Abstract
Immune Cell Deconvolution methods utilizing gene expression profiling to quantify immune cells in tissues and blood are an appealing alternative to flow cytometry. Our objective was to investigate the applicability of deconvolution approaches in clinical trial settings to better investigate the mode of action of drugs for autoimmune diseases. Popular deconvolution methods CIBERSORT and xCell were validated using gene expression from the publicly available GSE93777 dataset that has comprehensive matching flow cytometry. As shown in the online tool, ~ 50% of signatures show strong correlation (r > 0.5) with the remainder showing moderate correlation, or in a few cases, no correlation. Deconvolution methods were then applied to gene expression data from the phase III CLARITY study (NCT00213135) to evaluate the immune cell profile of relapsing multiple sclerosis patients treated with cladribine tablets. At 96 weeks after treatment, deconvolution scores showed the following changes vs placebo: naïve, mature, memory CD4(+) and CD8(+) T cells, non-class switched, and class switched memory B cells and plasmablasts were significantly reduced, naïve B cells and M2 macrophages were more abundant. Results confirm previously described changes in immune cell composition following cladribine tablets treatment and reveal immune homeostasis of pro- vs anti-inflammatory immune cell subtypes, potentially supporting long-term efficacy.