Constitutive activation of metalloproteinase ADAM10 in mantle cell lymphoma promotes cell growth and activates the TNFα/NFκB pathway
Bibliographic record
Abstract
One of the main functions of A Disintegrin and Metalloproteinase 10 (ADAM10) is to regulate the bioavailability of adhesion molecules and ligands to various cellular-signaling receptors. Constitutive activation of ADAM10 has been implicated in the pathogenesis of several types of solid tumors. In this study, we found that mantle cell lymphoma (MCL) cell lines and all 12 patient samples examined expressed the active/mature form of ADAM10. In contrast, PBMCs from healthy donors (n = 5) were negative. Using immunohistochemistry, ADAM10 was readily detectable in 20 of 23 (87%) MCL tumors, but absent in 5 reactive tonsils. Knockdown of ADAM10 using short interfering RNA (siRNA) in MCL cells significantly induced growth inhibition and cell-cycle arrest, and these changes were correlated with down-regulation of cyclin D1, up-regulation of p21(waf1), and significant reductions in the TNFα production/transcriptional activity of NFκBp65. The addition of recombinant ADAM10 to MCL cells led to the opposite biologic effects. Lastly, down-regulation of ADAM10 using siRNA enhanced the growth-suppressing effects mediated by the proteasome inhibitors MG132 and bortezomib. We conclude that constitutive activation of ADAM10 contributes to the growth of MCL and therefore inhibition of ADAM10 may be a useful strategy to enhance the response of MCL to other therapeutic agents.
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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".