Dataset Information

Serum IL-17F does not predict poor response to IM IFN?-1a in relapsing-remitting MS.

ABSTRACT:

Objective

There is a significant unmet need for serum biomarkers in relapsing-remitting multiple sclerosis (RRMS) that are predictive of therapeutic response to disease-modifying therapies. Following a recent Stanford study which reported that pretreatment levels of serum interleukin (IL)-17F could predict poor response to interferon-? (IFN?) therapy, we sought to validate the finding using samples from a large clinical trial.

Methods

The validation cohort included 54 good responders (GR) and 64 poor responders (PR) selected from 762 subjects with RRMS from the IM IFN?-1a dose comparison study (Avonex study C94-805). Subjects were classified as GR and PR based on the number of relapses, Expanded Disability Status Scale score, and new and enlarging T2 lesions on MRI. Serum samples were assayed for IL-17F using a multiplexed Luminex assay and for IL-17F/F using an ELISA. Replicate aliquots from the Stanford study were also assayed to assure reproducibility of methods.

Results

Median pretreatment and post-treatment serum IL-17F levels were not statistically significantly different between GR and PR, and serum IL-7/IL-17F ratios were also not predictive of response status. Replicate aliquots from the Stanford study showed good correlation to their original cohort (r = 0.77).

Conclusions

We were unable to validate the finding that serum IL-17F is a predictor of PR in a large independent cohort of subjects with RRMS. Differences in patient populations and methodology might explain the failure to validate the results from the Stanford study.

SUBMITTER: Bushnell SE

PROVIDER: S-EPMC3413762 | biostudies-literature | 2012 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Serum IL-17F does not predict poor response to IM IFNβ-1a in relapsing-remitting MS.

Bushnell S E SE Zhao Z Z Stebbins C C CC Cadavid D D Buko A M AM Whalley E T ET Davis J A JA Versage E M EM Richert J R JR Axtell R C RC Steinman L L Medori R R

Neurology 20120509 6

<h4>Objective</h4>There is a significant unmet need for serum biomarkers in relapsing-remitting multiple sclerosis (RRMS) that are predictive of therapeutic response to disease-modifying therapies. Following a recent Stanford study which reported that pretreatment levels of serum interleukin (IL)-17F could predict poor response to interferon-β (IFNβ) therapy, we sought to validate the finding using samples from a large clinical trial.<h4>Methods</h4>The validation cohort included 54 good respond ...[more]

PMID: 22573631

Similar Datasets

Project description:One of our new major finding among the genes that contributes to MS susceptibility is ICSBP1. The so called disease modifying therapies like interferon-beta (IFN-β), possibly acting on the peripheral T-cells, reduce the disease activity and the clinical progression, with a MRI-detectable effect in preventing lesion burden and cerebral atrophy development in RR-MS. It suggests a critical role of peripheral blood mononuclear cells (PBMCs) immune response and modulation in developing inflammation in the brain. We tested the hypothesis that the genetic effect of the susceptible allele ICSBP1 can impact the gene expression profile of molecules belonging to the interferon pathway. We therefore interrogated the PBMC for changes in gene expression profile. We correlate those changes with the minor allele frequency for ICSBP1, performing independent quantitative trait analysis for each treatment category. Expression Quantitative Trait Loci Association with a p value < 0.05 have been used in follow up analysis. The regression coefficient of the Quantitative trait association represents the degree of correlation between the gene expression for each interrogated target gene and the minor allele frequency of the SNP for our gene of interest. This coefficient has been used as input in the subsequent Gene Set Enrichment Analysis performed in a pre-ranked approach. The resulting GSEA-SNP method rests on the assumption that SNPs underlying a disease phenotype might affect genes constituting a signaling pathway or genes with a common regulation. Therefore, GSEA-SNP can facilitate the identification of pathways or of underlying biological mechanisms. We used microarrays to capture gene expression profile of untreated subjects and of subjects under disease modyfing treatment (Interferon Beta and Glatiramer Acetate), in order to correlate gene expression and genotype data and in order to identify sets of genes specifically regulated in the different treatment categories.

Project description:ObjectiveTo characterize effects of alemtuzumab treatment on measures of disability improvement in patients with relapsing-remitting multiple sclerosis (RRMS) with inadequate response (≥1 relapse) to prior therapy.MethodsComparison of Alemtuzumab and Rebif Efficacy in Multiple Sclerosis (CARE-MS) II, a 2-year randomized, rater-blinded, active-controlled, head-to-head, phase 3 trial, compared efficacy and safety of alemtuzumab 12 mg with subcutaneous interferon-β-1a (SC IFN-β-1a) 44 μg in patients with RRMS. Prespecified and post hoc disability outcomes based on Expanded Disability Status Scale (EDSS), Multiple Sclerosis Functional Composite (MSFC), and Sloan low-contrast letter acuity (SLCLA) are reported, focusing on improvement of preexisting disability in addition to slowing of disability accumulation.ResultsAlemtuzumab-treated patients were more likely than SC IFN-β-1a-treated patients to show improvement in EDSS scores (p < 0.0001) on all 7 functional systems. Significantly more alemtuzumab patients demonstrated 6-month confirmed disability improvement. The likelihood of improved vs stable/worsening MSFC scores was greater with alemtuzumab than SC IFN-β-1a (p = 0.0300); improvement in MSFC scores with alemtuzumab was primarily driven by the upper limb coordination and dexterity domain. Alemtuzumab-treated patients had more favorable changes from baseline in SLCLA (2.5% contrast) scores (p = 0.0014) and MSFC + SLCLA composite scores (p = 0.0097) than SC IFN-β-1a-treated patients.ConclusionsIn patients with RRMS and inadequate response to prior disease-modifying therapies, alemtuzumab provides greater benefits than SC IFN-β-1a across several disability outcomes, reflecting improvement of preexisting disabilities.Classification of evidenceThis study provides Class I evidence (based on rater blinding and a balance in baseline characteristics between arms) that alemtuzumab modifies disability measures favorably compared with SC IFN-β-1a.