Anisomycin inhibits angiogenesis, growth, and survival of triple-negative breast cancer through mitochondrial dysfunction, AMPK activation, and mTOR inhibition
Bibliographic record
Abstract
Aberrant upregulation of mitochondrial biogenesis is observed in breast cancer and holds potential therapeutic option. In our work, we showed that inhibition of mitochondrial function by anisomycin is effective against triple-negative breast cancer (TNBC). Anisomycin inhibits growth and induces caspase-dependent apoptosis in a panel of TNBC cell lines. Of note, anisomycin at a tolerable dose remarkably suppresses growth of TNBC in mice. In addition, anisomycin effectively targets breast cancer angiogenesis through inhibiting capillary network formation, migration, proliferation, and survival. Mechanistic studies show that although anisomycin activates p38 and JNK, their activations are not required for anisomycin's action. In contrast, anisomycin inhibits mitochondrial respiration, and decreases mitochondrial membrane potential and adenosine triphosphate (ATP) level. The inhibitory effect of anisomycin is significantly reversed in mitochondria respiration-deficient ρ0 cells. As a consequence, anisomycin activates AMPK and inhibits mammalian target-of-rapamycin signaling pathways. Our work demonstrated that anisomycin is a useful addition to the treatment armamentarium for TNBC.
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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".