Abstract AS01: Molecular genetic approaches to understanding ovarian cancer
Notice bibliographique
Résumé
Abstract Ovarian cancer remains a challenging condition to prevent, diagnose and treat. We have conducted several different studies that have attempted to advance knowledge in one or more of these areas. These projects are briefly summarized below. 1) Sequencing of samples from a BRCA1 mutation carrier with high grade serous carcinoma We performed whole exome sequencing (WES) on the blood, primary tumor, omental metastasis and recurrence following therapy with carboplatin and paclitaxel, from a patient carrying a BRCA1 p.S1841R mutation. We observed loss of heterozygosity in the BRCA1 mutation in the primary and subsequent tumors, and somatic mutations in TP53 and NF1 were identified, suggesting their role along with BRCA1 driving the tumor development. We were able to detect large chromosomal rearrangements using WES. A large deletion was present in the three tumors in the regions containing BRCA1, TP53, and NF1 mutations, and an amplification in the regions containing MYC. We did not observe the emergence of new mutations among tumors from diagnosis to relapse after chemotherapy. Mutations present in the primary tumor were the main drivers of metastases and chemotherapy resistance. 2) Identification of DICER1 mutations in non -epithelial ovarian cancer We used Sanger sequencing to sequence the RNase IIIa and IIIb domains of DICER1 in 154 gonadal tumours from 135 females and 19 males, and 43 extra-gonadal germ cell tumors (GCTs) from 26 females and 17 males. We identified heterozygous non-synonymous mutations in the RNase IIIb domain of DICER1 in 14/197 non-epithelial tumours (7.1%). Mutations were found in 9/28 SCSTs (32%), 5/118 gonadal GCTs (4.2%), 0/43 extra-gonadal GCTs and 0/8 miscellaneous tumours. The 14 mutations affected only five residues: E1705, D1709, E1788, D1810 and E1813. In all five patients where matched and constitutional DNA was available, the mutations were somatic. There were no mutations found in the RNase IIIa domain. More than half (8/15) of Sertoli-Leydig cell tumours (SLCTs) harbour DICER1 mutations in the RNase IIIb domain, while mutations are rarely found in GCTs. 3) Characterization of small cell carcinoma of the ovary, hypercalcemic type (SCCOHT) We sequenced the exomes of six individuals from three families with SCCOHT. After discovering segregating deleterious germline mutations in SMARCA4 in all three families, we tested DNA from a fourth affected family, which also carried a segregating SMARCA4 germline mutation. All the familial tumors sequenced harbored either a somatic mutation or loss of the wild-type allele. Immunohistochemical analysis of these cases and additional familial and non-familial cases showed loss of SMARCA4 (BRG1) protein in 38 of 40 tumors overall. Sequencing of cases with available DNA identified at least one germline or somatic deleterious SMARCA4 mutation in 30 of 32 cases. Additionally, the SCCOHT cell line BIN-67 had biallelic deleterious mutations in SMARCA4. Our findings identify alterations in SMARCA4 as the major cause of SCCOHT, which could lead to improvements in genetic counseling and new treatment approaches. Citation Format: Leora Witkowski, Jian Carrot-Zhang, Jacek Majewski, William D. Foulkes. Molecular genetic approaches to understanding ovarian cancer [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 AS01.
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 | 0,001 |
| 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 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 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 ».