Triptolide: An inhibitor of a disintegrin and metalloproteinase 10 (ADAM10) in cancer cells
Bibliographic record
Abstract
Triptolide, a diterpene triepoxide derived from Trypterygium wilfordii, is documented to have antitumor activity in a broad range of solid tumors and leukemia. The mechanisms that are involved in triptolide-mediated apoptosis or growth inhibition in cancer cells are not fully understood. We identified a disintegrin and metalloproteinase 10 (ADAM10) as a novel molecular target of triptolide using affinity chromatography and mass spectrometry. The identification was confirmed by western blot analysis using an anti-ADAM10 antibody. The expression of ADAM10 is enhanced in several tumors including leukemia and is involved in malignant cell growth and cancer progression. ADAM10 is a type 1 transmembrane glycoprotein that cleaves several plasma membrane proteins. We show that triptolide, at concentrations in the nM range, resulted in a significant decrease in ADAM10 expression followed by the appearance of ADAM10 cleaved product. Furthermore, triptolide reduced the viability of monocytic leukemic U937 cells. Triptolide treatment of MCF-7 breast cancer cells expressing ectopic ADAM10 or dominant negative ADAM10 (DN ADAM10) resulted in a decreased expression of ADAM10 with a concomitant increase in ADAM10 cleaved products. Moreover, siRNA-mediated knockdown of ADAM10 mRNA significantly affected the growth of MCF-7 cells. Interestingly, the combination of siRNA-mediated knockdown of ADAM10 mRNA expression and triptolide treatment lead to a further reduction in cell growth. Taken together, we provide evidence that ADAM10 is a novel target of triptolide, presenting a novel strategy to inhibit ADAM10 activity in tumorigenesis.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".