Faculty Bibliography

Pediatric Hispanic and Black patients with newly diagnosed B-acute lymphoblastic leukemia (B-ALL) experience worse overall survival (OS). We hypothesized that differential outcomes by race and ethnicity following relapse may contribute to disparities. We examined 2,053 patients with ALL enrolled on frontline Children's Oncology Group trials from 1996-2014 who relapsed. We assessed association of race and ethnicity, disease characteristics, and socioeconomic status with relapse survival predictors and post-relapse OS. For non-infant B-ALL, post-relapse OS (p=0.002) and disease-related prognosticators such as time-to-relapse (p=0.0002) differed by race and ethnicity. After adjusting for disease and patient characteristics, the OS association with overall race and ethnicity was attenuated, and lost statistical significance; Hispanic ethnicity specifically remained associated with worse OS (hazard ratio, HR=1.19, 95% confidence interval, CI 1.01-1.41). Patients from highest annual median household income ZIP codes (>$85,000, ~highest quartile of patients) had better 5-year OS compared to those from the lowest (<$50,000, HR=0.79, 95%CI 0.63-0.99). Non-Hispanic Black and Hispanic patients more commonly lived in lower income ZIP codes. For T-ALL, race, ethnicity and socioeconomic status were not associated with OS. Worse post-relapse outcomes among racial and ethnic minority patients are largely driven by prevalence of adverse disease-related factors at time of relapse, with a persistent disparity observed in Hispanic patients. The greatest impact in decreasing racial and ethnic B-ALL outcome disparities may come through targeting frontline treatment interventions to address increased relapse among Black and Hispanic patients, as well as developing and enabling equitable access to effective relapse treatments such as novel immunotherapies. (CCG 1991, POG 9404, POG 9407, POG 9904, POG 9905, POG 9906, COG AALL0232, COG AALL0331, COG AALL0434, COG AALL0631, COG AALL07P4, COG AALL08P1).

UNLABELLED:The influence of genetic ancestry on genomics in T-cell acute lymphoblastic leukemia (T-ALL) has not been fully explored. We examined the impact of genetic ancestry on multiomic alterations, survival outcomes, and risk stratification. Among 1,309 children and young adults with T-ALL treated on the Children's Oncology Group trial AALL0434, the prognostic value of five commonly altered T-ALL genes varied by ancestry-including NOTCH1, which was associated with superior overall survival for patients of European ancestry but was nonprognostic among patients of African ancestry. Integrating genetic ancestry with published T-ALL risk classifiers, we identified that an X01 penalized Cox regression classifier stratified patients regardless of ancestry, whereas a European multigene classifier misclassified patients of certain ancestries. Overall, 80% of patients harbored a genomic alteration in at least one gene with differential prognostic impact in an ancestry-specific manner. These data demonstrate the importance of incorporating genetic ancestry into genomic risk classification. SIGNIFICANCE/UNASSIGNED:There is a lack of studies examining the prognostic significance of genomic features by genetic ancestry in T-ALL, especially in non-European ancestral groups. In this study, we demonstrate how the prognostic value of individual alterations differs by genetic ancestry, warranting future studies to identify germline alleles affecting these associations. See related commentary by de Smith, p. xxx.

The twelfth multi-stakeholder Paediatric Strategy focused on cyclin-dependent kinase (CDK) inhibitors. Genetic aberrations in paediatric tumours increase CDK4/6 activity, thus the pathway is a therapeutic target. As a result, CDK4/6 inhibitors have been evaluated in clinical trials for children and young adults with different malignancies, both as single agents and in combination, including molecular enrichment in ESMART. In some instances, trials of different agents within this same class are very similar in design or target population, leading to duplication. Consistent with preclinical data with CDK4/6 inhibitors which mostly demonstrate cytostasis, but not tumour regression, objective responses are rare, although there may be slowing of tumour growth. Similar to adults, no predictive biomarkers have been identified and an integrated comprehensive clinical development strategy of this class of agents is lacking. Patient advocates believe that the many trials of CDK4/6 inhibitors, which have enrolled many children and young people, have not been matched by sufficient gains in knowledge. CDK9, CDK12 and CDK13 inhibitors, based on exploitation of transcriptional vulnerabilities, have shown promise in preclinical models of MYCN-driven neuroblastoma, osteosarcoma and translocation fusion-driven malignancies. The development of these inhibitors should be sequential, iterative and coordinated, including early engagement with regulators. In conclusion, there needs to be prioritisation and coordination of any further development of CDK4/6 inhibitors in paediatric malignancies. Definite tumour regression in preclinical models, not just cytostasis, should be taken as the go/no go decision point to progress such agents to clinical studies. Based on limited single agent activity in preclinical models, trials of new inhibitors should avoid unnecessary exposure of patients to monotherapy and rapidly progress to combination strategies, while retaining designs that allow early evaluation of activity. A framework to support integrated development strategies of new products across sponsors would be very beneficial.

Errors in chromosome segregation during gametogenesis, such as nondisjunction (NDJ) errors, have severe consequences in human reproduction, and a better understanding of their etiology is of fundamental interest in genetics. Mapping NDJ errors to meiotic/mitotic stages typically requires proband-parent comparison, limiting its applicability. Herein, we develop Mis-segregation Error Identification through Hidden Markov Models (MeiHMM), a method for inferring NDJ error stage and crossover events based on only genomic data of trisomic probands. Guided by triallelic genotype/haplotype configurations, MeiHMM discerns the allelic origin at each locus, which informs NDJ error during gamete formation, without identifying the parental origin of the trisomy. In 152 Down syndrome (DS) cases, MeiHMM achieved an accuracy of 96.1% in classifying NDJ errors, with a sensitivity of 91.6% in crossover identification, compared to proband-parents trio analysis. 17% of Meiosis II errors were misclassified as Meiosis I, mainly due to small proximal crossover events. Applying MeiHMM to 509 children with DS-associated childhood leukemia, we demonstrate that NDJ error is associated with the age of disease onset, somatic genomic abnormalities, and prognosis. Thus, MeiHMM is an effective method for trisomic NDJ error classification and crossover identification that can be applied broadly to study the etiology of congenital aneuploidy conditions.

The critical role of leukemia-initiating cells as a therapy-resistant population in myeloid leukemia is well established. However, the molecular signatures of such cells in acute lymphoblastic leukemia remain underexplored. Moreover, their role in therapy response and patient prognosis is yet to be systematically investigated across various types of acute leukemia. We used single-cell multiomics to analyze diagnostic specimens from 96 pediatric patients with acute lymphoblastic, myeloid, and lineage-ambiguous leukemias. Through the integration of single-cell multiomics with extensive bulk RNA sequencing and clinical data sets, we uncovered a prevalent, chemotherapy-resistant subpopulation that resembles hematopoietic stem and progenitor cells (HSPC-like) and is associated with poor clinical outcomes across all subtypes investigated. We identified a core transcriptional regulatory network (TRN) in HSPC-like blasts that is combinatorially controlled by HOXA/AP1/CEBPA. This TRN signature can predict chemotherapy response and long-term clinical outcomes. We identified shared potential therapeutic targets against HSPC-like blasts, including FLT3, BCL2, and the PI3K pathway. Our study provides a framework for linking intratumoral heterogeneity with therapy response, patient outcomes, and the discovery of new therapeutic targets for pediatric acute leukemias.

We used single-cell genomics to characterize a patient with T-cell acute lymphoblastic leukemia treated in the Children's Oncology Group AALL0434 trial with poor clinical outcome despite favorable genomic features, identifying a STAT1-mediated interferon-related transcriptional signature and inflammatory microenvironment associated with sensitivity to small-molecule JAK inhibition.

The influence of genetic ancestry on genomics in T-cell Acute Lymphoblastic Leukemia (T-ALL) has not been fully explored. We examined the impact of genetic ancestry on multi-omic alterations, survival outcomes, and risk stratification. Among 1309 children and young adults with T-ALL treated on the Children's Oncology Group trial AALL0434, the prognostic value of five commonly altered T-ALL genes varied by ancestry-including NOTCH1, which was associated with superior overall survival for patients of European ancestry but non-prognostic among patients of African ancestry. Integrating genetic ancestry with published T-ALL risk classifiers, we identified that a X01 Penalized Cox Regression classifier stratified patients regardless of ancestry, whereas a European multi-gene classifier misclassified patients of certain ancestries. Overall, 80% of patients harbored a genomic alteration in at least one gene with differential prognostic impact in an ancestry-specific manner. These data demonstrate the importance of incorporating genetic ancestry into genomic risk classification.

PURPOSE/OBJECTIVE:To reduce costs in genomic studies of time-to-event phenotypes like survival, researchers often sequence a subset of samples from a larger cohort. This process usually involves two phases: first, collecting inexpensive variables from all samples, and second, selecting a subset for expensive measurements, for example, sequencing-based biomarkers. Common two-phase designs include nested case-control and case-cohort designs. Additional designs include sampling subjects based on follow-up time, like extreme case-control designs. Recently an optimal two-phase design using a maximum likelihood-based method was proposed, which could accommodate arbitrary sample selection in the second phase. However, direct comparisons of this optimal design with others in terms of power and computational cost is lacking. METHODS:This study performs a direct evaluation of typical two-phase designs, including Tao's optimal design, on type I error, power, effect size estimation, and computational time, using both simulated and real data sets. RESULTS:Results show that the optimal design had the highest power and accurate effect size estimation under the Cox regression model. Surprisingly, logistic regression achieved similar power with much lower computational cost than a more sophisticated method. The study further applied these methods to the MP2PRT study, reporting hazard ratios of cancer subtypes on relapse risk. CONCLUSION/CONCLUSIONS:Recommendations for selecting two-phase designs and analysis methods are regarding power, bias of estimated effect size, and computational time.

Refractoriness to initial chemotherapy and relapse after remission are the main obstacles to curing T cell acute lymphoblastic leukemia (T-ALL). While tumor heterogeneity has been implicated in treatment failure, the cellular and genetic factors contributing to resistance and relapse remain unknown. Here we linked tumor subpopulations with clinical outcome, created an atlas of healthy pediatric hematopoiesis and applied single-cell multiomic analysis to a diverse cohort of 40 T-ALL cases. We identified a bone marrow progenitor (BMP)-like leukemia subpopulation associated with treatment failure and poor overall survival. The single-cell-derived molecular signature of BMP-like blasts predicted poor outcome across multiple subtypes of T-ALL and revealed that NOTCH1 mutations additively drive T-ALL blasts away from the BMP-like state. Through in silico and in vitro drug screenings, we identified a therapeutic vulnerability of BMP-like blasts to apoptosis-inducing agents including venetoclax. Collectively, our study establishes multiomic signatures for rapid risk stratification and targeted treatment of high-risk T-ALL.

Children's Oncology Group study AALL1931 investigated the efficacy and safety of recombinant Erwinia asparaginase (JZP458) in patients with acute lymphoblastic leukemia/lymphoblastic lymphoma and hypersensitivity reactions/silent inactivation to Escherichia coli-derived asparaginases. Each pegylated Escherichia coli asparaginase dose remaining in a patient's treatment plan was replaced by intramuscular (IM) or IV JZP458 (6 doses) administered Monday/Wednesday/Friday (MWF). Three IM cohorts (1a [25 mg/m2 MWF], n = 33; 1b [37.5 mg/m2 MWF], n = 83; 1c [25/25/50 mg/m2 MWF], n = 51) and 1 IV cohort (25/25/50 mg/m2 MWF, n = 62) were evaluated. The proportion (95% confidence interval [CI]) of patients maintaining nadir serum asparaginase activity (NSAA) levels of ≥0.1 IU/mL at the last 72 (primary end point) and 48 hours during course 1 was 90% (95% CI, 81-98) and 96% (95% CI, 90-100) in IM cohort 1c, respectively, and 40% (95% CI, 26-54) and 90% (95% CI, 82-98) in the IV cohort. Population pharmacokinetic modeling results were comparable with observed data, predicting the vast majority of patients would maintain therapeutic NSAA levels when JZP458 is administered IM or IV 25 mg/m2 every 48 hours, or IM 25/25/50 mg/m2 MWF, or with mixed IM and IV administration (IV/IV/IM 25/25/50 mg/m2 MWF). Drug discontinuation occurred in 23% and 56% of patients in the IM and IV cohorts, respectively; 13% and 33% because of treatment-related adverse events (mainly allergic reactions and pancreatitis). JZP458 achieves therapeutic NSAA levels via multiple IM and IV dosing schedules based on combined observed and modeled data with a safety profile consistent with other asparaginases. This trial was registered at www.ClinicalTrials.gov as #NCT04145531.