Conjugated Linoleic Acid Decreases MCF‐7 Human Breast Cancer Cell Growth and Insulin‐Like Growth Factor‐1 Receptor Levels
Bibliographic record
Abstract
In vitro work suggests that conjugated linoleic acid (CLA) isomers (c9,t11 and t10,c12) are cytotoxic to human breast cancer cells, however the mechanism remains unknown. Using human MCF-7 breast cancer cells, we examined the effects of c9,t11 and t10,c12 CLA compared to oleic acid (OA), linoleic acid (LA), or untreated cells on cell membrane phospholipid composition, cell survival, and the insulin-like growth factor-I (IGF-I) and the downstream insulin receptor substrate-1 (IRS-1). Both CLA isomers were incorporated into membrane phospholipids (p < 0.05). Compared to untreated cells, c9,t11 or t10,c12 CLA significantly reduced the metabolic activity of IGF-I stimulated MCF-7 cells, increased lactate dehydrogenase (LDH) release, and decreased cellular concentrations of the IGF-I receptor (IGF-IR) and insulin receptor substrate-1 (p < 0.05). Incubation with t10,c12 CLA also reduced the levels of phosphorylated IGF-1R. The effects on all of these measures were greater (p < 0.05) for t10,c12 CLA compared to c9,t11 CLA. There were few differences between LA-treated and c9,t11 CLA-treated cells, whereas cellular metabolic activity, LDH release, and IGF-IR concentrations differed between t10,c12 CLA-treated and LA-treated cells (p < 0.05). OA stimulated growth compared to the untreated condition (p < 0.05). In summary, this study demonstrated that the t10,c12 CLA isomer inhibits growth of MCF-7 cells and suggested that this may be mediated through incorporation into cellular phospholipids and interference with the function of IGF-I and related signaling proteins.
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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 | 0.001 |
| 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".