A transcriptomic signature predicting septic outcome in patients undergoing autologous stem cell transplantation.
Exp Hematol
; 65: 49-56, 2018 09.
Article
em En
| MEDLINE
| ID: mdl-29885947
ABSTRACT
Autologous hematopoietic stem cell transplantation is the standard treatment for multiple myeloma and relapsed or refractory lymphomas. After autologous hematopoietic stem cell transplantation, hematologic reconstitution and infectious complications are the two most critical issues. Although many patients develop infectious complications after therapeutic intensification, it remains impossible to predict infection for each individual. The goal of this work was to determine and identify a predictive transcriptomic signature of systemic inflammatory response syndrome and/or sepsis in patients receiving autologous hematopoietic stem cell transplantation. High-throughput transcriptomic and bioinformatics analysis were performed to analyze gene expression modulation in peripheral blood mononuclear cells in 21 patients undergoing autologous hematopoietic stem cell transplantation for hematological malignancies (lymphoma or multiple myeloma). Transcriptomic analysis of peripheral blood mononuclear cells samples collected just after conditioning regimen identified an 11-gene signature (CHAT, CNN3, ANKRD42, LOC100505725, EDAR, GPAT2, ENST00000390425, MTRM8, C6orf192, LOC10289230, and XLOC-005643) that was able to early predict (at least 2-7 days before its occurrence) the development of systemic inflammatory response syndrome or sepsis. The possibility of systemic inflammatory response syndrome or sepsis occurrence early prediction (2-7 days before occurrence) opens up new therapeutic strategies based on preemptive antibiotic and/or antifungal prophylaxis adapted to the specific risk profile of each patient.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Transplante Autólogo
/
Sepse
/
Transplante de Células-Tronco Hematopoéticas
/
Transcriptoma
Tipo de estudo:
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article