Department of Rheumatology, VU University medical center, de Boelelaan 1117, Amsterdam, 1081HV, the Netherlands.
Arthritis Res Ther. 2012 Apr 27;14(2):R95. doi: 10.1186/ar3819.
B cell depletion therapy is efficacious in rheumatoid arthritis (RA) patients failing on tumor necrosis factor (TNF) blocking agents. However, approximately 40% to 50% of rituximab (RTX) treated RA patients have a poor response. We investigated whether baseline gene expression levels can discriminate between clinical non-responders and responders to RTX.
In 14 consecutive RA patients starting on RTX (test cohort), gene expression profiling on whole peripheral blood RNA was performed by Illumina® HumanHT beadchip microarrays. Supervised cluster analysis was used to identify genes expressed differentially at baseline between responders and non-responders based on both a difference in 28 joints disease activity score (ΔDAS28 < 1.2) and European League against Rheumatism (EULAR) response criteria after six months RTX. Genes of interest were measured by quantitative real-time PCR and tested for their predictive value using receiver operating characteristics (ROC) curves in an independent validation cohort (n = 26).
Genome-wide microarray analysis revealed a marked variation in the peripheral blood cells between RA patients before the start of RTX treatment. Here, we demonstrated that only a cluster consisting of interferon (IFN) type I network genes, represented by a set of IFN type I response genes (IRGs), that is, LY6E, HERC5, IFI44L, ISG15, MxA, MxB, EPSTI1 and RSAD2, was associated with ΔDAS28 and EULAR response outcome (P = 0.0074 and P = 0.0599, respectively). Based on the eight IRGs an IFN-score was calculated that reached an area under the curve (AUC) of 0.82 to separate non-responders from responders in an independent validation cohort of 26 patients using Receiver Operator Characteristics (ROC) curves analysis according to ΔDAS28 < 1.2 criteria. Advanced classifier analysis yielded a three IRG-set that reached an AUC of 87%. Comparable findings applied to EULAR non-response criteria.
This study demonstrates clinical utility for the use of baseline IRG expression levels as a predictive biomarker for non-response to RTX in RA.
B 细胞耗竭疗法在肿瘤坏死因子（TNF）阻断剂治疗失败的类风湿关节炎（RA）患者中有效。然而，大约 40%至 50%的利妥昔单抗（RTX）治疗的 RA 患者反应不佳。我们研究了基线基因表达水平是否可以区分 RTX 治疗的临床无反应者和有反应者。
在开始接受 RTX 治疗的 14 例连续 RA 患者（试验队列）中，通过 Illumina® HumanHT 珠芯片微阵列进行全外周血 RNA 的基因表达谱分析。基于 28 个关节疾病活动评分（ΔDAS28<1.2）和六个月后 RTX 的欧洲抗风湿病联盟（EULAR）反应标准之间的差异，通过监督聚类分析确定基线时反应者和无反应者之间表达差异的基因。通过定量实时 PCR 测量感兴趣的基因，并在独立验证队列（n=26）中使用接收者操作特征（ROC）曲线测试其预测价值。
全基因组微阵列分析显示，RA 患者在开始 RTX 治疗前外周血细胞存在明显差异。在这里，我们证明只有一个由干扰素（IFN）I 型网络基因组成的簇，由一组 IFN I 型反应基因（IRGs）组成，即 LY6E、HERC5、IFI44L、ISG15、MxA、MxB、EPSTI1 和 RSAD2，与ΔDAS28 和 EULAR 反应结果相关（P=0.0074 和 P=0.0599）。基于这 8 个 IRG，计算了 IFN 评分，根据 0.0074 和 0.0599 的差异，使用接收者操作特征（ROC）曲线分析，根据 ΔDAS28<1.2 标准，在 26 例独立验证队列中，该评分能够将无反应者与有反应者区分开来，曲线下面积（AUC）为 0.82。高级分类器分析得出了一个包含三个 IRG 的集合，AUC 达到 87%。类似的发现适用于 EULAR 无反应标准。
本研究证明了基线 IRG 表达水平作为预测 RTX 治疗 RA 无反应的生物标志物的临床应用价值。
