In Vitro and in Vivo antitumor activity and the mechanism of siphonodictyal B in human colon cancer cells
Bibliographic record
Abstract
Liphagal, isolated from the marine sponge Aka coralliphaga, exhibits phosphatidylinositol 3-kinase alpha (PI3Kα) inhibitory activity and cytotoxic effects in human cancer cells. Siphonodictyal B, the biogenetic precursor of liphagal, also has PI3K inhibitory activity. However, its cytotoxic or antitumor activities have not been evaluated. In this study, we demonstrated that siphonodictyal B inhibits several kinases such as CDK4/6, CDK7, and PIM2 in addition to PI3K in vitro and that siphonodictyal B exhibits more potent cytotoxic effects than liphagal against human colon cancer cell lines. Furthermore, treatment with siphonodictyal B resulted in increased PARP cleavage, a larger sub-G1 fraction, and a larger annexin V-positive cell population, all of which are indicative of apoptosis induction. As a mechanism of apoptosis induction, we found that siphonodictyal B activates the p38 MAPK pathway, leading the upregulation of proapoptotic factors. Moreover, siphonodictyal B increased ROS levels, thus promoting p38 MAPK pathway activation. NAC, an ROS scavenger, almost completely reversed both the cytotoxic and p38 MAPK pathway-activating effects of siphonodictyal B. These results indicate that the p38 MAPK pathway might be involved downstream of ROS signaling as part of the mechanism of siphonodictyal B-induced apoptosis. Finally, siphonodictyal B displayed antitumor effects in a human colon cancer xenograft mouse model and increased p38 phosphorylation in tumor tissue. These results suggest that siphonodictyal B could serve as the basis of a novel anticancer drug.
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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".