Associations of T-Cell Receptor Repertoire Diversity with L-Asparaginase Allergy in Childhood Acute Lymphoblastic Leukemia.

Asparaginase is a critical component of therapy for childhood acute lymphoblastic leukemia (ALL), but it is commonly associated with allergy, which results in morbidity and poorer outcomes. The underlying basis of this allergy is undoubtedly immune-mediated, but the exact components of T-cell immunity have yet to be characterized. We performed longitudinal TCR sequencing of 180 bone marrow samples from 67 children with B-ALL treated as part of the Ma-Spore-ALL-2010 trial, and we evaluated the associations of TCR profile with asparaginase hypersensitivity, with functional validation of asparaginase activity in a separate cohort of 113 children. We found that a more diverse and dynamically changing TCR repertoire was associated with increased risk of clinical hypersensitivity and decreased L-asp activity. Allergic patients had a higher proportion of infrequent clonotypes, as well as a significantly lower degree of shared clonotypes amongst the cohort. Allergic patients also had significantly higher longitudinal variability of clonotypes across timepoints, where a higher dissimilarity between diagnosis and week 5 represented an 8.1-fold increased risk of an allergic event. After an allergy had occurred, there was shaping and convergence of the TCR repertoire towards a common antigen. Understanding the immunological basis of T-cell responses in allergy lays the groundwork for developing predictive biomarkers or strategies to mediate this common toxicity in childhood ALL.

Life-threatening infections during treatment for acute lymphoblastic leukemia on the Malaysia-Singapore 2003 and 2010 clinical trials: A risk prediction model.

AIM: Life-threatening infections significantly impact the care of children undergoing therapy for acute lymphoblastic leukemia (ALL) who are at risk of severe sepsis due to both host and treatment factors. Our aim was to develop a life-threatening infection risk prediction model that would allow remote rapid triage of patients to reduce time to first dose of antibiotics and sepsis-related mortality. METHODS: A retrospective analysis of 2068 fever episodes during ALL therapy was used for model building and subsequent internal validation. RESULTS: Three hundred and seventy-seven patients were treated for ALL in two institutions with comparable critical and supportive care resources. A total of 55 patients accounted for 71 admissions to the critical care unit for sepsis that led to eight septic deaths during a 16-year study period. A retrospective analysis of risk factors for sepsis enabled us to build a model focused on 13 variables that discriminated admissions requiring critical care well: area under the receiver operating characteristic curve of .82; 95% CI .76-.87, p<.001, and Brier score of .033. Significant univariate predictors included neutropenia, presence of symptoms of abdominal pain, diarrhea, fever during induction or steroid-based phases, and the lack of any localizing source of infection at time of presentation. CONCLUSION: We have developed a risk prediction model that can reliably identify ALL patients undergoing treatment who are at a higher risk of life-threatening sepsis. Clinical applicability can potentially be extended to low-middle income settings, and its utility should be further studied in real-world settings.

Distinct clinical characteristics of DUX4- and PAX5-altered childhood B-lymphoblastic leukemia.

Among the recently described subtypes in childhood B-lymphoblastic leukemia (B-ALL) were DUX4- and PAX5-altered (PAX5alt). By using whole transcriptome RNA sequencing in 377 children with B-ALL from the Malaysia-Singapore ALL 2003 (MS2003) and Malaysia-Singapore ALL 2010 (MS2010) studies, we found that, after hyperdiploid and ETV6-RUNX1, the third and fourth most common subtypes were DUX4 (n = 51; 14%) and PAX5alt (n = 36; 10%). DUX4 also formed the largest genetic subtype among patients with poor day-33 minimal residual disease (MRD; n = 12 of 44). But despite the poor MRD, outcome of DUX4 B-ALL was excellent (5-year cumulative risk of relapse [CIR], 8.9%; 95% confidence interval [CI], 2.8%-19.5% and 5-year overall survival, 97.8%; 95% CI, 85.3%-99.7%). In MS2003, 21% of patients with DUX4 B-ALL had poor peripheral blood response to prednisolone at day 8, higher than other subtypes (8%; P = .03). In MS2010, with vincristine at day 1, no day-8 poor peripheral blood response was observed in the DUX4 subtype (P = .03). The PAX5alt group had an intermediate risk of relapse (5-year CIR, 18.1%) but when IKZF1 was not deleted, outcome was excellent with no relapse among 23 patients. Compared with MS2003, outcome of PAX5alt B-ALL with IKZF1 codeletion was improved by treatment intensification in MS2010 (5-year CIR, 80.0% vs 0%; P = .05). In conclusion, despite its poor initial response, DUX4 B-ALL had a favorable overall outcome, and the prognosis of PAX5alt was strongly dependent on IKZF1 codeletion.

Practical Considerations for Using RNA Sequencing in Management of B-Lymphoblastic Leukemia: Malaysia-Singapore Acute Lymphoblastic Leukemia 2020 Implementation Strategy.

Despite the immense genetic heterogeneity of B-lymphoblastic leukemia [or precursor B-cell acute lymphoblastic leukemia (B-ALL)], RNA sequencing (RNA-Seq) could comprehensively interrogate its genetic drivers, assigning a specific molecular subtype in >90% of patients. However, study groups have only started to use RNA-Seq. For broader clinical use, technical, quality control, and appropriate performance validation are needed. We describe the development and validation of an RNA-Seq workflow for subtype classification, TPMT/NUDT15/TP53 variant discovery, and immunoglobulin heavy chain (IGH) disease clone identification for Malaysia-Singapore acute lymphoblastic leukemia (ALL) 2020. We validated this workflow in 377 patients in our preceding Malaysia-Singapore ALL 2003/Malaysia-Singapore ALL 2010 studies and proposed the quality control measures for RNA quality, library size, sequencing, and data analysis using the International Organization for Standardization 15189 quality and competence standard for medical laboratories. Compared with conventional methods, we achieved >95% accuracy in oncogene fusion identification, digital karyotyping, and TPMT and NUDT15 variant discovery. We found seven pathogenic TP53 mutations, confirmed with Sanger sequencing, which conferred a poorer outcome. Applying this workflow prospectively to the first 21 patients in Malaysia-Singapore ALL 2020, we identified the genetic drivers and IGH disease clones in >90% of patients with concordant TPMT, NUDT15, and TP53 variants using PCR-based methods. The median turnaround time was 12 days, which was clinically actionable. In conclusion, RNA-Seq workflow could be used clinically in management of B-cell ALL patients.

Identifying IGH disease clones for MRD monitoring in childhood B-cell acute lymphoblastic leukemia using RNA-Seq.

Identifying patient-specific clonal IGH/TCR junctional sequences is critical for minimal residual disease (MRD) monitoring. Conventionally these junctional sequences are identified using laborious Sanger sequencing of excised heteroduplex bands. We found that the IGH is highly expressed in our diagnostic B-cell acute lymphoblastic leukemia (B-ALL) samples using RNA-Seq. Therefore, we used RNA-Seq to identify IGH disease clone sequences in 258 childhood B-ALL samples for MRD monitoring. The amount of background IGH rearrangements uncovered by RNA-Seq followed the Zipf's law with IGH disease clones easily identified as outliers. Four hundred and ninety-seven IGH disease clones (median 2, range 0-7 clones/patient) are identified in 90.3% of patients. High hyperdiploid patients have the most IGH disease clones (median 3) while DUX4 subtype has the least (median 1) due to the rearrangements involving the IGH locus. In all, 90.8% of IGH disease clones found by Sanger sequencing are also identified by RNA-Seq. In addition, RNA-Seq identified 43% more IGH disease clones. In 69 patients lacking sensitive IGH targets, targeted NGS IGH MRD showed high correlation (R = 0.93; P = 1.3 × 10-14), better relapse prediction than conventional RQ-PCR MRD using non-IGH targets. In conclusion, RNA-Seq can identify patient-specific clonal IGH junctional sequences for MRD monitoring, adding to its usefulness for molecular diagnosis in childhood B-ALL.