The Role of Omega-3 Polyunsaturated Fatty Acids in Modulating Inflammation and Breast Cancer: A Systematic Review of In Vitro, Animal, and Human Studies
Bibliographic record
Abstract
Abstract Purpose of Review Inflammation is a hallmark of breast cancer (BC), influencing the tumor microenvironment (TME), immune evasion and tumor growth. N-3 polyunsaturated fatty acids (PUFA), particularly eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), have anti-inflammatory and immunomodulatory effects, potentially mediated through anti-inflammatory and immune pathways. Evidence is varied by study design, dosage, and formulations, making it difficult to identify consistent mechanisms and therapeutic potential. Therefore, this systematic review aims to provide a comprehensive assessment of the biological and mechanistic effects of n-3 PUFA on inflammation in BC. Methods A systematic search was conducted on PubMed, Web of Science, and the GOED (Global Organization for EPA and DHA) Clinical Study Database to identify preclinical and clinical studies investigating the effects of n-3 PUFA on inflammation and immune function in BC. Eligible studies were selected using predefined inclusion criteria (PROSPERO CRD42024499082) and assessed for risk of bias using Cochrane Handbook guidance. Primary outcomes included changes in cytokines, tumor-infiltrating immune cells, and inflammatory signaling pathways. Results Of the 860 articles screened, 67 met the inclusion criteria. Across study types, n-3 PUFA demonstrated significant anti-inflammatory and anti-tumoral effects. Clinical studies showed IL-6 levels decreased by 50–70% with n-3 PUFA treatment. Preclinical studies reported significant reductions in proinflammatory cytokines (IL-6, TNF-α, CCL2/MCP-1), alongside increases in non-inflammatory cytokines (IL-10, IL-2) and a 57–90% reduction in lipid mediators (PGE 2 ) and associated enzymes (COX-2) with n-3 PUFA treatment. In vitro findings showed large decreases (-40-80%) in NF-κB and matrix metalloproteinase (MMP-2, -9) activity with n-3 PUFA treatment. Variability in n-3 PUFA dose, form, and outcomes was noted across studies. Conclusions n-3 PUFA exhibit anti-inflammatory and immunomodulatory effects in BC, highlighting their potential as adjuvant therapies to modulate the TME. Standardized research methodologies and clinical trials are needed to clarify dose-response relationships and therapeutic applications.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".