Genomic analyses have redefined the molecular subgrouping of pediatric acute lymphoblastic leukemia (ALL). Molecular subgroups guide risk-stratification and targeted therapies, but outcomes of recently identified subtypes are often unclear, owing to limited cases with comprehensive profiling and cross-protocol studies. We developed a machine learning tool (ALLIUM) for the molecular subclassification of ALL in retrospective cohorts as well as for up-front diagnostics. ALLIUM uses DNA methylation and gene expression data from 1131 Nordic ALL patients to predict 17 ALL subtypes with high accuracy. ALLIUM was used to revise and verify the molecular subtype of 280 cases with undefined/B-other molecular phenotype, resulting in a single revised subtype for 85.4% of these cases. Our study shows the power of combining DNA methylation and gene expression data for resolving ALL subtypes and provides the first comprehensive population-based retrospective cohort study of molecular subtype frequencies in the Nordic countries, identifying subgroups with differential survival outcomes.
Pediatric acute myeloid leukemia (AML) is a heterogeneous disease composed of clinically relevant subtypes defined by recurrent cytogenetic aberrations. The majority of the aberrations used in risk grouping for treatment decisions are extensively studied, but still a large proportion of pediatric AML patients remain cytogenetically undefined and would therefore benefit from additional molecular investigation. As aberrant epigenetic regulation has been widely observed during leukemogenesis, we hypothesized that DNA methylation signatures could be used to predict molecular subtypes and identify signatures with prognostic impact in AML. To study genome-wide DNA methylation, we analyzed 123 diagnostic and 19 relapse AML samples on Illumina 450k DNA methylation arrays. We designed and validated DNA methylation-based classifiers for AML cytogenetic subtype, resulting in an overall test accuracy of 91%. Furthermore, we identified methylation signatures associated with outcome in t(8;21)/RUNX1-RUNX1T1, normal karyotype, and MLL/KMT2A-rearranged subgroups (p < 0.01). Overall, these results further underscore the clinical value of DNA methylation analysis in AML.
Purpose of the study: This study was aimed at identifying epigenome signature associated with risk of pediatric leukemia and uncovering molecular precursors of leukemia at birth in the blood of children before they develop the disease. Pediatric cancer is the leading cause of disease-related mortality in children and adolescents, with increasing incidence worldwide and lifelong sequelae in survivors. The most common form is leukemia, the causes of which are largely unknown. Growing evidence points to an origin in utero, when global redistribution of the epigenome modifications occurs driving tissue differentiation. Here, we sought to identify genome-wide differentially methylated genes at birth in newborns who later developed pediatric precursor B-cell ALL (pre-B ALL), compared with those who did not. Experimental procedures: Epigenome-wide DNA methylation was profiled in neonatal blood, with follow-up to pediatric pre-B ALL, using double-blinded analyses between prospective cohorts extending from birth to diagnosis and retrospective studies backtracking from clinical disease to birth. Validation was done using an independent technology and population (totaling 317 cases and 483 control) and complemented with pan-tissue methylation-stability (n=5,023 tissues; 30 types) and methylation-expression (n=2,294 tissues; 26 types) analyses. At diagnosis, methylation analysis was performed in leukemia tissues from pre-B ALL patients (n=644) with at least ten-year follow-up. Results: We found a limited number of loci (among which an imprinted tumor suppressor gene) as being significantly hypermethylated at birth in nested cases relative to controls in all tested populations, including European and Hispanic ancestries. Some DMRs were found to be stable over follow-up years after birth and across surrogate blood and target bone marrow tissues. Differential methylation was found to be associated with a change in gene expression and with worse pre-B ALL patient survival, supporting a functional and translational role for differential methylation. Conclusions: Our results provide proof-of-concept to detect at birth epigenetic alterations predisposing to childhood leukemia, reproducible in three continents and two ethnicities. DNA methylation alterations evident before diagnosis could be precursors of pediatric pre-B ALL development and actionable targets for risk assessment and prognosis. Citation Format: Akram Ghantous, Semira Gonseth Nusslé, Farah Nassar, Natalia Spitz, Alexei Novoloaca, Olga Krali, Ritu Roy, Shaobo Li, Maxime Caron, Lilys Lam, Peter Daniel Fransquet, John Casement, John Strathdee, Mark S. Pearce, Helen M. Hansen, Adam J. De Smith, Daniel Sinnett, Siri Eldevik Håberg, Jill McKay, Jessica Nordlund, Per Magnus, Terence Dwyer, Richard Saffery, Joseph Leo Wiemels, Monica Cheng Munthe-Kaas, Zdenko Herceg. Epigenome-wide DNA methylation alterations precede diagnosis since birth and affect prognosis of pediatric B-cell acute lymphoblastic leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB362.
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