Cytogenetically Normal Acute Myeloid Leukaemia at a Single Centre in South Africa

Abstract

Background and objectives: The heterogeneous molecular landscape of cytogenetically normal acute myeloid leukemia (CN-AML) renders it an ongoing therapeutic challenge. The European LeukemiaNet (ELN) 2017 guidelines attempted to address this by guiding post-remission therapy according to six prognostically informative mutations. However, its applicability in a South African setting remains unclear due to limited local data. This retrospective study aimed to describe a South African CN-AML cohort according to clinicopathological and molecular features as well as treatment outcomes and, consequently, to investigate the local applicability of a triple-mutation testing approach for risk stratification in accordance with the ELN 2017 guidelines, using nucleophosmin 1 (NPM1), fms-related receptor tyrosine kinase 3 internal tandem duplication (FLT3-ITD), and CCAAT enhancer-binding protein alpha (CEBPA) mutation status. Materials and methods: A review of cytogenetic results for adult de novo AML cases diagnosed at Groote Schuur Hospital between 2005 and 2018 was performed. CN-AML cases were further characterized via a review of clinical and laboratory data and additional molecular testing on stored DNA samples to allow for mutation-based risk stratification and outcome analysis. Results: In total, 218 patients with AML were identified, of which 33% were cytogenetically normal. NPM1, FLT3-ITD, and CEBPA mutations were found in 39%, 34%, and 9% of CN-AML cases, respectively. Retrospective risk stratification according to mutations in these three genes accurately identified both patients at a high risk of induction-resistant disease and those who required an allogeneic stem cell transplant in their first complete remission. Conclusion: Local rates of CN-AML and associated NPM1 and FLT3-ITD mutations were comparable to those of European cohorts. Limited mutation analysis in the form of triple-mutation testing proved to be an economical and therapeutically informative prognostication approach for CN-AML in a resource-limited setting.