Abstract B114: Soy isoflavones mediated inhibition of DLD-1 human colon adenocarcinoma cells is associated with up-regulation of estrogen receptor-β expression
Bibliographic record
Abstract
Abstract B114 We have previously demonstrated that soy isoflavones elicit a colon cancer preventive effect when exposed throughout the lifetime of rats, inclusive of in utero and post-natal stages using an experimental model. We also showed that soy isoflavones increased the expression of colon tumor estrogen receptor (ER)-β, one of the main candidates in endocrine disruption during colon carcinogenesis. To further understand the relationship between the role of soy isoflavones and ER-β in colon carcinogenesis, we examined the effects of soy isoflavones in DLD-1 human colon adenocarcinoma cells in the presence of ER-β or when expression was decreased by RNA interference (siRNA) in vitro. DLD-1 cells were treated with increasing concentrations of soy isoflavones composed of genistein, daidzein and glycitein at a ratio of 1:1:0.2 representing human soy isoflavone-rich food intake. Markers of cell signaling were determined following treatment with or without soy isoflavones in the presence or absence of ER-β gene silencing. Soy isoflavones inhibited the growth of DLD-1 cells dose dependently, with an IC50 for cytotoxicity at 24.82 µg/mL and an IC50 for cell viability at 17.01 µg/mL. At sub-cytotoxic doses, soy isoflavones modulated the expression of markers associated with MAP kinase, AKT and NFκB signalling pathways, cell proliferation and cell cycle regulation, all conducive to a growth restrictive effect. A 75% knockdown of ER-β at the gene and protein level was achieved in DLD-1 cells using siRNA, and this caused a differential expression of the molecular markers studied above. Our results suggest that ER-β appears crucial in mediating the growth suppressive effects of soy isoflavones. ER-β may play an important role in the action of several endocrine disruptors including food chemical contaminants during colon carcinogenesis. Citation Information: Cancer Prev Res 2008;1(7 Suppl):B114.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".