Abstract 2479: TP53 status as a marker of recurrence and survival in choroid plexus carcinomas
Notice bibliographique
Résumé
Abstract Choroid plexus carcinoma (CPC) is a rare intraventricular tumor more frequently observed in children, accounting for ∼20% of brain tumors in children under 2 yrs of age. This malignant neoplasm is categorized as a grade III tumor by the WHO, while benign choroid plexus papilloma (CPP) and atypical choroid plexus papilloma (aCPP) are categorized as grade I and II, respectively. More than 50% of CPC's carry a mutation in TP53. The role of p53 in the malignant progression of this tumor is not well understood, yet this knowledge is crucial to optimize patient treatment, increase survival and reduce long-term sequelae. The current treatment approach for CPC includes surgical resection and combination chemo- and radiation therapy. However, treatment response is highly variable; tumor progression and relapse is observed in ∼60% of patients, and most survivors experience significant long-term deficits. In this study, we sought to determine whether TP53 status could be used as a reliable marker to predict tumor aggressiveness and response to treatment in CPC patients. Thirty CPC, 26 CPP and 8 aCPP tumor samples for which TP53 status was available were selected from the SickKids Cancer Genetics tissue bank. Sequencing analysis revealed somatic TP53 in 60% of CPCs. These mutations were significantly less frequent in CPPs (12%, p=1.84x10−4). All aCPPs were wildtype (wt) for TP53. Relapse-free survival was only 12% in TP53 mut CPC patients compared to 40% for TP53 wt patients. Only 1 CPP patient relapsed 9 months after initial diagnosis. Five-year overall survival for TP53 mut CPC patients was significantly lower than that of TP53 wt patients (39% vs. 80%, respectively, p=0.04). Overall survival for 18 CPP patients for which we had 5-year survival data was 94%, and 100% for aCPP patients. Allele-specific copy number (ASCN) and FISH analysis, revealed extensive chromosomal imbalances in CPC tumors with TP53 mutations. TP53 wt CPCs had fewer chromosomal imbalances or none at all, very similar to CPPs. Gene expression data was used to examine the unsupervised clustering of our tumors. As expected, CPCs and CPPs cluster independently according to raw gene expression intensity, with TP53 wt CPCs segregating from the CPC mutant samples and clustering more closely to CPPs. Using an integrative analysis, we were able to identify unique behaviors and molecular characteristics that distinguish TP53 wt from TP53 mut CPCs. The clinical outcomes observed, supported by the genomic and transcriptomic data analyzed, suggest that TP53 mut and wt CPCs indeed form two distinct subgroups. This molecular genotyping approach may be valuable in stratifying patients to modulated therapy protocols in order to diminish treatment-related toxicity, and improve disease response and survival. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2479. doi:1538-7445.AM2012-2479
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 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) | 0,001 | 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 ».