Chloroethyl urea derivatives block tumour growth and thioredoxin-1 nuclear translocation
Bibliographic record
Abstract
Aryl chloroethyl ureas (CEUs) are new protein alkylating agents exhibiting anticancer activity both in vitro and in vivo. We report herein that 14C-labeled CEU derivatives, designated CEU-025 and CEU-027, covalently bind to thioredoxin-1 (TRX1). Covalent binding of these molecules slightly decreases the disulfide-reducing activity of recombinant TRX1, when compared with the effect of strong thioalkylating agents such as N-ethylmaleimide. Moreover, site-directed mutagenesis and diamide competition assays demonstrated that TRX1 cysteinyl residues are not the prime targets of CEUs. CEU-025 abrogates the nuclear translocation of TRX1 in human cancer cells. In addition, we show that CEU-025 can block TRX1 nuclear translocation induced by cisplatin. Unexpectedly, pretreatment with sublethal CEU-025 concentrations that block TRX1 nuclear translocation protected the cells against cisplatin cytotoxicity. Overexpression of TRX1 in HT1080 fibrosarcoma cells attenuated CEU-025 cytotoxicity, while its suppression using TRX1-specific siRNA increased the effects of CEU-025, suggesting that loss of function of TRX1 is involved, at least in part, in the cytotoxic activity of CEU-025. These results suggest that CEU-025 and CEU-027 exhibit anticancer activity through a novel, unique mechanism of action. The importance of TRX1 and the dependence of the cytotoxicity of CEU-025 and CEU-027 on TRX1 intracellular localization are also discussed.
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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".