Abstract 5351: Prevalence and function of p53 mutations among children with adrenocortical carcinoma (ADCC)
Bibliographic record
Abstract
Abstract Adrenocortical carcinoma (ACC) is a rare tumor in children, affecting 0.4 per million children worldwide. Incidence in adults is approximately 5-fold higher and may represent a distinct genetic and biologic entity. Mortality rates among patients with ACC are high and treatment options are limited. Previous studies have suggested that a majority of children who develop ACC possess germline mutations in the p53 tumor suppressor gene. In this study we sought to characterize the prevalence and mutational spectrum of p53 among a large multi-center cohort of children with ACC. We further compared the specific mutations found in these children with mutations found in individuals with the Li-Fraumeni syndrome, a familial cancer predisposition syndrome which is strongly associated with germline p53 mutation. Among 58 independent pedigrees assessed for p53 mutation, 29 (50%) carried a heterozygous mutation in p53. No mutation was identified more than once among this cohort. This is in contrast to families with the LFS, where 6 “hotspot” mutations are disproportionately over-represented, combined accounting for 20% of patients with identified p53 mutations. Missense mutations were noted in 28/29 individuals, with a single intragenic deletion identified in the remaining individual. Mutations were found predominantly within the DNA-binding domain (26/29 (90%)). One mutation was identified in the trans-activation domain and two in the oligomerization domain. In the course of this analysis, we identified several novel p53 mutations among children with ACC. These mutations were functionally characterized in vitro based on the ability of mutant p53 to activate transcription of known p53 target genes including those involved in DNA damage repair, cell-cycle arrest and apoptosis. Dominant-negative activity of these mutations was also assessed. Several of the novel mutations demonstrated either full p53 function or partial loss-of-function. The association of these seemingly milder mutations with adrenal tumorigenesis suggests that adrenal tissues may be more sensitive to partial decrease in p53 function than other LFS-affected tissues and that other predisposing or disease-modifying genetic alterations may exist to propel these cells towards a transformed fate. Further efforts to identify disease modifying loci, as well as pathogenic loci in children with wild-type p53 genes are underway via genome-wide analysis. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5351. doi:10.1158/1538-7445.AM2011-5351
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".