Notch Signaling Promotes Mature T-Cell Lymphomagenesis
Bibliographic record
Abstract
Peripheral T-cell lymphomas (PTCL) are agressive lymphomas that develop from mature T cells. The most common PTCLs are genetically, molecularly, and clinically diverse and are generally associated with dismal outcomes. While Notch signaling plays a critically important role in both the development of immature T cells and their malignant transformation, its role in PTCL is poorly understood, despite the increasingly appreciated function of Notch in regulating the proliferation and differentiation of mature T cells. Here, we demonstrate that Notch receptors and their Delta-like family ligands (DLL1/DLL4) play a pathogenic role in PTCL. Notch1 activation was observed in common PTCL subtypes, including PTCL-not otherwise specified (NOS). In a large cohort of PTCL-NOS biopsies, Notch1 activation was significantly associated with surrogate markers of proliferation. Complementary genetically engineered mouse models and spontaneous PTCL models were used to functionally examine the role of Notch signaling, and Notch1/Notch2 blockade and pan-Notch blockade using dominant-negative MAML significantly impaired the proliferation of malignant T cells and PTCL progression in these models. Treatment with DLL1/DLL4 blocking antibodies established that Notch signaling is ligand-dependent. Together, these findings reveal a role for ligand-dependent Notch signaling in driving peripheral T-cell lymphomagenesis. SIGNIFICANCE: This work demonstrates that ligand-dependent Notch activation promotes the growth and proliferation of mature T-cell lymphomas, providing new therapeutic strategies for this group of aggressive lymphomas.
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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".