HDAC inhibitor trichostatin A suppresses esophageal squamous cell carcinoma metastasis through HADC2 reduced MMP-2/9
Bibliographic record
Abstract
PURPOSE: The histone deacetylase (HDAC) inhibitor trichostatin A (TSA) has been shown to act as an anti-tumor agent; however, the effect and mechanism of TSA on the invasion of esophageal squamous cell carcinoma (ESCC) remains unknown. METHODS: To determine whether TSA suppresses the invasiveness of ESCC cell via HDAC2, the expression of HDAC2 in ESCC tissues and adjacent non-tumor tissues were compared using Western blot and immunohistochemistry. Cells were transfected with HDAC2 siRNAs and non-targeting control siRNA using Lipofectamine TM 2000. Cell invasion was investigated using a transwell assay. The protein levels of matrix metalloproteinase-2/9 (MMP-2/9) were examined by Western blot analysis. RESULTS: Expression of HDAC2 was significantly higher in ESCC than in adjacent non-tumor tissues. Additionally, the in vitro invasion assay found that both downregulation of HDAC2 expression and TSA treatment inhibited ESCC cell invasion by approximately 75%. Also, an MMP2/9-specific inhibitor sharply suppressed ESCC cell invasion. Furthermore, both downregulation of HDAC2 and treatment with TSA decreased MMP-2 and MMP-9 protein levels in ESCC cells. CONCLUSIONS: These results suggest that the inhibitory effect of TSA on cancer invasion is mediated through the suppression of HDAC2 expression, and that the reduction of MMP-2 and MMP-9 expression induced by HDAC2 may be involved in the anti-invasive effect of TSA.
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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 | 0.001 |
| 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".