Cohort study reveals that genomic risk profiling refines prognosis in pediatric B-ALL, indicating that genetic classification improves measurable residual disease risk stratification.
PURPOSE WHO5 (2022) classification of B-lymphoblastic leukemia (B-ALL) incorporates several novel entities requiring high-throughput sequencing for their accurate characterization. The clinical relevance of this classification in the context of contemporary measurable residual disease (MRD)–directed therapy is unclear. METHODS We analyzed 533 pediatric B-ALL uniformly treated with Indian Collaborative Childhood Leukaemia group (ICiCLe)-ALL-14 protocol as defined by WHO-2016 and reclassified them as per WHO5 using targeted sequencing, FISH, and cytogenetics. RESULTS Subtype-defining genomic abnormalities were identified in 81.2% of the cohort as per the WHO5 classification. Among the new subtypes, PAX5 alt and MEF2D -r were associated with a trend toward an inferior 3-year event-free survival (EFS) of 32.8% ( P = .003) and 33.7% ( P = .091), respectively. We developed a three-tier genomic risk stratification model incorporating 15 genomic subtypes and the IKZF1 deletion. Children with standard (SGR), intermediate (IGR), and high genomic risk (HGR) demonstrated 3-year EFS of 80.4%, 59.3%, and 45.8% ( P < .0001), and 3-year overall survival of 89.6%, 75.3%, and 62.3% ( P < .0001), respectively. Genomic risk further identified heterogeneous outcomes among ICiCLe risk groups ( P < .0001). SGR was associated with superior EFS irrespective of MRD status (3-year EFS 80.5% in postinduction [PI] MRD–negative v 80.8% PI-MRD–positive patients, P = .530). On multivariable analysis, genomic risk (hazard ratio [HR], 1.7 [95% CI, 1.41 to 2.01]; P < .0001), initial ICiCLe risk (HR, 1.3 [95% CI, 1.06 to 1.49]; P = .009), and PI-MRD (HR, 2.2 [95% CI, 1.66 to 2.90]; P < .0001) independently predicted EFS. CONCLUSION The study demonstrates the potential role of genomic risk stratification, in conjunction with MRD, in stratifying patients into clinically relevant risk categories.
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Rajpal et al. (2026) studied this question.
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