An Aurora kinase A-BOD1L1-PP2A B56 Axis promotes chromosome segregation fidelity
Bibliographic record
Abstract
Summary Cancer cells are often aneuploid and frequently display elevated rates of chromosome mis-segregation in a phenomenon called chromosomal instability (CIN). CIN is commonly caused by hyperstable kinetochore-microtubule (K-MT) attachments that reduces the efficiency of correction of erroneous K-MT attachments. We recently showed that UMK57, a chemical agonist of MCAK (alias KIF2C) improves chromosome segregation fidelity in CIN cancer cells although cells rapidly develop adaptive resistance. To determine the mechanism of resistance we performed unbiased proteomic screens which revealed increased phosphorylation in cells adapted to UMK57 at two Aurora kinase A phosphoacceptor sites on BOD1L1 (alias FAM44A). BOD1L1 depletion or Aurora kinase A inhibition eliminated resistance to UMK57 in CIN cancer cells. 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. Thus, an Aurora kinase A-BOD1L1-PP2A axis promotes faithful chromosome segregation during mitosis. (175 words)
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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) | 0.003 | 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".