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Introduction: Genetic information is highly relevant to the classification and risk assessment of myeloid neoplasms, especially myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML). Next generation sequencing (NGS) is increasingly used to track mutations and monitor measurable residual disease, but with the increased data comes a need to distinguish driver mutations from potentially unrelated variants caused by age-related clonal hematopoiesis (ARCH) or clonal hematopoiesis of indeterminant potential (CHIP). Herein, we evaluate a combined flow cytometry and NGS approach to identify oncogenic driver mutations within specific cell populations and increase variant accessibility by NGS. Methods: Proof of cell enrichment methodology was performed with a cell line expressing CD34 (hallmark of myeloid blasts). The cell line was spiked into healthy donor PBMCs at defined levels to create samples with varied tumor percentage. Purchased AML patient samples were also analyzed. CD34 expression of samples was confirmed by flow cytometry prior to- and following enrichment by anti-CD34 magnetic cell sorting technology. Sequencing libraries were prepared using the Archer VariantPlex Core Myeloid kit and sequenced on Illumina MiSeqs. Mutations were characterized using Archer software. The association between NGS and flow cytometry data was assessed through mapping the VAF data to the tumor population determined by flow cytometry. Results: Identified mutations in tested samples included known oncogenic mutations as well as mutations associated with ARCH/CHIP events. In a subset of samples, at least one mutation was identified at a VAF correlating to the tumor percentage determined by flow cytometry analysis; these mutations were enriched in the CD34+ cell fraction following magnetic cell sorting. Sequencing the enriched tumor fraction increased the VAF of these mutations, and simultaneously revealed additional tumor-associated mutations that were previously below the detection limit of the assay. Conversely, potential ARCH/CHIP mutations were present in both CD34+ and CD34- cell populations. Conclusion: Using a combination of flow cytometry, magnetic cell sorting, and NGS, variants specific to the tumor fraction of samples were identified. For patient specimens, the presence of ARCH/CHIP mutations in both enriched and residual cell populations indicate these variants evolved prior to the emergence of true leukemic progenitor cells; the identification of the flow-matched mutations only in the enriched population indicates the key role of these changes in the disease progression. Together, flow cytometry and cell-enriched NGS have the potential to enhance detection of disease-driving mutations earlier, thus, could be used as novel approaches to identify and treat myeloid neoplasms early with existing therapies and/or support development of new investigational agents. Citation Format: Sarah Johnson, Keegan Vaughan, Alexis Kurmis, Zeni Alfonso, Nathan Riccitelli. Assessing clonal evolution of myeloid neoplasms by flow cytometry guided, cell-enriched next generation sequencing. [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 3922.