Abstract 3409: Age of cancer onset differentiated by sex and TP53 codon change in Li-Fraumeni Syndrome patient population
Notice bibliographique
Résumé
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
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».