Abstract 3409: Age of cancer onset differentiated by sex and TP53 codon change in Li-Fraumeni Syndrome patient population
Bibliographic record
Abstract
Abstract Introduction:Li-Fraumeni Syndrome (LFS) is a highly penetrant autosomal dominantly inherited cancer predisposition disorder. Germline mutations of the TP53 tumor suppressor gene cause >80% of LFS and confer an increased risk of a range of early onset cancers, as well as of second tumors even in the absence of a family history of cancer. For this reason, we previously reported the implementation of a comprehensive life-long clinical surveillance protocol for individuals with a germline TP53 mutation for early tumor detection. Here, we set out to build a predictive model of age of onset of cancer in LFS patients to inform this screening protocol aiming to make it more targeted. We identify characteristics that differentiate the age of cancer onset consistently, across multiple LFS patient cohorts. Methods:The LFS cohort at Toronto’s Hospital for Sick Children (SickKids) (n = 171 patients) was used as a discovery set to identify factors that distinguish age of onset among LFS patients. This project focused specifically on patient characteristics such as sex and mutations within TP53, both as they appear on the genome and manifest in the protein, as predictors for age of onset. These predictors were tested in an exponential parametric survival model. Findings from the SickKids discovery set were tested for replication in the International Agency for Research on Cancer (IARC) TP53 database (n = 2374 patients). Results:In the discovery cohort, female sex was associated with a 1.53 fold later age of cancer onset than in males (p = 0.019). This did not replicate in the IARC TP53 set with 0.99 fold earlier onset for females than males (p = 0.843). However, in the discovery set, there appears to be a point at which female and male age of onset converges at 43 years. Controlling for onset before vs after 43 years in our replication set shows 1.12 (p= 0.0204) times later age of cancer onset in females than in males which is the same direction and significance as in our discovery set. The discovery cohort also showed 2.23 (p = 0.08) later cancer onset for individuals with a germline Arginine to Cysteine (Arg>Cys) codon change (model significance p = 0.047). This finding replicated in the IARC TP53 data set which showed individuals with an Arg>Cys codon change having onset 1.29 (p = 0.043) times later than those with a TP53 mutation that did not result in this codon change. Conclusions:Our study identified two LFS patient characteristics, sex and TP53 Arg>Cys codon change, which consistently differentiate age of cancer onset within the LFS patient population. Females under the age of 43 when compared to males under the age of 43 appear to have later tumor onset, an effect which disappears after the age of 43. Individuals with an Arg>Cys TP53 codon change are expected to have later onset cancer than those with TP53 mutations that do not result in this change. Future work will disentangle these findings further and build a more comprehensive predictive model of cancer onset in LFS patients. Citation Format: Lauren Erdman, Ben Brew, Jason Berman, Adam Shlien, Andrea Doria, David Malkin, Anna Goldenberg. Age of cancer onset differentiated by sex and TP53 codon change in Li-Fraumeni Syndrome patient population [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3409. doi:10.1158/1538-7445.AM2017-3409
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".