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Enregistrement W2574683350 · doi:10.1182/blood.v116.21.2346.2346

Anti-GvHD Effect of Antithymocyte Globulin Is Mediated by Antibodies Binding to T Cells and Regulatory NK Cells, and Less So or Not at All by Antibodies Binding to Other Mononuclear Cell Subsets

2010· article· en· W2574683350 sur OpenAlexaff
Mette Hoegh-Petersen, Minaa A. Amin, Yiping Liu, Alejandra Ugarte-Torres, Tyler Williamson, Peter Podgorny, James A. Russell, Jan Storek

Notice bibliographique

RevueBlood · 2010
Typearticle
Langueen
DomaineImmunology and Microbiology
ThématiqueImmunodeficiency and Autoimmune Disorders
Établissements canadiensUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésImmunologyAntibodyPolyclonal antibodiesFlow cytometryGraft-versus-host diseasePeripheral blood mononuclear cellPathogenesisBiologyCytotoxic T cellT cellImmune systemStem cellCell biologyIn vitro

Résumé

récupéré en direct d'OpenAlex

Abstract Abstract 2346 Introduction: Polyclonal rabbit-anti-human T cell globulin may decrease the likelihood of graft-vs-host disease (GVHD) without increasing the likelihood of relapse. We have recently shown that high levels of antithymocyte globulin (ATG) capable of binding to total lymphocytes are associated with a low likelihood of acute GVHD grade 2–4 (aGVHD) as well as chronic GVHD needing systemic therapy (cGVHD) but not increased likelihood of relapse (Podgorny PJ et al, BBMT 16:915, 2010). ATG is polyclonal, composed of antibodies for antigens expressed on multiple cell subsets, including T cells, B cells, NK cells, monocytes and dendritic cells. These cell subsets may play a role in the pathogenesis of GVHD. The anti-GVHD effect of ATG may be mediated through killing/inhibition of one or several of these cell subsets (eg, T cells) or their subsets (eg, naïve T cells as based on mouse experiments naïve T cells are thought to play a major role in the pathogenesis of GVHD). To better understand the mechanism of action of ATG on GVHD, we set out to determine levels of which ATG fraction (capable of binding to which cell subset) are associated with subsequent development of GVHD. Patients and Methods: A total of 121 patients were studied, whose myeloablative conditioning included 4.5 mg/kg ATG (Thymoglobulin). Serum was collected on day 7. Using flow cytometry, levels of the following ATG fractions were determined: capable of binding to 1. naïve B cells, 2. memory B cells, 3. naïve CD4 T cells, 4. central memory (CM) CD4 T cells, 5. effector memory (EM) CD4 T cells, 6. naïve CD8 T cells, 7. CM CD8 T cells, 8. EM CD8 T cells not expressing CD45RA (EMRA-), 9. EM CD8 T cells expressing CD45RA (EMRA+), 10. cytolytic (CD16+CD56+) NK cells, 11. regulatory (CD16-CD56high) NK cells, 12. CD16+CD56− NK cells, 13. monocytes and 14. dendritic cells/dendritic cell precursors (DCs). For each ATG fraction, levels in patients with versus without aGVHD or cGVHD were compared using Mann-Whitney-Wilcoxon test. For each fraction for which the levels appeared to be significantly different (p<0.05), we determined whether patients with high fraction level had a significantly lower likelihood of aGVHD or cGVHD than patients with low fraction level (high/low cutoff level was determined from ROC curve, using the point with maximum sum of sensitivity and specificity). This was done using log-binomial regression models, ie, multivariate analysis adjusting for recipient age (continuous), stem cell source (marrow or cord blood versus blood stem cells), donor type (HLA-matched sibling versus other), donor/recipient sex (M/M versus other) and days of follow up (continuous). Results: In univariate analyses, patients developing aGVHD had significantly lower levels of the following ATG fractions: binding to naïve CD4 T cells, EM CD4 T cells, naïve CD8 T cells and regulatory NK cells. Patients developing cGVHD had significantly lower levels of the following ATG fractions: capable of binding to naïve CD4 T cells, CM CD4 T cells, EM CD4 T cells, naïve CD8 T cells and regulatory NK cells. Patients who did vs did not develop relapse had similar levels of all ATG fractions. In multivariate analyses, high levels of the following ATG fractions were significantly associated with a low likelihood of aGVHD: capable of binding to naïve CD4 T cells (relative risk=.33, p=.001), EM CD4 T cells (RR=.30, p<.001), naïve CD8 T cells (RR=.33, p=.002) and regulatory NK cells (RR=.36, p=.001). High levels of the following ATG fractions were significantly associated with a low likelihood of cGVHD: capable of binding to naïve CD4 T cells (RR=.59, p=.028), CM CD4 T cells (RR=.49, p=.009), EM CD4 T cells (RR=.51, p=.006), naïve CD8 T cells (RR=.46, p=.005) and regulatory NK cells (RR=.55, p=.036). Conclusion: For both aGVHD and cGVHD, the anti-GVHD effect with relapse-neutral effect of ATG appears to be mediated by antibodies to antigens expressed on naïve T cells (both CD4 and CD8), EM CD4 T cells and regulatory NK cells, and to a lesser degree or not at all by antibodies binding to antigens expressed on B cells, cytolytic NK cells, monocytes or DCs. This is the first step towards identifying the antibody(ies) within ATG important for the anti-GVHD effect without impacting relapse. If such antibody(ies) is (are) found in the future, it should be explored whether such antibody(ies) alone or ATG enriched for such antibody(ies) could further decrease GVHD without impacting relapse. Disclosures: No relevant conflicts of interest to declare.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,016
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,007
Tête enseignante GPT0,220
Écart entre enseignants0,213 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2010
Routes d'admission1
Résumé présentoui

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