Want to download this as a PDF? Download now
The SureSeq™ Myeloid Fusion Panel, crafted in collaboration with leading experts in myeloid cancer research to align seamlessly with the latest clinical guidelines, was used in this study. Harnessing RNA-based partner gene agnostic technology, our panel allows for simultaneous interrogation of multiple baited target fusions enhancing sample classification, including identification of novel and rare fusions.
Acute myeloid leukaemia (AML) and acute lymphoblastic leukaemia (ALL) are both heterogeneous groups of haematological malignancies characterised by both phenotypic and genetic diversity, for which fusion genes are particularly prevalent1. For example in AML, well-documented fusion events include RUNX1::RUNX1T1, CBFB::MYH11 and PML::RARA, as well as rearrangements involving KMT2A and NUP982. An estimated 30% of AML patients carry a fusion gene(s)3, highlighting the significance of fusion gene research into disease classification, prognosis and treatment approaches4. Additionally, structural rearrangements of chromosome 3 at the MECOM locus [inv(3)(q21q26.2)/t(3;3)(q21;q26.2)] cause MECOM overexpression and are observed in 1–2.5% of AML patients2.
Traditionally, techniques such as fluorescence in situ hybridisation (FISH) and reverse transcription polymerase chain reaction (RT-PCR) have been employed for fusion gene detection5,6. However, with the advent of next-generation sequencing (NGS), there has been a paradigm shift in fusion gene identification and characterisation.
NGS-based fusion gene panels offer the advantage of simultaneous detection of multiple fusion genes in a single assay, including multiple partners for the same genes3. Additionally, interrogation of gene fusions can facilitate the discovery of novel fusion partners, thereby enhancing the depth and breadth of sample characterisation compared to conventional methods.
In this study, conducted at OGT’s state-of-the-art NGS research facility in Oxford, the SureSeq Myeloid Fusion Panel was used to corroborate previously characterised fusion-positive and fusion-negative samples, and typify fusions, if present, in a cohort of research biobank samples from Birmingham Women’s and Children’s NHS Foundation Trust.
50 RNA samples extracted from whole blood or bone marrow were obtained from Birmingham Women’s and Children’s NHS Foundation Trust*. This 50-sample cohort included 35 samples that were initially characterised as fusion-positive by either FISH, qPCR or G-band and 15 fusion-negative controls. Fusion-negative controls comprised of 2 samples containing fusions not targeted by the SureSeq Myeloid Fusion Panel (untargeted fusions) and 13 AML/ALL samples that were previously characterised as fusion-negative using FISH. Commercially obtained control RNAs included the Human Lymphocyte RNA cell line (AMSBio, UK) as a fusion-negative control and the Universal Human Reference RNA (Agilent, UK) as a fusion-positive control. All samples and controls were assessed using RNA TapeStation Analysis (Agilent, UK) to confirm that RNA was intact. 100–500 ng RNA was used for cDNA synthesis and subsequent OGT Universal NGS Workflow.
*3 initial samples were excluded from analysis following insufficient RNA extraction for further analysis.
The SureSeq Universal NGS Workflow Solution was used throughout this study, with the addition of a cDNA synthesis step (Figure 1).
Figure 1. Workflow of cDNA synthesis and sample library preparation
The approach offers a streamlined NGS library preparation protocol with Unique Molecular Identifiers (UMIs) and Unique Dual Indexes (UDIs), followed by hybridisation-based target enrichment. For this research study, we used the 61 kb SureSeq Myeloid Fusion Panel comprising 18 target genes (predominantly drivers) allowing for the agnostic detection of baited gene fusions. Furthermore, 3 housekeeping genes used in the panel are used to allow relative expression detection in MECOM. Sequencing was conducted using the MiSeq® V2 300 (Illumina, UK).
Sequencing data analysis was performed using OGT’s proprietary Interpret NGS Analysis Software. This software was used to easily visualise fusion genes detected, focus in on breakpoints, the number of reads spanning each breakpoint and alignment of sequence reads at nucleotide resolution. Additionally, the software was used to report normalised gene expression levels related to MECOM rearrangements.
With 100% of the samples displaying cDNA synthesis efficiency above the acceptance threshold and >99% uniquely mapped reads (Figure 2), all samples passed quality control and were further analysed for fusion presence.
Figure 2. Quality metrics for processed samples. Note, due to a sample processing error, higher than expected levels of DNA (>500 ng) were pooled for some samples prior to sequencing leading to reduced UMR (%), consequently a pass rate of 100% is not observed in Figure 2B.
Table 1 lists the fusion content of the 50-sample cohort (35 fusion-positive samples and 15 fusion-negative controls) tested in this study. The study examined 5 commonly occurring fusions in either AML or ALL using 30 samples: ETV6::RUNX1; RUNX1::RUNX1T1; BCR::ABL1; PML::RARA and CBFB::MYH11. We also successfully detected MECOM inv(3);t(3;3) events that result in MECOM overexpression. Furthermore, we tested the partner-agnostic fusion detection capability of SureSeq Myeloid Fusion workflow using 4 samples containing 3 of the most-common KMT2A rearrangements in AML: KMT2A::MLLT3, KMT2A::MLLT10 and KMT2A::AFF1. 15 negative controls (2 untargeted fusions and 13 fusion-negative samples) were also assessed to confirm assay specificity. We observed 100% concordant detection in all 50 samples, which had previously been characterised by either FISH, qPCR or G-band testing. Furthermore, OGT’s SureSeq Interpret software allowed detection of reciprocal fusions for ETV6::RUNX1, PML::RARA and BCR::ABL1 that are known to occur frequently in AML or ALL patients which are not typically tested for by FISH or qPCR.
Table 1. Concordance of SureSeq Myeloid Fusion with orthogonal methods.*With FISH/qPCR/G-band orthogonal testing
MECOM rearrangements involving inv(3)/t(3;3), which are included in the WHO classification for AML, are rare recurrent cytogenetic abnormalities found in a subset of AML cases and are associated with poor prognosis. The inv(3)/t(3;3) MECOM rearrangements are unique as they do not form fusion genes, rather they ‘hijack’ the GATA2 enhancer resulting in MECOM overexpression. Our assay successfully detected a MECOM inv(3)/t(3;3) rearrangement in our sample cohort (Table 1) for which overexpression was characterised relative to housekeeping genes while negative controls showed no MECOM expression above our detection threshold (Figure 3).
Figure 3. Confident detection of MECOM Expression with SureSeq.
Figure 3 shows the consistent and confident detection of MECOM overexpression in research and commercial samples (including positive and negative controls). MECOM expression is normalised to the expression of housekeeping genes and expression values are calculated as counts per million (CPM). ‘Research (+)’ refers to the research sample containing GATA2::MECOM (inv(3)/t(3;3)) noted in Table 1 (n=1). ‘Commercial (+)’ refers to Universal Human Reference RNA (UHRR) used as positive control (n=1). ‘Research (-)’ refers to blood extracted RNA with no GATA2::MECOM (inv(3)/t(3;3)) (n=3). ‘Commercial (-)’ refers to normal human lymphocyte RNA used as negative control (n=1). Error bars represent standard deviation.
The SureSeq Myeloid Fusion Panel facilitates partner-agnostic fusion detection as shown by multiple KMT2A rearrangements tested in this study (Figure 3). We tested 3 of the most recurrent KMT2A rearrangements in AML: KMT2A::MLLT3; KMT2A::AFF1; KMT2A::MLLT10 and successfully detected all three fusions. While the KMT2A breakpoint was located consistently in exon 8 or 9; the breakpoints in partner genes are more variable (Figure 4). Our assay identified exact location of breakpoints which is especially important for establishing target(s) for monitoring of measurable residual disease (MRD), identifying changes in gene expression and altered splicing and/or polyadenylated events.7,8
Figure 4 highlights the partner-agnostic fusion detection capability of the SureSeq Myeloid Fusion Panel with breakpoints identified in 3 KMT2A rearrangements: KMT2A::MLLT3; KMT2A::AFF1; KMT2A::MLLT10.
Figure 4. Partner-agnostic fusion detection for multiple breakpoints
Our ability to detect multiple breakpoints and multiple fusions in a single run further highlights the benefits of the SureSeq Myeloid Fusion Panel over FISH or single-gene assays like qPCR, allowing users to combine multiple tests into a single assay.
Traditionally, detection of fusion events in research sample cohorts has been challenged by the need for individual testing of samples as well as the need to focus on a select group of fusions for efficiency.
Our research shows that the SureSeq Myeloid Fusion Panel is highly accurate, detecting all known fusion events in positive samples and no detection in negative samples. Our results highlight the confidence researchers can attain in our panel when replacing their existing FISH, qPCR and/or G-band with the SureSeq Myeloid Fusion Panel, and thereby negating the need for individual testing of samples by enabling the simultaneous detection of multiple fusion genes within a single assay. Additionally, the ability to simultaneously detect MECOM overexpression serves to further streamline user’s workflows by easily folding this detection into the existing workflow.
Ready to experience the benefits of the SureSeq Myeloid Fusion Panel? Talk to one of our NGS experts today
SureSeq™: For research use only; not for use in diagnostic procedures.
Call +44 (0)1865 856800 Email contact@ogt.com
Send us a message and we will get back to you
Visit USA site
Visit Canada site