PanCancer analysis of somatic mutations in repetitive regions reveals recurrent mutations in snRNA U2
Bibliographic record
Abstract
Current somatic mutation callers are biased against repetitive regions, preventing the identification of potential driver alterations in these loci. We developed a mutation caller for repetitive regions, and applied it to study repetitive non protein-coding genes in more than 2200 whole-genome cases. We identified a recurrent mutation at position c.28 in the gene encoding the snRNA U2. This mutation is present in B-cell derived tumors, as well as in prostate and pancreatic cancer, suggesting U2 c.28 constitutes a driver candidate associated with worse prognosis. We showed that the GRCh37 reference genome is incomplete, lacking the U2 cluster in chromosome 17, preventing the identification of mutations in this gene. Furthermore, the 5'-flanking region of WDR74, previously described as frequently mutated in cancer, constitutes a functional copy of U2. These data reinforce the relevance of non-coding mutations in cancer, and highlight current challenges of cancer genomic research in characterizing mutations affecting repetitive genes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".