Docosahexaenoic acid (DHA) supplementation attenuates changes in the concentration, phenotype, and response of immune peripheral blood cells in breast cancer patients undergoing neoadjuvant therapy. Secondary findings from the DHA-WIN trial
Bibliographic record
Abstract
BACKGROUND: Breast cancer neoadjuvant therapy may negatively impact the immune system. As a secondary outcome of the docosahexaenoic acid (DHA) for women with breast cancer in the neoadjuvant setting (DHA-WIN trial), we sought to assess the effects of an intervention with DHA on parameters of immune function of women undergoing neoadjuvant therapy. METHODS: Women with early-stage breast cancer in the neoadjuvant setting were recruited for the DHA-WIN trial and randomly assigned to receive either 4.4 g/day of DHA or a placebo for 18 weeks in conjunction with their neoadjuvant chemotherapy for breast cancer. Venous blood was collected to isolate peripheral blood mononuclear cells. Immune parameters were assessed by measuring white blood cell concentration, flow cytometry, and cytokines concentration after mitogen-stimulated immune response. RESULTS: In the placebo group the proportion of T cells (CD3 +), and functionally active monocytes (CD14 + HLA-DR +) was reduced at the last cycle of chemotherapy (15 weeks) but remained constant in the DHA group (P interaction < 0.05). The neutrophil-to-lymphocyte ratio (NLR) was maintained in the DHA group but increased in the placebo at the end of chemotherapy (P-interaction = 0.02). An increase in this ratio was associated with lower chance of achieving pathological complete response (OR = 0.32, 95% CI [0.14,0.16], P = 0.01). After 15 weeks of therapy, the DHA-supplemented group had higher concentrations of stimulated cytokines IL-4, IL-10, and the T helper type 1 cytokine IFN-γ after phytohemagglutinin (PHA) challenge, and higher concentrations of TNF-α and IFN-γ cytokines after lipopolysaccharide exposure (P < 0.05). CONCLUSION: Supplementing DHA during breast cancer neoadjuvant chemotherapy improved systemic immune function by attenuating changes in blood cell concentrations, preventing depletion of immune cells, and enhancing ex vivo cytokine secretion after stimulation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".