Abstract POSTER-BIOL-1349: The oncogenic role of DICER1 RNase IIIb domain mutations in ovarian sertoli-leydig cell tumors
Notice bibliographique
Résumé
Abstract DICER1, an endoribonuclease required for microRNA (miRNA) biogenesis, is essential for embryogenesis and development of many organs including ovary. Germline truncating mutations in DICER1 are seen in families with the pleuropulmonary blastoma-family tumour and dysplasia syndrome. These individuals have a propensity to develop ovarian Sertoli-Leydig cell tumors (SLCTs), a rare class of sex-cord stromal cell tumors that occur in young female. We have recently identified hotspot somatic mutations in RNase IIIb domain (simplified as ‘hotspot mutations’ thereafter) of DICER1 in half of SLCTs. These hotspot mutations impaired IIIb cleavage activity of DICER1 in in vitro cleavage assay and caused a global abolishment of 5p-miRNAs and a partial reduction of 3p-miRNAs in mouse embryonic stems cells expressing ectopic mutant DICER1. However, whether the miRNA biogenesis defect occurs in tumor samples and how DICER1 hotspot mutations promote tumorigenesis are largely unknown. By reviewing the histological features of ovarian SLCTs, we observed a strong correlation between DICER1 hotspot mutation and ovairain SLCTs with retiform pattern, which is often malignant with worse prognosis. Using Illumina small RNA sequencing technology and Exiqon miRNA realtime qPCR, we reported that the global expression of 5p-miRNAs was dramatically reduced in ovarian SLCTs carrying DICER1 hotspot mutations compared to their counterparts without DICER1 hotspot mutation. Although the 3p-miRNAs were largely unaffected, a subset of 3p-miRNAs was significantly increased in ovarian SLCTs with DICER1 hotspot mutations. To address the impact of DICER1 mutation on cell fate, we examined the gene expression profile in SLCTs using Illumina DASL whole transcriptome analysis followed by validation with Nanostring nCounter system. The miRNA production defect was associated with deregulation of genes governing cell fate determination in ovary, such as CYP19A1 (aromatase), FOXL2, FST, FGF9 and FGFR2, and genes that are targets of let-7, such as HMGA2, DICER1, ARID3A and CDC25A. Accordingly, knockin of DICER1 hotspot mutation in SVOG3e cells (immortalized human granulosa cells) led to altered miRNA biogenesis and deregulated expression of genes crucial for ovarian gonadal genesis and cellular transformation. SVOG3e Cells expressing DICER1 hotspot mutation grew faster than those with wildtype DICER1, which was at least partially due to loss of let-7 expression because inhibition of let-7 function by a miRNA sponge also accelerated cell growth. Furthermore, we also showed that loss of function of RNase IIIa domain of DICER1 had similar effect on cell proliferation as wildtype DICER1. Taken together, our data revealed that the hotspot somatic mutations of DICER1 in RNase IIIb domain cause systemic loss of 5p-miRNAs and selective upregulation of some 3p-miRNAs to drive pseudo-differentiation of testicular elements in ovary and cause oncogenic transformation. Thus, our current study sheds lights on the oncogenic potential of DICER1 hotspot mutations in tumor development and sets the stage for developing effective treatment method for malignant ovarian SLCTs. Citation Format: Yemin Wang, Jiamin Chen, Winnie Yang, Janine Senz, Michael S. Anglesio, Blake Gilks, Gregg B. Morin, David G. Huntsman. The oncogenic role of DICER1 RNase IIIb domain mutations in ovarian sertoli-leydig cell tumors [abstract]. In: Proceedings of the 10th Biennial Ovarian Cancer Research Symposium; Sep 8-9, 2014; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(16 Suppl):Abstract nr POSTER-BIOL-1349.
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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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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) | 0,012 | 0,002 |
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 ».