Richard Aplenc

PURPOSE: Dexrazoxane has been associated with preservation of left ventricular (LV) systolic function in relatively small studies of long-term childhood cancer survivors. What remains less clear is whether this association is also seen in larger populations over time and what effect dexrazoxane has on cardiomyopathy screening recommendations. METHODS: We analyzed echocardiographic data from participants who received doxorubicin treatment and were enrolled on Children's Oncology Group protocols P9404, P9425, P9426, P9754, and Dana Farber Cancer Institute protocol 95-01. Except for P9754, all protocols featured up-front 1:1 random assignment with dexrazoxane administered uniformly as an intravenous bolus before doxorubicin (10:1 mg/m ² dexrazoxane:doxorubicin dose). Blinded central echocardiogram remeasurements were used when possible; otherwise, data were abstracted from institutional reports. Differences and associations by ± dexrazoxane were estimated using generalized estimating equations and Cox proportional hazard models, adjusting for age, sex, doxorubicin dose, chest radiotherapy, and echocardiogram data type. RESULTS: Among 895 patients (mean follow-up, 5.9 years, 230 with ≥10-year follow-up; median doxorubicin dose, 360 mg/m ² ; 51% dexrazoxane-exposed) with evaluable echocardiograms (n = 2,279; 1,581 centrally remeasured; 698 report only), preserved LV systolic function was observed in patients treated with dexrazoxane (z-score difference 0.4 [95% CI, 0.2 to 0.5]) versus without. Dexrazoxane was also associated with decreased hazards of reduced LV function (fractional shortening P = .001). CONCLUSION: Dexrazoxane exerts a significant doxorubicin cardioprotective effect on LV systolic function long term and may reduce screening needs.

PURPOSE: The Children's Oncology Group phase III clinical trial AAML1831 (ClinicalTrials.gov identifier: NCT04293562 ) evaluated liposomal daunorubicin and cytarabine (CPX-351) versus standard daunorubicin/cytarabine (DA) induction therapy in children and young adults with newly diagnosed AML. We hypothesized that CPX-351 given during induction 1 and 2 would improve outcomes compared with DA. PATIENTS AND METHODS: Patients (21 years and younger) were randomly assigned to two cycles of DA induction (arm A = DA) or CPX-351 (arm B = CPX-351). All patients also received gemtuzumab ozogamicin in induction 1. Postinduction chemotherapy was according to risk assignment made at the end of induction 1 (EOI1). Those with high-risk (HR) AML received consolidation with allogeneic hematopoietic stem-cell transplantation (HSCT), whereas low-risk (LR) patients received chemotherapy alone. Protocol-specified interim analysis monitored efficacy and futility of CPX-351 induction with respect to the primary end point, event-free survival (EFS) from study entry. Disease-free survival (DFS) was calculated to determine the impact of EOI1 risk assignment. RESULTS: Seven hundred twenty-one eligible patients with FLT3 wild-type AML were randomly assigned to DA (n = 358) or CPX-351 (n = 363). Interim analysis determined that the futility monitoring rule was crossed because of inferior EFS in the CPX-351 arm and the random assignment was stopped. The two-year EFS from study entry was 62.2% for DA versus 51.2% for CPX-351 ( P = .011). DFS for patients with HR AML was comparable for both arms. However, DFS was significantly lower and cumulative incidence of relapse (CIR) was higher for LR patients assigned to CPX-351 versus DA (2-year DFS from EOI1: DA: 73.8% v CPX-351 57.5% [ P = .001]; 2-year CIR Arm DA: 23.6% v CPX-351: 39.9% [ P = .001]). CONCLUSION: CPX-351 was inferior to DA induction in the AAML1831 trial with differential EFS largely driven by events in LR patients.

KMT2A-rearranged (KMT2A-r) acute leukemias are especially prevalent in the pediatric population. KMT2A-fusion proteins drive leukemogenic gene expression through an interaction with a chromatin complex that includes the scaffold protein menin, giving rise to aggressive acute leukemias. RAS pathway mutations are also common in pediatric leukemia. In a cohort of 1750 patients enrolled on Children's Oncology Group (COG) trials, we identified RAS pathway mutations in 43% of AML cases. The presence of RAS pathway mutations in KMT2A-r AML was associated with a lower complete remission (CR) rate, poor event-free (EFS) and overall survival (OS), and early relapses. Given the inferior outcome observed for children with dual mutations, we next sought to identify efficacious targeted drug combinations for this subset of childhood leukemia. We evaluated RAS/MAPK targeting using the MEK1/2 inhibitor selumetinib in combination with the menin inhibitor revumenib. Treatment of AML cell lines and cultured leukemia cells from patient-derived xenograft (PDX) models resulted in a synergistic decrease in viability and promoted cell cycle arrest, apoptosis and downregulation of Myc targets in the combination compared to each drug alone. In vivo, the combination treatment of AML pediatric PDX models harboring KMT2A-r and RAS mutations reduced leukemia burden compared to single drug treatments, but without improving overall survival compared to menin inhibition alone. Our preclinical study suggests a potential targeted treatment combination for KMT2A-r and RAS pathway mutant leukemia, but one which will require further optimization. COG completed clinical trials AAML03P1, AAML0531, AAML1031 and C2961.

The European LeukemiaNet has periodically issued guidelines for the diagnosis and management of acute myeloid leukemia (AML) in adults. These consensus recommendations, most recently updated in 2022, incorporate recent advances in genomic testing, disease detection methods, target identification, and response assessment. Although similarities exist between AML in children and adults, pediatric AML is frequently characterized by unique cytogenetic and molecular features, which require distinct genetic and immunophenotypic diagnostics, therapeutic approaches, response assessment criteria, and supportive care strategies. To address these specific needs, an international panel of pediatric hematologist-oncologists, biologists, geneticists, and laboratory medicine scientists convened to develop recommendations for the diagnosis and management of AML in children, adolescents, and young adults (hereafter termed pediatric AML) that are discussed in this special report.

PURPOSE: Electronic data capture (EDC) has the potential to improve trial data accuracy and efficiency. The Children's Oncology Group Pediatric Early Phase Clinical Trials Network (PEP-CTN) and Pediatric Brain Tumor Consortium (PBTC) conducted a joint pilot that aimed to assess feasibility of automated transfer of laboratory data from electronic health records to the Medidata Rave EDC (Rave). Second, we compared data from automated extraction (EXTRACTED) and manual ascertainment (MANUAL) during the original studies using two representative tests, bilirubin and platelet count (PLT). METHODS: Data from 78 patients treated on seven completed PBTC or PEP-CTN trials at seven hospitals were included. Each consortium created a Rave instance to receive data. Sites elected to use local methods or the ExtractEHR R package. Postextraction data were uploaded to the Rave Batch Uploader (BU)–associated file transfer protocol client and BU uploaded data into Rave. After successful upload, discrepancies between EXTRACTED and MANUAL data were categorized. RESULTS: All sites successfully extracted required laboratory data and had 1+ complete upload. PBTC/PEP-CTN operational effort and close collaboration with hospital site technical teams was required. Owing to study closure timing, only two sites checked EXTRACTED data from their first patient list; this identified incomplete mapping that was fixed before second patient list extraction. Beyond incomplete mapping, discrepancies for bilirubin and PLT were commonly due to mismatched values or units (Consortium 1 PLT: 3/10 (30%); Consortium 2 PLT: 152/176 (86%)). CONCLUSION: This study demonstrated that automated laboratory data ascertainment is feasible in pediatric cooperative oncology group trials. Although this required up-front central operational and local site-based effort, lessons learned from this pilot can inform future studies using automated data capture.

Supplementary Figure S1. T-ALL subtype classifying driver genes among individuals of European, Admixed American, and African ancestry. Supplementary Figure S2. T-ALL subtype classifying driver genes among patients with Early T-cell Precursor (ETP)-like subtype among individuals of European, Admixed American and African ancestry. Supplementary Figure S3. Distribution of 15 genomically defined T-ALL subtypes described by Pölönen and colleagues (16) among individuals of African and Non-African ancestry. Supplementary Figure S4. 5-year event free survival for NOTCH1 and FBXW7 by ancestral group. Supplementary Figure S5. Prevalence of (A) coding versus non-coding alterations and (B) types of pathogenic variants in NOTCH1 among individuals of African versus non-African ancestry. Supplementary Figure S6. Event free survival among all patients, patients of European, Admixed American, and African ancestry by NOTCH1 alterations (no mutation, favorable, unfavorable). Supplementary Figure S7. NOTCH1 coding mutation types (frameshift, missense, nonsense) on a lollipop plot in patients of European, African, and Admixed American Ancestry. Supplementary Figure S8. 5-year event free survival for genes with at least 5% frequency for each ancestral group (CDKN2A, PHF6, PTEN, DNM2). Supplementary Figure S9. 5-year event free survival for genes with at least 5% frequency for each ancestral group (LEF1, MYB, MYC, 6q loss). Supplementary Figure S10. 5-year event free survival for genes with at least 5% frequency for each ancestral group (WT1, USP7, IL7R, N/KRAS). Supplementary Figure S11. Distribution of genetic ancestral composition of individuals by categorically defined genetic ancestry.

T-cell Acute Lymphoblastic Leukemia subtype by Categorical Genetic Ancestry

Association of Genetic Ancestry (25% interval) as Continuous Variables with Survival Outcomes.

T-cell Acute Lymphoblastic Leukemia Genomic Subtype Description.

Association of Genetic Ancestries (25% Interval) as Continuous Variables with Biologic Subtype (TAL1 DP-like as reference subtype) Using Multinomial Regression Model.