NOTCH1 dimeric signaling is essential for T-cell leukemogenesis and leukemia maintenance
Bibliographic record
Abstract
ABSTRACT: T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive malignancy that is characterized by an expansion of T-cell progenitors and DNA mutations that lead to overactive NOTCH1 signaling in >50% of T-ALL cases. Using synthetic models of human T-ALL, we report that NOTCH1 dimeric signaling was crucial for the leukemogenesis of human hematopoietic stem/progenitor cells (HSPCs) from cord blood. We also identified a Notch dimerization-dependent gene signature, including the HES4 transcription factor, which induced a proliferative advantage in human HSPCs and in Notch dimerization-dependent, patient-derived xenografts of T-ALL. Interestingly, in human T-ALL cells, HES4 enforced the expression of the Δ133p53 isoform with the concomitant block of proapoptotic p53 target genes and the induction of BCL2L1 gene expression and antiapoptotic B-cell lymphoma extra-large protein. In addition, through an integrated experimental approach that included genetically modified cell lines, RNA/chromatin immunoprecipitation sequencing, and single-cell RNA sequencing profiles of primary T-ALL samples, we revealed cell subsets with Notch dimerization-dependent gene signatures, which indirectly correlated with proapoptotic genes and directly associated with cell markers of poor clinical outcome in primary T-ALL samples. Taken together, these findings highlight the crucial role of NOTCH1 dimeric signaling in human T-cell leukemogenesis and T-ALL maintenance, suggesting that a possible benefit can be obtained with a therapeutic strategy that target NOTCH1 dimer signaling or its downstream effectors.
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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 | 0.000 |
| 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".