Determination of the Relative Efficacy of Eicosapentaenoic Acid and Docosahexaenoic Acid for Anti-Cancer Effects in Human Breast Cancer Models
Bibliographic record
Abstract
Epidemiological studies have associated high fish oil consumption with decreased risk of breast cancer (BC). n-3 long chain polyunsaturated fatty acids (n-3 LCPUFA), eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) found in fish and fish oils exert anti-cancer effects. However, few studies have examined the relative efficacy of EPA and DHA alone and in mixtures on BC subtypes. This was the objective of the present review, as this research is a necessity for the translation of findings to human health and disease. The literature suggests that DHA has a greater anti-cancer effect in triple negative BC (TNBC). In estrogen positive (ER+) BC, DHA has a greater effect on cell viability, while both fatty acids have similar effects on apoptosis and proliferation. These effects are associated with preferential uptake of DHA into TNBC lipid rafts and EPA in ER+ BC. EPA:DHA mixtures have anti-cancer activity; however, the ratio of EPA:DHA does not predict the relative incorporation of these two fatty acids into membrane lipids as EPA appears to be preferentially incorporated. In summary, DHA and EPA should be considered separately in the context of BC prevention. The elucidation of optimal EPA:DHA ratios will be important for designing targeted n-3 LCPUFA treatments.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".