Inhibition of Tumor Cells Proliferation and Migration by the Flavonoid Furin Inhibitor Isolated From Oroxylum indicum
Bibliographic record
Abstract
BACKGROUND: The medicinally active plant Oroxylum indicum (OI) has drawn considerable research interest because of its many observed biological activities. Of particular interest is its antitumorigenic activity. The plant is a rich source of flavonoids and their glycosides. Recently flavonoids have been described as inhibitors of kexin-type proteases of superfamily Proprotein Convertase Subtilisin/ Kexins (PCSKs) which have been implicated in tumor growth and malignancy. These enzymes particularly furin (PCSK3) cleaves inactive precursor growth factors into their mature forms that promote tumor growth. As a result, finding furin-inhibitors became of high interest in cancer research. In this regard, the plant OI with known anticancer activities may provide an important source. OBJECTIVE: The objective of this study is to examine and compare anti-tumorigenic activity of furin inhibitory flavonoid compounds from OI. RESULTS: Studies were conducted to evaluate the effect on CT-26 cell proliferation and migration of 4 flavonoids baicalein, chrysin, oroxylin-A and its glycoside isolated from OI. Data revealed that baicalein exhibited most potent inhibitory effect on proliferation and migration on the analyzed tumor cell line. Baicalein at 10 μM completely blocked the proliferation even after 5 days. The results are consistent with the observed in vitro anti-furin activity of baicalein as measured against a fluorogenic peptide and pro-hVEGF-C as substrates. Mature VEGF-C is a strong indicator and biomarker of tumor progression and therefore the antifurin activity may explain the observed anticancer properties of baicalein. Since baicalein is the major constituent of OI, our data provided scientific rationale for the observed anticancer activity of OI and also offered a new lead molecule for future exploration as potential antitumor agents.
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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) | 0.002 | 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".