Abstract LB362: Epigenome-wide DNA methylation alterations precede diagnosis since birth and affect prognosis of pediatric B-cell acute lymphoblastic leukemia
Bibliographic record
Abstract
Abstract 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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".