Abstract B023: Identifying molecular programs of progesterone-driven mammary stem cell expansion
Notice bibliographique
Résumé
Abstract Lifetime exposure to ovarian hormones plays a crucial role in determining a woman's risk for breast cancer: the risk of developing breast cancer is positively correlated with the number of ovarian-hormone-dependent menstrual cycles. Progesterone is an ovarian steroid hormone that peaks during the luteal phase of the female menstrual cycle. Recent research has revealed that progesterone is a key mediator of cellular changes in the mammary gland that likely underlies the correlation between ovarian hormones and breast cancer risk. These studies have shown that progesterone can exert mitogenic effects through paracrine signaling between specific mammary epithelial populations and control mammary stem cell (MaSC) expansion. Such findings provide new insights into MaSC dynamics and underscore the involvement of ovarian hormones in regulating fundamental mammary epithelial changes. Given the differentiation potential of luminal progenitors and MaSCs, they are the proposed cellular targets of transformation in breast cancer. Although it is known that progesterone can induce luminal and basal cell expansion, the underlying mechanisms driving hormone action within the different cellular compartments (basal, luminal and stromal) of the mammary gland are yet to be defined. Therefore, I hypothesize that the transcriptional response to progesterone will reveal important paracrine signaling pathways involved in MaSC changes. To test my hypothesis, mRNA expression profiles were generated from the different mammary cellular compartments under defined hormone treatments. More specifically, basal, luminal and stromal cells were FACS purified after 2 weeks of hormone stimulation with progesterone, estrogen, progesterone plus estrogen, or vehicle control and subjected to microarray analyses using the Agilent platform. To analyze this microarray data, an optimal pre-processing method was generated before any downstream analysis. After pre-processing, significantly altered genes under each hormone treatment were investigated and cross compared within different cellular compartments. Our lab is interested in examining progesterone-mediated ligand and receptor expression changes in the different epithelial compartments that may play a paracrine role in altering the MaSC population. Once significantly altered ligand-receptor pairs are identified, I will validate specific pathways through both in vivo and in vitro experiments utilizing knockout mice to test their functional significance and investigate the effects of aberrant signaling in these pathways in cell culture assays. Progesterone is believed to play a crucial role in MaSC regulation and this might in part explain why a greater number of reproductive cycles and hormone replacement therapy using progestins contribute to a higher risk of developing breast cancer. MaSCs are postulated to be involved in breast cancer initiation, hence elucidating the mechanisms that induce MaSC expansion will allow us to identify putative targets that can be harnessed to control stem/progenitor cells and limit cellular transformation. Citation Format: Yu-Jia Shiah, Purna A. Joshi, Alexander G. Beristain, Michelle Chan-Seng-Yue, Paul C. Boutros, Rama Khokha. Identifying molecular programs of progesterone-driven mammary stem cell expansion. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research: Genetics, Biology, and Clinical Applications; Oct 3-6, 2013; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Res 2013;11(10 Suppl):Abstract nr B023.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| 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 | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».