Abstract PR13: TERT is frequently mutated in adult-type granulosa cell tumors of the ovary compared to other malignant sex cord-stromal tumors
Notice bibliographique
Résumé
Abstract The telomerase reverse transcriptase (TERT) gene is highly expressed in stem cells and silenced upon differentiation. Cancer cells can attain immortality by activating TERT to maintain telomere length and telomerase activity, a crucial step of tumorigenesis. Two somatic mutations in the TERT promoter (C228T; C250T) have been identified in multiple cancers, such as melanoma and glioblastoma, as gain-of-function mutations that promote transcriptional activation of TERT. A recent study investigating TERT promoter mutations in ovarian carcinomas found mutations in 15% of clear cell carcinomas. However, it is unknown whether these mutations are prevalent in adult-type granulosa cell tumors (AGCTs) of the ovary, Sertoli-Leydig cell tumors (SLCTs), and other malignant sex cord-stromal tumors. We performed whole-genome sequencing on ten AGCT cases with matched normal and identified the TERT C228T promoter mutation in 50% of cases. We found that AGCT cases with mutated TERT promoter have increased expression of TERT mRNA compared to those with wild-type TERT promoter. All five TERT promoter mutated cases had high levels of TERT mRNA expression, whereas three of the five wild-type TERT cases had no measurable TERT mRNA expression. There was a tendency towards longer telomere lengths in AGCT cases with the TERT promoter mutation relative to those without, although it was not statistically significant. These results suggest that telomerase may be activated by a different method in the cases with no TERT promoter mutations but have TERT mRNA expression. The remaining cases with neither TERT promoter mutations nor TERT mRNA expression likely maintain their telomeres using a telomerase-independent method, such as the alternative lengthening of telomeres pathway. TERT C228T allelic discrimination analysis of 331 AGCTs, 5 SLCTs, and 18 other malignant sex cord-stromal tumors detected the mutation in 56/247 (23%) of primary AGCTs, 22/84 (26%) of recurrent AGCTs, 1/5 (20%) of SLCTs and (0/18) 0% of other malignant sex cord-stromal tumors. The single SLCT case with the TERT promoter mutation was poorly differentiated and harbored the pathognomonic FOXL2 mutation of AGCT, suggesting this SLCT case may actually be an AGCT. In 204 AGCT cases with available survival data, there was a trend towards worse disease-specific survival in patients with the TERT promoter mutation compared to those without; however, statistical significance was not reached (p = 0.128, log-ranked test). In 5 AGCT cases with primary and recurrent tissues, we found that the TERT promoter mutation was absent in the primary tumors but present in the recurrent tumors, suggesting that TERT C228T mutation may play an active role in progression of AGCTs. Overall, we found that TERT C228T promoter mutation was most common in AGCTs among the different malignant sex cord-stromal tumors. Our data confirm the activation of telomerase in AGCTs via TERT C228T promoter mutation, although alternative telomerase activation methods in AGCTs may exist. Our results suggest that TERT activation may play a role in AGCT recurrence. As such, telomere biology may be important for the progression of AGCTs. This abstract is also being presented as Poster B54. Citation Format: Jessica A. Pilsworth, Dawn R. Cochrane, Zhouchunyang Xia, Geraldine Aubert, Anniina E. M. Färkkilä, Hugo M. Horlings, Satoshi Yanagida, Winnie Yang, Jamie L. P. Lim, Yikan Wang, Ali Bashashati, Jacqueline Keul, Adele Wong, Esther Oliva, Sohrab P. Shah, Stefan Kommoss, Friedrich Kommoss, Peter M. Lansdorp, Duncan M. Baird, David G. Huntsman. TERT is frequently mutated in adult-type granulosa cell tumors of the ovary compared to other malignant sex cord-stromal tumors. [abstract]. In: Proceedings of the AACR Conference: Addressing Critical Questions in Ovarian Cancer Research and Treatment; Oct 1-4, 2017; Pittsburgh, PA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(15_Suppl):Abstract nr PR13.
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) | 0,002 | 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 ».