Cell cycle arrest and apoptosis responses of human breast epithelial cells to the synthetic organosulfur compound p-methoxyphenyl p-toluenesulfonate.
Bibliographic record
Abstract
BACKGROUND: There are several studies documenting that organosulfur compounds show promise as anticancer agents. Although some mechanisms of the antiproliferative activity of naturally occurring organosulfur compounds have been elucidated, few studies have reported the differential response of human breast cells to these compounds. MATERIALS AND METHODS: The effect of the synthetic sulfonate ester, p-methoxyphenyl p-toluenesulfonate on growth inhibitory activity depending upon the estrogen-receptor (ER), p53, bcl-2 and caspase-3 status of cells was investigated by comparing its effects on three distinct human breast cancer cell lines (MCF-7, MDA-MB-231 and MDA-MB-453) and on one normal human mammary epithelial cell line (MCF-10A). RESULTS: This sulfonate ester selectively killed cancer cells at doses of 100 microM. Flow cytometry analysis showed that treatment with p-methoxyphenyl p-toluenesulfonate caused different cell cycle responses in the four cell lines but no clear association with p53 status was observed. Apoptosis was also induced in cells harboring different levels of Bcl-2 expression, but again independently of the p53 or ER status of the cells. CONCLUSION: These results suggest that p-methoxyphenyl p-toluenesulfonate acts on multiple signaling pathways leading to growth inhibition and activation of mechanisms of cell death selectively affecting survival of breast cancer cells. Thus, p-methoxyphenyl p-toluenesulfonate is the first member of a new class of tumor-specific chemotherapeutic agents for the treatment of breast cancer.
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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".