Interactive Effects of Flaxseed and Flaxseed Oil and Trastuzumab on the Growth of Breast Tumors Overexpressing HER2
Bibliographic record
Abstract
Trastuzumab (TRAS), a first line therapy for human epidermal growth factor receptor 2 (HER2)-overexpressing breast cancer, is limited by innate and acquired resistance. Approaches to enhance TRAS effectiveness and prevent resistance are needed. Flaxseed (FS) contains high levels of lignans and oil (FSO) rich in the n-3 polyunsaturated fatty acid α-linolenic acid (ALA). FS is commonly consumed by breast cancer patients and has demonstrated anticancer effects. This thesis determined whether FS, FSO and ALA, alone and combined with TRAS, could reduce the growth of HER2-overexpressing breast cancer and explored potential mechanisms with focus on HER2 signaling. Dietary FS and FSO alone did not affect growth of HER2-overexpressing, estrogen receptor (ER) positive breast tumors (BT-474) in athymic mice; however, FSO enhanced TRAS effectiveness in reducing tumor growth and cell proliferation and increasing apoptosis. Dietary FSO reduced biomarkers of HER2 signaling (pHER2, pAkt/Akt, pMAPK/MAPK). Tumor levels of ALA and its metabolites eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) were elevated in FS and FSO-fed mice while conversion of ALA to EPA and DHA did not occur in BT-474 cells in vitro. Using concentrations derived from in vivo studies, ALA and DHA, alone and combined with TRAS, reduced BT-474 cell growth in vitro but only DHA reduced biomarkers of HER2 signaling (pAkt/Akt and pMAPK/MAPK). To further understand ALA mechanisms, it was tested in MCF-7 cells (ER+, low HER2) and was shown to affect the expression of ER-related signaling biomarkers. ALA did not prevent the development of TRAS resistance but reduced the growth of TRAS-resistant BT-474 derivatives and the TRAS-resistant UACC-732 cells. Together, these findings improve the understanding of the effects and mechanisms of FS and its components, particularly ALA in breast cancer and suggest that ALA-rich FSO may be a cost-effective complementary treatment for women with breast cancer being treated with TRAS.
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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 | 0.000 | 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) | 0.001 | 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".