Discovery of serum proteomic biomarkers for prediction of response to infliximab (a monoclonal anti-TNF antibody) treatment in rheumatoid arthritis: An exploratory analysis

Abstract

Biologics such as TNF antagonists are a new class of drugs that have greatly improved Rheumatoid Arthritis (RA) treatment. However, for unknown reasons, individual patients with RA respond to one of these drugs but not to others even those targeting the same molecule. Methods to predict response are sorely needed because these drugs are currently selected by trial and error, what is very inefficient and prejudicial for the patient and the healthcare system. Here, we have explored the discovery of protein biomarkers in serum from patients treated with infliximab, one of the major anti-TNF drugs. The study was based in a quantitative proteomics approach using 8-plex iTRAQ labeling. It combined depletion of the most abundant serum proteins, two-dimensional LC fractionation, protein identification and relative quantification with a hybrid Orbitrap mass spectrometer. This approach allowed the identification of 315 proteins of which 237 were confidently quantified with two or more peptides. The detection range covered up to 6 orders of magnitude including multiple proteins at the ng/mL level. A new set of putative biomarkers was identified comprising 14 proteins significantly more abundant in the non-responder patients. The differential proteins were enriched in apolipoproteins, components of the complement system and acute phase reactants. These results show the feasibility of this approach and provide a set of candidates for validation as biomarkers for the classification of RA patients before the beginning of treatment, so that anticipated non-responders could be treated with an alternative drug. Rheumatoid Arthritis (RA) treatment. However, for unknown reasons, individual 3 patients with RA respond to one of these drugs but not to others even those targeting the 4 same molecule. Methods to predict response are sorely needed because these drugs are 5 currently selected by trial and error, what is very inefficient and prejudicial for the 6 patient and the healthcare system. Here, we have explored the discovery of protein 7 biomarkers in serum from patients treated with infliximab, one of the major anti-TNF 8 drugs. The study was based in a quantitative proteomics approach using 8-plex iTRAQ 9 labeling. It combined depletion of the most abundant serum proteins, two-dimensional 10 LC fractionation, protein identification and relative quantification with a hybrid 11Orbitrap mass spectrometer. This approach allowed the identification of 315 proteins of 12 which 237 were confidently quantified with two or more peptides. The detection range 13 covered up to 6 orders of magnitude including multiple proteins at the ng/mL level. A 14 new set of putative biomarkers was identified comprising 14 proteins significantly more 15 abundant in the non-responder patients. The differential proteins were enriched in 16 apolipoproteins, components of the complement system and acute phase reactants. 17These results show the feasibility of this approach and provide a set of candidates for 18 validation as biomarkers for the class...

ACPA-positive and ACPA-negative rheumatoid arthritis differ in their requirements for combination DMARDs and corticosteroids: secondary analysis of a randomized controlled trial

“…Genetic markers also offer promise with a recent large genome-wide association study reporting the first definitive genetic association (in the CD84 gene) with anti-TNF response [25]. Other smaller studies suggest that stimulated whole blood cell pro-inflammatory cytokine levels [26] and serum proteins [27] may be useful in predicting anti-TNF efficacy. These findings are promising but lack clinical utility, since most markers require validation in larger cohorts or associate with only small differences in treatment response.…”

Proteomics to predict the response to tumour necrosis factor-α inhibitors in rheumatoid arthritis using a supervised cluster-analysis based protein score

“…The other six studies all proposed predictors of response to therapy; however, none of these studies performed a technical replication or separate validation in new patients, and the overlap of discovered predictors between studies is restricted to CCL2 (monocyte chemoattractant protein-1, MCP-1), which has been cross-validated in two studies (14,15). However, CCL2 was not shown to be predictive in our study and was not identified in the studies using mass spectrometry (17,18), implying that it is not a consistent predictor. Several other proteins proposed as predictors in earlier studies were measured in our xMAP panel, including chemokine (C-X-C motif) ligand 4 (CXCL4), granulocyte-macrophage colony-stimulating factor (GM-CSF), IL-1α, IL-1β, IL-6, IL-8, IL-15, IL-19, IP-10, and TNF-α.…”

“…It is therefore not expected that patients with a low DAS28 and high HAQ will have a better response to any non-TNFi. Proteomic approaches to the prediction of response have been studied before (14)(15)(16)(17)(18)(19)(20)(21)). An overview of these studies and reported results is presented in Table 5.…”

A Quantitative Proteomic Approach to Identify Significantly Altered Protein Networks in the Serum of Patients with Lymphangioleiomyomatosis (LAM)

“…We have provided a dynamic list of proteins which were significantly altered in the circulation of LAM patients, three of which we validated in individual LAM and healthy control samples in order to strengthen the mass spectrometry findings. The strength of this study is that we have validated, in a larger population, four of the proteins (similar to other serum screening studies [39]) identified to differ in two separate LAM cohorts subsequent to screening with iTRAQ labels.…”