Differentially Expressed RNA from Public Microarray Data Identifies Serum Protein Biomarkers for Cross-Organ Transplant Rejection and Other Conditions
Differentially Expressed RNA from Public Microarray Data Identifies Serum Protein Biomarkers for Cross-Organ Transplant Rejection and Other Conditions
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DOI：
10.1371/journal.pcbi.1000940
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发表时间：
2010-09-01
影响因子：
4.3
通讯作者：
Butte, Atul J.
中科院分区：
文献类型：
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作者：
Chen, Rong;Sigdel, Tara K.;Butte, Atul J.
血清蛋白常用于疾病的诊断，但由于筛选血清蛋白质组的灵敏度低而难以发现。微阵列数据的公共存储库，如基因表达综合库（GEO），包含超过16，000种生物条件的RNA表达谱，覆盖了美国30%以上的死亡率。我们假设，编码血清和尿液可检测蛋白质的基因，以及在疾病损伤组织中显示RNA差异表达的基因，将成为这些疾病理想的诊断蛋白质生物标志物。我们发现，在22种疾病中，预测的蛋白质生物标志物显著富集了已知的诊断蛋白质生物标志物，在至少有三个数据集可用的疾病中，富集程度显著更高。然后，我们使用这种策略来寻找新的生物标志物，表明不同类型的移植实体器官的急性排斥反应（AR）。我们整合了三个基于活检的AR微阵列研究，分别来自儿童肾移植、成人肾移植和成人心脏移植，并确定了45个在所有三个中上调的基因。从这一组中，我们选择了10种蛋白质用于39例肾移植患者的血清ELISA测定，并发现了三种在AR中显着较高的蛋白质。有趣的是，在研究的63名心脏移植受者中，所有三种蛋白质在AR期间也显著升高。我们最好的标记物，血清PECAM 1，鉴定肾AR的敏感性为89%，特异性为75%，并且通过免疫组织化学在肾、肝和心脏移植活检中也显示AR表达增加。我们的研究结果表明，整合来自疾病样本甚至公开数据集的基因表达微阵列测量结果可以成为发现新诊断血清蛋白生物标志物的强大，快速和具有成本效益的策略。
Serum proteins are routinely used to diagnose diseases, but are hard to find due to low sensitivity in screening the serum proteome. Public repositories of microarray data, such as the Gene Expression Omnibus (GEO), contain RNA expression profiles for more than 16,000 biological conditions, covering more than 30% of United States mortality. We hypothesized that genes coding for serum-and urine-detectable proteins, and showing differential expression of RNA in disease-damaged tissues would make ideal diagnostic protein biomarkers for those diseases. We showed that predicted protein biomarkers are significantly enriched for known diagnostic protein biomarkers in 22 diseases, with enrichment significantly higher in diseases for which at least three datasets are available. We then used this strategy to search for new biomarkers indicating acute rejection (AR) across different types of transplanted solid organs. We integrated three biopsy-based microarray studies of AR from pediatric renal, adult renal and adult cardiac transplantation and identified 45 genes upregulated in all three. From this set, we chose 10 proteins for serum ELISA assays in 39 renal transplant patients, and discovered three that were significantly higher in AR. Interestingly, all three proteins were also significantly higher during AR in the 63 cardiac transplant recipients studied. Our best marker, serum PECAM1, identified renal AR with 89% sensitivity and 75% specificity, and also showed increased expression in AR by immunohistochemistry in renal, hepatic and cardiac transplant biopsies. Our results demonstrate that integrating gene expression microarray measurements from disease samples and even publicly-available data sets can be a powerful, fast, and cost-effective strategy for the discovery of new diagnostic serum protein biomarkers.