Targeting Deacetylase Sirt-1 Reprograms Treg Function in Immune Thrombocytopenia
Notice bibliographique
Résumé
Introduction: Immune thrombocytopenia (ITP) is the most common acquired bleeding disorder dominated by loss of self-tolerance, where dysfunction of regulatory T cells (Tregs) claims its role. CD38 is a type II glycoprotein with exoenzymatic activities, widely expressed on the surface of antibody-secreting cells, activated T cells, natural killer cells, and myeloid cells. Clinical studies of anti-CD38 monoclonal antibodies in the treatment of autoimmune diseases are robust. Zhang et al. recently reported that anti-CD38 targeted therapy rapidly boosted platelet levels by clearing plasma cells and potentially altering CD4+ T cells in patients with ITP. However, the underlying mechanism of its long-term efficacy remains to be elucidated. It is suggested that deficiency of Sirtuin-1 (Sirt-1), a class III histone deacetylase, promoted Treg stability and enhanced Foxp3 acetylation in graft versus host disease. The objective of this study was to explore whether a sustained response of anti-CD38 targeted therapy is associated with Sirt-1-modulated Tregs in ITP. Methods: The proportion of Tregs in peripheral blood mononuclear cells (PBMCs) cultured with different concentration of CD38 monoclonal antibody were detected by flow cytometry. Immunosuppressive functions of Tregs on the proliferation of CFSE-labeled CD4+ CD25- effector T cells, and on CD8+ cytotoxic T lymphocyte-induced platelet apoptosis were assessed. The level of Sirt-1 in CD4+ T cells from ITP patients and healthy controls, as well as the intergroup differences in Sirt-1 levels treated with or without CD38 monoclonal antibody were analyzed by quantitative real-time PCR and western blot. Furthermore, EX527, a Sirt-1 inhibitor and SRT1720, a Sirt-1 agonist, as well as lentiviral interference of Sirt-1 in Tregs were used to verify the target of anti-CD38 therapy. Finally, a murine model of active ITP was established by intraperitoneal injection of C57BL/6 CD61-KO splenocytes immunized with CD61+ platelets to severe combined immunodeficient mice, aiming to investigate whether targeting Sirt-1 reprograms Treg function in ITP. Results: CD38 monoclonal antibody significantly increased the proportion of Tregs among PBMCs and CD4+ T cells, and enhanced the immunosuppressive functions of Tregs in vitro. The expression level of Sirt-1 in CD4+ T cells from ITP patients was significantly higher than that from healthy controls, and CD38 monoclonal antibody significantly decreased the expression of Sirt-1 in CD4+ T cells. An elevated frequency of Treg population was noticed when programming CD4+ T cells from ITP patients in the presence of Sirt-1 inhibitor, which mirrors anti-CD38 therapy; while a reduced frequency of Treg proportion was observed with Sirt-1 agonist. Tregs transfected with Sirt-1 shRNA had a significantly stronger immunosuppressive function, compared with those transfected with the control lentivirus. And Sirt-1 shRNA interference masked the effect of CD38 monoclonal antibody on Tregs. Moreover, a total of four treatment groups were established in the active ITP mice, among which the control solvent (Group A), inhibition of CD38 (Group B), inhibition of Sirt-1 (Group C), and inhibition of both CD38 and Sirt-1 (Group D) were administered intraperitoneally every other day. In both Group B and C, significantly ameliorated thrombocytopenia, increasedproportion of splenic Tregs, down-regulated Sirt-1 in Foxp3 positive frozen sections, and restoration of anti-/pro-inflammatory cytokine profiles was demonstrated, compared with Group A. Conclusion: In summary,CD38 monoclonal antibody potentially reprograms the immunosuppressive function of Tregs by inhibiting Sirt-1, which provides a novel target for the management of ITP. This study suggested versatile mechanisms of anti-CD38 therapy in autoimmune disorders and rationalized its long-term efficacy in patients with ITP.
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 | 0,000 | 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) | 0,002 | 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 ».