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Document Type |
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Thesis |
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Document Title |
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Application of Customized Myeloid Next Generation Sequencing Panel in the Diagnosis of Myeloid Malignancies جدوى استخدام منصة التسلسل عالية الإنتاجية (NGS) لتشخيص امراض الدم النخاعي |
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Subject |
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Faculty of Applied Medical Sciences |
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Document Language |
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Arabic |
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Abstract |
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Background:
Genetic mutations are the major diagnostic factors in the diagnosis and prognosis of leukemias and it becomes difficult to assess these variants by using single gene analysis. Therefore, this study aims to develop fast and cost-effective method for the genetic screening of myeloid malignances by using customized next generation sequencing (NGS) panel.
Method:
Customized myeloid panel was designed and investigated on 15 acute myeloid leukemia patients. The panel includes 11 genes which are the most common mutated genes in myeloid malignancies. This panel was designed to sequence the full genomic sequence of the following genes: CALR, IDH1, IDH2, JAK2, FLT3, NPM1, MPL, TET2, SF3B1, TP53, and MLL.
Results:
Among 15 patients, fourteen real pathogenic variants were identified in nine samples and negative results were found in six samples. The positive findings were found on JAK2, FLT-3, SF3B1 and TET2 genes. Interestingly, non- classical FLT3 mutations (c.1715A>C, c.2513delG and c.2507dupT) were detected in patients that where negative for FLT3-ITD and TKD by routine molecular results. All identified variants are pathogenic and the high coverage of the assay allowed us to predict variant at low frequency (1%) with 1000x coverage.
Conclusion:
Utilizing the custom panel allowed us to identify variants that are either not detected by routine test or variant not routinely requested. Sequencing the whole genes allowed us to discover new potential pathogenic variants that might be common in our population and it is importance in disease diagnosis. This study strength on utilizing the NGS in routine diagnosis for providing optimal healthcare toward personalized medicine. |
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Supervisor |
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Dr. Heba A AL-Khatabi |
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Thesis Type |
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Master Thesis |
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Publishing Year |
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1443 AH
2022 AD |
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Added Date |
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Wednesday, January 25, 2023 |
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Researchers
| وجدان علي القحطاني | Al-Qahtani, Wejdan Ali | Researcher | Master | |
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