Antibody-coupled monolithic silica microtips for highthroughput molecular profiling of circulating exosomes.
Antibody-coupled monolithic silica microtips for highthroughput molecular profiling of circulating exosomes.
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DOI：
10.1038/srep06232
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发表时间：
2014-08-29
影响因子：
4.6
通讯作者：
Nakagawa H
中科院分区：
文献类型：
--
作者：
Ueda K;Ishikawa N;Tatsuguchi A;Saichi N;Fujii R;Nakagawa H
Exosome介导的信号转导在肿瘤的进展和转移中起着多种关键作用。从癌症诊断的角度来看，循环外切体是理想的生物标记物来源，因为肿瘤细胞的分子特征在其上转录。然而，从体液中分离纯外切体是耗时的，而且对于全面分析外切体蛋白和miRNAs仍然是需要解决的主要挑战。在这里，我们构建了抗CD9抗体偶联的高孔整体式硅胶微尖，可以自动、快速和可重复地从多个临床样本中提取外显子。我们应用这些技巧通过分析46个血清样本来探索外显体上的肺癌生物标记蛋白。对1,369个外切体蛋白进行了质谱分析，确定CD91为肺腺癌外切体上的特异性抗原，并用CD9-CD91外切体夹心ELISA法对212个样本进行了验证。我们的简单装置不仅可以促进生物标记物的发现研究，而且可以促进关于外切体的广泛的组学研究。
Exosome-mediated signal transportation plays a variety of critical roles in cancer progression and metastasis. From the aspect of cancer diagnosis, circulating exosomes are ideal resources of biomarkers because molecular features of tumor cells are transcribed on them. However, isolating pure exosomes from body fluids is time-consuming and still major challenge to be addressed for comprehensive profiling of exosomal proteins and miRNAs. Here we constructed anti-CD9 antibody-coupled highly porous monolithic silica microtips which allowed automated rapid and reproducible exosome extraction from multiple clinical samples. We applied these tips to explore lung cancer biomarker proteins on exosomes by analyzing 46 serum samples. The mass spectrometric quantification of 1,369 exosomal proteins identified CD91 as a lung adenocarcinoma specific antigen on exosomes, which was further validated with CD9-CD91 exosome sandwich ELISA measuring 212 samples. Our simple device can promote not only biomarker discovery studies but also wide range of omics researches about exosomes.
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DOI：
10.1007/978-1-61779-068-3_15
发表时间：
2011-01-01
期刊：
SERUM/PLASMA PROTEOMICS: METHODS AND PROTOCOLS
影响因子：
--
作者：
Taylor, Douglas D.;Zacharias, Wolfgang;Gercel-Taylor, Cicek
通讯作者：
Gercel-Taylor, Cicek
影响因子：
4.8
作者：
Vassiliou, G;Benoist, F;McPherson, R
通讯作者：
McPherson, R
影响因子：
64.5
作者：
Luga, Valbona;Zhang, Liang;Wrana, Jeffrey L.
通讯作者：
Wrana, Jeffrey L.
影响因子：
5.3
作者：
Wang, Wei;Nishioka, Yasuhiko;Sone, Saburo
通讯作者：
Sone, Saburo
影响因子：
3.7
作者：
Khan S;Jutzy JM;Valenzuela MM;Turay D;Aspe JR;Ashok A;Mirshahidi S;Mercola D;Lilly MB;Wall NR
通讯作者：
Wall NR