Noninvasive proteome analysis of psoriatic stratum corneum reflects pathophysiological pathways and is useful for drug profiling.

Abstract

Protein expression is disturbed in the psoriatic stratum corneum (SC). Noninvasive methods for the description of pathophysiological changes and drug profiling in psoriasis are desirable. Undertake large-scale noninvasive protein expression studies in psoriatic SC to identify biomarkers of pathophysiological processes and use them for drug profiling. Psoriatic SC was harvested through repetitive tape-stripping. Nonlesional and lesional SC, as well as vehicle-treated and drug-treated lesional SC samples were collected. Protein extracts from nonlesional and lesional skin biopsies were used for comparison. Calcipotriol-betamethasone (CB) was used as a reference medication. Proteins extracted from pooled tape strips were quantified using mass spectrometry (MS), Western blotting, enzyme-linked immunosorbent assay and Luminex technologies. MS-based methods identified 140 proteins differentially expressed in psoriatic SC. Epidermis development, glycolysis, regulation of apoptosis, cytoskeleton organization and peptide cross-linking were modulated, all reflecting perturbed epidermal differentiation. Using antibody-based techniques, increased levels of sICAM1, of CXCL1- and CXCL8-attracting neutrophils, of CXCL10- and CCL4-attracting T helper (Th) 1 cells, and of CCL2- and CCL4-attracting monocytes and dendritic cells were observed. Quantification of the Th1 and Th17 markers tumour necrosis factor, interleukin (IL) 12B, IL17A and IL17F in lesional SC was successful, while the Th2 cytokines IL4, IL5 and IL13, not involved in the disease process, were not detected. The pruritic cytokine IL31 was detected in lesional SC. CXCL1, CXCL8, CXCL10 and sICAM were used to investigate disease remission, ranking three topical treatments according to their known clinical efficacy. Protein biomarker quantification in psoriatic SC detects key pathophysiological mechanisms and enables noninvasive drug profiling in translational medicine settings.