Molecular Plasticity Results in Oncofetal Reprogramming and Therapeutic Vulnerabilities in Juvenile Myelomonocytic Leukemia
Bibliographic record
Abstract
Persistent fetal gene expression in childhood neoplasms is usually explained by a maturation block originating in the prenatal phase. In contrast, reactivation of fetal genes in adult malignancies is considered a consequence of oncofetal reprogramming (OFR) and is associated with aggressive disease. By reconstructing epigenetic ontogeny in juvenile myelomonocytic leukemia (JMML), we identified a postnatal maturation state of JMML stem cells with high transcriptional plasticity indicative of OFR in high-risk disease. Similarly, postnatal activation of oncogenic signaling by inducible Ptpn11E76K mutation in mice triggered molecular plasticity and reactivation of fetal gene expression. Integrative multi-omics analysis revealed aberrant CD52 expression as a feature of high-risk JMML stem cells. Anti-CD52 treatment depleted JMML stem cells and blocked disease propagation in xenograft models. Our results challenge the prevailing maturation block model of pediatric leukemogenesis and establish RAS-associated stem cell plasticity as a determinant of OFR and potential therapeutic vulnerabilities in high-risk JMML. SIGNIFICANCE: Persistent fetal gene expression in pediatric malignancies is considered a consequence of prenatal maturation blockade. In this study, we demonstrate that oncogenic PTPN11 mutations enhance cellular plasticity. This leads to partial restoration of fetal molecular programs, creating new therapeutically exploitable vulnerabilities. See related commentary by Miao and Xu, pp. 168.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".