Abstract 1333: Specific RB1 mutations and risk of subsequent neoplasms among survivors of hereditary retinoblastoma.
Bibliographic record
Abstract
Abstract The retinoblastoma tumor suppressor gene (RB1) is a key regulator of cell cycle control, most notably through E2F transcription factor binding. Deregulation of RB1 is important in many cancers. Survivors of hereditary retinoblastoma, caused by a germline mutation in RB1, experience substantially elevated risks for subsequent neoplasms, particularly bone and soft tissue sarcomas and melanomas. Oncogenic RB1 mutations arise from a range of DNA alterations and occur throughout the gene. No previous study has evaluated how the specific location and functional consequences of these RB1 mutations may differentially confer risk for specific subsequent neoplasms. As part of a biomarker study nested within a long-term follow-up study of the risk of subsequent cancers in retinoblastoma survivors, we identified germline RB1 mutations in 76/80 (95%) survivors of hereditary retinoblastoma who developed at least one subsequent neoplasm and had sufficient DNA for mutation testing (median follow-up time=47 years, range 7-71 years). Survivors were classified into four groups according to whether they ever developed a soft tissue sarcoma (STS, N=47), melanoma (without STS, N=10), bone tumor (without STS, N=5), or another type of subsequent malignant neoplasm (N=14). The identified mutations were distributed throughout RB1, from the promoter through exon 25. Nonsense, frameshift, or splice mutations that resulted in premature termination of the RB1 residue sequence were identified in 51 (67%) survivors, with the remaining classified as having loss of multiple exons (N=6), loss or rearrangement of a single exon (N=5), a splice mutation (N=7), a missense mutation (N=4), or an intronic substitution with unknown consequence (N=3). Preliminary analyses indicated that RB1 mutations resulting in loss of >2 exons were more common in survivors with a subsequent STS (40/47, 85%) than those with a subsequent melanoma (6/10, 60%) or bone tumor (2/5, 40%; Fisher's exact P<0.001). In an analysis of the RB1 regions impacted by the mutation, those that affected E2F binding (including mutations affecting the E2F binding site, Domain B, or Domain C) were more common in survivors with a subsequent STS (46/47, 98%) or melanoma (9/10, 90%) than those with a bone tumor (2/5, 40%; Fisher's exact P=0.020). Further analyses will include 14 additional survivors who developed a subsequent neoplasm for whom mutation testing is ongoing, and comparison of the spectrum of RB1 mutations in these survivors to hereditary retinoblastoma survivors without a subsequent neoplasm. If confirmed, such correlations between specific RB1 mutations and subsequent neoplasm risk may inform long-term surveillance practices for hereditary retinoblastoma survivors and provide insight into the key role of RB1 in oncogenesis. Citation Format: Lindsay M. Morton, Jeannette R. Wong, Brenda L. Gallie, David H. Abramson, Johanna M. Seddon, Michael Dean, Bert Gold, Alisa M. Goldstein, Ruth A. Kleinerman, Margaret A. Tucker. Specific RB1 mutations and risk of subsequent neoplasms among survivors of hereditary retinoblastoma. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1333. doi:10.1158/1538-7445.AM2013-1333
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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 | 0.000 | 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) | 0.002 | 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".