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

工作背景：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。为了解决这个精确医学问题，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得到充分证实，并且高维度单细胞技术如质谱细胞术（即CyTOF）已揭示了在RA中扩增并与成功治疗相联系的CD4+ T细胞的广泛多样性（1）。然而，驱动和维持RA的精确T细胞亚群和关键效应子功能仍有待完全解决，很少有研究专门研究它们在TNFi治疗反应中的作用。将从开始用TNFi治疗的40名RA患者提供PBMC和血清样品。在治疗前和1小时采集样本，然后在2周、4周和6周采集谷值样本，并在3个月时进行随访采集。还将提供使用DAS 28评分系统记录的疾病活动。成功的候选人将监督每次随访访视时收集的血清中药物水平数据的生成。将使用我们实验室已经建立的CyTOF抗体组进行CD4+ T细胞的免疫表型分析（2）。实验室数据将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在学生的第一年产生。候选人可以选择参与实验室工作，如果有愿望获得一些实验室经验。这是一个正在进行的收集，因此额外的样本将可用于验证实验后，在项目时间轴。这个学生将应用最先进的统计技术，以CDT细胞亚群丰度，细胞内信号转导，并确定最重要的细胞类型与谷血清药物水平和改善疾病活动在早期治疗TNFi。识别RA中对TNFi的治疗反应的生物标志物将增强患者分层和靶向治疗，更好地确定致病性T细胞亚群在确定重要临床结果中的作用，并识别对治疗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.