Analysis of Predictive Biomarkers for Estimation of MS Patients' Long-Term IFN- Therapy Outcome (S31.001)

Abstract

Objective: We aimed to analyze expressional behaviour and its correlation with disease course under IFN-β-therapy in relapsed-remitting MS (RRMS) patients of the IFN-β inducible MX1-gene and two novel potential expressional marker candidates that we extracted from our data sets: IL17RC and GPR2. Background IFN-β is one of the first-line immune-modulatory therapy option of RRMS. However, individual prediction of therapy outcome is difficult. With increasing treatment options of RRMS predictive biomarkers are needed to assess therapeutic effectiveness of available medications for individual patients. One of the genes whose mRNA level is controversially discussed to be predictive for therapy outcome is MX1. Furthermore, we identified two novel predictive marker candidates from our data. Design/Methods: We used Affymetrix microarrays and additional TaqMan RT-PCR to measure RNA expression patterns in peripheral blood-mononuclear cells of 61 RRMS patients. Blood samples were taken before start and at several time-points during of IFN-β therapy. We obtained patients clinic data over 5 year9s duration of treatment. First, we analysed changes in expression patterns over a time-course before and during treatment. Next, we linked our expression data to the clinical therapy outcome in the individual patients. We confirmed our findings using GEO-published data. Results: In patient groups with high and low MX1-mRNA-levels, IFN-β-induced expression changes after one month revealed a similar expression pattern of MX 1 and IFN-β-inducible genes of the IFN-β-induction pathway and also clinical outcome of both patient group were similar. IL17RC and GPR3 both exhibit different expressional changes under IFN-β-influence in therapy responders and non-responders (p Conclusions: In contrast to previous publication we found MX1 expression levels not to correlate with IFN-β-therapy outcome. However, here we present two novel therapeutic biomarker candidates, with distinct expression levels in responders and non-responders to IFN-β-treatment. Supported by: DFG, EUPHA*MS, Bayer healthcare, Teva, Merck-Serono. Disclosure: Dr. Paap has nothing to disclose. Dr. Hecker has received personal compensation for activities with Bayer HealthCare as speaker. Dr. Koszcan has nothing to disclose. Dr. Thiesen has nothing to disclose. Dr. Zettl has received personal compensation for activities with Biogen Idec, Merck Serono, Novartism and Teva Neuroscience. Dr. Zettl has received research support from Biogen Idec, Bayer Healthcare, Merck Serono, Novartis and Teva Neuroscience.