Omega‐3 fatty acids decrease prostate cancer progression associated with an anti‐tumor immune response in eugonadal and castrated mice
Bibliographic record
Abstract
BACKGROUND: Several lines of evidence suggest effects of dietary fat on prostate cancer (PCa) development and progression. Targeting omega (ω)-3:ω6 fatty acids (FA) ratio could be beneficial against PCa by favorably modulating inflammation. Here, we studied the effects of ω3- and ω6-enriched diets on prostate tumor growth and inflammatory response in androgen-deprived and non-deprived conditions. METHODS: Immune-competent eugonadal and castrated C57BL/6 mice were injected with TRAMP-C2 prostate tumor cells and daily fed with ω3- or ω6-enriched diet. FA and cytokine profiles were measured in blood and tumors using gas chromatography and multiplex immunoassay, respectively. Immune cell infiltration in tumors was profiled by multicolor flow cytometry. RESULTS: ω3-enriched diet decreased prostate TRAMP-C2 tumor growth in immune-competent eugonadal and castrated mice. Cytokines associated with Th1 immune response (IL-12 [p70], IFN-γ, GM-CSF) and eosinophil recruitment (eotaxin-1, IL-5, and IL-13) were significantly elevated in tumors of ω3-fed mice. Using in vitro experiments, we confirmed ω3 FA-induced eotaxin-1 secretion by tumor cells and that eotaxin-1 secretion was regulated by androgens. Analysis of immune cell infiltrating tumors showed no major difference of immune cells' abundance between ω3- and ω6-enriched diets. CONCLUSIONS: ω3-enriched diet reduces prostate tumor growth independently of androgen levels. ω3 FA can inhibit tumor cell growth and induce a local anti-tumor inflammatory response. These findings warrant further examination of dietary ω3's potential to slow down the progression of androgen-sensitive and castrate-resistant PCa by modulating immune cell function in tumors.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".