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A proteome resource of ovarian cancer ascites: Integrated proteomic and bioinformatic analyses to identify putative biomarkers

机译:卵巢癌腹水的蛋白质组资源:蛋白质组学和生物信息学综合分析,以鉴定假定的生物标志物

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Epithelial ovarian cancer is the most lethal gynecological malignancy, and disease-specific biomarkers are urgently needed to improve diagnosis, prognosis, and to predict and monitor treatment efficiency. We present an in-depth proteomic analysis of selected biochemical fractions of human ovarian cancer ascites, resulting in the stringent and confident identification of over 2500 proteins. Rigorous filter schemes were applied to objectively minimize the number of false-positive identifications, and we only report proteins with substantial peptide evidence. Integrated computational analysis of the ascites proteome combined with several recently published proteomic data sets of human plasma, urine, 59 ovarian cancer related microarray data sets, and protein-protein interactions from the Interologous Interaction Database (ID)-D-2 (http://ophid.utoronto.ca/i2d) resulted in a short-list of 80 putative biomarkers. The presented proteomics analysis provides a significant resource for ovarian cancer research, and a framework for biomarker discovery.
机译:上皮性卵巢癌是最致命的妇科恶性肿瘤,急切需要疾病特异性的生物标志物以改善诊断,预后以及预测和监测治疗效率。我们对人类卵巢癌腹水的选定生化成分进行了深入的蛋白质组学分析,从而对2500多种蛋白质进行了严格而有信心的鉴定。严格的过滤方案被应用于客观地减少假阳性鉴定的数量,并且我们仅报告具有大量肽证的蛋白质。腹水蛋白质组的综合计算分析,结合最近发表的人类血浆,尿液,59种卵巢癌相关微阵列数据集的蛋白质组学数据集以及来自内部相互作用数据库(ID)-D-2的蛋白质-蛋白质相互作用(http:/ /ophid.utoronto.ca/i2d)筛选出80个假定的生物标记物。提出的蛋白质组学分析为卵巢癌研究提供了重要资源,并为生物标记物发现提供了框架。

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