<i>c-Myc</i> is an important direct target of Notch1 in T-cell acute lymphoblastic leukemia/lymphoma
Bibliographic record
Abstract
Human acute T-cell lymphoblastic leukemias and lymphomas (T-ALL) are commonly associated with gain-of-function mutations in Notch1 that contribute to T-ALL induction and maintenance. Starting from an expression-profiling screen, we identified c-myc as a direct target of Notch1 in Notch-dependent T-ALL cell lines, in which Notch accounts for the majority of c-myc expression. In functional assays, inhibitors of c-myc interfere with the progrowth effects of activated Notch1, and enforced expression of c-myc rescues multiple Notch1-dependent T-ALL cell lines from Notch withdrawal. The existence of a Notch1-c-myc signaling axis was bolstered further by experiments using c-myc-dependent murine T-ALL cells, which are rescued from withdrawal of c-myc by retroviral transduction of activated Notch1. This Notch1-mediated rescue is associated with the up-regulation of endogenous murine c-myc and its downstream transcriptional targets, and the acquisition of sensitivity to Notch pathway inhibitors. Additionally, we show that primary murine thymocytes at the DN3 stage of development depend on ligand-induced Notch signaling to maintain c-myc expression. Together, these data implicate c-myc as a developmentally regulated direct downstream target of Notch1 that contributes to the growth of T-ALL cells.
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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 | 0.001 |
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".