Oleate Promotes the Proliferation of Breast Cancer Cells via the G Protein-coupled Receptor GPR40
Bibliographic record
Abstract
Evidence from epidemiological studies and animal models suggests a link between high levels of dietary fat intake and risk of breast cancer. In addition, obesity, in which circulating lipids are elevated, is associated with increased risk of various cancers. Relative to this point, we previously showed that oleate stimulates the proliferation of breast cancer cells and that phosphatidylinositol 3-kinase plays a role in this process. Nonetheless, questions remain regarding the precise mechanism(s) by which oleate promotes breast cancer cell growth. Pharmacological inhibitors of the GTP-binding proteins G(i)/G(o), phospholipase C, Src, and mitogenic-extracellular signal-regulated kinase 1/2 (MEK 1/2) decreased oleate-induced [3H]thymidine incorporation in the breast cancer cell line MDA-MB-231. In addition, oleate caused a rapid and transient rise in cytosolic Ca2+ and an increase in protein kinase B phosphorylation. Overexpressing in these cells the G protein-coupled receptor GPR40, a fatty acid receptor, amplified oleate-induced proliferation, whereas silencing the GPR40 gene using RNA interference decreased it. Overexpressing GPR40 in T47D and MCF-7 breast cancer cells that are poorly responsive to oleate allowed a robust proliferative action of oleate. The data indicate that the phospholipase C, MEK 1/2, Src, and phosphatidylinositol 3-kinase/protein kinase B signaling pathways are implicated in the proliferative signal induced by oleate and that these effects are mediated at least in part via the G protein-coupled receptor GPR40. The results suggest that GPR40 is implicated in the control of breast cancer cell growth by fatty acids and that GPR40 may provide a link between fat and cancer.
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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) | 0.002 | 0.001 |
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".