Proteomic analysis of biomarkers predicting the response to triple therapy in patients with rheumatoid arthritis

Jian Chen; Meng-shi Tang; Li-chang Xu; Shu Li; Yan Ge; Jin-feng Du; Xi Xie; Jing Tian; Jin-wei Chen; Fen Li

Biomedicine & Pharmacotherapy (Aug 2019)

Proteomic analysis of biomarkers predicting the response to triple therapy in patients with rheumatoid arthritis

Jian Chen,
Meng-shi Tang,
Li-chang Xu,
Shu Li,
Yan Ge,
Jin-feng Du,
Xi Xie,
Jing Tian,
Jin-wei Chen,
Fen Li

Affiliations

Jian Chen: Department of Rheumatology and Immunology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China
Meng-shi Tang: Department of Rheumatology and Immunology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China
Li-chang Xu: International Department of YALI High School, Changsha, Hunan, China
Shu Li: Department of Rheumatology and Immunology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China
Yan Ge: Department of Rheumatology and Immunology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China
Jin-feng Du: Department of Rheumatology and Immunology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China
Xi Xie: Department of Rheumatology and Immunology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China
Jing Tian: Department of Rheumatology and Immunology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China
Jin-wei Chen: Department of Rheumatology and Immunology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China
Fen Li: Department of Rheumatology and Immunology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China; Corresponding author at: Department of Rheumatology and Immunology, the Second Xiangya Hospital, No.139 Ren Min Middle Road, Changsha, China.

Journal volume & issue: Vol. 116
p. 109026

Abstract

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Absract: Objective: Patients with rheumatoid arthritis (RA) usually receive triple therapy with methotrexate (MTX), leflunomide (LEF) and infliximab (IFX), but nearly one-third of them do not respond to triple therapy. This study aimed to identify biomarkers for predicting the efficacy of triple therapy to optimize personalized treatment of RA. Methods: All 20 enrolled patients met 2010 ACR/EULAR criteria for RA and were classified into good, moderate and non-responders (GR, MR, NR) for triple therapy. The Responders (R) were defined as the sum of GR and MR. Protein profiles of 4 responders and 4 non-responders were investigated via isobaric tags for relative and absolute quantification (iTRAQ), and differentially expressed proteins (DEPs) with high-confidence peptides were validated in 15 responders and 5 non-responders by parallel response monitoring (PRM). Results: iTRAQ identified 51 DEPs between responders and non-responders (p ±1.2). The top five up-regulated DEPs were B7Z7M2, A0A087WZR4, Q53FL1, P08254 and G3V2V8, while the top five down-regulated proteins were Q6MZX9, B3KP77, P0DJI9, P0DJI8 and P02787. Targeted mass spectrometry by PRM identified 10 candidate biomarkers, and 3 DEPs including fibrinogen beta chain, epididymal secretory protein Li 282 and testicular tissue protein Li 70 were confirmed as predictive biomarkers. Conclusion: This study demonstrated the feasibility of exploring biomarkers by applying iTRAQ and PRM mass spectrometry techniques, and a panel of biomarkers were identified to predict clinical response of IFX + MTX + LEF treatment in active RA patients.

Published in Biomedicine & Pharmacotherapy

ISSN: 0753-3322 (Print); 1950-6007 (Online)
Publisher: Elsevier
Country of publisher: France
LCC subjects: Medicine: Therapeutics. Pharmacology
Website: https://www.journals.elsevier.com/biomedicine-and-pharmacotherapy

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