Rapid gene fusion testing using the NanoString nCounter platform to improve pediatric leukemia diagnoses in Sub-Saharan Africa - Gastier-Foster, Julie M.; Lutwama, Fredrick; Mbabazi, Olive; Mlenga, Steven; Ulaya, Kennedy; Namazzi, Ruth; Hollingsworth, E. Faith; Lopez-Terrada, Dolores; Fisher, Kevin E.; Roy, Angshumoy; Allen, Carl E.; Poplack, David G.; et al. (Frontiers in Oncology, 2024)
Risk stratification and molecular targeting have been key to increasing cure rates for pediatric cancers in high-income countries. In contrast, precise diagnosis in low-resource settings is hindered by insufficient pathology infrastructure. The Global HOPE program aims to improve outcomes for pediatric cancer in Sub-Saharan Africa (SSA) by building local clinical and diagnostic capacity. This study aimed to assess the feasibility of implementing molecular assays to improve leukemia diagnoses in SSA. Custom NanoString nCounter gene fusion assays, previously validated in the US, were used to test samples from suspected leukemia patients. The NanoString platform was chosen due to relatively low cost, minimal technical and bioinformatics expertise required, ability to test suboptimal RNA, and rapid turnaround time. Fusion results were analyzed blindly, then compared to morphology and flow cytometry results. Of 117 leukemia samples, 74 were fusion-positive, 30 were negative, 7 were not interpretable, and 6 failed RNA quality. Nine additional samples were negative for leukemia by flow cytometry and negative for gene fusions. All 74 gene fusions aligned with the immunophenotype determined by flow cytometry. Fourteen samples had additional information available to further confirm the accuracy of the gene fusion results. The testing provided a more precise diagnosis in >60% of cases, and 9 cases were identified that could be treated with an available tyrosine kinase inhibitor if detected at diagnosis. As risk-stratified and targeted therapies become more available in SSA, implementing this testing will enable the treatment of pediatric cancer to move toward incorporating risk stratification for optimized therapy.