Uev1A promotes breast cancer cell survival and chemoresistance through the AKT-FOXO1-BIM pathway
Bibliographic record
Abstract
Abstract Background Ubiquitin-conjugating enzyme variantUEV1Ais required for Ubc13-catalyzed K63-linked poly-ubiquitination that regulates several signaling pathways including NF-κB, MAPK and PI3K/AKT. Previous reports implicateUEV1Aas a potential proto-oncogene and have shown thatUEV1Apromotes breast cancer metastasis through constitutive NF-кB activation. Ubc13-Uev1A along with TARF6 can also ubiquitinate AKT but its downstream events are unclear. Methods In this study, we experimentally manipulatedUEV1expression in two typical breast cancer cell lines MDA-MB-231 and MCF7 under serum starvation conditions and monitored AKT activation and its downstream protein levels, as well as cellular sensitivity to chemotherapeutic agents. Results We found that overexpression ofUEV1Ais sufficient to activate the AKT signaling pathway that in turn inhibitsFOXO1andBIMexpression to promote cell survival under serum starvation conditions and enhances cellular resistance to chemotherapy. Consistently, experimental depletion of Uev1 in breast cancer cells inhibits AKT signaling and promotes FOXO1 and BIM expression to reduce cell survival under serum starvation stress and enhance chemosensitivity. Conclusions Uev1A promotes cell survival under serum starvation stress through the AKT-FOXO1-BIM axis in breast cancer cells, which unveals a potential therapeutic target in the treatment of breast cancers.
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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".