Abstract 4765: The role of estrogen receptor signalling in serous ovarian cancer.
Notice bibliographique
Résumé
Abstract Epithelial ovarian cancer is a heterogeneous group of diseases with multiple histotypes which can be broadly divided into a dualistic model based on morphological, molecular genetic, and clinical features. The most common and aggressive of all EOC, accounting for 90% of deaths, is High Grade Serous Carcinoma (HGSC). It is characterized by a genetically unstable, rapidly growing phenotype, is diagnosed at advanced stage with poorly defined cancer precursors compared to the more indolent Low Grade Serous Carcinoma (LGSC). Reproductive hormone receptor status (estrogen/ progesterone receptor) may be an important indicator of response to anti-hormonal therapy in ovarian cancer. There have been few reports detailing the expression of ER in HGSC, LGSC and the normal fallopian tube epithelium, the likely cell of origin of both histotypes. We hypothesize that some ER mediated signaling is maintained despite the loss of progesterone receptor in HGSC compared to the LGSC. Methodology: Snap-frozen tissues (43 HGSC and 18 LGSC) were selected from the UHN Biobank. We used our previously published gene expression profiles to generate a candidate gene list, which was chosen based on the presence of known estrogen responsive elements. They were validated by qPCR and immunohistochemistry on HGSC and LGSC tissue microarrays. Human fallopian tube epithelial cell lines were treated with estradiol at 50nm to determine ‘normal’ ER response. An ER positive cancer cell line (SKOV3) was used to determine the cellular response to candidate genes. IHC was scored using automated image analysis. Statistical analysis was performed using ANOVA and Fisher's Exact Test. Results: 35/43 (81%) of HGSC were ER+/PR- whilst 9/27 of LGSC were ER+/PR- and 18/27 ER+/PR+. Gene expression analysis of ER+ HGSC and ER- HGSC revealed 881 genes with more than a 2-FC in gene expression including 202 genes with known or putative estrogen responsive elements. They are involved in immune response, locomotion, metanephrous development and cellular adhesion. We compared genes that were differentially expressed between normal fallopian tube cells obtained during pre- or post-ovulation (93 genes). 42 ‘FTE-normal’ genes were differentially expressed between ER- versus ER+ HGSC. We selected 5 genes to validate by qPCR and IHC, based on gene ontology and known associations to cancer pathways. Conclusions: These results show that HGSC is predominantly an ER+/ PR- cancer (80%) while LGSC is predominantly an ER positive/ PR positive cancer (66%). Our data also indicate that some ER signalling is maintained in the absence of the progesterone receptor and ER+ HGSC are transcriptionally different from ER- HGSC although, there is no distinct clinical benefit between these two groups. ER is still able to transcriptionally activate a subset of known ER target genes and this information should provide further insight into the use of hormone receptors as indicators of anti-hormone therapy in ovarian cancer. Citation Format: Sophia Hl George, Anca Milea, Ramlogan Sowamber, Danielle Toccalino, Patricia A. Shaw. The role of estrogen receptor signalling in serous ovarian cancer. [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 4765. doi:10.1158/1538-7445.AM2013-4765
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 | 0,000 |
| 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 | 0,001 | 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) | 0,004 | 0,001 |
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 ».