Sea Cucumber Derived Triterpenoid Glycoside Frondoside A: A Potential Anti-Bladder Cancer Drug
Bibliographic record
Abstract
Bladder cancer is a highly recurrent disease and a common cause of cancer-related deaths worldwide. Despite recent developments in diagnosis and therapy, the clinical outcome of bladder cancer remains poor; therefore, novel anti-bladder cancer drugs are urgently needed. Natural bioactive substances extracted from marine organisms such as sea cucumbers, scallops, and sea urchins are believed to have anti-cancer activity with high effectiveness and less toxicity. Frondoside A is a triterpenoid glycoside isolated from sea cucumber, Cucumaria frondosa. It has been demonstrated that Frondoside A exhibits anti-proliferative, anti-invasive, anti-angiogenic, anti-cancer, and potent immunomodulatory effects. In addition, CpG oligodeoxynucleotide (CpG-ODN) has also been shown to have potent anti-cancer effects in various tumors models, such as liver cancer, breast cancer, and bladder cancer. However, very few studies have investigated the effectiveness of Frondoside A against bladder cancer alone or in combination with CpG-ODN. In this study, we first investigated the individual effects of both Frondoside A and CpG-ODN and subsequently studied their combined effects on human bladder cancer cell viability, migration, apoptosis, and cell cycle in vitro, and on tumor growth in nude mice using human bladder cancer cell line UM-UC-3. To interrogate possible synergistic effects, combinations of different concentrations of the two drugs were used. Our data showed that Frondoside A decreased the viability of bladder cancer cells UM-UC-3 in a concentration-dependent manner, and its inhibitory effect on cell viability (2.5 μM) was superior to EPI (10 μM). We also showed that Frondoside A inhibited UM-UC-3 cell migration, affected the distribution of cell cycle and induced cell apoptosis in concentration-dependent manners, which effectively increased the sub-G1 (apoptotic) cell fraction. In addition, we also demonstrated that immunomodulator CpG-ODN could synergistically potentiate the inhibitory effects of Frondoside A on the proliferation and migration of human bladder cancer cell line UM-UC-3. In in vivo experiments, Frondoside A (800 μg/kg/day i.p. for 14 days) alone and in combination with CpG-ODN (1 mg/kg/dose i.p.) significantly decreased the growth of UM-UC-3 tumor xenografts, without any significant toxic side-effects; however, the chemotherapeutic agent EPI caused weight loss in nude mice. Taken together, these findings indicated that Frondoside A in combination with CpG-ODN is a promising therapeutic strategy for bladder cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.002 | 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; both teacher heads agree on what is shown here.
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".