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1556 RNA Fusions and Their Association with DNA Alterations in Myeloid Neoplasia Patients Identified By a Single Tube Multimodal Comprehensive Genomic Profiling Test

Program: Oral and Poster Abstracts
Session: 617. Acute Myeloid Leukemias: Biomarkers, Molecular Markers and Minimal Residual Disease in Diagnosis and Prognosis: Poster I
Hematology Disease Topics & Pathways:
Research, epidemiology, Clinical Research, real-world evidence, Technology and Procedures, profiling, molecular testing, omics technologies
Saturday, December 9, 2023, 5:30 PM-7:30 PM

Michal Krawczyk1*, Lina Zelinger, PhD2*, Cynthie Wong, PhD2*, Hyunjun Nam, PhD.3*, Brad Thomas, PhD.4*, Nathan D Montgomery, MD, PhD2, Derek D Lyle, MD2* and Fernando Lopez-Diaz, PhD3*

1Neogenomics inc, Aliso Viejo, CA
2NeoGenomics, Fort Myers, FL
3Neogenomics inc, San Diego, CA
4Neogenomics inc., Houston, TX

Background: Recent updates into NCCN professional guidelines have included adding several genomic biomarkers for myeloid disorders. Detecting SNVs, indels, select CNVs and genomic rearrangements in a single comprehensive genomic profiling test is invaluable for clinical care. Moreover, WHO recognizes 23 genomic rearrangements or fusions which define subclasses of AML, MDS/MPN and related neoplasms, and their detection is essential for patient management. Here we present joint prevalence data of gene fusions and other genomic alterations in myeloid disorders in a cohort of 312 patients analyzed by a CLIA grade single-tube NGS assay capable of concurrent analysis of DNA and RNA alterations.

Methods: Total nucleic acid (TNA) from bone marrow or peripheral blood was analyzed by a CLIA grade custom amplicon-based multimodal NGS test reporting DNA mutations in 126 genes and gains/losses in 17 genes by DNA-seq, and RNA fusions from 40 genes by RNA-seq. Libraries were sequenced on a NovaSeq6000 instrument, and fusions were called with in-house developed BI pipeline using the distribution of AI-assisted fusion confidence scores to improve the signal to noise discrimination for fusion calls before validation. Deidentified patient data was used according to an IRB approved protocol.

Results: Analytical validation of RNA fusion calling against FISH and Sanger-seq in 74 hematologic disorder samples demonstrated 96.7% sensitivity and 98.2% specificity with 100% reproducibility. This improved fusion detection module was added to our CLIA validated NGS assay, which at tumor purity of >20%, already detects SNVs (VAF >3%), Indels (<81 bp, VAF >3%) and copy number gains/losses with a sensitivity of 98.3%, 98.9 % and 96 % for SNV, Indels and copy number gains/losses, respectively and a specificity of >99.9% for SNV/Indels and 98.4% for gene gains/losses. Next, data from a total of 789 patients serially tested with this assay was used to study the distribution of myeloid fusion events in community cases which included 312 adult patients with confirmed/suspected myeloid disorders including AML, CML, MDS/MPN and other disorders while 477 patients had a diagnosis of lymphoid leukemias. Fifty five (55) % of the Myeloid leukemia patients were male and 45% female, with a median age of 67.5 (22-87) and 71 (22-89) years, respectively. 27% (84/312) of them presented a gene fusion, of which in 21% of cases it involved a gene from WHO/NCCN fusion gene recommendations. Prevalence for common fusions were 6.7% for BCR::ABL1; 5.1% for PML::RARA; 2.6% (8/312) for KMT2A; 1.9% for RUNX1::RUNX1T1; 1.6% CBFB::MYH11; 1.3% for PICALM::MLLT10 and 1 % for NUP98. Other fusions were detected in <1% patients. Fusions of PDGFRA, ETV6, ZNF384, FGFR1 and other genes were also observed. BCR::ABL1 fusions were seen not only in CML patients but also in a patient with AML. For KMT2A, 25% (2/8) of fusions detected by NGS in all patients were confirmed by Sanger-seq but missed by FISH, which correlates with higher sensitivity of the NGS assay. Interestingly, the prevalence of fusion positive cases on the lymphoid leukemia patients (17%, 80/477) tested on the same period of time. Novel fusions were called in ~8% of all patients with high confidence. We validated by Sanger sequencing the CCND2::MGP fusion, which was identified on a patient with AML. This fusion protein is predicted to be oncogenic as it lacks the region from CCND2 including Thr280, a residue required for ccnd2 degradation. Finally, we analyzed the relationship between fusions and recurrently mutated genes. We found that DNA alterations in CALR, EZH2, FLT3, KIT, and ZRSR2 were enriched in fusion positive cases. Conversely alterations on a subset of genes were absent on fusion positive cases and enriched on fusion negative cases. Those included alterations on CEBPA, IDH1/2, KMT2A, MPL, NPM1, BCOR, IKZF1, FBXW7 STAG2, CSF3R, PDGFRA, PHF6, PTPN11.

Conclusions: A robust low-noise RNA fusion detection assay coupled us DNA alterations on myeloid disorders in a single assay enables to fully molecularly characterize acute myeloid leukemias and other myeloid disorders. Frequencies of well-known fusions in a small community-based cohort were similar to studies performed in academic settings with subsets of gene alterations being mutually exclusive from fusions. Larger studies are needed to confirm those associations.

Disclosures: Krawczyk: NeoGenomics inc: Current Employment. Zelinger: NeoGenomics: Current Employment. Wong: NeoGenomics: Current Employment. Nam: NeoGenomics inc: Current Employment. Thomas: NeoGenomics inc: Current Employment. Montgomery: NeoGenomics: Current Employment. Lyle: NeoGenomics: Current Employment, Current equity holder in publicly-traded company. Lopez-Diaz: NeoGenomics inc: Current Employment, Current equity holder in publicly-traded company.

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