New diterpenes from the marine sponge Spongionella sp. overcome drug resistance in prostate cancer by inhibition of P-glycoprotein
Bibliographic record
Abstract
Spongian diterpenes are a group of marine natural compounds possessing various biological activities. However, their anticancer activity is still poorly studied and understood. We isolated six spongian diterpenes from the marine sponge Spongionella sp., including one new spongionellol A and five previously known molecules. The structures were elucidated using a detailed analysis MS and NMR spectra as well as by comparison with previously reported data. Two of them, namely, spongionellol A and 15,16-dideoxy-15α,17β-dihydroxy-15,17-oxidospongian-16-carboxylate-15,17-diacetate exhibited high activity and selectivity in human prostate cancer cells, including cells resistant to hormonal therapy and docetaxel. The mechanism of action has been identified as caspase-dependent apoptosis. Remarkably, both compounds were able to suppress expression of androgen receptor (AR) and AR-splice variant 7, as well as AR-dependent signaling. The isolated diterpenes effectively inhibited drug efflux mediated by multidrug-resistance protein 1 (MDR1; p-glycoprotein). Of note, a synergistic effect of the compounds with docetaxel, a substrate of p-glycoprotein, suggests resensitization of p-glycoprotein overexpressing cells to standard chemotherapy. In conclusion, the isolated spongian diterpenes possess high activity and selectivity towards prostate cancer cells combined with the ability to inhibit one of the main drug-resistance mechanism. This makes them promising candidates for combinational anticancer therapy.
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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".