Selection for CD49A+ and CD26- cells in pancreatic islet-like clusters differentiated from human pluripotent stem cells improves their therapeutic activity in diabetic mice
Notice bibliographique
Résumé
Abstract BackgroundCell therapy of diabetes aims at restoring the physiological control of blood glucose by transplantation of functional pancreatic islet cells. Human islets from post-mortem donations have shown efficiency but the demand for islets vastly exceeds the availability of donations. A potentially unlimited source of cells for such transplantations would be islet cells derived from in vitro differentiation of human pluripotent stem cells (hPSC), such as embryonic stem cells (hESC). The islet-like clusters (ILC) produced by the known differentiation protocols contain various cell populations. Among these, the beta cells that express both insulin and the transcription factor Nkx6.1 seem to be the most efficient to restore normoglycemia in diabetes animal models. Our aim was to find markers allowing selection of these efficient cells.MethodsFunctional Cell-Capture Screening (FCCS), using an array of antibodies to cell surface proteins, was used to identify markers that preferentially capture the cells expressing insulin, or expressing both insulin and Nkx6.1, from hESC-derived ILC cells. In order to test whether selection for such markers could improve cell therapy in diabetic mouse models, we used ILC produced from a clinical-grade line of hESC by a refined differentiation protocol adapted to up-scalable bioreactors. The ILC, dissociated to single cells, were fractionated by Magnetic Activated Cell Sorting (MACS) for presence of the marker. The sorted cells, re-aggregated into clusters, were encapsulated in microspheres made of alginate modified to reduce foreign body reaction. Implantation was done intraperitoneally in C57BL/6 immuno-competent mice that were made diabetic by prior injections of Streptozotocin (STZ).ResultsCD49A (integrin alpha1) was identified by FCCS as a marker for cells double positive (DP) for insulin (and C-peptide) as well as Nkx6.1 in ILC derived by hESC differentiation. After sorting by MACS with CD49A antibodies, the ILC fraction enriched in CD49A+ cells rapidly reduced glycemia when implanted in the diabetic mice, whereas mice receiving the CD49A depleted population remained highly diabetic. CD49A-enriched ILC cells also produced significantly higher levels of human C-peptide in mouse blood. Another marker, CD26 (DPP4, dipeptidyl peptidase-4), was identified by FCCS as binding insulin-expressing cells which are Nkx6.1-negative. Depletion of CD26+ cells followed by enrichment for CD49A+ cells increased DP cells to over 70%. After this double selection, the CD26 depleted/CD49A enriched ILC were more active than non-sorted ILC to reduce glycemia in the diabetic mice.ConclusionsRefining the composition of ILC differentiated from hPSC by negative selection to remove cells expressing CD26 and positive selection for CD49A expressing cells can enable more effective cell therapy of diabetes.
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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) | 0,004 | 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 ».