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.

尽管有许多治疗类风湿性关节炎（RA）患者的方法，但很少有信息