Department of Anatomy, Physiology and Genetics, USU Center for Medical Proteomics, Uniformed Services University School of Medicine, Bethesda, MD, USA.
Proteomics Clin Appl. 2011 Jun;5(5-6):311-21. doi: 10.1002/prca.201000109. Epub 2011 May 18.
Kidney transplantation is the treatment of choice for end stage renal disease, with long-term allograft loss being the major obstacle, and for which potential treatments are based on a histological diagnosis. The problem is that markers for predicting graft rejection are limited in number, are invasive, and are quite non-specific. We have hypothesized that protein biomarkers might be discovered in the urine of patients when acute or chronic rejection might be occurring.
We have established a workflow in which initial screening for candidate biomarkers is first performed using urine samples on large-scale antibody microarrays. This approach generated several dozen candidates. The next step is to qualify some of the strongest signals using the high-throughput Reverse Capture Protein Microarray platform.
Four top candidates including ANXA11, Integrin α3, Integrin β3 and TNF-α, initially identified by the antibody microarray platform, were all qualified using Reverse Capture Protein Microarrays. We also used receiver operating condition (ROC) curves to independently quantify the specificity and sensitivity of these four analytes.
The present data suggest that these novel four analytes in the urine, together or independently, may contribute to a robust and quantitative urine proteomic signature for diagnosing acute or chronic rejection of renal allografts.
肾移植是治疗终末期肾病的首选方法，长期移植物丢失是主要障碍，潜在的治疗方法基于组织学诊断。问题是，预测移植物排斥的标志物数量有限，具有侵入性，且特异性不高。我们假设，当发生急性或慢性排斥反应时，患者尿液中可能会发现蛋白质生物标志物。
我们建立了一个工作流程，首先使用尿液样本在大规模抗体微阵列上对候选生物标志物进行初步筛选。这种方法产生了数十个候选者。下一步是使用高通量反向捕获蛋白微阵列平台对一些最强信号进行定性。
最初在抗体微阵列平台上鉴定的四个候选标志物，包括 ANXA11、整合素α3、整合素β3 和 TNF-α，均通过反向捕获蛋白微阵列进行了鉴定。我们还使用接收者操作特性 (ROC) 曲线独立量化了这四种分析物的特异性和敏感性。
目前的数据表明，尿液中的这四种新型分析物，无论是单独使用还是联合使用，都可能有助于建立一种强大且定量的尿液蛋白质组学特征，用于诊断肾移植的急性或慢性排斥反应。
