The future of mammary stem cell biology: the power of in vivo transplants
Notice bibliographique
Résumé
The recent review by Smith and Medina [1] of in vivo transplantation models and their role in investigating mammary stem cell (MaSC) biology provides comprehensive coverage of the history and complexity of the 'gold standard' MaSC assay in mice. This includes a description of the pioneering studies that showed that mammary epithelial outgrowths can be generated in cleared mammary fat pads transplanted with explants or admixtures of mammary cells [2]. However, this approach clearly does not lend itself to prospective analysis of isolated subpopulations in order to identify which cells possess in vivo regenerative activity. More recently, success in obtaining complex mammary gland structures from transplanted suspensions of single cells has now made this possible [3-7]. Moreover, the regenerated structures have been shown to contain daughter cells with the same in vivo repopulating activity of the original stem cell transplanted [4,6]. A major contribution from this advance has been the demonstration that the MaSCs thus defined are highly enriched in the CD49fhi/CD29hi/CD24+/mod/Sca-1- subset [4-6]. Nevertheless, it is important to recognize that these stem cells represent under 10% of this basal population. This population also contains mature myoepithelial cells and, in all likelihood, other basal cell intermediates that are yet to be identified. Smith and Medina [1] suggest that a conflict may exist in the consistency of CD49f, CD29 and CD24 as positive mouse MaSC markers. However, we find the results reported thus far to be in full agreement with one another. The CD49fhi/CD24med population described by Stingl and coworkers [6] is identical to the CD29hi/CD24+ population described by Shackleton and colleagues [4] and to the CD49fhi/CD24lo/Sca-1-population reported by Sleeman and coworkers [5]. Specifically, there is considerable overlap (> 85%) between the fraction of CD24+ cells that are CD49fhi and CD29hi, suggesting that α6 and β1 integrin (CD49f and CD29, respectively) are co-expressed in the basal stem cell-enriched population (unpublished data). Although the MaSC-enriched population is CD24+, the level of expression is clearly lower than in cells with luminal features, including luminal progenitors [5,6]. Different levels of fluorescence are obtained with different anti-CD24 reagents and staining protocols, and this has led to differential reporting of MaSCs as CD24+, CD24mod, or CD24lo [8]. The resultant confusion is unfortunate and underscores the need for improved standardization in phenotyping procedures and nomenclature. There is also consistency in the reported phenotypes of luminal progenitors and their more mature progeny. The latter are widely recognized to be CD24+/hi/CD29lo/CD61-/prominin-1+/Sca-1+, whereas the luminal progenitors are CD24+/hi/CD29lo/CD61+/prominin-1-. The CD24hi/prominin-1-/Sca-1- population described by Sleeman and coworkers [8] contains within it the CD29lo/CD24+/CD61+population isolated by Asselin-Labat and coworkers [9] (Smalley MJ, unpublished data). This accounts for our similar observations of oestrogen receptor-α expression being largely confined to the more mature CD24+/hi/CD61-/prominin-1+/Sca-1+ luminal cells (although a potentially important finding is that a small fraction of luminal progenitor cells also express ER-α) [8-10]. Smith and Medina [1] rightly highlight the combinatorial interactions between various epithelial cells and the mammary fat pad stroma that occur during the formation of a complete mammary gland. At a single cell level, the MaSC clearly must undergo asymmetric divisions in the stroma to yield progeny that ultimately generate a complete bilayered mammary tree. However, they also suggest that undue emphasis on the isolation of MaSCs is deflecting attention from more fundamental issues of the nature of the cellular interactions that must take place. Although we share their interest and perceived importance of these issues, we believe continuing efforts to purify and more precisely characterize the various cell types involved in these processes will provide an essential complementary approach. The separation of mammary epithelial subpopulations, through the identification of biologically distinct stem, progenitor and mature cell types, has the unique power to provide a clear framework for investigations of how different types of cells within the mammary gland normally communicate with each other and their environment and which of these can be bona fide targets of oncogenic transformation. Delineating the molecular signals and their collective roles in regulating normal MaSC behaviour as well as how these may be disrupted to produce malignant breast cancer populations holds significant challenges for the future. The use of cell purification and characterization studies has proven a highly insightful strategy in the haematopoietic system and has led to the identification of clinically useful diagnostic markers and therapies. Taking a lead from this experience, we anticipate that a continuing focus on the isolation of functionally distinct mammary epithelial populations from both murine and human sources at increasing purities, if developed critically, will play an important role in enabling similar progress in the mammary field.
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,003 |
| 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 ».