OL Oncology Letters 1792-1074 1792-1082 D.A. Spandidos 10.3892/ol.2022.13607 OL-25-01-13607 Articles A genomic DNA-based NGS method for the simultaneous detection of multiple fusion genes in pediatric leukemia LiuRong 1 * FengShunqiao 1 * LiYanchun 2 * PanHongchao 3 LiangChao 2 SuYanhui 3 DongJiahao 2 LiBenshang 4 * ChenZhong 2 3 CuiXiaodai 5 Department of Hematology, Children's Hospital of Capital Institute of Pediatrics, Beijing 100020, P.R. China Beijing Hightrust Diagnostics, Co., Kindstar Globalgene Technology, Inc., Beijing 100176, P.R. China Shanghai Simplegene Clinical Laboratory, Co., Kindstar Globalgene Technology, Inc., Shanghai 200025, P.R. China Key Laboratory of Pediatric Hematology and Oncology Ministry of Health, Department of Hematology and Oncology, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, P.R. China Department of Key Laboratory, Children's Hospital of Capital Institute of Pediatrics, Beijing 100020, P.R. China Correspondence to: Dr Zhong Chen, Beijing Hightrust Diagnostics, Co., Kindstar Globalgene Technology, Inc., Building 3, 1 Disheng North Street, Beijing 100176, P.R. China, E-mail: chenzhong@kindstar.com.cn Dr Xiaodai Cui, Department of Key Laboratory, Children's Hospital of Capital Institute of Pediatrics, 2 Yabao Road, Chaoyang, Beijing 100020, P.R. China, E-mail: xdcui61@sina.com

Contributed equally

 01 2023 22 11 2022 25 1 21 20092022 26102022 Copyright © 2022, Spandidos Publications 2022

Fusion genes are products of chromosomal translocations that generate either a dysregulated partner gene or a chimeric fusion protein with new properties, and contribute significantly to leukemia development and clinical risk stratification. However, simultaneous detection of several hundreds of fusion genes has always been a challenge in a clinical laboratory setting. In the present study, a total of 182 pediatric patients with leukemia were screened for fusion genes by employing a novel genomic DNA-, instead of RNA-, based next-generation sequencing (NGS) method. This involved the comparison of the multiply targeted capture sequencing method with a detection panel of 270 fusion genes (MTCS-270) with an RNA-based multiplex reverse transcription-PCR technique with a detection panel of 57 fusion genes (MRTP-57). MRTP-57 has been well established in the clinical lab at Beijing Hightrust Diagnostics, Co. (Beijing, China) for an up-front leukemia diagnosis and served as the control technique in the present study. In the series, MTCS-270 and MRTP-57 yielded a positive fusion gene detection rate of 50.0% (91/182) and 41.8% (76/182), respectively, indicating an advantage of MTCS-270 over MRTP-57 in overall detection sensitivity. Specifically, all the fusion genes detected by MRTP-57 were also identified by MTCS-270, clearly signifying the respectable detection accuracy of MTCS-270. Notably, across the patients screened, MTCS-270 identified more samples with fusion genes than MRTP-57, illustrating a broader fusion gene detection coverage by MTCS-270. The present study provides solid evidence that this DNA-based NGS approach can be used as a potential detection tool together with other well-established molecular cytogenetic methods for leukemia management, and to the best of our knowledge, represents the largest leukemia fusion gene identification analysis by genomic NGS.

 leukemia fusion genes next-generation sequencing reverse transcription-PCR Funding: No funding was received. Introduction

Leukemia is a heterogeneous clonal malignancy that develops from hematopoietic stem cells. All the different molecular events involved in the development of leukemia result from genetic or chromosomal lesions in blood-forming cells, commonly including duplication of genetic material, loss of genetic information, inactivation of genes that normally suppress tumor development, chromosomal translocations and the release of abnormal fusion proteins. Leukemia is classified by the dominant cell type, and by duration from onset to death (1,2). The 2016 revision to the World Health Organization (WHO) Classification of myeloid neoplasms and acute leukemia mainly divides leukemia into acute myeloid leukemia (AML), acute lymphocytic leukemia (ALL) and other types of hematological neoplasms (1). The 2016 WHO Classification also categorizes AML into 11 genetic subtypes and ALL into nine genetic subtypes, with each subtype containing relatively unique clinical and prognostic characteristics. During diagnosis, molecular cytogenetic abnormalities are the primary indicators that must be investigated for patients with leukemia for the purpose of assessing risk stratification. Notably, chromosomal translocations resulting in fusion genes account for the most important genetic events and are specific for some particular subtypes of leukemia, such as t(8;21)(q22;q22), inv(16)(p13q22), t(16;16)(p13;q22) and t(15;17)(q22;q12) in AML, t(12;21)(p13;q22), t(9;22)(q34;q11.2), t(1;19)(q23;p13) and 11q23/MLL-rearrangements in ALL, and t(9;22)(q34;q11.2) in chronic myelocytic leukemia (CML) (1,2). Importantly, fusion genes have also been reported in association with 40–50% of childhood AML and ALL cases (3,4). Although not all the fusion genes identified have clinical relevance, a number of them do play a significant role in leukemia diagnosis, risk stratification or minimal residual disease detection (1,2). Therefore, efficient screening and detection of multiple fusion genes plays a significant role in managing patients with leukemia.

Detection of fusion genes can be achieved at RNA (transcripts of fusion genes) or genomic DNA levels. With the development of an RNA-based multiplex reverse transcription-PCR (RT-PCR) technique, simultaneous screening of several tens of fusion genes has become feasible (5). This has provided great convenience over standard molecular cytogenetic tests [traditional chromosome and fluorescence in situ hybridization (FISH) analysis] for the clinical diagnosis and treatment of patients with leukemia. However, although RT-PCR allows for the highly sensitive detection of fusion gene transcripts at RNA levels, it requires primer pairs specific for the fusion gene breakpoints. In consideration of the great number of fusion genes and breakpoint variants reported in leukemia, it is difficult and not practically feasible to simultaneously analyze several hundreds of fusion genes and breakpoint variants (5).

With the progress of molecular biology technology, especially following the widespread applications of next-generation sequencing (NGS), NGS has allowed systematic identification of molecular features associated with leukemia (6–8). In the present study, a novel genomic DNA-, instead of RNA-, based NGS method was adopted to simultaneously detect >200 fusion genes in a group of pediatric patients with leukemia. In particular, the DNA-based NGS method involving the multiply targeted capture sequencing method with a detection panel of 270 fusion genes (MTCS-270; Table I) was compared with an RNA-based RT-PCR technique involving multiplex RT-PCR with a detection panel of 57 fusion genes (MRTP-57; Table I) for parallel analysis of fusion genes. The MTCS-270 method followed the same technical principles reported previously by our group (9). MRTP-57 has been well established in the clinical lab at Beijing Hightrust Diagnostics, Co. (Beijing, China) for an up-front leukemia diagnosis and served as the control technique in the present study. To the best of our knowledge, the present study presents the largest fusion gene identification analysis by DNA-based NGS in leukemia.

 Materials and methods <sec> <title>Patient samples

All 182 pediatric patients enrolled in the present study were diagnosed at the Department of Hematology, Children's Hospital of Capital Institute of Pediatrics Beijing, China between January 2018 and December 2019. At hospital admission, bone marrow samples were obtained from the patients as part of a diagnosis, from which DNA and RNA were extracted for analysis. This research was approved by the Ethics Committee at the Children's Hospital of Capital Institute of Pediatrics (Beijing, China). All parents/guardians of the minor patients (<18 years old) included in the study signed a written informed consent form.

 Genomic DNA library preparation and multiply targeted capture sequencing

A QIAamp DNA Blood Mini Kit (Qiagen GmbH) was used to extract total DNA from bone marrow samples according to the manufacturer's instructions. Each DNA sample was quantified (20–100 ng/µl) with the Qubit™ dsDNA BR Assay kit (Thermo Fisher Scientific, Inc.) and DNA integrity was evaluated by 2% agarose gel electrophoresis. High-quality genomic DNA (OD 260/280 ratio of 1.8-2.0) was fragmented by sonication (cycles, 10; cycle time, 60 sec; temperature, 4°C) using a Covaris S2 (Covaris LLC). The fragmented DNA was repaired, ligated with Illumina adapters (Illumina, Inc.) and size-selected at 350 to 400 base pairs (bp). Subsequently, the size-selected product was amplified, tagged with a unique index using the Illumina DNA prep kit, and validated using the Agilent 2100 Bioanalyzer (Agilent Technologies, Inc.).

The amplified DNA product was captured with a customized panel of biotinylated oligoprobes using MyGenostics GenCap Enrichment technology (MyGenostics, Inc.). The capture experiment was performed according to the manufacturer's protocol. For the detection of a fusion gene involving a gene of interest, the oligoprobes were designed to capture the whole region of the gene and to cover the likely break regions of a fusion partner gene. These oligoprobes were projected to identify 270 types of fusion genes found in leukemia (Table I). Finally, the captured DNA library was amplified, quantified with the Qubit™ dsDNA BR Assay kit (Thermo Fisher Scientific, Inc.), and sequenced at ~20 pM using the HiSeq X Reagent Kit on a HiSeq X Ten system (Illumina, Inc.) for paired reads at 150 bp. Fig. 1 shows the location of biotinylated oligoprobes relative to two representatives of commonly detected fusion genes in this study (BCR/ABL1 and PML/RARα).

For bioinformatics analysis, sequence variant detection was performed by using paired-end sequencing data, as previously described [Phrap (http://www.phrap.org/), SAMtools (http://samtools.sourceforge.net/)] (9,10).

 RNA collection and multiplex RT-PCR

The MRTP-57 protocol followed a previously reported strategy (11). In brief, bone marrow samples were prepared first by the trizol (ZYMO Research Corp.) homogenization method according to the manufacturer's recommendations. Subsequent total RNA extraction was performed using the Direct-zol™ RNA MiniPrep (ZYMO Research Corp.) assay. Extracted RNA was resuspended in RNase-free water, and the concentration and quality determined using a NanoDrop ND-1000 Spectrophotometer (NanoDrop Technologies; Thermo Fisher Scientific, Inc.). The RNA samples were reverse transcribed into high-quality cDNA using optimized primers [oligo (dT)-based primers and random hexamer primers] and other related reagents from Takara Bio, Inc. (RNase inhibitor, dNTPs and moloney murine leukemia virus reverse transcriptase). Using an ABI system (Veriti96; Applied Biosystems; Thermo Fisher Scientific, Inc.), the RT-PCR procedure was then performed with individual primer sets (Table SI), which were specifically designed for the detection of 57 fusion genes commonly reported as primary genetic events involved in leukemogenesis (Table I).

Dependent on the breakpoints involved, some fusion genes may need only one pair of primers to cover the hot-breakpoint regions, while other may need two or more pairs of primers to do so, as illustrated in Table SI.

A multiplex touchdown RT-PCR strategy was used to detect the fusion genes. In brief, the samples were initially heated at 94°C for 2 min, followed by 20 cycles of amplification each at 94°C for 30 sec, 68°C (decreasing incrementally by 0.5°C per cycle) for 30 sec and 72°C for 1 min, followed by another 20 cycles of amplification each at 94°C for 30 sec, 58°C for 30 sec and 72°C for 1 min, and culminating with a final cycle at 72°C for 10 min.

 Results

Bone marrow samples were obtained from 182 newly diagnosed pediatric patients (102 men and 80 women; <18 years; median age, 4 years), including 46 patients with AML (median age, 6 years), 116 with B-cell ALL (B-ALL; median age, 5 years), 13 with T-cell ALL (T-ALL; median age, 5 years), 5 with CML (median age, 8 years) and 2 with juvenile myelomonocytic leukemia (JMML; ages, 3 years and 10 months). These samples were analyzed using MTCS-270 in parallel with MRTP-57. The clinical information and detection results are shown in Table II, Table III, Table IV.

In the 46 AML samples screened (Table II), 28 (60.9%) and 21 (45.7%) were identified as containing fusion genes using MTCS-270 and MRTP-57, respectively (Fig. 2). All 21 samples with fusion genes detected by MRTP-57 were also identified by MTCS-270, signifying the accuracy and effectiveness of MTCS-270 in detecting these fusion genes. Due to the technical constraints of MRTP-57 in experimental design, numerous leukemia-related fusion genes could not be included in the detection panel for analysis; by contrast, MTCS-270 had a much broader fusion gene detection range and was able to identify 7 additional fusion genes in the AML samples screened. Each additional fusion gene detected was different (i.e., CBFA2T3/GLIS2, NIFA/CBFA2T1, ZEB2/RUNX1, MYO1F/KMT2A, NUP98/NSD1, HOXA11AS/PBX1 and EWSR/ELF5), demonstrating the more comprehensive capability of MTCS-270 in fusion gene detection. Notably, by combining both the MTCS-270 and MRTP-57 detection approaches, the frequently observed fusion genes in AML, such as the AML1/ETO, PML/RARA, CBFβ/MYH11 and MLL-related fusion genes, were detected in 5/46 (10.9%), 4/46 (8.7%), 2/46 (4.3%) and 9/46 (19.6%) samples, respectively, which was generally consistent with the findings reported in the literature (12,13). Furthermore, MTCS-270 was able to differentiate isoforms of affected fusion genes, which was beyond the detection capability of MRTP-57. For example, in the positively identified AML cases, 2 isoforms of the AML1/ETO fusion gene (i.e., AML1 exons 1–5 to ETO exons 2–12 and AML1 exons 1–5 to ETO exons 3–12), 3 isoforms of PML/RARA (i.e., PML exons 1–6 to RARA exons 3–9, PML exons 1–3 to RARA exons 3–9 and PML exons 1–6+ to RARA exons 3–9), 2 isoforms of CBFβ/MYH11 (i.e., CBFβ exons 1–4 to MYH11 exons 34–41 and CBFβ exons 1–5 to MYH11 exons 33–41) and 2 isoforms of MLL/AF9 (i.e., MLL exons 1–9 to AF9 exons 6–11 and MLL exons 1–10 to AF9 exons 6–11) were observed, further illustrating the precision of MTCS-270 in fusion gene analysis.

In the 116 B-ALL samples screened (Table III), 55 (47.4%) and 49 (42.2%) were identified as containing fusion genes using MTCS-270 and MRTP-57, respectively (Fig. 3). Similar to the results from the AML group, all the 49 samples with fusion genes identified by MRTP-57 were also included in the positively detected samples by MTCS-270; furthermore, 6 additional samples were found to carry fusion genes by MTCS-270, but not by MRTP-57, including 3 samples with IGH/MYC, 1 with IGH/CRLF2, 1 with PAX5/WDR5 and 1 with HOXA11/MIR181A1HG. The analyses of MTCS-270 together with MRTP-57 revealed that the commonly observed fusion genes in the B-ALL samples screened were ETV6/RUNX1 in 22/116 (19.0%), BCR/ABL1 (P190) in 7/116 (6.0%), ZNF384-related fusion genes in 6/116 (5.2%), MLL-related fusion genes in 5/116 (4.3%), E2A/PBX1 in 4/116 (3.4%) and MEF2D/BCL-9 in 4/116 (3.4%), which was generally consistent with observations reported in the literature (14–16). Finally, as with the AML samples, several isoforms of the affected fusion genes were distinguished only by MTCS-270, including 2 isoforms of the ETV6/RUNX1 fusion gene (i.e., ETV6 exons 1–5 to RUNX1 exons 2–8 and ETV6 exons1-5 to RUNX1 exons 3–8), 2 isoforms of MLL/AF4 (i.e., MLL exons 1–8 to AF4 exons 4–20 and MLL exons 1–10 to AF4 exons 4–20), 2 isoforms of MLL/ENL (i.e., MLL exons 1–10 to ENL exons 1–12 and MLL exons 1–10 to ENL exons 7–12) and 2 isoforms of MEF2D/BCL9 (i.e., MEF2D exons 1–3 to BCL9 exons 9–10 and MEF2D exons 1–6 to BCL9 exon 10).

In the remaining patients, 1/13 T-ALL (Table III), 4/5 CML (Table IV) and 1/2 JMML (Table IV) samples containing disease-relevant fusion genes were detected by MRTP-57; by contrast, in addition to the aforementioned fusion genes, MTCS-270 also detected that 1 more T-ALL and 1 more CML sample that contained disease-related fusion genes. Notably, in comparison with MRTP-57, MTCS-270 was also able to differentiate 2 isoforms of the BCR/ABL1 (P210) fusion gene and to disclose the presence of BCR/EXOSC2, a variant of the BCR/ABL1 fusion gene, in CML samples.

 Discussion

Clinically, FISH and RT-PCR are the methods commonly employed for detection of fusion genes in leukemia. However, due to various technical constraints, such as intensive labor and reagent costs, as well as some limitations involved in experimental design and execution, it is practically impossible to simultaneously analyze several tens to several hundreds of fusion genes and breakpoint variants by these two methods. RNA-based NGS (RNA-Seq) is the leading technique for characterizing transcriptomes of cells in a patient sample, providing a theoretically ideal tool for simultaneous detection of multiple fusion genes in leukemia. In addition, due to its capability in simultaneously identifying global gene transcripts and diverse RNA species, RNA-Seq has the promise to revolutionize clinical testing for a wide range of disorders (17). However, due to some challenges encountered in translating this technology into clinical practice, including ongoing efforts to establish reference standards, achieving testing results with high reproducibility, accuracy and precision, and several potential procedure-related technical difficulties (such as inappropriate sample handling and preparation resulting in RNA instability, degradation, composition biases and gene expression artifacts, as well as RNA capture inefficiency), at present RNA-Seq is not commonly recommended as an up-front approach for multiple fusion gene detection in the clinical setting (17).

DNA-, but not RNA-, based NGS has been well documented in detecting genomic structural and single-nucleotide variants (6,9,18); in addition, it has been reported to simultaneously analyze some fusion genes and breakpoint variants in leukemic cells (19). This approach identified breakpoints and flanking sequences at the genomic level through the design and synthesis of capture probes spanning genomic regions of fusion gene breakpoints. This method required lower amounts of genomic DNA for analysis, possessed a relatively lower workload for multiple-sample handling and could yield more meaningful information, such as detailed breakpoints and flanking sequences of fusion genes. In order to further appreciate the efficacy of this approach in analyzing genomic aberrations of leukemic cells, the present study focused on fusion genes, one of the most difficult and complex types of genomic aberrations, as the targets for evaluation. The effectiveness of this approach was assessed by simultaneously analyzing >200 fusion genes in patient samples.

In the present study, MTCS-270 and MRTP-57 yielded an overall positive fusion gene detection rate of 50.0% (91/182) and 41.8% (76/182), respectively, indicating an advantage of MTCS-270 over MRTP-57 in overall detection sensitivity. Specifically, all the fusion genes detected by MRTP-57 were also identified by MTCS-270 across all the leukemia samples studied, clearly signifying the respectable detection accuracy and effectiveness of MTCS-270.

Notably, MTCS-270 identified more samples with disease-related fusion genes (including 7 additional fusion genes in AML, 6 in B-ALL, 1 in T-ALL and 1 in CML) than MRTP-57, reflecting the fact that MTCS-270 was designed to capture more fusion genes than MRTP-57 and thus had a much broader detection coverage. From the additional cases with fusion genes identified exclusively by MTCS-270, the AML sample with CBFA2T3/GLIS2 and the ALL sample with PAX5/WDR5 were selected as a case in point, to further verify the detection accuracy of MTCS-270. RT-quantitative PCR with the primers and probes (Table SII) designed according to the breakpoints identified in the MTCS-270 analysis were employed to conduct the verification study on the extracted RNA samples (Table SII). The ABL1 gene served as the internal control in this verification study. The results showed that quantification cycle values were 26 for CBFA2T3/GLIS2 (23 for ABL1) and 28 for PAX5/WDR5 (24 for ABL1) (Fig. 4), clearly confirming the presence of these two fusion genes in the patients screened.

Finally, MTCS-270 was capable of distinguishing isoforms of affected fusion genes, such as 2 isoforms of AML1/ETO, 3 of PML/RARA, 2 of CBFβ/MYH11 and 2 of MLL/AF9 in patients with AML, and 2 isoforms of ETV6/RUNX1, 2 of MLL/AF4, 2 of MLL/ENL and 2 of MEF2D/BCL9 in patients with B-ALL, and finally 2 isoforms of BCR/ABL1 in patients with CML. This was above the analyzing capability of MRTP-57 and further demonstrated the analytic precision of MTCS-270 in such examinations. Precise differentiation of isoforms of affected fusion genes could be clinically significant. For example, based on various breakpoint cluster regions within the PML locus, the PML/RARα fusion genes are termed long (L)-type, variant (V)-type and short (S)-type. Acute promyelocytic leukemia patients with S-type PML/RARA have a poorer prognosis compared with those with L-type PML/RARA (20).

The proposed DNA-based NGS method can be further improved by adding more targeted and clinically significant fusion genes to the detection panel, which would allow for an even broader detection coverage for leukemia. Although the present study highlighted the efficacy of MTCS-270 in detecting leukemia-related fusion genes, it should be considered as a complementary approach to RNA-based multiplex RT-PCR and other well-established molecular cytogenetic methods, as genomic DNA-based NGS has its technical limitations. For example, DNA-based NGS is unable to detect numerous complex chromosomal rearrangements due to a lack of recognizable fusion genes generated. In this event, karyotyping or FISH analysis is often needed to resolve the issue. In prospect, the transcriptional profile provided by RNA-Seq may soon supplant current multiplex RT-PCR methods for the up-front detection of various fusion genes in leukemia.

In summary, a genomic DNA-, instead of RNA-, based NGS method was utilized to simultaneously analyze >200 leukemia-related fusion genes. In comparison with the multiplex RT-PCR approach, the NGS method employed in the present study demonstrated an improved fusion gene detection efficacy in terms of technical sensitivity, accuracy, precision and overall comprehensiveness, which provides solid evidence that this genomic NGS method can be used as a potential detection tool, together with other well-established molecular cytogenetic methods, for leukemia management.

 Supplementary Material Supporting Data Acknowledgements

Not applicable.

 Availability of data and materials

The datasets generated and/or analyzed during the current study are available in figshare (https://doi.org/10.6084/m9.figshare.21391575.v1).

 Authors' contributions

ZC, RL, BL and XC contributed to the conception of the study. HP, CL, YS and JD performed the experiments. ZC, YL and JD contributed significantly to the data analysis and manuscript preparation. SF and BL helped perform the analysis with constructive discussions. RL and ZC confirm the authenticity of all the raw data. All authors read and approved the final version of the manuscript.

 Ethics approval and consent to participate

This research was approved by the Ethics Committee of the Children's Hospital of Capital Institute of Pediatrics (Beijing, China). All parents/guardians of the pediatric patients included in the study signed a written informed consent form.

 Patient consent for publication

Not applicable.

 Competing interests

The authors declare that they have no competing interests.

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Location of biotinylated oligoprobes relative to two representative fusion gene partners (BCR/ABL1 and PML/RARα).

Detection results for patients with acute myeloid leukemia. MTCS-270, multiply targeted capture sequencing method with a detection panel of 270 fusion genes; MRTP-57, RNA-based multiplex reverse transcription-PCR technique with a detection panel of 57 fusion genes.

Detection results for patients with ALL. MTCS-270, multiply targeted capture sequencing method with a detection panel of 270 fusion genes; MRTP-57, RNA-based multiplex reverse transcription-PCR technique with a detection panel of 57 fusion genes; T-ALL, T-cell acute lymphocytic leukemia; B-ALL, B-cell acute lymphocytic leukemia.

Verification study using reverse transcription-quantitative PCR to confirm the presence of two fusion genes (CBFA2T3/GLIS2 and PAX5/WDR5) in the respective patients. (A) The AML sample with CBFA2T3/GLIS2. (B) The ALL sample with PAX5/WDR5. Cq value, quantification cycle value; ΔRn, ∆ normalized reporter.

Fusion genes targeted by the MTCS-270 and MRTP-57 detection panels.

Technique Fusion gene
MTCS-270 ABL1/PRRC2B, ACIN1/NUTM1, ACTB/GLI1, AKAP9/BRAF, ALK/PTPN3, ALPHA/TFEB, AML1/CLCA2, AML1/ETO, AML1/ERG, AML1/LRP16AML1/MDS1, AML1/MTG16, AML1/PRDM16, AML1/PRDX4, AML1/ZFPM2, ANKRD11/SPG7, ARID1B/ZNF384, API2/MALT1, ATF7IP/JAK2, ATIC/ALK, BCOR/RARα, BCR/ABL1, BCR/EXOSC2, BCR/FGFR1, BCR/JAK2, BCR/PDGFRα, BMP2K/ZNF384, BMP6/MYC, BTL/ETV6, CALM/AF10, CARS/ALK, CBFA2T3/GLIS2, CBFβ/MYH11, CBP/MORF, CCDC6/ROS1, CCND1/MYC, CCND3/MYC, CEV14/PDGFRβ, CHD4/EP300, CIC/DUX4, CLTC/ALK, CLTC/TFE3, CREBBP/ZNF384, CSF2RA/CRLF2, DEK/CAN, DGKH/ZFAND3, DUX4/FRG2B, E2A/HLF, E2A/PBX1, E2A/TFPT, ELF1/FOXO1, EMILIN2/PAX5, EML1/ABL1, EML4/ALK, EP300/ZNF384, EPC1/PHF1, ERBB2IP/MAST4, ERG/DUX4, ETV6/ABL1, ETV6/CDX2, ETV6/FLT3, ETV6/MDS1, ETV6/MDS2, ETV6/NID1, ETV6/NTRK3, ETV6/PDGFRα, ETV6/PDGFRβ, ETV6/RUNX1, EWS/CREB1, EWS/ERG, EWS/ETV1, EWS/ETV4, EWS/FEV, EWS/FLI1, EWSR1/ELF5, EWSR1/ZNF384, FGFR1/RANBP2, FGFR2/CIT, FIP1L1/PDGFRα, FIP1L1/RARα, FN1/ALK, FOXK2/CLIP2, FOXO3/MYC, FOXP1/ABL1, FUS/ATF1, FUS/CHOP, FUS/CREB3L1, FUS/CREB3L2, HOXA11/MIR181A1HG, HOXA11AS/PBX1, IGH/BCL10, IGH/BCL2, IGH/BCL6, IGH/BCL9, IGH/CCND1, IGH/CRLF2, IGH/CEBPA, IGH/CEBPB, IGH/CEBPD, IGH/CEBPE, IGH/EPOR, IGH/MAFB, IGH/MALT1, IGH/MYC, IGK/MYC, IGL/MYC, IKZF1/CDK2, IKZF1/NUTM1, JAK2/SNX29, KIF5B/ALK, KIF5B/PDGFRα, KIF5B/RET, MEF2D/BCL9, MEF2D/CSF1R, MEF2D/DAZAP1, MEF2D/FOXJ2, MEF2D/HNRNPUL1, MEF2D/SS18, MLL/AF1P, MLL/AF1Q, MLL/AF4, MLL/AF6, MLL/AF9.MLL/AF10.MLL/AF17.MLL/AFX, MLL/ARHGEF12, MLL/CASC5, MLL/CBL, MLL/CREBBP, MLL/DIAPH2, MLL/ELL, MLL/ENL, MLL/FLNA, MLL/GAS7, MLL/KIAA0284, MLL/MEF2C, MLL-PTD, MLL/SEPT5, MLL/SEPT6, MLL/SEPT9, MLL/TET1, MLL/TIRAP, MLL/USP2, MOZ/CBP, MOZ/EP300, MOZ/TIF2, MSL2/TBL1XR1, MSN/ALK, MUM1/IRF4, MYH9/ALK, MYH9/IL2RB, MYO1F/KMT2A, MYST3/CREBBP, NCOR1/LYN, NDE1/PDGFRβ, NDUFA4/SCIN, NFIA/CBFA2T1, NFIA/CBFA2T3, NIN/PDGFRβ, NOC4L/FBRSL1, NONO/TFE3, NPM/ALK, NPM/MLF1, NPM/RARα, NT5C2/MLL, NUMA1/RARα, NUP214/ABL1, NUP98/ADD3, NUP98/BPTF, NUP98/CCDC28A, NUP98/DDX10, NUP98/FN1, NUP98/HOXA, NUP98/HOXA9, NUP98/HOXA10, NUP98/HOXA11, NUP98/HOXA13, NUP98/HOXC11, NUP98/HOXC13, NUP98/HOXD11, NUP98/HOXD13, NUP98/JARID1A, NUP98/LEDGF, NUP98/NSD1, NUP98/NSD3, NUP98/PHF23, NUP98/PMX1, NUP98/POU1F1, NUP98/PRRX2, NUP98/RAP1GDS1, NUP98/RARG, NUP98/SETBP1, NUP98/TOP1, P2RY8/CRLF2, P2RY8/PAX5, P2RY8/ZBED1, PAG1/ABL2, PALM/NCLN, PAX3/FKHR, PAX3/MLLT7, PAX3/NCOA1, PAX5/ASXL1, PAX5/WDR5, PAX5/AUTS2, PAX5/CBFA2T3, PAX5/ESRRB, PAX5/IGH, PAX5/JAK2, PAX5/KIF3B, PAX5/MLLT3, PAX5/RNF38, PAX5/TEL, PAX5/ZCCHC7, PAX5/ZNF521, PAX7/FKHR, PCM1/JAK2, PDE4DIP/PDGFRβ, PDZD7/ETV6, PICALM/BRAF, PIM3/BRD1, PIM3/METRNL, PIM3/SLC7A5, PLEKHA6/NTRK3, PLK5/ATN1, PLZF/RARα, PML/RARα, PPF1BP1/JAK2, PPFIBP1/ALK, PRC1/KIF7, PRCC/TFE3, PRDM16/RPN1, PRKAR1A/RARα, PRKG2/PDGFRβ, PRRC2B/BCR, RAEP1/PDGFRβ, RUNX1/EVX1, SET/CAN, SIL/TAL1, SSBP2/PDGFRβ, STAT5b/RARα, STRN/ALK, STRN3/JAK2, STRN/PDGFRα, SYNRG/ZNF384, TAF15/ZNF384, TCF3/ZNF384, TCRB/HOX11, TCRB/HOXA1, TCRB/LMO2, TCRB/TAL1, TCRB/TAL2, TCRD/HOX11, TCRD/LMO1, TCRD/LMO2, TCRD/RANBP17, TCRD/TAL1, TCTA/TAL1, TFG/ALK, TFG/CHN, TFG/NTRK1, TERF2/JAK2, TLS/ERG, TMPRSS2/ETV6, XBP1/MYC, ZEB2/PDGFRβ, ZEB2/RUNX1, ZMYND8/RELA, ZNF124/PUS3, ZNF384/RNF180
MRTP-57 AML1/ETO, AML1/ERG, AML1/MDS1, ARID1B/ZNF384, BCR/ABL1 (P190, P210, P230), BMP2K/ZNF384, CBFβ/MYH11, CREBBP/ZNF384, DEK/CAN, E2A/HLF, E2A/PBX1, EP300/ZNF384, ETV6/ABL1, ETV6/PDGFRα, ETV6/PDGFRβ, ETV6/RUNX1, EWSR1/ZNF384, FIP1L1/PDGFRα, FIP1L1/RARA, MEF2D/BCL9, MEF2D/CSF1R, MEF2D/DAZAP1, MEF2D/FOXJ2, MEF2D/HNRNPUL1, MEF2D/SS18, MLL/AF1P, MLL/AF1Q, MLL/AF4, MLL/AF6, MLL/AF9, MLL/AF10, MLL/AF17, MLL/AFX, MLL/ENL, MLL/ELL, MLL-PTD, NPM/ALK, NPM/MLF1, NPM/RARA, NUMA1/RARA, NUP98/HOXA9, NUP98/HOXA11, NUP98/HOXA13, NUP98/HOXC11, NUP98/HOXD13, NUP98/PMX1, NUP98/RARG, PLZF/RARA, PML/RARA(L,V,S), PRKARIA/RARA, SET/CAN, SIL/TAL1, STAT5B/RARA, SYNRG/ZNF384, TAF15/ZNF384, TCF3/ZNF384, TLS/ERG

MTCS-270, multiply targeted capture sequencing method with a detection panel of 270 fusion genes. MRTP-57, RNA-based multiplex reverse transcription-PCR technique with a detection panel of 57 fusion genes; L, (gene) long-type; S, (gene) short-type; V, (gene) variant-type.

Clinical information and detection results for patients with AML.

Clinical information MTCS-270 MRTP-57
Diagnosis AML AML
Age, years
  Median 6 6
  Range 0-13 0-13
Sex, n
  Male 25 25
  Female 21 21
Fusion gene, n (fusion breakpoint)
  AML1/ETO 1 (E1-5_E2-12)a 5
4 (E1-5_E3-12)
  PML/RARα 1 (E1-6_E3-9) L 4
2 (E1-3_E3-9) S
1 (E1-6+_E3-9) V
  NPM/RARα 1 (E1-4_E3-9) 1
  CBFβ/MYH11 1 (E1-4_E34-41) 2
1 (E1-5_E33-41)
  MLL/AF9 1 (E1-9_E6-11) 5
4 (E1-10_E6-11)
  MLL/AF10 1 (E1-9_E9-24) 1
  MLL/AF1Q 1 (E1-8_E2) 2
1 (E1-9_E2)
  MLL/ENL 1 (E1-8_E2-12) 1
  CBFA2T3/GLIS2 1 (E1-11_E5-8)
  NIFA/CBFA2T1 1 (E1-4_E3-12)
  MYO1F/KMT2A 1 (E1_E9-36)
  ZEB2/RUNX1 1 (E1-2_E2-8)
  NUP98/NSD1 1 (E1-12_E6-23)
  HOXA11AS/PBX1 1 (E1-4_E2-1)
  EWSR1/ELF5 1 (E1-8_E2-7)
Total patients with fusion genes, n 28 21
Total patients analyzed, n 46 46
Fusion gene detection frequency, % 60.9 45.7

(E1-5_E2-12) signifies a fusion of AML1 exons 1–5 to ETO exons 2–12. This nomenclature has been followed throughout the table. AML, acute myeloid leukemia; E, exon; L, (gene) long-type; MRTP-57, multiplex RT-PCR with a detection panel of 57 fusion genes; MTCS-270, multiply targeted capture sequencing method with a detection panel of 270 fusion genes; S, (gene) short-type; V, (gene) variant-type.

Clinical information and detection results for patients with ALL.

MTCS-270 MRTP-57
Clinical information Diagnosis
B-ALL T-ALL B-ALL T-ALL
Age, years
  Median 5 5 5 5
  Range 0-14 1-9 0-14 1-9
Sex, n
  Male 67 6 67 6
  Female 49 7 49 7
Fusion gene, n (fusion breakpoint)
  ETV6/RUNX1 19 (E1-5_E2-8)a 22
3 (E1-5_E3-8)
  BCR/ABL1 7 (E1_E2-11) 7
  E2A/PBX1 4 (E1-16_E3-9) 4
  MLL/AF4 2 (E1-8_E4-20) 3
1 (E1-10_E4-20)
  MLL/ENL 1 (E1-10_E1-12) 2
1 (E1-10_E7-12)
  TCF3/ZNF384 3 (E1-13_E3-11) 3
  TAF15/ZNF384 1 (E1-9_E3-11) 1
  EP300/ZNF384 2 (E1-6_E3-11) 2
  MEF2D/BCL9 3 (E1-3_E9-10) 4
1 (E1-6_E10)
  TLS/ERG 1 (E1-7_10) 1
  SIL/TAL1 1 (E1_E1-5) 1
  IGH/MYC 3 (IGHJ _E2-3)
  IGH/CRLF2 1 (IGHJ_E1-6)
  RUNX1/EVX1 1 (E1_E2-3)
  PAX5/WDR5 1 (E1-5_E2-14)
  HOXA11/MIR181A1HG 1 (E2-1_E3)
Total patients with fusion gene, n 55 2 49 1
Total patients analyzed, n 116 13 116 13
Fusion gene detection frequency, % 47.4 15.4 42.2 7.7

(E1-5_E2-8) signifies a fusion of ETV6 exons 1–5 to RUNX1 exons 2–8. This nomenclature has been followed throughout the table. ALL, acute lymphocytic leukemia; B-ALL, B-cell ALL; E, exon; MRTP-57, multiplex RT-PCR with a detection panel of 57 fusion genes; MTCS-270, multiply targeted capture sequencing method with a detection panel of 270 fusion genes; T-ALL, T-cell ALL.

Clinical information and detection results for the patients with CML and JMML.

MTCS-270 MRTP-57
Clinical information Diagnosis
CML JMML CML JMML
Age, years
  Median 8 N/A 8 N/A
  Range 5-10 0-3 5-10 0-3
Sex, n
  Male 3 1 3 1
  Female 2 1 2 1
Fusion gene, n (fusion breakpoint)
  BCR/ABL1 1 (E13-22_E2-11) 4
3 (E14-22_E2-11)
  BCR/EXOSC2 1 (E1_E9)a
  MLL/ELL 1 (E1-9_E2-12) 1
Total patients with fusion genes, n 5 1 4 1
Total patients analyzed, n 5 2 5 2

(E1_E9) signifies a fusion of BCR exon 1 to EXOSC2 to exon 9. This nomenclature also applies to MLL/ELL (E1-9_E2-12). CML, chronic myelocytic leukemia; E, exon; JMML, juvenile myelomonocytic leukemia; MRTP-57, multiplex RT-PCR with a detection panel of 57 fusion genes; MTCS-270, multiply targeted capture sequencing method with a detection panel of 270 fusion genes.