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: 10460247
• 负责人: Harris R Perlman
• 金额: $ 57.09万
• 依托单位: NORTHWESTERN UNIVERSITY AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-18 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10460247
• 关键词: Aftercare; Anti-Tumor Necrosis Factor Therapy; Antirheumatic Agents; Biological Markers; Biological Response Modifier Therapy; Biology; Biopsy; Cell Separation; Characteristics; Clinical; Clinical Data; Clinical Trials; Computational Biology; Computer Analysis; Consumption; Data; Decision Making; Disease; Disease Pathway; Epidemiology; Exhibits; Future; Gene Expression; Gene Expression Profile; Genes; Genetic Transcription; Individual; Joints; Medical center; Methotrexate; Monitor; Mutation; Oncologist; Organ; Patient Recruitments; Patients; Pharmaceutical Preparations; Pharmacotherapy; Prediction of Response to Therapy; Predictive Value; Predisposition; Process; Publishing; Randomized; Research Personnel; Resistance; Rheumatoid Arthritis; Sample Size; Subgroup; Synovial Membrane; TNF gene; Testing; Therapeutic; Time; Tissues; Treatment Efficacy; United States; Work; arthritis registry; arthritis therapy; base; clinical practice; cohort; cost; differential expression; effective therapy; functional genomics; indexing; individual patient; ineffective therapies; inhibitor; macrophage; novel; novel marker; patient response; patient stratification; peripheral blood; precision medicine; predicting response; predictive marker; predictive signature; recruit; response; rheumatologist; standard of care; tool; transcriptome sequencing; transcriptomics; treatment response; tumor; ultrasound

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.

尽管针对类风湿性关节炎 (RA) 患者的治疗方法有很多，但目前的信息很少 指导针对个体患者选择最有效的治疗方法。百分之四六十 RA 患者对传统疾病治疗有反应（由 ACR50 反应标准定义） 抗风湿药物 (cDMARD) 或 cDMARD 加抗肿瘤坏死因子 (TNF) 治疗。 此外，临床试验中 20-40% 的 RA 受试者从未表现出哪怕是最小的反应 （ACR20 响应标准）。因此，显然需要开发精准治疗 RA 患者，新的生物标志物将增强我们预测治疗的能力 反应并限制无效治疗。大多数情况下，外周血已被用于 识别预测生物​​标志物，但这些研究缺乏足够的精度来允许他们 纳入临床实践。因此，类似于肿瘤学家，他们通过以下方式识别突变： 对肿瘤活检进行测序以指导治疗，我们的方法是对目标滑膜进行活检 RA 中的器官可识别反映对特定治疗的敏感性或耐药性的变化。 我们汇集了六家领先的医疗中心创建了 REASON，这是一个与 患者招募、临床数据管理、超声引导的既定框架 滑膜活检、细胞分选、RNA 测序 (RNA-seq) 和计算分析。我们的 数据显示，从超声引导的滑膜组织活检中分离出巨噬细胞 来自 RA 患者的数据足以进行 RNA 测序，在患者之间表现出转录差异 RA，并且重要的是，根据以下标准设定 RA 患者的分层框架： 最突出的疾病途径。我们是第一个识别出 6 个转录模块的人 通过超声引导滑膜从分离的滑膜巨噬细胞中共同调节基因 活检，与临床疾病状态和 cDMARD 单独相关或 生物疗法（bDMARD）。这项研究确立了 REASON 在美国的领先地位 用于超声引导滑膜活检并证明其可行性和治疗潜力 分离少量滑膜巨噬细胞进行 RNA 测序以建立精准医学 RA 治疗方法和了解病理学。虽然我们发表的研究表明 RA 患者中与 bDMARD 或甲氨蝶呤使用相关的转录特征 当疾病处于活动状态时，迫切需要鉴定可预测治疗反应的基因。 我们的首要假设是滑膜巨噬细胞的功能基因组分析将 识别新的转录特征，以告知对特定疗法的反应 个别患者，从而使研究人员和最终临床医生能够识别药物 最有可能对每个患者有效。