Literature DB >> 26108918

A clinically based protein discovery strategy to identify potential biomarkers of response to anti-TNF-α treatment of psoriatic arthritis.

Emily S Collins1,2, Aisha Q Butt1, David S Gibson3, Michael J Dunn1, Ursula Fearon1,2, Arno W van Kuijk4, Danielle M Gerlag4, Eliza Pontifex2, Douglas J Veale1,2, Paul P Tak4, Oliver FitzGerald1,2, Stephen R Pennington1.   

Abstract

PURPOSE: Psoriatic arthritis (PsA) can be treated using biologic therapies targeting biomolecules such as tumor necrosis factor alpha, interleukins (IL)-17 and IL-23. Although 70% PsA patients respond well to therapy, 30% patients show no or limited clinical improvement. Biomarkers that predict response to therapy would help to avoid unnecessary use of expensive biologics in nonresponding patients and enable alternative treatments to be explored. EXPERIMENTAL
DESIGN: Patient synovial tissue samples from two clinical studies were analysed using difference in-gel electrophoresis-based proteomics to identify protein expression differences in response to anti-TNF-α treatment. Subsequent multiplexed MRM measurements were used to verify potential biomarkers.
RESULTS: A total of 119 proteins were differentially expressed (p<0.05) in response to anti-TNF-α treatment and 25 proteins were differentially expressed (p<0.05) between "good responders" and "poor responders". From these differentially expressed proteins, MRM assays were developed for four proteins to explore their potential as treatment predictive biomarkers. CONCLUSION AND CLINICAL RELEVANCE: Gel-based proteomics strategy has demonstrated differential protein expression in synovial tissue of PsA patients, in response to anti-TNF-α treatment. Development of multiplex MRM assays to these differentially expressed proteins has the potential to predict response to therapy and allow alternative, more effective treatments to be explored sooner.
© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  Anti-TNF-α; Biomarkers; Proteomics; Psoriatic arthritis; Synovium

Mesh:

Substances:

Year:  2015        PMID: 26108918     DOI: 10.1002/prca.201500051

Source DB:  PubMed          Journal:  Proteomics Clin Appl        ISSN: 1862-8346            Impact factor:   3.494


  5 in total

Review 1.  Exploring the Psoriatic Arthritis Proteome in Search of Novel Biomarkers.

Authors:  Shalini M Mahendran; Vinod Chandran
Journal:  Proteomes       Date:  2018-01-24

2.  Urinary proteomics can define distinct diagnostic inflammatory arthritis subgroups.

Authors:  Stefan Siebert; Duncan Porter; Caron Paterson; Rosie Hampson; Daniel Gaya; Agnieszka Latosinska; Harald Mischak; Joost Schanstra; William Mullen; Iain McInnes
Journal:  Sci Rep       Date:  2017-01-16       Impact factor: 4.379

Review 3.  Biomarkers predictive of treatment response in psoriasis and psoriatic arthritis: a systematic review.

Authors:  Conor Magee; Hannah Jethwa; Oliver M FitzGerald; Deepak R Jadon
Journal:  Ther Adv Musculoskelet Dis       Date:  2021-05-08       Impact factor: 5.346

4.  ATRPred: A machine learning based tool for clinical decision making of anti-TNF treatment in rheumatoid arthritis patients.

Authors:  Bodhayan Prasad; Cathy McGeough; Amanda Eakin; Tan Ahmed; Dawn Small; Philip Gardiner; Adrian Pendleton; Gary Wright; Anthony J Bjourson; David S Gibson; Priyank Shukla
Journal:  PLoS Comput Biol       Date:  2022-07-05       Impact factor: 4.779

Review 5.  Integrating imaging and biomarker assessment to better define psoriatic arthritis and predict response to biologic therapy.

Authors:  Ashley Elliott; Dennis McGonagle; Madeleine Rooney
Journal:  Rheumatology (Oxford)       Date:  2021-12-24       Impact factor: 7.580

  5 in total

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