Table 1_Clinical characteristics and prognostic analysis of different fusion gene abnormalities in childhood acute lymphoblastic leukaemia.docx

ObjectiveThis study aimed to analyze the clinical features and prognostic significance of different fusion gene subtypes in pediatric patients with acute lymphoblastic leukaemia (ALL).
MethodsClinical data from 132 childhood patients with ALL diagnosed between 2016 and 2025 were retrospectively analyzed. Patients were categorized based on fusion gene status: TEL::AML1, BCR::ABL, E2A::PBX1, MLL::AF4, SIL::TAL1, other, negative and unknown. Clinical characteristics, laboratory findings, treatment responses, minimal residual disease status and survival outcomes were compared among different fusion gene groups. Survival analyses included overall survival (OS), event-free survival (EFS) and recurrence-free survival using the Kaplan–Meier method and Cox regression models.
ResultsAmong 132 patients, the fusion gene distribution was as follows: negative (48.5%), unknown (32.6%), TEL::AML1 (7.6%), BCR::ABL (3.8%), E2A::PBX1 (3.0%), MLL::AF4 (2.3%), other (1.5%) and SIL::TAL1 (0.8%). B-cell immunophenotype predominated (88.6%). E2A::PBX1-positive patients showed the most favorable outcomes with 100% 5-year OS and EFS. TEL::AML1-positive patients demonstrated good prednisone responses (90%), with 90% 5-year OS. BCR::ABL and MLL::AF4 cases presented with elevated white blood cell counts (median 86.9 and 96.5 × 109/L, respectively), higher lactate dehydrogenase levels and inferior treatment responses. In multivariate analysis, poor prednisone response (hazard ratio [HR] = 3.41, p = 0.005) and high-risk classification (HR = 4.92, p < 0.001) were independent adverse prognostic factors for EFS.
ConclusionFusion gene abnormalities significantly influence the clinical presentation and prognosis of childhood ALL. E2A::PBX1 and TEL::AML1 demonstrate favorable outcomes, whereas BCR::ABL, MLL::AF4 and SIL::TAL1 are associated with unfavorable prognosis. These findings provide valuable insights for risk stratification and treatment optimization in pediatric ALL.