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与制药相关的细胞因子受体:来自人类蛋白质组初稿的经验教训。

Pharmaceutical relevant cytokine receptors: lessons from the first drafts of the human proteome.

作者信息

Garbers Christoph, Rose-John Stefan

机构信息

Institute of Biochemistry, Kiel University , Olshausenstrasse 40, 24098 Kiel, Germany.

出版信息

J Proteome Res. 2015 Feb 6;14(2):1330-2. doi: 10.1021/pr500875b. Epub 2014 Dec 8.

Abstract

Although a plethora of human proteins are ubiquitously expressed, several proteins with high pharmaceutical relevance show a tissue- or cell-type specific expression pattern. Science across all disciplines, ranging from developmental biology to personalized medicine, would benefit from detailed knowledge about this so-called human proteome. Two recent publications in Nature use large-scale proteomics to create first drafts of the human proteome, which are freely accessible online. In this Letter, we analyze the proteomic data with regard to the expression of three different cytokine receptors, the Tumor Necrosis Factor (TNF)α Receptor I (TNFRSF1A) and II (TNFRSF1B) and the Interleukin-6 Receptor (IL-6R). Therapeutic inhibition of these proteins is highly effective in a high number of inflammatory diseases, and TNFα blocking agents alone were sold for almost $30 billion in 2013. We find that the known expression pattern of the three receptors is not reflected in the current drafts of the human proteome, as the proteomics data fail to detect protein expression in several cell types and tissues which are known to express these cytokine receptors. Thus, our results suggest that the current drafts of the human proteome are far from complete, and that the data have to be used with caution especially in terms of personalized medicine.

摘要

尽管大量人类蛋白质在全身广泛表达,但一些具有高度药物相关性的蛋白质呈现出组织或细胞类型特异性的表达模式。从发育生物学到个性化医学,所有学科的研究都将受益于有关这个所谓人类蛋白质组的详细知识。《自然》杂志最近发表的两篇论文利用大规模蛋白质组学技术绘制了人类蛋白质组的初稿,这些初稿可在网上免费获取。在这篇通讯文章中,我们分析了蛋白质组学数据中三种不同细胞因子受体的表达情况,即肿瘤坏死因子(TNF)α受体I(TNFRSF1A)、II(TNFRSF1B)和白细胞介素-6受体(IL-6R)。对这些蛋白质的治疗性抑制在许多炎症性疾病中具有高效性,仅TNFα阻断剂在2013年的销售额就接近300亿美元。我们发现,这三种受体的已知表达模式并未在当前的人类蛋白质组初稿中得到体现,因为蛋白质组学数据未能检测到已知表达这些细胞因子受体的几种细胞类型和组织中的蛋白质表达。因此,我们的结果表明,当前的人类蛋白质组初稿远未完整,尤其在个性化医学方面,这些数据的使用必须谨慎。

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