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

探索治疗对接受生物药物治疗炎症性关节炎患者的 CD4 T 细胞亚群的影响。

• 批准号: 2281966
• 金额: --
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2281966
• 关键词: Exploring; influence; treatment; CD4+; cell

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.

背景：肿瘤坏死因子抑制物(TNFi)治疗对大约20%的类风湿性关节炎(RA)患者无效，目前还没有办法预测哪些患者不会受益。为了解决这一精确医学问题，需要可靠的TNFi反应生物标志物。CD4+T细胞在类风湿关节炎发病机制中的作用已得到充分证实，高维单细胞技术，如质量细胞分析(CyTOF)，揭示了在类风湿关节炎中扩增并与成功治疗相关的广泛多样性的CD4+T细胞[1]。然而，驱动和维持类风湿性关节炎的确切T细胞亚群和关键效应器功能仍未完全解决，很少有研究专门研究它们在治疗反应中的作用。将提供40名开始接受TNFi治疗的RA患者的PBMC和血清样本。在治疗前和治疗后1小时采集样本，然后在2周、4周和6周进行槽式采样，并在3个月时进行随访采集。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后续访问中收集的血清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细胞免疫表型抗体小组进行(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仪核心设施的实验室团队在学生第一年期间生成。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，因此将在项目时间表的晚些时候提供更多的样本用于验证实验。这个学生将应用最先进的统计技术来表征T细胞亚群的丰度、细胞内的信号转导，并识别与低谷血清药物水平和在使用TNFi的早期治疗期间疾病活动的改善相关的最重要的细胞类型。识别类风湿关节炎患者对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。