Anti-cancer effects of baicalein in non-small cell lung cancer in-vitro and in-vivo
Bibliographic record
Abstract
BACKGROUND: Baicalein is a widely used Chinese herbal medicine derived from Scutellaria baicalenesis, which has been traditionally used as anti-inflammatory and anti-cancer therapy. In this study we examined the anti-tumour pathways activated following baicalein treatment in non-small cell lung cancer (NSCLC), both in-vitro and in-vivo. METHODS: The effect of baicalein treatment on H-460 cells in-vitro was assessed using both BrdU assay (cell proliferation) and High Content Screening (multi-parameter apoptosis assay). A xenograft nude mouse model was subsequently established using these cells and the effect of baicalein on tumour growth and survival assessed in-vivo. Tumours were harvested from these mice and histological tissue analysis carried out. VEGF, 12-lipoxygenase and microvessel density (CD-31) were assessed by immunohistochemistry (IHC), while H and E staining was carried out to assess mitotic index. Gene expression profiling was carried out on corresponding RNA samples using Human Cancer Pathway Finder Arrays and qRT-PCR, with further gene expression analysis carried out using qRT-PCR. RESULTS: Baicalein significantly decreased lung cancer proliferation in H-460 cells in a dose dependent manner. At the functional level, a dose-dependent induction in apoptosis associated with decreased cellular f-actin content, an increase in nuclear condensation and an increase in mitochondrial mass potential was observed. Orthotopic treatment of experimental H-460 tumours in athymic nude mice with baicalein significantly (p < 0.05) reduced tumour growth and prolonged survival. Histological analysis of resulting tumour xenografts demonstrated reduced expression of both 12-lipoxygenase and VEGF proteins in baicalein-treated tumours, relative to untreated. A significant (p < 0.01) reduction in both mitotic index and micro-vessel density was observed following baicalein treatment. Gene expression profiling revealed a reduction (p < 0.01) in both VEGF and FGFR-2 following baicalein treatment, with a corresponding increase (p < 0.001) in RB-1. CONCLUSION: This study is the first to demonstrate efficacy of baicalein both in-vitro and in-vivo in NSCLC. These effects may be mediated in part through a reduction in both cell cycle progression and angiogenesis. At the molecular level, alterations in expression of VEGF, FGFR-2, and RB-1 have been implicated, suggesting a molecular mechanism underlying this in-vivo effect.
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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 | 0.001 |
| 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".