Common Fragile Site Profiling in Epithelial and Erythroid Cells Reveals that Most Recurrent Cancer Deletions Lie in Fragile Sites Hosting Large Genes
Bibliographic record
Abstract
Cancer genomes exhibit numerous deletions, some of which inactivate tumor suppressor genes and/or correspond to unstable genomic regions, notably common fragile sites (CFSs). However, 70%-80% of recurrent deletions cataloged in tumors remain unexplained. Recent findings that CFS setting is cell-type dependent prompted us to reevaluate the contribution of CFS to cancer deletions. By combining extensive CFS molecular mapping and a comprehensive analysis of CFS features, we show that the pool of CFSs for all human cell types consists of chromosome regions with genes over 300 kb long, and different subsets of these loci are committed to fragility in different cell types. Interestingly, we find that transcription of large genes does not dictate CFS fragility. We further demonstrate that, like CFSs, cancer deletions are significantly enriched in genes over 300 kb long. We now provide evidence that over 50% of recurrent cancer deletions originate from CFSs associated with large genes.
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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 | 0.001 |
| 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".