Abstract Details

Title Gene Expression Biomarkers for IFN-? Treatment Response in Relapsing-Remitting Multiple Sclerosis

Topic MS and Related Diseases

Presentation(s) P05 - (-)

Poster/Presentation
Number 143

Objective

Background BACKGROUND: IFN-? is known to be effective for the treatment of RRMS, in reducing the number of acute relapses and suppressing disease progression. However, currently, there is no tool for predicting treatment efficacy in individual patients.

Design/Methods DESIGN/METHODS: We used 48 HG-U133A2 (Affymetrix) gene-expression microarrays, extracted from blood samples from RRMS patients prior to treatment initiation with IFN-? (n=48, 29 females, age 37.8±1.5 years, disease duration 6.6±1.1 years, expanded disability status scale (EDSS) 2.0±0.2). Good treatment response at 2 years of treatment was defined as reduction by at least 1 relapse compared with the 2 years rate prior to treatment combined with annual increase of up to 0.5 in the EDSS score. Statistical comparison of the baseline expression of differentiating genes between responders and non-responders patients was performed to identify potential markers for treatment response.

Results RESULTS: Good clinical outcome was observed in 34/48 (70%) of IFN-? treated patients. A signature of 627 gene-transcripts differentiated between good and poor responders. This signature was significantly enriched with genes related to T cell growth and proliferation (P=1.37E-03) that were over-expressed in good responders at baseline. A 3-gene classifier combined from PRUNE, POU6F1, and TRD@, known to be related to cellular growth, showed robust discrimination rate for treatment response (91.3%), with 97%(33/34) sensitivity, and 86%(12/14) specificity. These genes expressed individual prediction ability demonstrated by large area under the curve (AUC) (range 0.815-0.847), high sensitivity (range 85-97%) and moderate specificity (range 57-78%).

Conclusions CONCLUSIONS: Our findings suggest that baseline high T-cell growth and proliferation related genes signify good response for IFN-? treatment. Treatment outcome can be accurately predicted by the expression level of 3 genes (PRUNE, POU6F1, TRD@) playing a role in T-cell growth.

Authors/Disclosures
Saar Anis, MD (Cleveland Clinic) PRESENTER	Dr. Anis has nothing to disclose.
	No disclosure on file
Erez Hanael	No disclosure on file
Michael Gurevich (Sheba Medical Center)	No disclosure on file
Anat Achiron, MD, PhD, FAAN (Sheba Medical Center, Tel-Hashomer)	Dr. Achiron has nothing to disclose.
Ralf Linker (Uniklinik Erlangen)	Dr. Linker has received personal compensation in the range of $5,000-$9,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Novartis. Dr. Linker has received personal compensation in the range of $0-$499 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Springer. The institution of Dr. Linker has received research support from Novartis. The institution of Dr. Linker has received research support from Biogen.

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