Item request has been placed! ×
Item request cannot be made. ×
loading  Processing Request

Evaluation of serum MMP-9 as predictive biomarker for antisense therapy in Duchenne

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
  • معلومة اضافية
    • بيانات النشر:
      Nature Publishing Group
    • الموضوع:
      2017
    • Collection:
      Newcastle University Library ePrints Service
    • نبذة مختصرة :
      © 2017 The Author(s). Duchenne Muscular Dystrophy (DMD) is a severe muscle disorder caused by lack of dystrophin. Predictive biomarkers able to anticipate response to the therapeutic treatments aiming at dystrophin re-expression are lacking. The objective of this study is to investigate Matrix Metalloproteinase-9 (MMP-9) as predictive biomarker for Duchenne. Two natural history cohorts were studied including 168 longitudinal samples belonging to 66 patients. We further studied 1536 samples obtained from 3 independent clinical trials with drisapersen, an antisense oligonucleotide targeting exon 51: an open label study including 12 patients; a phase 3 randomized, double blind, placebo controlled study involving 186 patients; an open label extension study performed after the phase 3. Analysis of natural history cohorts showed elevated MMP-9 levels in patients and a significant increase over time in longitudinal samples. MMP-9 decreased in parallel to clinical stabilization in the 12 patients involved in the open label study. The phase 3 study and subsequent extension study clarified that the decrease in MMP-9 levels was not predictive of treatment response. These data do not support the inclusion of serum MMP-9 as predictive biomarker for DMD patients.
    • File Description:
      application/pdf
    • Relation:
      https://eprints.ncl.ac.uk/244732; https://eprints.ncl.ac.uk/fulltext.aspx?url=244732/C736B5D5-92E7-4261-B75B-87BEDB75A19B.pdf&pub_id=244732
    • الدخول الالكتروني :
      https://eprints.ncl.ac.uk/244732
    • Rights:
      https://creativecommons.org/licenses/by/4.0/
    • الرقم المعرف:
      edsbas.E3F4FB98