Chemical Enhancers of Cytokine Signaling that Suppress Microfilament Turnover and Tumor Cell Growth
Bibliographic record
Abstract
The transforming growth factor-beta (TGF-beta) family of cytokines regulates cell proliferation, morphogenesis, and specialized cell functions in metazoans. Herein, we screened a compound library for modifiers of TGF-beta signaling in NMuMG epithelial cells using a cell-based assay to measure Smad2/3 nuclear translocation. We identified five enhancers of TGF-beta signaling that share a core structure of diethyl 2-(anilinomethylene)malonate (DAM), and D(50) values of 1 to 4 micromol/L. Taking advantage of the Mgat5 mutant phenotype of accelerated receptor loss to endocytosis, we determined that DAM-1976 restored the sensitivity of Mgat5(-/-) carcinoma cells to both TGF-beta and epidermal growth factor (EGF). In Mgat5 mutant and wild-type carcinoma cells, DAM-1976 enhanced and prolonged TGF-beta- and EGF-dependent Smad2/3 and Erk activation, respectively. DAM-1976 reduced ligand-dependent EGF receptor endocytosis, actin microfilament turnover, and cell spreading, suggesting that the compound attenuates vesicular trafficking. Hyperactivation of intracellular signaling has the potential to suppress tumor cell growth and, in this regard, DAM-1976 represents a new pharmacophore that increases basal activation of Smad2/3 and Erk, inhibits microfilament remodeling, and suppresses carcinoma cell growth.
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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".