Development and validation of a single‐cell network profiling assay‐based classifier to predict response to induction therapy in paediatric patients with de novo acute myeloid leukaemia: a report from the Children's Oncology Group

摘要: Single cell network profiling (SCNP) is a multi-parameter flow cytometry technique for simultaneous interrogation of intracellular signalling pathways. Diagnostic paediatric acute myeloid leukaemia (AML) bone marrow samples were used to develop classifier response induction therapy in 53 and validated an independent set 68 samples. The area under the curve receiver operating characteristic (AUC(ROC)) was calculated be 0·85 training after exclusion deaths, AUC(ROC) 0·70 (P = 0·02) 0·67 0·04) validation when deaths (intent treat) included. highest predictive accuracy noted cytogenetic intermediate risk patients (AUC(ROC) 0·88, P 0·002), subgroup that lacks prognostic/predictive biomarkers response. Only white blood count associated with set. After controlling these variables, SCNP score complete remission 0·017), indicating provides information other clinical variables jointly This first predict chemotherapy. Herein we demonstrate usefulness quantitative modulated conditions provide on AML disease biology