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

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.

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► First label-based proteomics study for prediction of response to biologics in RA
► High performance of dual-pressure LIT CID + HCD combination for iTRAQ quantitation
► We report 14 serum potential markers for prediction of response to treatment in RA
► Most of these biomarkers related with RA or chronic inflammation processes
► Could help classify RA patients as responders and non-responders before treatment