Biomarkers in Predicting Response to Treatment in Bone Marrow Samples From Young Patients With Acute Myeloid Leukemia

Overview

RATIONALE: Studying samples of bone marrow from patients with cancer in the laboratory may help doctors predict how well patients will respond to treatment. PURPOSE: This research trial is studying biomarkers in predicting response to treatment in bone marrow samples from young patients with acute myeloid leukemia.

OBJECTIVES: Primary * To validate the accuracy of a pre-specified acute myeloid leukemia (AML) induction response classifier or the My Profile™ AML Induction Therapy Assay (run in a Good Laboratory Practice \[GLP\] laboratory using Good Manufacturing Practice \[GMP\] reagents) in predicting response to cytarabine-based induction chemotherapy in pediatric patients with non-M3 AML. Secondary * To validate the continuous score from the pre-specified induction response classifier as a predictor of response to induction chemotherapy, after controlling for the simultaneous effects of clinical variables at base-line and/or pre-induction therapy (e.g., age, WBC, and percentage \[%\] of blasts), and tests commonly available after the start of induction therapy (e.g., cytogenetics and molecular markers). * To validate the accuracy of the pre-specified induction response classifier as a binary predictor of induction response using a pre-specified cutpoint to assign patients to no response (NR) or complete response (CR) groups. * To validate the accuracy of the pre-specified induction response classifier as a binary predictor of induction response using a pre-specified cutpoint to assign patients to NR or CR groups, after controlling for the simultaneous effects of clinical variables at base-line (pre-induction therapy) (e.g., age, WBC, % blasts) and clinical variables, including tests commonly available after start of induction therapy (e.g., age, WBC, cytogenetics). OUTLINE: Cryopreserved bone marrow mononuclear cell specimens are analyzed by cell networking profiling assays. Results are then compared with patient outcomes and demographics from COG-AAML03P1 and COG-AAML0531 studies. Molecular markers analyzed include Flt3ITD, NPM1, CEBPA, and MRA.

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