Literature DB >> 21059672

Gene profiling predicts rheumatoid arthritis responsiveness to IL-1Ra (anakinra).

Carine Bansard1, Thierry Lequerré, Céline Derambure, Olivier Vittecoq, Martine Hiron, Alain Daragon, Sophie Pouplin, Maryvonne Daveau, Olivier Boyer, François Tron, Xavier Le Loët, Jean-Philippe Salier.   

Abstract

OBJECTIVES: The overall non-response rate to biologics remains 30-40% for patients with RA resistant to MTX. The objective of this study was to predict responsiveness to the anakinra-MTX combination by peripheral blood mononuclear cell gene profiling in order to optimize treatment choice.
METHODS: Thirty-two patients treated with anakinra (100 mg/day s.c.) and MTX were categorized as responders when their 28-joint DAS (DAS-28) had decreased by ≥1.2 at 3 months. Pre-treatment blood samples had been drawn.
RESULTS: For seven responders and seven non-responders, 52 microarray-identified mRNAs were expressed as a function of the response to treatment, and unsupervised hierarchical clustering correctly separated responders from non-responders. The levels of seven of these 52 transcripts, as assessed by real-time, quantitative RT-PCR, were able to accurately classify 15 of 18 other patients (8 responders and 10 non-responders), with 87.5% specificity and 77.8% negative-predictive value for responders. Among the 52 genes, 56% were associated with IL-1β.
CONCLUSION: This predictive gene expression profile was obtained with a non-invasive procedure. After further validation in other cohorts of patients, it could be proposed and used on a large scale to select likely RA responders to combined anakinra-MTX. Trial registration. Clinical Trials; NCT00213538 (http://www.clinicaltrials.gov).

Entities:  

Mesh:

Substances:

Year:  2010        PMID: 21059672     DOI: 10.1093/rheumatology/keq344

Source DB:  PubMed          Journal:  Rheumatology (Oxford)        ISSN: 1462-0324            Impact factor:   7.580


  12 in total

1.  Differences and similarities in the transcriptional profile of peripheral whole blood in early and late-onset preeclampsia: insights into the molecular basis of the phenotype of preeclampsiaa.

Authors:  Tinnakorn Chaiworapongsa; Roberto Romero; Amy Whitten; Adi L Tarca; Gaurav Bhatti; Sorin Draghici; Piya Chaemsaithong; Jezid Miranda; Sonia S Hassan
Journal:  J Perinat Med       Date:  2013-09-01       Impact factor: 1.901

2.  The peripheral whole-blood transcriptome of acute pyelonephritis in human pregnancya.

Authors:  Ichchha Madan; Nandor Gabor Than; Roberto Romero; Piya Chaemsaithong; Jezid Miranda; Adi L Tarca; Gaurav Bhatti; Sorin Draghici; Lami Yeo; Moshe Mazor; Sonia S Hassan; Tinnakorn Chaiworapongsa
Journal:  J Perinat Med       Date:  2014-01       Impact factor: 1.901

3.  Blood-based identification of non-responders to anti-TNF therapy in rheumatoid arthritis.

Authors:  Ty M Thomson; Reynald M Lescarbeau; David A Drubin; Daphna Laifenfeld; David de Graaf; David A Fryburg; Bruce Littman; Renée Deehan; Aaron Van Hooser
Journal:  BMC Med Genomics       Date:  2015-06-03       Impact factor: 3.063

4.  Factors affecting the accuracy of a class prediction model in gene expression data.

Authors:  Putri W Novianti; Victor L Jong; Kit C B Roes; Marinus J C Eijkemans
Journal:  BMC Bioinformatics       Date:  2015-06-21       Impact factor: 3.169

5.  Fluorescently activated cell sorting followed by microarray profiling of helper T cell subtypes from human peripheral blood.

Authors:  Chiaki Ono; Zhiqian Yu; Yoshiyuki Kasahara; Yoshie Kikuchi; Naoto Ishii; Hiroaki Tomita
Journal:  PLoS One       Date:  2014-11-07       Impact factor: 3.240

Review 6.  Interleukin-1 as a common denominator from autoinflammatory to autoimmune disorders: premises, perils, and perspectives.

Authors:  Giuseppe Lopalco; Luca Cantarini; Antonio Vitale; Florenzo Iannone; Maria Grazia Anelli; Laura Andreozzi; Giovanni Lapadula; Mauro Galeazzi; Donato Rigante
Journal:  Mediators Inflamm       Date:  2015-02-16       Impact factor: 4.711

7.  Peripheral blood derived gene panels predict response to infliximab in rheumatoid arthritis and Crohn's disease.

Authors:  Bertalan Mesko; Szilard Poliska; Andrea Váncsa; Zoltan Szekanecz; Karoly Palatka; Zsolt Hollo; Attila Horvath; Laszlo Steiner; Gabor Zahuczky; Janos Podani; And Laszlo Nagy
Journal:  Genome Med       Date:  2013-06-28       Impact factor: 11.117

8.  Pre-silencing of genes involved in the electron transport chain (ETC) pathway is associated with responsiveness to abatacept in rheumatoid arthritis.

Authors:  C Derambure; G Dzangue-Tchoupou; C Berard; N Vergne; M Hiron; M A D'Agostino; P Musette; O Vittecoq; T Lequerré
Journal:  Arthritis Res Ther       Date:  2017-05-25       Impact factor: 5.156

Review 9.  Gene expression analysis in RA: towards personalized medicine.

Authors:  A N Burska; K Roget; M Blits; L Soto Gomez; F van de Loo; L D Hazelwood; C L Verweij; A Rowe; G N Goulielmos; L G M van Baarsen; F Ponchel
Journal:  Pharmacogenomics J       Date:  2014-03-04       Impact factor: 3.550

10.  Evaluation of gene expression classification studies: factors associated with classification performance.

Authors:  Putri W Novianti; Kit C B Roes; Marinus J C Eijkemans
Journal:  PLoS One       Date:  2014-04-25       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.