394 Gene expression based molecular test proves clinical validity as diagnostic aid for the differential diagnosis of psoriasis and eczema in formalin fixed and paraffin embedded tissue

Abstract

Abstract Highly specific and efficient drugs have been developed to treat noncommunicable chronic inflammatory skin diseases (ncISD). Due to their specificity, these drugs require precise diagnostics to attribute the most efficient treatment to each patient. Diagnosis is complicated by the complex pathogenesis of ncISD and their clinical and histological overlap. Especially, precise diagnosis of psoriasis and atopic eczema is difficult in special cases, and molecular tools need to be developed to support gold standard diagnosis. Psoriasis and eczema are among the most prevalent skin diseases worldwide with a combined incidence rate of at least 2%. Although more than a dozen of immune-modulating therapies, particularly monoclonal antibodies targeting specific cytokines or their receptors, have become available over the last decade allowing highly effective treatment, the ultimate breakthrough would include accurate diagnostic tools. Diagnosis of both diseases largely depends on a subjective visual exam and histopathological examination. Due to phenotypical overlaps of both diseases, up to 50% of cases with a palmoplantar localization are misdiagnosed. To close this diagnostic gap, a gene expression-based classifier using NOS2 and CCL27 has been proposed and its clinical validity examined and proven in various patient cohorts. This study aims to develop a real-time based molecular classifier (MC) to distinguish psoriasis from atopic eczema in formalin-fixed, paraffin-embedded (FFPE)-fixed skin samples for diagnostic measures and to evaluate the potential of minimally invasive microbiopsies and noninvasive tape strips or sampling disks for molecular diagnosis. The FFPE, micro-(Ø1mm) and macrobiopsies (Ø4–6 mm), and tape strips were collected from psoriasis and eczema lesions and analysed by real-time polymerase chain reaction (PCR) for the expression of NOS2 and CCL27. A molecular classifier (MC) was established using a linear regression model. We transferred the RNAprotect-based molecular classifier to FFPE samples and were able to produce comparable results. Whereas the RNAprotect based MC distinguished psoriasis from eczema with a sensitivity and specificity for psoriasis of 97.7% and 100%, respectively, and an AUC of 0.99, the FFPE-based classifier determined probabilities for psoriasis with a sensitivity and specificity and of 92% and 100%, respectively, and an AUC of 0.97. To test if microbiopsies are also adequate tissue samples for the MC, we analysed gene expression in 83 pairs of macro- and microbiopsies by real-time quantitative-PCR. Delta-CT values showed no significant difference between macro- and microbiopsies. The MC led to reliable results in the vast majority of samples (91.57%) independent of biopsy size, with a small increase of misclassification (4.98%). The FFPE-based molecular classifier (MC) precisely separates eczema from psoriasis and efficiently identifies subtypes of both diseases. The reliability of the two markers NOS2 and CCL27 has been shown in FFPE tissue facilitating a possible implementation of this molecular diagnostic aid in routine clinical pathological practice. We further show that the gene expression profile of RNA later fixed microbiopsies is comparable to standard 4–6 mm biopsies and that microbiopsies are equally suited for the MC. We demonstrate the potential of tape strips of inflamed epidermis for molecular diagnostics of ncISD. Due to the minimally invasive sampling procedure, tape stripping may be particularly useful for the testing of visible and sensitive skin areas and in children as well as for repetitive sampling procedures necessary to monitor treatment responses over time. In summary, the MC discriminates psoriasis from eczema producing meaningful results in a broad range of skin tissue derived from invasive to minimally invasive sampling techniques. Further efforts are required to simplify and shorten the labor- and cost-intensive procedures of RNA isolation and real-time PCR. One possible solution is a fully automated and closed system, which would allow the integration of molecular diagnostics into the routine patient management at the point of care.