The matricellular protein <scp>CCN3</scp> regulates <scp>NOTCH1</scp> signalling in chronic myeloid leukaemia
Bibliographic record
Abstract
Deregulated NOTCH1 has been reported in lymphoid leukaemia, although its role in chronic myeloid leukaemia (CML) is not well established. We previously reported BCR-ABL down-regulation of a novel haematopoietic regulator, CCN3, in CML; CCN3 is a non-canonical NOTCH1 ligand. This study characterizes the NOTCH1–CCN3 signalling axis in CML. In K562 cells, BCR-ABL silencing reduced full-length NOTCH1 (NOTCH1-FL) and inhibited the cleavage of NOTCH1 intracellular domain (NOTCH1-ICD), resulting in decreased expression of the NOTCH1 targets c-MYC and HES1. K562 cells stably overexpressing CCN3 (K562/CCN3) or treated with recombinant CCN3(rCCN3) showed a significant reduction in NOTCH1 signalling (> 50% reduction in NOTCH1-ICD, p < 0.05).Gamma secretase inhibitor (GSI), which blocks NOTCH1 signalling, reduced K562/CCN3 colony formation but increased that of K562/control cells. GSI combined with either rCCN3 or imatinib reduced K562 colony formation with enhanced reduction of NOTCH1 signalling observed with combination treatments. We demonstrate an oncogenic role for NOTCH1 in CML and suggest that BCR-ABL disruption of NOTCH1–CCN3 signalling contributes to the pathogenesis of CML.
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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".