Human peripheral mononuclear cells (PBMCs) are a primary source of various immune cells – including but not limited to NK-cells, B-cells, and T-cells of various subtypes and stages of differentiation. PBMCs are an excellent model system for studying effects of potential drugs on the immune system, as many of the modulatory effects of compound treatment can be recapitulated. In this complex cell mixture, activation or suppression of the immune response (immunomodulation) is often seen in concert with coordinated cytokine secretion patterns.
T-cells can be activated by treatment with phytohemagglutinin (PHA), which will trigger proliferation of the T-cell population as well as modulate the cytokine secretion profile of a PBMC culture as a whole. T-cells are identified by the surface marker CD3. A specific subtype, cytotoxic T-cells (CTL), will also express CD8. Compounds that alter the ability of PHA-stimulated T-cells to proliferate or secrete certain cytokines might be candidate immune-modulatory compounds for further investigation.
PBMCs were batch-labeled with the MultiCyt® FL4 Cell Proliferation Dye before plating into 384-well plates containing compounds from a SAR expansion selection based on known immunomodulatory substances. Each plate also included four reference substances as dilution series (Resveratrol, Verapamil, Dexamethasone and Mitomycin C). Following plating of cells, PHA was added and cells were incubated for 3 days under appropriate tissue culture conditions. After incubation was complete, 10 µL aliquots were stamped from each treatment plate into a multiplex of immunophenotyping antibodies (anti-CD3-FITC and anti-CD8-PE) and the MultiCyt FL3 Membrane Integrity Dye. A second stamp of 3 µL from the same motherplate was used for QBeads detection of IL-17f, IL-6, and TNF. Each plate was read on the iQue Screener immediately after staining, without wash steps. Each 384-well plate took about 25 minutes to read (Fig A, courtesy of IntelliCyt Corp.)
Among all the data generated by the iQue Screener, eleven parameters were extracted based on their biological significance.
Data were normalized plate-wise to the PHA-activated control cell population, using a modified z score transformation, and activity profiles were generated.
Calculation of the Euclidian distance between profiles and subsequent similarity search against the profiles of the reference substances allowed the identification of compounds displaying specific phenotypes (Fig B: Cpds1-4 induce dexamethasone-like, Cpds 5-9 verapamil-like phenotypes).
Through clustering and subsequent visual inspection of the activity profiles, compounds eliciting new phenotypes (i.e. phenotypes not covered by the controls or reference substances) were identified as well. Examples for compounds inducing TNF secretion are shown in Fig C.
|1||Total cells||% proliferated cells|
|2||% viable cells|
|3|| Cytotoxic T-cells
|% cytotoxic T-cells (CTL)|
|4||% viable CTL|
|5||% proliferated CTL|
|% non-cytotoxic T-cells (nCTL)|
|7||% viable nCTL|
|8||% proliferated nCTL|
|9||Secreted cytokines||IL-6 (median FL2-H)|
|10||TNF (median FL2-H)|
|11||IL-17f (median FL2-H)|
High-throughput, multiplex screening of compounds on primary cells generates information-rich multivariate compound activity profiles that can be used for identifying or prioritizing potential therapeutics candidates.
Application of advanced data mining techniques to these profiles allows for the rapid identification of compounds with activity similar to reference substances (potentially bridging the gap between phenotype and mechanism of action), but also identifies compounds eliciting new, potentially interesting phenotypes.