Mass Cytometry and Topological Data Analysis Reveal Immune Parameters Associated with Complications after Allogeneic Stem Cell Transplantation.
Cell Rep
; 20(9): 2238-2250, 2017 Aug 29.
Article
em En
| MEDLINE
| ID: mdl-28854371
ABSTRACT
Human immune systems are variable, and immune responses are often unpredictable. Systems-level analyses offer increased power to sort patients on the basis of coordinated changes across immune cells and proteins. Allogeneic stem cell transplantation is a well-established form of immunotherapy whereby a donor immune system induces a graft-versus-leukemia response. This fails when the donor immune system regenerates improperly, leaving the patient susceptible to infections and leukemia relapse. We present a systems-level analysis by mass cytometry and serum profiling in 26 patients sampled 1, 2, 3, 6, and 12 months after transplantation. Using a combination of machine learning and topological data analyses, we show that global immune signatures associated with clinical outcome can be revealed, even when patients are few and heterogeneous. This high-resolution systems immune monitoring approach holds the potential for improving the development and evaluation of immunotherapies in the future.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Leucemia
/
Estatística como Assunto
/
Transplante de Células-Tronco Hematopoéticas
/
Citometria de Fluxo
Tipo de estudo:
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
Cell Rep
Ano de publicação:
2017
Tipo de documento:
Article
País de afiliação:
Suécia