Chromatid cohesion defects may underlie chromosome instability in human colorectal cancers
Bibliographic record
Abstract
Although the majority of colorectal cancers exhibit chromosome instability (CIN), only a few genes that might cause this phenotype have been identified and no general mechanism underlying their function has emerged. To systematically identify somatic mutations in potential CIN genes in colorectal cancers, we determined the sequence of 102 human homologues of 96 yeast CIN genes known to function in various aspects of chromosome transmission fidelity. We identified 11 somatic mutations distributed among five genes in a panel that included 132 colorectal cancers. Remarkably, all but one of these 11 mutations were in the homologs of yeast genes that regulate sister chromatid cohesion. We then demonstrated that down-regulation of such homologs resulted in chromosomal instability and chromatid cohesion defects in human cells. Finally, we showed that down-regulation or genetic disruption of the two major candidate CIN genes identified in previous studies (MRE11A and CDC4) also resulted in abnormal sister chromatid cohesion in human cells. These results suggest that defective sister chromatid cohesion as a result of somatic mutations may represent a major cause of chromosome instability in human 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 | 0.001 | 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".