Development of a Precision Medicine-based Diagnostic Tool for Membranous Nephropathy

膜性肾病精准医学诊断工具的开发

• 批准号: 10602134
• 负责人: Christopher P Larsen
• 金额: $ 101.85万
• 依托单位: NEPHROPATHOLOGY ASSOCIATES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-15 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10602134
• 关键词: Agreement; Antigens; Arkansas; Artificial Intelligence; Autoantibodies; Autoantigens; Autoimmune Diseases; Benchmarking; Biological Assay; Biopsy; Blinded; CLIA certified; Chronic Inflammatory Demyelinating Polyneuropathy; Classification; Clinical; Collaborations; Comparative Study; Core Biopsy; Cost Sharing; Data; Data Analyses; Development; Diagnosis; Disease; Disease Progression; Disease remission; Ensure; Equipment; Etiology; Exclusion; Frozen Sections; Generations; Goals; Human; Individual; Investigation; Kidney Failure; Laboratories; Lead; Life; Link; Malignant Neoplasms; Mass Spectrum Analysis; Medical; Membranous Glomerulonephritis; Methods; Modality; Molecular; Monitor; Nephrotic Syndrome; Outcome; Patients; Performance; Periodicity; Phase; Phospholipase A2; Price; Process; Prognosis; Proteins; Proteomics; Protocols documentation; Publications; Quality Control; Reagent; Resources; Running; Sampling; Science; Serology; Serology test; Services; Severities; Standardization; System; Systemic Lupus Erythematosus; Testing; Thrombospondins; Time; Tissues; Training; Translating; Universities; Validation; base; biobank; clinical practice; commercialization; comorbidity; cost; diagnostic tool; experimental study; follow-up; improved; instrument; instrumentation; kidney biopsy; novel; novel strategies; personalized medicine; phase 1 study; phase 1 testing; precision medicine; programs; receptor; statistical and machine learning; success; tool; trend; validation studies

Project Summary The goal of this program is to initiate commercialization of a mass spectrometry (MS)-based workflow for the diagnosis and classification of membranous nephropathy (MN), a leading cause of nephrotic syndrome, leading to kidney failure in a third of patients. Since the 1950’s, most forms of MN were considered idiopathic in origin, however, based on numerous publications in recent years, it is now broadly accepted that MN is caused by autoantibodies against approximately 20 different endogenous human proteins. The most common MN autoantigen is the phospholipase A2 receptor (PLA2R), and serological analysis of autoantibody titers against this protein has proven to be an indispensable serological tool for monitoring disease progression, severity, and remission (1-3). Arkana and others have identified additional novel autoantigens in MN cases (4-9), and given the success of PLA2R serological testing for personalized treatment, the characterization and clinical validation of the remaining MN autoantigens is urgently required. Furthermore, follow-up investigation of patients positive for these newly identified autoantigens have been linked to life-threatening comorbidities including cancer and specific autoimmune diseases. Because classifying patients based on MN autoantigen may reveal severe underlying conditions, and PLA2R serology will identify only 70% of primary cases, Arkana has partnered with proteomics experts at the University of Arkansas for Medical Sciences (UAMS) to develop an unbiased, MS- based approach to classifying MN of all antigen types. Phase I studies evaluated nearly 300 tissue biopsies from MN patients with previously determined autoantigens including PLA2R, thrombospondin type-1 domain containing 7A (THSD7A) (10), and exostosin1/2 (EXT1/2) (11), with triple negative cases also included. After evaluating a range of computational, statistical, and artificial intelligence data analysis modalities, ranked Z- scores were found to be an effective metric for autoantigen classification, correctly classifying over 95% of samples. During the proposed Phase II program, Arkana will continue collaborating with UAMS to translate this powerful method to clinical practice and commercial availability. Quality control metrics will be developed for the inclusion/exclusion of incoming samples, to ensure the reliability and repeatability of MS analysis and support verification of autoantigen classifications. The analytical pipeline will also be broadened to accommodate additional autoantigen targets, many of which were identified by Arkana’s recent MS analysis of hundreds of biobanked MN samples. Finally, the method will be transferred to Arkana’s CLIA laboratory and validated in a comparative study with UAMS comprising approximately 300 blinded samples representing the full breadth of MN autoantigen classes. Launching this workflow as a commercially available service will not only offer clinicians unprecedented detail for the diagnosis and treatment of MN patients, but also reveal potentially life-threatening comorbidities undetectable by prior generation strategies.

项目概要 该计划的目标是启动基于质谱 (MS) 的工作流程的商业化 膜性肾病（MN）的诊断和分类，膜性肾病是肾病综合征的主要原因， 自 20 世纪 50 年代以来，大多数类型的 MN 被认为是特发性的。 然而，根据近年来的大量出版物，现在人们普遍认为 MN 是由 由针对大约 20 种不同内源性人类蛋白的自身抗体产生 最常见的 MN。 自身抗原是磷脂酶 A2 受体 (PLA2R)，对自身抗体滴度进行血清学分析 该蛋白质已被证明是监测疾病进展、严重程度和病情的不可或缺的血清学工具。 Arkana 和其他人在 MN 病例中发现了其他新的自身抗原 (4-9)，并给予缓解。 PLA2R 血清学检测在个性化治疗、表征和临床验证方面的成功 此外，还迫切需要对阳性患者进行后续调查。 因为这些新发现的自身抗原与危及生命的合并症有关，包括癌症和 因为根据 MN 自身抗原对患者进行分类可能会发现严重的自身免疫性疾病。 Arkana 与 阿肯色大学医学科学分校 (UAMS) 的蛋白质组学专家开发了一种公正的 MS- 基于对所有抗原类型的 MN 进行分类的方法，第一阶段研究评估了近 300 个组织活检。 具有先前确定的自身抗原（包括 PLA2R、血小板反应蛋白 1 型结构域）的 MN 患者 含有 7A (THSD7A) (10) 和外骨蛋白 1/2 (EXT1/2) (11)，还包括三阴性病例。 评估一系列计算、统计和人工智能数据分析模式，排名为 Z- 分数被发现是自身抗原分类的有效指标，正确分类了 95% 以上 在拟议的第二阶段计划中，Arkana 将继续与 UAMS 合作翻译此内容。 将为临床实践和商业可用性开发强大的方法。 纳入/排除传入样品，以确保 MS 分析和支持的可靠性和可重复性 自身抗原分类的验证也将扩大以适应。 其他自身抗原目标，其中许多是通过 Arkana 最近对数百个 最后，该方法将被转移到阿卡纳的 CLIA 实验室并在一个实验室中进行验证。 与 UAMS 的比较研究包括大约 300 个盲样本，代表了整个领域 MN 自身抗原类作为商业服务启动不仅会提供服务。 MN患者的诊断和治疗细节前所未有，但也揭示了潜在的危及生命的风险 上一代策略无法检测到的合并症。