Abstract / Summary
Background: Induction failure (IF) after standard induction chemotherapy is associated with poor outcomes in pediatric acute myeloid leukemia (pAML); however, whether established molecular markers such as FLT3-ITD retain prognostic significance across induction response states remains incompletely understood. We characterized the genomic landscape of IF and evaluated the prognostic significance of FLT3-ITD according to induction response. Methods: This multi-cohort study integrated a TARGET discovery cohort (n = 1979) and an independent cohort from the Children’s Hospital of Chongqing Medical University (CHCMU; n = 98). Clinical characteristics, somatic mutations, fusion profiles, and gene–gene interaction patterns were compared between patients with and without IF. Multivariable logistic regression identified genomic factors associated with IF, and survival analyses evaluated the prognostic impact of FLT3-ITD according to induction response. Results: IF was associated with inferior OS (overall survival) (pooled HR = 3.24, 95% CI: 2.66–3.95). FLT3 mutations were consistently enriched in IF patients, whereas KIT mutations and favorable core-binding factor fusions were more frequent among non-IF patients. NUP98-NSD1 fusion was strongly enriched in IF patients in the TARGET cohort. Gene interaction analyses revealed reduced recurrent co-mutation patterns among IF patients. FLT3 mutation independently and reproducibly associated with IF. Among patients achieving induction remission, FLT3-ITD remained associated with inferior OS (HR = 1.34, 95% CI: 1.06–1.69, p = 0.014), whereas no statistically significant additional prognostic effect was detected among patients with IF. Conclusions: This study characterizes the genomic landscape of IF in pAML and identifies FLT3 mutation as a reproducible marker of induction resistance. Achieving induction remission does not eliminate the adverse prognostic significance of FLT3-ITD, supporting the integration of molecular risk and treatment response in subsequent risk stratification.