Gene Expression Signatures to Predict Treatment Response in Systemic Sclerosis

预测系统性硬化症治疗反应的基因表达特征

基本信息

批准号：
8834415
负责人：
MICHAEL W FANGER
金额：
$ 63.91万
依托单位：
CELDARA MEDICAL, LLC
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-09-06 至 2016-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8834415
关键词：
Adverse effects Algorithms Archives Autoantibodies Autoimmune Diseases Biochemical Pathway Bioinformatics Biological Markers Biopsy Blood Vessels Cellcept Classification Clinical Clinical Course of Disease Clinical Trials DNA Microarray Chip Development Diagnosis Diagnostic Disease Enrollment Etiology Exposure to Fibrosis Freezing Gene Expression Gene Expression Profile Gene Expression Profiling Genes Gleevec Goals Gold Health Heart Hereditary Disease Heterogeneity Imatinib mesylate Immunosuppressive Agents Individual Inflammatory Laboratories Lung Maps Measures Molecular Molecular Profiling Nature Observational Study Organ Outcome Outcome Measure Paraffin Embedding Pathogenesis Pathway interactions Patient Selection Patients Pharmaceutical Preparations Pharmacologic Substance Phase Physicians Pilot Projects Publishing Relative (related person)Research Design Risk Sampling Scleroderma Services Signal Pathway Skin Systemic Scleroderma Testing Translating Tyrosine Kinase Inhibitor Validation Work base clinical phenotype cohort cost design drug development effective therapy effectiveness trial efficacy trial improved insight lymphocyte proliferation malignant breast neoplasm mycophenolate mofetil nano-string novel novel diagnostics open label patient population prospective research clinical testing response risk benefit ratio standard of care technology development tool treatment planning treatment response

项目摘要

DESCRIPTION (provided by applicant): Today, systemic sclerosis (SSc) clinical trials generally include all subsets; some may benefit, others do not, confounding measures of efficacy. Because each expression subset has a different underlying deregulated molecular pathway, no single drug is expected to benefit all patients i.e. rational patient selection is required to facilitate drug development. Further, a quantitative measure of clinical outcome and endpoints will enable a scientific measure of trial effectiveness and avoid the difficulties associated with the cyclic nature of SSc. For example, response to imatinib mesylate (Gleevec(R)), a tyrosine kinase inhibitor and to mycophenolate mofetil (Cellcept), an attenuator of lymphocyte proliferation, can be quantitatively measured by gene expression. Finally, insights into the molecular pathways defining each subtype will enable us to identify and potentially design new drugs. Beyond drug development, subtyping will help individual patients and their doctors by allowing an individualized treatment plan informed by each patient's subtype. Together, these benefits are both exciting and compelling, and are fundamentally changing what it means to be diagnosed with SSc. This work will provide insights into the pathogenesis of the disease that may influence the development of new treatments by other groups or pharmaceutical companies. The immediate result of this study is the validation and prospective clinical testing of gene expression biomarkers on a new platform for predicting treatment response in SSc. Development of this technology into a clinical diagnostic tool and service will significantly improve the management and ultimately the health of patients with SSc.

描述（由申请人提供）：如今，系统性硬化症（SSc）临床试验通常包括所有子集；有些人可能受益，有些人则不然，从而混淆了功效衡量标准。由于每个表达子集具有不同的潜在失调分子途径，因此预计没有一种药物可以使所有患者受益，即需要合理的患者选择以促进药物开发。此外，对临床结果和终点的定量测量将能够对试验有效性进行科学测量，并避免与 SSc 的循环性质相关的困难。例如，可以通过基因表达来定量测量对甲磺酸伊马替尼(Gleevec )(一种酪氨酸激酶抑制剂)和对吗替麦考酚酯(Cellcept)(一种淋巴细胞增殖衰减剂)的反应。最后，对定义每种亚型的分子途径的深入了解将使我们能够识别并可能设计新药物。除了药物开发之外，亚型分析还可以根据每个患者的亚型制定个性化的治疗计划，从而帮助个体患者及其医生。总之，这些好处既令人兴奋又引人注目，并且从根本上改变了诊断 SSc 的含义。这项工作将深入了解该疾病的发病机制，这可能会影响其他团体或制药公司新疗法的开发。这项研究的直接结果是在一个新平台上对基因表达生物标志物进行验证和前瞻性临床测试，用于预测 SSc 的治疗反应。将该技术开发成临床诊断工具和服务将显着改善 SSc 患者的管理并最终改善其健康状况。