Optimization of analytical and pre-analytical variables associated with an ex vivo cytokine secretion assay.

Purpose: Measurements of cytokine release in whole blood after ex vivo stimulation are useful in drug development. The components contributing to variation within such assays have not been clearly defined. Therefore, we characterized the sources of variability within an ex vivo stimulation assay for TNF-alpha release.

Method: Fresh whole blood or mononuclear cells from a cell preparation tube were added to silanized, screw-top tubes with a final concentration of 1 microg/mL lipopolysaccharide (LPS). Each tube was purged with 95% air/5%CO2 and incubated 4 or 6 h at 37 degrees C in a metabolic water bath. Plasma TNF-alpha was next measured in supernatants by immunoassay. Total method variability was assessed in 10 normal donors each drawn in the morning and afternoon over 3 days. Four additional samples were pre-treated with dexamethasone to investigate inhibition of TNF-alpha release.

Results: Our analysis indicated precise temperature control, the timing and duration of stimulation, and the surface properties of the stimulation vessel most significantly influenced assay performance. A comparison of multiple anticoagulants indicated that careful consideration should be taken in selecting the optimal anticoagulant. The estimated total assay CV for all anticoagulants tested was less than 33.81%. The analytical variability (stimulation and measurement) was less than 25.88% CV. The one exception was mononuclear cells collected in sodium heparin. The total variability estimate incorporated day-to-day, diurnal, inter-donor, tube-to-tube and immunoassay variability. Using our optimized conditions, TNF-alpha release was inhibited by dexamethasone with a mean IC50 of 33.3 +/- 4.6 nM.

Conclusions: We have described an optimal set of conditions for collection, storage and processing of an ex vivo cytokine stimulation assay. These conditions were selected for operational feasibility, minimal imprecision and elimination of potential confounding factors. The end result is a more robust method that can be applied to clinical drug development.