Abstract LB-47: SPEN is a novel candidate tumor suppressor gene that regulates response to tamoxifen in estrogen receptor positive breast cancers.
Notice bibliographique
Résumé
Abstract The majority of breast cancers are hormone-responsive and are treated with anti-estrogens, such as tamoxifen. However, most of the 30 and 50% of estrogen receptor positive (ER+) patients that initially respond to tamoxifen eventually become resistant to the drug. Although there are several mechanisms responsible for resistance of breast cancers to tamoxifen, no predictive biomarkers for tamoxifen resistance are in clinical use besides the estrogen receptor (ER) and the progesterone receptors (PR). Using a novel integrative genomic method based on the discovery of nonsense mutations in deleted chromosomal fragments, we identified a nonsense mutation in the SPEN gene in the T47D breast cancer cell line. SPEN is a transcriptional repressor of the estrogen-signaling pathway, which is recruited to estrogen-responsive elements upon activation of the ER. We found 4 somatic mutations (2 nonsense and 2 missense) in 23 breast tumors showing loss of heterozygosity at the SPEN locus. Moreover, tissue microarrays showed that SPEN was frequently over-expressed in the nucleus of normal breast epithelial cells, but in only 10% of breast tumor cells, suggesting that inactivation of SPEN in breast cancer contributes to disease progression. In vitro, overexpression of SPEN in the T47D breast cancer cell line, in which SPEN is mutated and endogenous levels of the protein are very low, resulted in significantly decreased cell proliferation and anchorage-independent growth, decreased PR expression as well as increased sensitivity to tamoxifen. Remarkably, tamoxifen treatment induced 5-fold higher levels of apoptosis in SPEN-overexpressing compared to control T47D cells. In addition, using a tissue microarray of 100 tumor samples from ER+ breast cancer patients treated with tamoxifen only, we found that patients whose tumors express high levels of SPEN had a much better prognosis than patients whose tumors express low or no levels of the protein. To identify transcriptional targets of SPEN besides the PR, we performed gene expression profiling on a panel of breast cancer cell lines in which SPEN was either overexpressed or knocked-down. We found an inverse relationship between SPEN and Apolipoprotein D (APOD) expression, suggesting that SPEN potently repressed transcription of the APOD gene. APOD encodes a glycoprotein from the lipocalin family, which can chelate multiple molecules including progesterone, arachidonic acid as well as tamoxifen itself. Hence, our analysis shows that the loss or mutation of SPEN in ER+ breast cancers has the potential to affect tumor growth as well as sensitivity to tamoxifen, in part through upregulation of APOD expression. Together, our results highlight the role of SPEN as a novel putative tumor suppressor gene in breast cancer and suggest that SPEN is a candidate predictive biomarker of tamoxifen resistance in ER+ breast cancer patients. Citation Format: Stéphanie Légaré, Luca Cavallone, Aline Mamo, Catherine Chabot, Dana Keilty, Anthony Magliocco, Alexander Klimowicz, Patricia Tonin, Mark Basik. SPEN is a novel candidate tumor suppressor gene that regulates response to tamoxifen in estrogen receptor positive breast cancers. [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 LB-47. doi:10.1158/1538-7445.AM2013-LB-47
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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) | 0,002 | 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 ».