cPLA2α mediates TGF-β-induced epithelial–mesenchymal transition in breast cancer through PI3k/Akt signaling
Bibliographic record
Abstract
A high incidence of tumor recurrence and metastasis has been reported in breast cancer patients; nevertheless, the underlying molecular mechanisms are largely unknown. Epithelial-mesenchymal transition (EMT), which is induced by transforming growth factor-β (TGF-β), has been implicated in tumorigenesis and breast cancer metastasis. EMT events are now directly associated with tumor metastasis, and this progress is dependent on the inflammatory microenvironment. Cytosolic phospholipase A2α (cPLA2α) has been shown to participate in a series of biological processes including inflammation and cancer development. However, the role and molecular mechanism of cPLA2α in breast cancer EMT and metastasis remain enigmatic. In this study, we found that cPLA2α was commonly overexpressed in most human breast cancer tissues and significantly correlated with a poor prognosis for human breast cancer. Functional studies demonstrated that cPLA2α overexpression was significantly associated with elevated migration and invasion in MDA-MB-231 and T47D cells. Conversely, reduced cPLA2α expression strongly attenuated metastasis and the EMT program of MDA-MB-231 cells. Further study found that knockdown of cPLA2α in MDA-MB-231 cells inhibited TGF-β-induced EMT through the PI3K/Akt signaling pathway. Animal experiments revealed that cPLA2α downregulation in MDA-MB-231 cells markedly restrained tumorigenesis and metastasis in vivo. This study indicates the potential role of cPLA2α in breast cancer metastasis and indicates that this molecule is a promising therapeutic target for breast cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".