Regulation of Metformin Response by Breast Cancer Associated Gene 2
Bibliographic record
Abstract
Adenosine monophosphate-activated protein kinase (AMPK), a master regulator of cellular energy homeostasis, has emerged as a promising molecular target in the prevention of breast cancer. Clinical trials using the United States Food and Drug Administration (FDA)-approved, AMPK-activating, antidiabetic drug metformin are promising in this regard, but the question of why metformin is protective for some women but not others still remains. Breast cancer associated gene 2 (BCA2/Rabring7/RNF115), a novel Really Interesting New Gene (RING) finger ubiquitin E3 ligase, is overexpressed in >50% of breast tumors. Herein, we report that BCA2 is an endogenous inhibitor of AMPK activation in breast cancer cells and that BCA2 inhibition increases the efficacy of metformin. BCA2 overexpression inhibited both basal and inducible Thr172 phosphorylation/activation of AMPKα1, while BCA2-specific small interfering RNA (siRNA) enhanced phosphorylated AMPKα1 (pAMPKα1). The AMPK-suppressive function of BCA2 requires its E3 ligase-specific RING domain, suggesting that BCA2 targets some protein controlling (de)phosphorylation of AMPKα1 for degradation. Activation of AMPK by metformin triggered a growth inhibitory signal but also increased BCA2 protein levels, which correlated with AKT activation and could be curbed by an AMPK inhibitor, suggesting a potential feedback mechanism from pAMPKα1 to pAkt to BCA2. Finally, BCA2 siRNA, or inhibition of its upstream stabilizing kinase AKT, increased the growth inhibitory effect of metformin in multiple breast cancer cell lines, supporting the conclusion that BCA2 weakens metformin's efficacy. Our data suggest that metformin in combination with a BCA2 inhibitor may be a more effective breast cancer treatment strategy than metformin alone.
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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) | 0.001 | 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 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".