Clinical studies suggest packed red blood cell (PRBC) transfusion modulates recipients' immune responses, resulting in increased rates of infection, morbidity and mortality. In addition, there is evidence that increased length of storage of PRBC before transfusion is associated with worse outcomes. The mechanisms driving immunosuppression and transfusion-related poor patient outcomes remain largely undefined. As dendritic cells (DC) play a critical role in initiation and regulation of the immune response, this study investigated transfusion-mediated modulation of expression of DC genes involved in inflammation, antigen presentation and signal transduction.


Monocyte-derived DC (MoDC) were differentiated following exposure to PRBC (at either D2, D14, D28 or D42 of routine storage) in an in vitro transfusion model. Gene expression profiling of MoDC generated “post-transfusion” was assessed at each time point using quantitative real time PCR using ΔΔCT method (relative to GAPDH and matched “no transfusion control”) and data analysed using ANOVA (95% CI). Expression array (Applied Biosystems) consisted of 28 genes broadly categorised into 1) chemokines, cytokines and receptors, 2) antigen presentation, 3) signal transduction.


PRBC transfusion significantly modulated expression of genes associated with signal transduction (CD86, CD44, TAP2, all p<0.05) and antigen presentation (NFκB2, RELA, RELB, all p<0.05). Modulation of gene expression was associated with the storage age of the PRBC to which the “recipient” was exposed. Networks of gene interactions were generated (Ingenuity Systems) to illustrate potential mechanisms of immune deregulation that are associated with transfusion-related DC modulation.


This study reports, for the first time, transfusion-driven modulation of DC gene expression that was associated with the storage age of PRBC transfused. These results provide a basis for the early assessment of immune function that we plan to translate into clinical studies to evaluate the efficacy of diagnostic tools to predict poor patient outcomes.


No relevant conflicts of interest to declare.

Author notes


Asterisk with author names denotes non-ASH members.