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Molecular and clinical significance of FLT3, NPM1, DNMT3A and TP53 mutations in acute myeloid leukemia patients. | LitMetric

Molecular and clinical significance of FLT3, NPM1, DNMT3A and TP53 mutations in acute myeloid leukemia patients.

Mol Biol Rep

Department of Biology, College of Science, University of Sulaimani, Sulaymaniyah, Iraq.

Published: October 2023

Background: Acute myeloid leukemia (AML) is a type of blood cancer that affects the bone marrow and blood cells. AML is characterized by the rapid growth and accumulation of abnormal white blood cells, known as myeloblasts, which interfere with the production of normal blood cells.

Aims: The main aim was to determine the relationship between these genetic alterations and the clinico-haematological parameters and prognostic factors with therapy for Iraqi patients with AML.

Methods: We used Sanger Sequencing to detect the mutations in 76 AML patients. Clinical data of AML patients were retrospectively analysed to compare the prognosis of each gene mutation group.

Results: Somatic mutations were identified in 47.4% of the enrolled patients in a core set of pathogenic genes, including FLT3 (18 patients, 23.7%), DNMT3A (14, 18.4%), NPM1 (11, 14.5%) and TP53 (5, 6.8%). As multiple mutations frequently coexisted in the same patient, we classified patients into 10 further groups. Two novel mutations were detected in FLT3-ITD, with new accession numbers deposited into NCBI GenBank (OP807465 and OP807466). These two novel mutations were computationally analysed and predicted as disease-causing mutations. We found significant differences between patients with and without the detected mutations in disease progression after induction therapy (remission, failure and death; pv = < 0.001) and statistically significant differences were reported in total leukocyte count (pv = < 0.0001).

Conclusion: These genes are among the most frequently mutated genes in AML patients. Understanding the molecular and clinical significance of these mutations is important for guiding treatment decisions and predicting patient outcomes.

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Source
http://dx.doi.org/10.1007/s11033-023-08680-2DOI Listing

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