Faculty Bibliography

BACKGROUND:Treatment of pediatric B-acute lymphoblastic leukemia (B-ALL) impacts both patients and their caregivers. An understanding of family functioning during therapy can inform family-centered care. We aimed to prospectively identify negative and positive changes in family life as perceived by caregivers throughout ALL therapy. METHODS:Caregivers of children aged ≥4 years with average-risk B-ALL enrolled on the Children's Oncology Group trial AALL0932 who consented to an ancillary study were asked: "How has family life changed since your child's diagnosis of leukemia for the better or for the worse?" Written free responses were collected at approximately 2, 8, 17, 26 (end of therapy for females), and 38 (end of therapy for males) months post-diagnosis. Inductive content analysis was used to create codes, subcategories, and categories. Descriptive statistics were used to characterize the sample and frequencies of reported codes. RESULTS:Overall, 994 responses were collected from caregivers of 468 children across all timepoints. Twenty-seven individual codes were identified, categorized by negative changes (reported by 89% of caregivers) and positive changes (reported by 58% of caregivers). Subcategories of negative changes, including changes in daily routines, work and finance, patient health and care needs, effects on other family members, and emotional changes, were identified across all timepoints, but were most prevalent early in therapy. Importantly, positive changes were also identified, including family support, community support, and changes in outlook. CONCLUSION/CONCLUSIONS:This study identifies negative and positive family changes perceived by caregivers of children undergoing B-ALL therapy that can inform future interventions to better support families.

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.

BACKGROUND:B-cell acute lymphoblastic leukemia (B-cell ALL) is the most common childhood cancer. Despite a high overall cure rate, relapsed B-cell ALL remains a leading cause of cancer-related death among children. The addition of the bispecific T-cell engager molecule blinatumomab (an anti-CD19 and anti-CD3 single-chain molecule) to therapy for newly diagnosed standard-risk (as defined by the National Cancer Institute) B-cell ALL in children may improve outcomes. METHODS:We conducted a phase 3 trial involving children with newly diagnosed standard-risk B-cell ALL who had an average or high risk of relapse. Patients were randomly assigned to receive chemotherapy alone or chemotherapy plus two nonsequential 28-day cycles of blinatumomab. The primary end point was disease-free survival. RESULTS:The data and safety monitoring committee reviewed the results from the first interim efficacy analysis, which included 1440 patients who had undergone randomization (722 to chemotherapy alone and 718 to blinatumomab and chemotherapy) and recommended early termination of randomization. At a median follow-up of 2.5 years, the estimated 3-year disease-free survival (±SE) was 96.0±1.2% with blinatumomab and chemotherapy and 87.9±2.1% with chemotherapy alone (difference in restricted mean survival time, 72 days; 95% confidence interval, 36 to 108; P<0.001 by stratified log-rank test). The estimated 3-year disease-free survival among patients with an average relapse risk was 97.5±1.3% with blinatumomab and chemotherapy and 90.2±2.3% with chemotherapy alone; among those with a high relapse risk, the corresponding values were 94.1±2.5% and 84.8±3.8%. Cytokine release syndrome, seizures, and sepsis of grade 3 or higher were rare during blinatumomab cycles, but the overall incidence of nonfatal sepsis and catheter-related infections was significantly higher among patients with an average relapse risk who had been assigned to receive blinatumomab and chemotherapy than among those assigned to receive chemotherapy alone. CONCLUSIONS:Adding blinatumomab to combination chemotherapy in patients with newly diagnosed childhood standard-risk B-cell ALL of average or high risk of relapse significantly improved disease-free survival. (Funded by the National Institutes of Health and others; AALL1731 ClinicalTrials.gov number, NCT03914625.).