Optimization of a Cytokine Cocktail for the Expansion of Cord Blood CD34+ Cells into Megakaryocytes Progenitors.
Notice bibliographique
Résumé
Abstract Platelet transfusion remains the only therapy available to restore safe platelet levels in thrombocytopenic patients following stem cell transplantation. However, the development of improved cytokine cocktail for the pre-expansion of megakaryocyte progenitors (Mk-p) to support the transplantation may reduce the demand for platelet transfusions. Toward this, we previously reported the results of two-level factorial design screens of 6 cytokines (SCF, FL, IL-3, IL-6, IL-9 and IL-11) with TPO which identified TPO, SCF, FL and IL-9 as the best combination for the expansion of cord blood (CB) CD34+ cells into Mk-p (ASH abstract#1673, 2006). The objective of this study was to find the optimal concentration levels of these cytokines and validate the newly optimized cocktails. In brief, CB CD34+ cells were first expanded for 6 days in various conditions specified by a central composite design (CCD). The expansion of various hematopoietic populations and Mk-p were determined by FACS and CFU-Mk assay respectively, while the capacity of the expanded cells to produce Mk and platelets ex vivo was also measured at day-14 using the cytokine cocktail BS1 (optimized for the production of CB Mk). Statistical analysis of these responses revealed the synergistic effects of the cytokines and provided mathematical models for the expansion of Mk-p and the day-14 final Mk production. The CCD results demonstrated that SCF and TPO were the principal cytokines for the expansion of Mk and CFU-Mk at day-6. This was evident by their positive individual effect and their strong positive synergistic effect (+25% on CFU-Mk, P<0.02). Importantly, a strong negative interaction between TPO and IL-9 on the expansion of CFU-Mk was also revealed (−39%, p<0.001), as well as a strong positive interaction between FL and SCF on the expansion of CD34+ cells (+50%, P=0.05). Under the CCD settings FL and IL-9 effects on CFU-Mk expansion did not reach statistical significance, though the CFU-Mk model (R2=0.95) suggested that IL-9 should be used at the lowest concentration while FL could have a positive effect when used within a certain range. The next experiments were done to validate or complement the CCD-based models. The positive effect of SCF on CFU-Mk was confirmed. In regards to IL-9, we confirmed the model prediction that under optimum SCF and TPO concentration (determined by the response surface map), that removal of IL-9 was beneficial to the expansion of CFU-Mk (1.4–1.5- fold increase), while the addition of FL was found to slightly increase the expansion of CFU-Mk (1.2-fold). Finally, the CCD models were used to optimized 2 new cocktails; one specific for the expansion of Mk-p (ocMk-p) and one for the production of Mk at day-14 (ocMk). The yields and efficiencies of each cocktail was compared to the control cocktails TGS and BS1; TGS is currently used in clinical trial for the expansion of progenitors prior transplantation (TPO, G-CSF and SCF at 100 ng/ml), whereas BS1 (TPO,SCF, IL-6, IL-9) is known to favor good CFU-Mk expansion and excellent Mk production. Preliminary experiments have shown that ocMk-p increased the expansion of CFU-Mk up to 1.4 ±0.2 fold (range +1.2–1.9, n=3) compared to TGS while using 85% less cytokines, and that ocMk increased final Mk (P=0.01) and platelets (P<0.05) yields by 1.4- and 1.7-fold respectively compared to BS1 (n=8). In conclusion, two new cocktails were optimized using a dose-response surface methodology which allow maximal expansion while using significantly less cytokines.
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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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,001 | 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 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 ».