Background Acute myeloid leukemia (AML) is a heterogeneous stem cell malignancy marked by considerable genetic and clinical variability. Accurate risk stratification through molecular profiling is essential for tailoring treatment approaches and improving patient outcomes. In the Middle East and North Africa (MENA) region, AML often presents at a younger age compared to Western populations, suggesting possible regional or ethnic variations in disease biology.

Qatar, with its small geographic area, predominantly young population, and government-funded universal healthcare system, offers a unique setting for population-based hematologic studies. These factors facilitate comprehensive data capture and equitable access to diagnostic and therapeutic services. This study aims to characterize the genetic landscape of the Qatar AML cohort (AML-QC) based on the European LeukemiaNet (ELN) 2022 risk classification and to evaluate its association with clinical outcomes in patients treated with intensive chemotherapy.

Methods We retrospectively analyzed patients diagnosed with AML at the National Center for Cancer Care and Research (NCCCR) between January 2015 and January 2024. Demographic, laboratory, treatment, and outcome data were collected for patients who received intensive chemotherapy, defined as 3+7 or FLAG-IDA. Cytogenetic data, including conventional karyotyping and FISH, and molecular data from NGS (available from 2020 onward) were included into the analysis.

Results A total of 193 patients who received intensive therapy during the study period were included. The median age was 41 years (range 31–49), with 118 patients (61.1%) under the age of 45. The majority were male (145 patients, 75%). AML was broadly classified into two major categories: AML with defining genetic abnormalities, which accounted for 83% of the cohort, and the remaining cases were AML with differentiation. Among patients in the “defining genetic abnormalities” group, the most frequent subtypes were AML with NPM1 mutation (21%), AML with RUNX1::RUNX1T1 fusion (15%), AML with CBFB::MYH11 fusion (11%), AML with KMT2A rearrangement (9%), AML with DEK::NUP214 fusion (3%), AML with CEBPA mutation (2%), AML with MECOM rearrangement (1%), and AML with BCR::ABL1 fusion (1%). Additionally, 20% of the overall cohort was classified as AML, myelodysplasia-related.

Genetic mutations were detected in 65% of the patients, with the following distribution: FLT3 (25%), NPM1 (21%),C-KIT (12%), NRAS (9%), DNMT3A (7%), TP53 (6%), IDH2 (5%), IDH1 (4%), KRAS (4%), PTPN11 (2%), SF3B1 (2%), GATA2 (2%), RUNX1 (2%), CEBPA (2%), CBL (2%), CSF3R (2%), SRSF2 (1%), U2AF1 (1%), NF1 (1%), and ASXL1 (1%). Based on ELN 2022 risk stratification, 38% of patients were classified as favorable risk, 34% as high risk, and 28% as intermediate risk.

Conclusion Our cohort is enriched by a higher number of AML cases with defining recurrent genetic abnormalities, with an approximately equal distribution across high and favorable risk categories, and a younger age at diagnosis—highlighting the potential role of germline predisposition syndromes that warrant further evaluation.

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2025
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