Abstract Background: 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. Discerning true fusions from artificial calls in RNAseq-based tests is challenging due to biological and technical noise. We previously developed a method to identify fusion transcripts by a single-tube NGS assay capable of concurrent analysis of DNA and RNA alterations in ALL patients. We expanded the assay with an improved fusion calling algorithm and used it to study the landscape of myeloid RNA fusions in the clinical setting. Methods: Total nucleic acid (TNA) from bone marrow or peripheral blood was analyzed in our clinical laboratory by a CLIA grade custom amplicon-based multimodal NGS assay, targeting 302 genes by DNA-seq and 185 genes by RNA-seq. Libraries were sequenced on a NovaSeq6000 instrument, and fusions were called from RNA: de-duplicated and error-corrected UMI reads were processed by an in-house developed BI pipeline leveraging machine learning, to assign a final confidence score (F1). Deidentified patient data was used according to an approved IRB. Results: Distribution of F1 scores was used to improve the discrimination between technical noise and real fusion calls. Analytical validation of RNA fusion calling against FISH and Sanger-seq in 74 hematologic disorder samples demonstrated 98.2% specificity and 97.0% sensitivity. Data from 789 patients was used to study the distribution of myeloid fusion events in community cases. 17% of patients had fusions involving genes from WHO/NCCN recommendations. Frequencies for most common fusions were 2.3% (18/789) for KMT2A, 2% for PML::RARA, 1.9% for BCR::ABL1, 0.8% for RUNX1::RUNX1T1 and CBFB::MYH11 and 0.6% for NUP98. Fusions of PDGFRA, ETV6, ZNF384, FGFR1 and other genes were also observed and BCR::ABL1 fusions were seen not only in CML patients but also in a patient with AML. For KMT2A, 25% (2/8) fusions detected by NGS were confirmed by Sanger-seq but missed by FISH, which correlates with higher sensitivity of the NGS assay. Novel fusions were called in ~8% of patients. This included an AML patient with a CCND2::MGP fusion, resulting in cyclin D2 (CCND2), frequently activated by DNA mutations in AML, fused to matrix Gla protein, a highly expressed gene in hematopoietic progenitor cells. The fusion was confirmed by Sanger-seq, and shown to lack ex5 of CCND2, which contains Thr280, a residue required for ccnd2 degradation. This fusion is thus predicted to generate high cellular levels of oncogenic ccnd2-mgp. Conclusions: Frequencies of well-known fusions in real world data obtained by a robust low-noise RNA fusion assay were similar to other studies done in academic setting. Reliable detection of bona-fide RNA fusions with this clinical test is invaluable for patient care and novel fusion identification. Citation Format: Michal Krawczyk, Chaugiang Duong, Lina Zelinger, Fei Ye, Hyunjun Nam, Brad Thomas, Vincent Funari, Shashikant Kulkarni, Fernando Lopez-Diaz. Landscape of known and novel myeloid neoplasia fusions identified by a multimodal comprehensive genomic profiling test in 789 patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1401.