Somatic and Germline <i>TP53</i> Alterations in Second Malignant Neoplasms from Pediatric Cancer Survivors
Bibliographic record
Abstract
Abstract Purpose: Second malignant neoplasms (SMNs) are severe late complications that occur in pediatric cancer survivors exposed to radiotherapy and other genotoxic treatments. To characterize the mutational landscape of treatment-induced sarcomas and to identify candidate SMN-predisposing variants, we analyzed germline and SMN samples from pediatric cancer survivors. Experimental Design: We performed whole-exome sequencing (WES) and RNA sequencing on radiation-induced sarcomas arising from two pediatric cancer survivors. To assess the frequency of germline TP53 variants in SMNs, Sanger sequencing was performed to analyze germline TP53 in 37 pediatric cancer survivors from the Childhood Cancer Survivor Study (CCSS) without any history of a familial cancer predisposition syndrome but known to have developed SMNs. Results: WES revealed TP53 mutations involving p53′s DNA-binding domain in both index cases, one of which was also present in the germline. The germline and somatic TP53-mutant variants were enriched in the transcriptomes for both sarcomas. Analysis of TP53-coding exons in germline specimens from the CCSS survivor cohort identified a G215C variant encoding an R72P amino acid substitution in 6 patients and a synonymous SNP A639G in 4 others, resulting in 10 of 37 evaluable patients (27%) harboring a germline TP53 variant. Conclusions: Currently, germline TP53 is not routinely assessed in patients with pediatric cancer. These data support the concept that identifying germline TP53 variants at the time a primary cancer is diagnosed may identify patients at high risk for SMN development, who could benefit from modified therapeutic strategies and/or intensive posttreatment monitoring. Clin Cancer Res; 23(7); 1852–61. ©2016 AACR.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".