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首页> 外文期刊>Molecular & cellular proteomics: MCP >A web-based tool for in silico biomarker discovery based on tissue-specific protein profiles in normal and cancer tissues.
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A web-based tool for in silico biomarker discovery based on tissue-specific protein profiles in normal and cancer tissues.

机译:一种基于Web的工具,用于基于正常组织和癌症组织中的组织特异性蛋白质概况进行计算机电子生物标记物发现。

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摘要

Here we report the development of a publicly available Web-based analysis tool for exploring proteins expressed in a tissue- or cancer-specific manner. The search queries are based on the human tissue profiles in normal and cancer cells in the Human Protein Atlas portal and rely on the individual annotation performed by pathologists of images representing immunohistochemically stained tissue sections. Approximately 1.8 million images representing more than 3000 antibodies directed toward human proteins were used in the study. The search tool allows for the systematic exploration of the protein atlas to discover potential protein biomarkers. Such biomarkers include tissue-specific markers, cell type-specific markers, tumor type-specific markers, markers of malignancy, and prognostic or predictive markers of cancers. Here we show examples of database queries to generate sets of candidate biomarker proteins for several of these different categories. Expression profiles of candidate proteins can then subsequently be validated by examination of the underlying high resolution images. The present study shows examples of search strategies revealing several potential protein biomarkers, including proteins specifically expressed in normal cells and in cancer cells from specified tumor types. The lists of candidate proteins can be used as a starting point for further validation in larger patient cohorts using both immunological approaches and technologies utilizing more classical proteomics tools.
机译:在这里,我们报告了一种可公开使用的基于Web的分析工具的开发情况,该工具可用于探索以组织或癌症特异性方式表达的蛋白质。搜索查询基于正常蛋白质和人类蛋白质图谱门户中癌细胞中的人类组织概况,并依赖于病理学家对代表免疫组织化学染色组织切片的图像进行的单独注释。这项研究使用了约180万张代表3000多种针对人类蛋白质的抗体的图像。该搜索工具允许对蛋白质图谱进行系统的探索,以发现潜在的蛋白质生物标记。这样的生物标志物包括组织特异性标志物,细胞类型特异性标志物,肿瘤类型特异性标志物,恶性肿瘤标志物和癌症的预后或预测标志物。在这里,我们显示了数据库查询的示例,以针对这些不同类别中的几种类别生成候选生物标记蛋白集。然后可以通过检查基础的高分辨率图像来验证候选蛋白质的表达谱。本研究显示了一些搜索策略的例子,这些策略揭示了几种潜在的蛋白质生物标记,包括在正常细胞和特定肿瘤类型的癌细胞中特异性表达的蛋白质。候选蛋白质列表可作为起点,通过免疫学方法和利用更多经典蛋白质组学工具的技术在更大的患者队列中进行进一步验证。

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