Patterns of missplicing caused by<i>RB1</i>gene mutations in patients with retinoblastoma and association with phenotypic expression
Bibliographic record
Abstract
We have analyzed RNA from retinoblastoma patients and unaffected carriers with various RB1 gene mutations to determine the patterns of missplicing and associations with phenotypic expression. Most sequence alterations in or in the neighborhood of conserved splice signals that we tested resulted in simple exon skipping (15 mutations) or intron inclusion (new acceptor AG-sites, four mutations) as expected. Two mutations resulted in skipping of a neighboring exon (exon 11), a complex pattern indicating competition for correct lariat formation. We observed no activation of a cryptic splice site but found that a recurrent missense mutation in exon 7 creates a new splice site (two families). RT-PCR analysis enabled us to confirm the presence and to characterize the transcriptional consequences of gross insertions and deletions in the RB1 gene in six patients, including two patients with mutational mosaicism. We also used RT-PCR analysis to search for unknown mutations in 15 patients and identified three oncogenic point mutations deep in introns. Two of these mutations are recurrent thus indicating that, despite the vast extent of the introns of the RB1 gene, few bases are effective targets for oncogenic mutations. When analyzing associations between phenotypic expression (16 families) and mutational consequences we observed no link to the presence or absence of a premature termination codon in the mutant transcript. However, the location of a mutation relative to the splice sequence has a strong and consistent influence on phenotypic expression.
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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 | 0.001 |
| 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".