DCB-3503, a Tylophorine Analog, Inhibits Protein Synthesis through a Novel Mechanism
Bibliographic record
Abstract
BACKGROUND: DCB-3503, a tylophorine analog, inhibits the growth of PANC-1 (human pancreatic ductal cancer cell line) and HepG2 (human hepatocellular cancer cell line) tumor xenografts in nude mice. The inhibition of growth leads to cancer cell differentiation instead of cell death. However, the mechanisms of action of tylophorine analogs is unknown. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we show that DCB-3503 suppresses the expression of pro-oncogenic or pro-survival proteins with short half-lives, including cyclin D1, survivin, beta-catenin, p53, and p21, without decreasing their mRNA levels. Proteasome inhibitor reversed the inhibitory effect of DCB-3503 on expression of these proteins. DCB-3503 inhibited the incorporation of radiolabeled amino acid and thymidine, and to a much lesser degree of uridine, in a panel of cell lines. The mechanism of inhibition of protein synthesis is different from that of cycloheximide (CHX) as assayed in cell culture and HeLa in vitro translation system. Furthermore, in contrast to rapamycin, DCB-3503 does not affect protein synthesis through the mTOR pathway. DCB-3503 treatment shifts the sedimentation profiles of ribosomes and mRNAs towards the polysomal fractions while diminishing monosome abundance, indicative of the inhibition of the elongation step of protein synthesis. Preferential down regulation of several studied proteins under these conditions is likely due to the relative short half-lives of these proteins. CONCLUSION/SIGNIFICANCE: The inhibitory effect of DCB-3503 on translation is apparently distinct from any of the current anticancer compounds targeting protein synthesis. Translation inhibitors with novel mechanism could complement current chemotherapeutic agents for the treatment of human cancers and suppress the occurrence of drug resistance.
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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) | 0.001 | 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".