Tranilast inhibits cell proliferation and migration and promotes apoptosis in murine breast cancer
Bibliographic record
Abstract
The malignant transformation of breast epithelium involves a number of cellular pathways, including those dependent on signaling from TGF beta. Tranilast [N-(3, 4-dimethoxycinnamonyl)-anthranilic acid] is a drug that is used in Japan to control allergic disorders in patients, and its mechanism of action involves TGF beta. In view of the multiple roles of TGF beta in tumor progression, we hypothesized in this study that tranilast impacts cell proliferation, apoptosis, and migration. Using the mouse breast cancer cell line 4T1, our studies showed that tranilast increases AKT1 phosphorylation and decreases ERK1/2 phosphorylation. Alterations in the cell cycle mediators' cyclin D1, p27, cyclin A, pRB, cyclin B, and Cdc2 were observed after exposure to tranilast, favoring cell arrest beyond the G1/S phase. Tranilast reduced tumor cell proliferation even when it was amplified by exogenous TGF beta. TGF beta-neutralizing antibody did not cause a significant decrease in cell proliferation. Tranilast treatment upregulates p53, induces PARP cleavage in vitro, consistent with a promotion of tumor cell apoptosis. TGF beta-neutralizing antibody downregulates endoglin and matrix metalloproteinases (MMP)-9 levels in vitro indicating that the tranilast effect is mediated through TGF beta modulation. Tranilast treatment results in the inhibition of cell migration and invasion. Western blot analysis of tumor lysates from tranilast-treated mice shows decreased levels of TGF beta1, endoglin, and significantly higher levels of p53 and cleaved PARP. Cleaved caspase 3 expression is significantly elevated in tranilast-treated mouse breast tumors. To conclude, tranilast induces cellular and molecular changes in murine breast cancer that can be exploited in preclinical therapeutic trials.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".