Omega-3 Polyunsaturated Fatty Acids Time-Dependently Reduce Cell Viability and Oncogenic MicroRNA-21 Expression in Estrogen Receptor-Positive Breast Cancer Cells (MCF-7)
Bibliographic record
Abstract
The omega-3 polyunsaturated fatty acid (n-3 PUFA), α-linolenic acid (ALA), and its metabolites, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), independently reduce the growth of breast cancer cells in vitro, but the mechanisms, which may involve microRNA (miRNA), are still unclear. The expression of the oncomiR, miR-21, is reduced by DHA treatment, but the effects of ALA on miR-21, alone or combined with EPA and DHA under physiologically relevant concentrations, have not been investigated. The effects of ALA alone and +/-EPA and DHA at the blood molar ratios seen in either humans (1.0:1.0:2.5, ALA:EPA:DHA) or mice (1.0:0.4:3.1, ALA:EPA:DHA) post flaxseed oil consumption (containing ALA) were assessed in vitro in MCF-7 breast cancer cells. Cell viability and the expression of miR-21 and its molecular target, phosphatase and tension homolog (PTEN, gene and protein), at different time points, were examined. At 1, 3, 48 and 96 h ALA alone and 24 h animal ratio treatments significantly reduced MCF-7 cell viability, while 1 and 3 h ALA alone and human and animal ratio treatments all significantly reduced miR-21 expression, and 24 h animal ratio treatment reduced miR-21 expression; these effects were not associated with changes in PTEN gene or protein expressions. We showed for the first time that ALA alone or combined with EPA and DHA at levels seen in human and animal blood post-ALA consumption can significantly reduce cell viability and modulate miR-21 expression in a time- and concentration-dependent manner, with the animal ratio containing higher DHA having a greater effect. The time dependency of miR-21 effects suggests the significance of considering time as a variable in miRNA studies, particularly of miR-21.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
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".