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Heba A Alkhatabi,1,2 Wejdan Alqahtani,3 Reem Alsolami,1,2 Aisha Elaimi,1,4 Mohannad S Hazzazi,1,2 Majed N Almashjary,1,2 Hind A Alkhatabi,5 Mohammad E Alghuthami,6 Yara M Daous,2,7 Elrashed B Yasin,8 Ahmed Barefah2,9 1Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, 22254, Saudi Arabia; 2Hematology Research Unit (HRU), King Fahad Medical Research Center, King Abdulaziz University, Jeddah, 22254, Saudi Arabia; 3Department of Medical Laboratory, King Abdulaziz University Hospital, Jeddah, Saudi Arabia; 4Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah, 22254, Saudi Arabia; 5Department of Biochemistry, College of Science, University of Jeddah, Jeddah, 21589, Saudi Arabia; 6GCC Accreditation Center GAC, Jeddah, Saudi Arabia; 7Department of Pathology, Faculty of Medicine, King Abdulaziz University, Jeddah, 22254, Saudi Arabia; 8Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, King Abdulaziz University, Rabigh, 25732, Saudi Arabia; 9Hematology Department, Faculty of Medicine, King Abdulaziz University, Jeddah, 21589, Saudi ArabiaCorrespondence: Elrashed B Yasin, Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, King Abdulaziz University, Rabigh, 25732, Saudi Arabia, Tel +966 5 60910199, Email eyasin@kau.edu.saPurpose: Genetic mutations are major factors in the diagnosis and prognosis of leukemia, and it is difficult to assess these variants using single-gene analysis. Therefore, this study aimed to develop a fast and cost-effective method for genetic screening of myeloid malignancies using a customized next-generation sequencing (NGS) panel.Patients and Methods: A customized myeloid panel was designed and investigated in 15 acute myeloid leukemia patients. The panel included 11 genes that were most commonly mutated in myeloid malignancies. This panel was designed to sequence the complete genome of CALR, IDH1, IDH2, JAK2, FLT3, NPM1, MPL, TET2, SF3B1, TP53, and MLL.Results: Among the 15 patients, 14 actual pathogenic variants were identified in nine samples, and negative results were found in six samples. Positive findings were observed for JAK2, FLT3, SF3B1, and TET2. Interestingly, non-classical FLT3 mutations (c.1715A>C, c.2513delG, and c.2507dupT) were detected in patients who were negative for FLT3-ITD and TKD by routine molecular results. All identified variants were pathogenic, and the high coverage of the assay allowed us to predict variants at a low frequency (1%) with 1000x coverage.Conclusion: Utilizing a custom panel allowed us to identify variants that were not detected by routine tests or those that were not routinely investigated. Using the costuming panel will enable us to sequence all genes and discover new potential pathogenic variants that are not possible with other commercially available panels that focus only on hotspot regions. This study’s strength in utilizing NGS and implanting a customized panel to identify new pathogenic variants that might be common in our population and important in routine diagnosis for providing optimal healthcare for personalized medicine.Keywords: myeloid malignancies, myeloid leukemia, FLT3, NGS, genomic sequence