Exploring the influence of treatment on CD4+ T-cell sub-populations in patients receiving biologic drugs for their inflammatory arthritis.

背景：肿瘤坏死因子抑制剂（TNFi）治疗对大约20%的类风湿性关节炎（RA）患者无效，目前没有办法预测哪些患者不会受益。为了解决这个精准医疗问题，需要可靠的TNFi反应生物标志物。CD4+ t细胞在RA发病机制中的作用已经得到了很好的证实，高维单细胞技术，如细胞计数术（即CyTOF）已经揭示了CD4+ t细胞的广泛多样性，这些细胞在RA中扩增并随着治疗的成功而收缩(1)。然而，确切的t细胞亚群和关键效应功能驱动和延续RA仍有待完全解决，很少有研究专门研究它们在TNFi治疗反应中的作用。将提供40名开始接受TNFi治疗的RA患者的pbmc和血清样本。在治疗前和1小时采集样本，在2周、4周和6周进行槽采样，在3个月进行随访收集。使用DAS28评分系统记录的疾病活动也将可用。成功的候选人将监督在每次随访中收集的血清中药物水平数据的生成。CD4+ t细胞的免疫表型将使用我们实验室已经建立的CyTOF抗体面板进行(2)。实验室数据将在第一年由曼彻斯特大学肌肉骨骼研究中心和流式细胞术核心设施的实验室团队生成。如果希望获得一些实验室经验，候选人可以选择参与实验室工作。这是一个正在进行的收集，因此在项目时间表的后期将提供额外的样品用于验证实验。该学生将应用最先进的统计技术来表征t细胞亚群丰度，细胞内信号转导，并确定与血清药物水平和TNFi早期治疗期间疾病活动改善相关的最重要的细胞类型。识别RA对TNFi治疗反应的生物标志物将加强患者分层和靶向治疗，更好地表征致病性t细胞亚群在决定重要临床结果中的作用，并表征耐药或与良好治疗反应相关的分子特征。

Background: Tumour necrosis factor inhibitor (TNFi) therapy is ineffective for approximately 20% of rheumatoid arthritis (RA) patients and there is currently no way to predict which patients will not benefit. To address this precision medicine question, reliable biomarkers of TNFi response are needed. The role of CD4+ T-cells in the pathogenesis of RA is well established and high dimensional single cell technologies such as mass cytometry (i.e. CyTOF) have revealed a broad diversity of CD4+ T-cells that are expanded in RA and contract with successful treatment (1). However, the precise T-cell subsets and key effector functions driving and perpetuating RA remains to be completely resolved and very few studies have specifically investigated their role in treatment response to TNFi. PBMCs and serum samples will be made available from 40 RA patients commencing treatment with TNFi. Samples are collected at pre-treatment and 1-hour, followed by trough sampling at 2-weeks, 4-weeks and 6-weeks, with follow-up collection at 3-months. Disease activity recorded using the DAS28 scoring system will also be available. The successful candidate will oversee the generation of drug level data in serum collected at each follow-up visit. Immunophenotyping of CD4+ T-cell will be performed using a CyTOF antibody panel that is already established in our laboratory (2). Laboratory data will be generated during the first year of the studentship by the laboratory team in the Centre for Musculoskeletal Research and the Flow Cytometry Core Facility within University of Manchester. The candidate has the option of being involved in the laboratory work if there is a desire to acquire some laboratory experience. This is an ongoing collection therefore additional samples will be made available for validation experiments later in the project timeline.This studentship will apply state-of-the-art statistical techniques to characterise T-cell subset abundance, intracellular signal transduction and to identify the most important cell-types associated with trough serum drug levels and improvement in disease activity during early treatment with TNFi. Identifying biomarkers of treatment response to TNFi in RA will enhance patient stratification and targeted therapy, better characterise the role of pathogenic T-cell subsets in determining important clinical outcomes and characterise molecular signatures that are resistant to treatment or correlated with good treatment response.