Abstract 1352: Epithelial-mesenchymal transition (EMT) gene variants influence epithelial ovarian cancer risk in women of European, African and Asian ancestry.
Notice bibliographique
Résumé
Abstract Introduction The epithelial-mesenchymal transition (EMT) pathway contributes to epithelial ovarian cancer (EOC) progression. Previously we identified associations of single nucleotide polymorphisms (SNPs) in EMT-related genes and EOC risk (data not shown). To further investigate the role of EMT-related gene variants in EOC and to derive more reliable risk estimates, we evaluated associations for 795 SNPs from 278 EMT-related genes in a replication study of 43 studies within the Ovarian Cancer Association Consortium (OCAC). Methods The study population included 14,736 cases and 23,448 controls of European ancestry, 89 cases and 200 controls of African ancestry, and 249 cases and 1574 controls of Asian ancestry. The 795 SNPs were genotyped using an Illumina Infinium iSelect BeadChip as part of the Collaborative Oncological Gene-environment Study (COGS). For women of European ancestry, both invasive cancers combined and the four main histological subtypes (serous [n=8,372], endometroid [n=2,068], clear cell [n=1,025] and mucinous [n=943] were analyzed, while for women of African and Asian ancestries only the serous subtype was analyzed. SNP analyses were conducted using unconditional logistic regression under a log-additive model separately for women of each ancestry. All analyses were adjusted for study site and population substructure within each ancestry. Results For women of European ancestry, the strongest evidence of an association for invasive cancers combined was observed for IGF1R rs10794486 (OR=1.05, 95%CI=1.02-1.09, P=0.002), which was also associated with serous (P=0.019), but not the other histological subtypes. In the histological subtype-specific analysis, the most significant association for serous was observed at NRP2 rs3771044 (OR=1.09, 95%CI=1.03-1.15, P=0.00014), for endometroid at rs1770247 (13q31.3, OR=1.16, 95%CI=1.07-1.25, P=0.00028), for clear cell at rs4848300 (2q13, OR=0.84, 95%CI=0.76-0.93, P=0.00099) and for mucinous at SEMA4B rs8030039 (OR=1.09, 95%CI=1.01-1.17, P=0.00019). For women of African ancestry, the strongest association for serous histological subtype was observed at F9 rs6048 (OR=1.71, 95%CI=1.17-2.50, P=0.006). This SNP was not significant in women of European or Asian ancestry. The strongest association for women of Asian ancestry was IGF1R rs10794486 (OR=1.68, 95%CI=1.16-2.45, P=0.007), which was also significant in women of European, but not African, ancestry. Conclusion Findings from this large study provide additional evidence that variants in EMT-related genes may be associated with ovarian cancer risk and that EMT susceptibility loci may differ by ovarian cancer histological subtypes. Furthermore, the findings suggest that susceptibility locus for the serous subtype may be different for women of African ancestry. Future studies are warranted to confirm these findings. Citation Format: Ernest K. Amankwah, Jonathan Tyrer, Hui-Yi Lin, Ya-Yu Tsai, Zhihua Chen, Gang Han, Xiaotao Qu, Ellen Goode, Julie Cunninghan, Edward Iverson, Susan Ramus, Andrew Berchuck, Joellen Schildkraut, Alvaro Monteiro, Simon Gayther, Steven Narod, Paul Pharoah, Thomas A. Sellers, Catherine Phelan. Epithelial-mesenchymal transition (EMT) gene variants influence epithelial ovarian cancer risk in women of European, African and Asian ancestry. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1352. doi:10.1158/1538-7445.AM2013-1352
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 | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».