β-catenin mediates growth defects induced by centrosome loss in a subset of APC mutant colorectal cancer independently of p53
Bibliographic record
Abstract
Colorectal cancer is the third most common cancer and the second leading cause of cancer-related deaths worldwide. The centrosome is the main microtubule-organizing center in animal cells and centrosome amplification is a hallmark of cancer cells. To investigate the importance of centrosomes in colorectal cancer, we induced centrosome loss in normal and cancer human-derived colorectal organoids using centrinone B, a Polo-like kinase 4 (Plk4) inhibitor. We show that centrosome loss represses human normal colorectal organoid growth in a p53-dependent manner in accordance with previous studies in cell models. However, cancer colorectal organoid lines exhibited different sensitivities to centrosome loss independently of p53. Centrinone-induced cancer organoid growth defect/death positively correlated with a loss of function mutation in the APC gene, suggesting a causal role of the hyperactive WNT pathway. Consistent with this notion, β-catenin inhibition using XAV939 or ICG-001 partially prevented centrinone-induced death and rescued the growth two APC-mutant organoid lines tested. Our study reveals a novel role for canonical WNT signaling in regulating centrosome loss-induced growth defect/death in a subset of APC-mutant colorectal cancer independently of the classical p53 pathway.
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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".