Mullighan, Charles G

Abstract Cytokine receptor–like factor 2 rearrangement (CRLF2r), an aberration causing a Philadelphia chromosome–like gene expression profile and a poor prognostic marker in B-cell acute lymphoblastic leukemia (B-ALL), endows relative chemotherapeutic resistance. Extramedullary disease (EMD), including both central nervous system (CNS) and non-CNS involvement, can also be associated with worse outcomes. The relationship between CRLF2r and EMD is unknown. Based on an initial observation of patients with relapsed/refractory (R/R) CRLF2r B-ALL and EMD, a single-center retrospective review was conducted to evaluate the incidence of EMD in patients with CRLF2r B-ALL. Across 177 children, adolescents, and young adults with R/R B-ALL, 21 (11.9%) harbored CRLF2r, of whom 19 (90.5%) had EMD at some point during their treatment course. In contrast, only 78 of the 156 patients (50%) without CRLF2r ever had EMD (P = .0003). In the CRLF2r cohort, 8 (38.1%) presented with EMD at diagnosis: 7 with CNS and 1 with non-CNS EMD. At relapse, 17 (80.9%) had EMD: 4 (19%) had CNS EMD, 9 (42.9%) had non-CNS EMD, and 4 (19%) had both. Isolated EMD was observed in 2 patients (11.8%) at first relapse and in 3 (17.6%) with multiple relapses. Given these findings, further study to evaluate this potential association between EMD and CRLF2r in R/R B-ALL is indicated.

PURPOSE 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 Recommendations for selecting two-phase designs and analysis methods are regarding power, bias of estimated effect size, and computational time.

PURPOSE Although cure rates for childhood acute lymphoblastic leukemia (ALL) exceed 90%, ALL remains a leading cause of cancer death in children. Half of relapses arise in children initially classified with standard-risk (SR) disease. MATERIALS AND METHODS To identify genomic determinants of relapse in children with SR ALL, we performed genome and transcriptome sequencing of diagnostic and remission samples of children with SR (n = 1,381) or high-risk B-ALL with favorable cytogenetic features (n = 115) enrolled on Children's Oncology Group trials. We used a case-control study design analyzing 439 patients who relapsed and 1,057 who remained in complete remission for at least 5 years. RESULTS Genomic subtype was associated with relapse, which occurred in approximately 50% of cases of PAX5 -altered ALL (odds ratio [OR], 3.31 [95% CI, 2.17 to 5.03]; P = 3.18 × 10 –8 ). Within high-hyperdiploid ALL, gain of chromosome 10 with disomy of chromosome 7 was associated with favorable outcome (OR, 0.27 [95% CI, 0.17 to 0.42]; P = 8.02 × 10 –10 ; St Jude Children's Research Hospital validation cohort: OR, 0.22 [95% CI, 0.05 to 0.80]; P = .009), and disomy of chromosomes 10 and 17 with gain of chromosome 6 was associated with relapse (OR, 7.16 [95% CI, 2.63 to 21.51]; P = 2.19 × 10 –5 ; validation cohort: OR, 21.32 [95% CI, 3.62 to 119.30]; P = .0004). Genomic alterations were associated with relapse in a subtype-dependent manner, including alterations of INO80 in ETV6::RUNX1 ALL, IKZF1 , and CREBBP in high-hyperdiploid ALL and FHIT in BCR::ABL1 -like ALL. Genomic alterations were also associated with the presence of minimal residual disease, including NRAS and CREBBP in high-hyperdiploid ALL. CONCLUSION Genetic subtype, patterns of aneuploidy, and secondary genomic alterations determine risk of relapse in childhood ALL. Comprehensive genomic analysis is required for optimal risk stratification.

PURPOSE Acute lymphoblastic leukemia (ALL) can occur across all age groups, with a strikingly higher cure rate in children compared with adults. However, the pharmacological basis of age-related differences in ALL treatment response remains unclear. METHODS Studying 767 children and 309 adults with newly diagnosed B-cell ALL enrolled on frontline trials at St Jude Children's Research Hospital, MD Anderson Cancer Center, the Alliance for Clinical Trials in Oncology, and the ECOG-ACRIN Cancer Research Group, we determined the ex vivo sensitivity of leukemia cells to 21 drugs. Twenty-three ALL molecular subtypes were identified using RNA sequencing. We systematically characterized the associations between drug response and ALL genomics in children, adolescents and young adults, and elderly adults. We evaluated the effect of age-related gene expression signature on ALL treatment outcomes. RESULTS Seven ALL drugs (asparaginase, prednisolone, mercaptopurine, dasatinib, nelarabine, daunorubicin, and inotuzumab ozogamicin) showed differential activity between children and adults, of which six were explained by age-related differences in leukemia molecular subtypes. Adolescents and young adults showed similar patterns of drug resistance as older adults, relative to young children. Mercaptopurine exhibited subtype-independent greater sensitivity in children. Transcriptomic profiling uncovered subclusters within CRLF2 -, DUX4 -, and KMT2A -rearranged ALL that were linked to age and cytotoxic drug resistance. In particular, a subset of children had adult-like ALL on the basis of leukemia gene expression patterns across subtypes, despite their chronological age. Resistant to cytotoxic drugs, children with adult-like ALL exhibited poor prognosis in pediatric ALL trials, even after adjusting for age and minimal residual diseases. CONCLUSION Our results provide pharmacogenomic insights into age-related disparities in ALL cure rates and identify leukemia prognostic features for treatment individualization across age groups.

PURPOSE Patients with Down syndrome (DS) and B-ALL experience increased rates of relapse, toxicity, and death. We report results for patients with DS B-ALL enrolled on Children's Oncology Group trials between 2003 and 2019. METHODS We analyzed data for DS (n = 743) and non-DS (n = 20,067) patients age 1-30 years on four B-ALL standard-risk (SR) and high-risk trials. RESULTS Patients with DS exhibited more frequent minimal residual disease (MRD) ≥0.01% at end induction (30.8% v 21.5%; P < .001). This difference persisted at end consolidation only in National Cancer Institute (NCI) high-risk patients (34.0% v 11.7%; P < .0001). Five-year event-free survival (EFS) and overall survival (OS) were significantly poorer for DS versus non-DS patients overall (EFS, 79.2% ± 1.6% v 87.5% ± 0.3%; P < .0001; OS, 86.8% ± 1.4% v 93.6% ± 0.2%; P < .0001), and within NCI SR and high-risk subgroups. Multivariable Cox regression analysis of the DS cohort for risk factors associated with inferior EFS identified age >10 years, white blood count >50 × 103/μL, and end-induction MRD ≥0.01%, but not cytogenetics or CRLF2 overexpression. Patients with DS demonstrated higher 5-year cumulative incidence of relapse (11.5% ± 1.2% v 9.1% ± 0.2%; P = .0008), death in remission (4.9% ± 0.8% v 1.7% ± 0.1%; P < .0001), and induction death (3.4% v 0.8%; P < .0001). Mucositis, infections, and hyperglycemia were significantly more frequent in all patients with DS, while seizures were more frequent in patients with DS on high-risk trials (4.1% v 1.8%; P = .005). CONCLUSION Patients with DS-ALL exhibit an increased rate of relapse and particularly of treatment-related mortality. Novel, less-toxic therapeutic strategies are needed to improve outcomes.

Abstract Myeloid neoplasms and acute leukemias derive from the clonal expansion of hematopoietic cells driven by somatic gene mutations. Although assessment of morphology plays a crucial role in the diagnostic evaluation of patients with these malignancies, genomic characterization has become increasingly important for accurate diagnosis, risk assessment, and therapeutic decision making. Conventional cytogenetics, a comprehensive and unbiased method for assessing chromosomal abnormalities, has been the mainstay of genomic testing over the past several decades and remains relevant today. However, more recent advances in sequencing technology have increased our ability to detect somatic mutations through the use of targeted gene panels, whole-exome sequencing, whole-genome sequencing, and whole-transcriptome sequencing or RNA sequencing. In patients with myeloid neoplasms, whole-genome sequencing represents a potential replacement for both conventional cytogenetic and sequencing approaches, providing rapid and accurate comprehensive genomic profiling. DNA sequencing methods are used not only for detecting somatically acquired gene mutations but also for identifying germline gene mutations associated with inherited predisposition to hematologic neoplasms. The 2022 International Consensus Classification of myeloid neoplasms and acute leukemias makes extensive use of genomic data. The aim of this report is to help physicians and laboratorians implement genomic testing for diagnosis, risk stratification, and clinical decision making and illustrates the potential of genomic profiling for enabling personalized medicine in patients with hematologic neoplasms.

Abstract The classification of myeloid neoplasms and acute leukemias was last updated in 2016 within a collaboration between the World Health Organization (WHO), the Society for Hematopathology, and the European Association for Haematopathology. This collaboration was primarily based on input from a clinical advisory committees (CACs) composed of pathologists, hematologists, oncologists, geneticists, and bioinformaticians from around the world. The recent advances in our understanding of the biology of hematologic malignancies, the experience with the use of the 2016 WHO classification in clinical practice, and the results of clinical trials have indicated the need for further revising and updating the classification. As a continuation of this CAC-based process, the authors, a group with expertise in the clinical, pathologic, and genetic aspects of these disorders, developed the International Consensus Classification (ICC) of myeloid neoplasms and acute leukemias. Using a multiparameter approach, the main objective of the consensus process was the definition of real disease entities, including the introduction of new entities and refined criteria for existing diagnostic categories, based on accumulated data. The ICC is aimed at facilitating diagnosis and prognostication of these neoplasms, improving treatment of affected patients, and allowing the design of innovative clinical trials.