Abstract P5-02-01: A FACS-free purification method to study estrogen signaling, organoid formation, and metabolic reprogramming in mammary epithelial cells
Notice bibliographique
Résumé
Abstract Mammary epithelial cells (MECs) are known to have their metabolism reprogrammed following pregnancy to allow the increased energy requirements for lactation. The estrogen receptor α (ERα) is mainly associated with the regulation of biological pathways linked to mammary gland development but its influence on MECs metabolism is still unknown. Our hypothesis is that ERα reprograms cell metabolism in normal MECs, a phenomenon that would be reprogrammed during breast carcinogenesis. Few in vitro models are used to study MECs, and most of them do not express ERα. Primary MECs can be used to overcome this issue, but methods to purify these cells generally require flow cytometry and fluorescence-activated cell sorting (FACS), which require specialized instruments and expertise. Herein, we present in detail a FACS-free protocol for purification and primary culture of mouse MECs to study ERα metabolic functions using mass spectrometry (MS). Purified MECs from nulliparous mice remain differentiated for up to six days with >85% luminal epithelial cells in two-dimensional culture. When seeded in Matrigel, they form organoids that recapitulate the mammary gland morphology in vivo by developing lumens, contractile cells, and lobular structures. MECs express a functional ERα signaling pathway in both two- and three-dimensional cell culture, as shown at the mRNA and protein levels and by the phenotypic characterization. Extracellular metabolic flux analysis showed that estrogens induce a metabolic switch favouring aerobic glycolysis over mitochondrial respiration in MECs grown in two-dimensions, a phenomenon known as the Warburg effect. We also performed (MS)-based metabolomics in organoids. Estrogens altered the levels of metabolites from various pathways, including aerobic glycolysis, citric acid cycle, urea cycle, and amino acid metabolism, demonstrating that ERα reprograms cell metabolism in mammary organoids. To further understand this reprogramming, stable isotope tracer analysis in primary culture organoids are currently performed. In addition, pregnancy and breast-feeding are known to be protective against breast carcinogenesis. Consequently, we also performed MEC purification and organoid culture using mammary glands from multiparous mice. Intriguingly, organoid phenotypic characterization indicated a difference in organoid structures between MECs from nulliparous and multiparous mice. Furthermore, we observe significant differences in estrogenic response between both conditions, suggesting that pregnancy and/or lactation promotes the establishment of specific epigenetic marks that are preserved even ex vivo. Chromatin immunoprecipitation of specific histone marks and MS-based metabolic studies are ongoing to better understand the different responses of mammary organoids to estrogens between nulliparous and multiparous mice. Overall, we have optimized mouse MEC isolation and purification for two- and three-dimensional cultures and for MS-based metabolomics. We demonstrated that these organoids retain a functional ERα pathway over time and that ERα significantly reprograms multiple metabolic pathways. This model represents a valuable tool to study how estrogens modulate mammary gland biology, and particularly how these hormones reprogram metabolism during lactation and breast carcinogenesis. Citation Format: Aurélie Lacouture, Cynthia Jobin, Alisson Clemenceau, Cindy Weidmann, Line Berthiaume, Dominic Bastien, Isabelle Laverdière, Martin Pelletier, Caroline Diorio, Francine Durocher, Étienne Audet-Walsh. A FACS-free purification method to study estrogen signaling, organoid formation, and metabolic reprogramming in mammary epithelial cells [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P5-02-01.
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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,006 |
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 ».