Docosahexanoic Acid Improves Chemotherapy Efficacy by Inducing CD95 Translocation to Lipid Rafts in ER<sup>−</sup> Breast Cancer Cells
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Bibliographic record
Abstract
Docosahexanoic acid (DHA) and eicosapentanoic acid (EPA) have been shown to possess anti-carcinogenic properties in mammary cancers, both in vitro and in vivo. The objective of this study was to investigate the effect of treating three different breast cancer cell lines with DHA or EPA on cellular growth, chemotherapy efficacy, and CD95 expression and localization in the cell. MDA-MB-231, MCF-7 and SKBr-3 cells were incubated with EPA or DHA with or without chemotherapy agents [doxorubicin (dox), Herceptin]. Cell growth was assessed by WST-1 assay and CD95 expression was investigated using flow cytometry, Western blotting and confocal microscopy. DHA and EPA inhibited the growth of all three breast cancer cell lines in a dose-dependent fashion (P < 0.05). DHA, and to a lesser extent EPA, induced the movement and raft clustering of CD95 in the cell membrane (via confocal microscopy) and the surface expression (via flow cytometry) in MDA-MB-231 cells. Neither fatty acid altered the growth/metabolic activity of the non-transformed MCF-12A breast cell line. Pre-treatment with DHA, but not EPA, improved the efficacy of dox in estrogen receptor negative MDA-MB-231 cells (P < 0.05), but not in the other two cell lines. Pre-treating cells with DHA increased CD95 surface expression (threefold) and the plasma membrane raft content of CD95 (2fold) and FADD (>4-fold) after dox treatment, compared to dox treatment alone (P < 0.05). This study demonstrated that pre-treatment of estrogen receptor negative MDA-MB-231 cells with DHA increased the anti-cancer effects of dox and presents evidence to suggest that this may be mediated in part by CD95-induced apoptosis.
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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 | 0.000 | 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) | 0.000 | 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 it