MEF2C opposes Notch in lymphoid lineage decision and drives leukemia in the thymus
Bibliographic record
Abstract
Rearrangements that drive ectopic MEF2C expression have recurrently been found in patients with human early thymocyte progenitor acute lymphoblastic leukemia (ETP-ALL). Here, we show high levels of MEF2C expression in patients with ETP-ALL. Using both in vivo and in vitro models of ETP-ALL, we demonstrate that elevated MEF2C expression blocks NOTCH-induced T cell differentiation while promoting a B-lineage program. MEF2C activates a B cell transcriptional program in addition to RUNX1, GATA3, and LMO2; upregulates the IL-7R; and boosts cell survival by upregulation of BCL2. MEF2C and the Notch pathway, therefore, demarcate opposite regulators of B- or T-lineage choices, respectively. Enforced MEF2C expression in mouse or human progenitor cells effectively blocks early T cell differentiation and promotes the development of biphenotypic lymphoid tumors that coexpress CD3 and CD19, resembling human mixed phenotype acute leukemia. Salt-inducible kinase (SIK) inhibitors impair MEF2C activity and alleviate the T cell developmental block. Importantly, this sensitizes cells to prednisolone treatment. Therefore, SIK-inhibiting compounds such as dasatinib are potentially valuable additions to standard chemotherapy for human ETP-ALL.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".