analyzed separately in normal karyotype AML (NK-AML), the frequencies of the mutations were: NPM1: 52.2%; FLT3-ITD: 24%; TKD: 4.3%. When the RNA expression of BAALC, WT1, ERG1, CXCR4 and MN1 was compared in patients with NPM1 or FLT3 mutations, we noticed that patients with NPM1 had significantly low expression of BAALC, MN1 and ERG1 while those with FLT3 mutations (ITD or TKD) had higher expression of these genes (Figure1). There was no significant association with CXCR4 or WT1 expression and these mutations. When analyzed separately in the normal karyotype AML, these associations were still significant. In addition, the relapsed patients had significantly higher expression of BAALC, MN1, and ERG1 RNA compared to de-novoAML cases (data not shown). To conclude, we show that NPM1 or FLT3 mutations acquire the prognostic significance due to several factors including BAALC, ERG1 and MN1expression levels in addition to drug metabolizing enzymes’ and drug transporter expression. These factors must be taken into consideration when attempting to personalize chemotherapy in AML. Disclosures: No relevant conflicts of interest to declare.

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Immunosuppression and Outcomes in Acute Myeloid Leukemia

10.1101/2021.09.03.458879 ◽

2021 ◽

Author(s):

Francesca Ferraro ◽

Christopher Miller ◽

Keegan Christensen ◽

Nichole M. Helton ◽

Margareth O'Laughlin ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

T Cell ◽

Rna Sequencing ◽

Mhc Class Ii ◽

T Cell Activation ◽

Myeloid Leukemia ◽

Cell Activation ◽

Independent Set ◽

Normal Karyotype ◽

Acute Myeloid

Acute myeloid leukemia (AML) patients rarely have long first remissions (> 5 years) after standard-of-care chemotherapy, unless classified as favorable risk at presentation. Identification of the mechanisms responsible for long vs. more typical, short remissions may help to define prognostic determinants for chemotherapy responses. Using exome sequencing, RNA sequencing and functional immunologic studies, we characterized 28 Normal Karyotype (NK)-AML patients with >5 year first remissions after chemotherapy (Long First Remissions, LFR) and compared them to a well-matched group of 31 NK-AML patients who relapsed within 2 years (Standard First Remissions, SFR). Our combined analyses indicated that genetic risk profiling at presentation (as defined by ELN 2017 Criteria) was not sufficient to explain the outcomes of many SFR cases. Single cell RNA-sequencing studies of 15 AML samples showed that SFR AML cells differentially expressed many genes associated with immune suppression. The bone marrow of SFR cases had significantly fewer CD4+ Th1 cells; these T cells expressed an exhaustion signature and were resistant to activation by T-cell receptor stimulation in the presence of autologous AML cells. T cell activation could be restored by removing the AML cells, or blocking the inhibitory MHC Class II receptor, LAG3. Most LFR cases did not display these features, suggesting that their AML cells were not as immunosuppressive. These findings were confirmed and extended in an independent set of 50 AML cases representing all ELN 2017 risk groups. AML cell-mediated suppression of CD4+ Tcell activation at presentation is strongly associated with unfavorable outcomes in AML patients treated with standard chemotherapy.

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Immunosuppression and outcomes in adult patients with de novo acute myeloid leukemia with normal karyotypes

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2116427118 ◽

2021 ◽

Vol 118 (49) ◽

pp. e2116427118

Author(s):

Francesca Ferraro ◽

Christopher A. Miller ◽

Keegan A. Christensen ◽

Nichole M. Helton ◽

Margaret O’Laughlin ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

T Cell ◽

Rna Sequencing ◽

T Cell Activation ◽

Myeloid Leukemia ◽

Cell Activation ◽

De Novo ◽

Independent Set ◽

Normal Karyotype ◽

Acute Myeloid

Acute myeloid leukemia (AML) patients rarely have long first remissions (LFRs; >5 y) after standard-of-care chemotherapy, unless classified as favorable risk at presentation. Identification of the mechanisms responsible for long vs. more typical, standard remissions may help to define prognostic determinants for chemotherapy responses. Using exome sequencing, RNA-sequencing, and functional immunologic studies, we characterized 28 normal karyotype (NK)-AML patients with >5 y first remissions after chemotherapy (LFRs) and compared them to a well-matched group of 31 NK-AML patients who relapsed within 2 y (standard first remissions [SFRs]). Our combined analyses indicated that genetic-risk profiling at presentation (as defined by European LeukemiaNet [ELN] 2017 criteria) was not sufficient to explain the outcomes of many SFR cases. Single-cell RNA-sequencing studies of 15 AML samples showed that SFR AML cells differentially expressed many genes associated with immune suppression. The bone marrow of SFR cases had significantly fewer CD4+ Th1 cells; these T cells expressed an exhaustion signature and were resistant to activation by T cell receptor stimulation in the presence of autologous AML cells. T cell activation could be restored by removing the AML cells or blocking the inhibitory major histocompatibility complex class II receptor, LAG3. Most LFR cases did not display these features, suggesting that their AML cells were not as immunosuppressive. These findings were confirmed and extended in an independent set of 50 AML cases representing all ELN 2017 risk groups. AML cell–mediated suppression of CD4+ T cell activation at presentation is strongly associated with unfavorable outcomes in AML patients treated with standard chemotherapy.

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Fusion gene detection by RNA sequencing complements diagnostics of acute myeloid leukemia and identifies recurring NRIP1-MIR99AHG rearrangements

Haematologica ◽

10.3324/haematol.2021.278436 ◽

2021 ◽

Author(s):

Paul Kerbs ◽

Sebastian Vosberg ◽

Stefan Krebs ◽

Alexander Graf ◽

Helmut Blum ◽

...

Keyword(s):

Acute Myeloid Leukemia ◽

Rna Sequencing ◽

Myeloid Leukemia ◽

Fusion Gene ◽

Mirna Cluster ◽

Fusion Genes ◽

Rna Seq ◽

Gene Detection ◽

Clinical Routine ◽

Acute Myeloid

Identification of fusion genes in clinical routine is mostly based on cytogenetics and targeted molecular genetics, such as metaphase karyotyping, FISH and RT-PCR. However, sequencing technologies are becoming more important in clinical routine as processing-time and costs per sample decrease. To evaluate the performance of fusion gene detection by RNA sequencing (RNAseq) compared to standard diagnostic techniques, we analyzed 806 RNA-seq samples from acute myeloid leukemia (AML) patients using two state-of-the-art software tools, namely Arriba and FusionCatcher. RNA-seq detected 90% of fusion events that were reported by routine with high evidence, while samples in which RNA-seq failed to detect fusion genes had overall lower and inhomogeneous sequence coverage. Based on properties of known and unknown fusion events, we developed a workflow with integrated filtering strategies for the identification of robust fusion gene candidates by RNA-seq. Thereby, we detected known recurrent fusion events in 26 cases that were not reported by routine and found discrepancies in evidence for known fusion events between routine and RNA-seq in three cases. Moreover, we identified 157 fusion genes as novel robust candidates and comparison to entries from ChimerDB or Mitelman Database showed novel recurrence of fusion genes in 14 cases. Finally, we detected the novel recurrent fusion gene NRIP1-MIR99AHG resulting from inv(21)(q11.2;q21.1) in nine patients (1.1%) and LTN1-MX1 resulting from inv(21)(q21.3;q22.3) in two patients (0.25%). We demonstrated that NRIP1-MIR99AHG results in overexpression of the 3' region of MIR99AHG and the disruption of the tricistronic miRNA cluster miR-99a/let-7c/miR-125b-2. Interestingly, upregulation of MIR99AHG and deregulation of the miRNA cluster, residing in the MIR99AHG locus, are known mechanism of leukemogenesis in acute megakaryoblastic leukemia. Our findings demonstrate that RNA-seq has a strong potential to improve the systematic detection of fusion genes in clinical applications and provides a valuable tool for fusion discovery.

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