概要: A major unmet need in rheumatoid arthritis (RA) is the choice of treatment options for patients with an inadequate response to anti-TNF agents (anti-TNF–IR). In order to identify pharmacodynamic biomarkers and assess differential effects of TNF- and non–TNF-targeting agents on RA patients with an inadequate response to anti-TNF–IR in comparison with biologic-naïve patients, peripheral protein markers and gene expression levels in association with clinical response posttreatment in two disease strata were assessed in disease-modifying antirheumatic drug (DMARD)-IR and anti-TNF-IR patients. Serum proteomics results indicated the existence of specific pharmacodynamic markers for golimumab and mavrilimumab, regardless of prior anti-TNF treatment. In contrast, both antibodies induced early and sustained suppression of RA disease markers, including IL-6, CRP, IL2RA, and MMP1, in DMARD-IR patients. Golimumab-induced early changes rapidly returned toward baseline concentrations in anti-TNF–IR patients, whereas mavrilimumab-induced changes were maintained through Day 169. RNA sequencing demonstrated gene expression changes at Day 169 after administration of mavrilimumab but not golimumab in anti-TNF–IR patients. Additionally, receiver operating characteristic curve and regression analysis showed the association of early IL-6 change and subsequent clinical responses to golimumab in anti-TNF-IR patients. Our results revealed golimumab- and mavrilimumab-specific pharmacodynamic biomarkers, and demonstrated differential biomarker-treatment relationships in anti-TNF–IR and DMARD-IR patients respectively. Early IL-6 change after anti-TNF antibody treatment may be a potential predictive biomarker for selection of different treatment regimens in anti-TNF-IR patients.
项目整体设计: For RNAseq study, PAXgene whole blood tubes were collected from 75 DMARD-IR and 63 anti-TNF-IR RA patients at baseline and at day 169 of post-treatment by golimumab and marvrilimumab. Whole transcriptome profiles of these patients and 20 health donors were generated from RNAseq data. Differentially expressed genes (DEG) resulted from drug-treatment were identified by pairwise comparisons between post-treatment and baseline data of the same patients. DEGs related with RA disease were identified by comparing baseline data with the data of health donors.
