Abstract LB-095: Aurora-A is elevated in cancer cells due to inactivation of EF1A2-PTEN-GSK3b regulated late S-G2 phase specific degradation pathway
Bibliographic record
Abstract
Abstract Elevated expression of Aurora kinase-A oncoprotein is detected in a subset of human cancers across different organ sites. The mechanism(s) underlying over expression of the protein in cancer cells have not been well elucidated. This study demonstrates that inactivation of a novel mechanism of EF1A2 regulated PTEN-GSK3β-SCF complex mediated Aurora-A protein degradation pathway in S-G2 phases of mitosis leads to enhanced stability/steady state level of Aurora-A in cancer cells. EEF1A2 regulates interaction of Aurora-A with activated PTEN, GSK3β, Neddylated CUL1 and FBXW7, promoting ubiquitination mediated degradation of Aurora-A that is rescued in EEF1A2 knockdown cells. Ectopic expression of EEF1A2, on the other hand, enhances formation of the complex with GSK3β mediated inactivating phosphorylation and reduction in Aurora-A protein, recapitulating the S-G2 phase events. Genetic ablation of EEF1A2 and PTEN in both in vitro cell lines and in vivo mouse models validated the results. Aurora-A over expressing mouse models of mammary carcinoma and human breast cancer tissue samples also corroborated the findings. Therapeutic targeting of PTEN-GSK3β-AKT pathway may, therefore, be effective in treating a subset Aurora-A over expressing cancers. Citation Format: Warapen Treekitkarnmongkol, Luisa Maren Solis, Kazuharu Kai, Kaori Sasai, Ignacio I. Wistuba, Aysegul A. Sahin, Kwong K. Wong, Alastair M. Thompson, Yoshimi Jltsumori, Jonathan M. Lee, Lidong Qin, Tasneem Bawa-Khalfe, Roland Rad, Catherine M. Abbott, Hiroshi Katayama, Subrata Sen. Aurora-A is elevated in cancer cells due to inactivation of EF1A2-PTEN-GSK3b regulated late S-G2 phase specific degradation pathway [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr LB-095.
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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) | 0.003 | 0.001 |
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".