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Synovial Macrophage Transcriptional Signatures for Predicting Therapeutic Efficacy

Synovial Macrophage Transcriptional Signatures for Predicting Therapeutic Efficacy
用于预测治疗效果的滑膜巨噬细胞转录特征
批准号:
9766023
负责人:
Harris R Perlman
金额:
$63.65万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-18 至 2024-07-31

项目摘要

项目成果

Harris R Perlman的其他基金

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中文摘要
翻译
尽管治疗类风湿性关节炎(RA)的方法很多,但几乎没有关于 指导为个别患者选择最有效的治疗方法。4060%的 类风湿关节炎患者对常规疾病修改的反应(由ACR50反应标准定义) 抗风湿药物(CDMARDS)或cDMARDS加抗肿瘤坏死因子(TNF)治疗。 此外,在临床试验中,20-40%的RA受试者从未表现出哪怕是最低限度的反应 (ACR20响应标准)。因此,显然有必要发展以精确为基础的治疗 类风湿性关节炎患者,新的生物标志物将增强我们预测治疗的能力 反应和限制无效的治疗。在很大程度上,外周血被用来 识别预测性生物标记物,但这些研究缺乏足够的精确度来允许他们的 纳入临床实践。因此,类似于肿瘤学家,他们通过 对肿瘤活检的顺序进行直接治疗,我们的方法是对滑膜进行活检,靶点是滑膜 RA中的器官,以识别反映对特定治疗的敏感性或耐药性的变化。 我们召集了六个领先的医疗中心来创造原因,一个联盟与 建立了患者招募、临床数据管理、超声引导的框架 滑膜活检、细胞分类、RNA测序(rna-seq)和计算分析。我们的 数据显示,从超声引导下的滑膜组织活检中分离出的巨噬细胞 来自RA患者的足够的RNA-SEQ,在不同患者之间表现出转录差异 与RA,重要的是,设定了RA患者分层的框架,根据 最突出的致病途径。我们首次鉴定出6个转录模块 超声引导下分离的滑膜巨噬细胞的共调控基因 活检,分别与临床疾病状态和cDMARD或 生物疗法(BDMARD)。这项研究确立了Reason在美国处于领先地位 用于超声引导的滑膜活检,并证明了其可行性和治疗潜力 分离低数量滑膜巨噬细胞用于RNA-SEQ建立精密药物 类风湿关节炎的治疗方法和对病理生物学的了解。虽然我们发表的研究发现 类风湿关节炎患者使用bDMARD或甲氨蝶呤相关的转录特征 对于活动性疾病,有一个核心需要确定预测治疗反应的基因。 我们的主要假设是滑膜巨噬细胞的功能基因组分析将 识别新的转录信号,影响对特定治疗的反应 单个患者,从而使研究人员和最终的临床医生能够识别药物 最有可能为每个病人工作。
英文摘要
Despite the many therapies for patients with rheumatoid arthritis (RA), there is little information to guide selection of the most effective treatment for an individual patient. Forty-sixty percent of patients with RA respond (defined by ACR50 response criteria) to conventional disease modifying anti-rheumatic drugs (cDMARDs) or cDMARDs plus anti-tumor necrosis factor (TNF) therapy. Moreover, 20-40% of RA subjects in clinical trials never demonstrate even a minimal response (ACR20 response criteria). Hence, there is a clear need to develop precision-based therapy for patients with RA, whereby novel biomarkers will enhance our ability to predict therapeutic response and limit ineffective therapy. For the most part, peripheral blood has been utilized for identifying predictive biomarkers, but these studies lacked sufficient precision to allow their incorporation into clinical practice. Thus, similar to an oncologist, who identify mutations through sequencing of tumor biopsies to direct therapy, our approach is to biopsy the synovium, the target organ in RA to identify changes that reflect sensitivity or resistance to a particular therapy. We brought together six leading medical centers to create REASON, a consortium with an established framework for patient recruitment, curation of clinical data, ultrasound-guided synovial biopsies, cell sorting, RNA sequencing (RNA-seq), and computational analyses. Our data show that macrophages isolated from ultrasound-guided synovial tissue biopsies obtained from patients with RA are sufficient for RNA-seq, exhibit transcriptional differences across patients with RA, and, importantly, set the framework for the stratification of patients with RA according to the most prominent disease pathway. We are the first to identify 6 transcriptional modules of co-regulated genes from isolated synovial macrophages via ultrasound-guided synovial biopsy, that are individually associated with clinical disease status and cDMARD or biologic therapy (bDMARD). This study established REASON as a leader in the United States for ultrasound-guided synovial biopsies and demonstrates the feasibility and therapeutic potential of isolating low numbers of synovial macrophages for RNA-seq to establish a precision-medicine approach for RA therapy and to understand pathobiology. While our published study identified transcriptional signatures associated with bDMARD or methotrexate usage in RA patients with active disease, there is a central need to identify genes that are predictive of response to therapy. Our overarching hypothesis is that functional genomic analysis of synovial macrophages will identify novel transcriptional signatures that inform on response to particular therapies in individual patients, thereby enabling researchers and, ultimately, clinicians to identify the drug most likely to work for each patient.
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Macrophage Heterogeneity in Rheumatoid Arthritis
Macrophage Heterogeneity in Rheumatoid Arthritis
Synovial Macrophage Transcriptional Signatures for Predicting Therapeutic Efficacy
Synovial Macrophage Transcriptional Signatures for Predicting Therapeutic Efficacy