An Aurora kinase A-BOD1L1-PP2A B56 axis promotes chromosome segregation fidelity
Bibliographic record
Abstract
Cancer cells are often aneuploid and frequently display elevated rates of chromosome mis-segregation, called chromosomal instability (CIN). CIN is caused by hyperstable kinetochore-microtubule (K-MT) attachments that reduce the correction efficiency of erroneous K-MT attachments. UMK57, a chemical agonist of the protein MCAK (mitotic centromere-associated kinesin), improves chromosome segregation fidelity in CIN cancer cells by destabilizing K-MT attachments, but cells rapidly develop resistance. To determine the mechanism, we performed unbiased screens, which revealed increased phosphorylation in cells adapted to UMK57 at Aurora kinase A phosphoacceptor sites on BOD1L1 (protein biorientation defective 1-like-1). BOD1L1 depletion or Aurora kinase A inhibition eliminated resistance to UMK57. BOD1L1 localizes to spindles/kinetochores during mitosis, interacts with the PP2A phosphatase, and regulates phosphorylation levels of kinetochore proteins, chromosome alignment, mitotic progression, and fidelity. Moreover, the BOD1L1 gene is mutated in a subset of human cancers, and BOD1L1 depletion reduces cell growth in combination with clinically relevant doses of Taxol or Aurora kinase A inhibitor.
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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) | 0.002 | 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".