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本文引用的文献

1
Proteomics cataloging analysis of human expressed prostatic secretions reveals rich source of biomarker candidates.对人类前列腺分泌液进行蛋白质组编目分析,发现了丰富的生物标志物候选来源。
Proteomics Clin Appl. 2008 Apr 1;2(4):543-555. doi: 10.1002/prca.200780159.
2
Rethinking screening for breast cancer and prostate cancer.重新思考乳腺癌和前列腺癌的筛查
JAMA. 2009 Oct 21;302(15):1685-92. doi: 10.1001/jama.2009.1498.
3
Peptide separations by on-line MudPIT compared to isoelectric focusing in an off-gel format: application to a membrane-enriched fraction from C2C12 mouse skeletal muscle cells.在线 MudPIT 与凝胶外等电聚焦分离肽段:在 C2C12 鼠骨骼肌细胞膜富集部分中的应用。
J Proteome Res. 2009 Oct;8(10):4860-9. doi: 10.1021/pr900318k.
4
Comparative systems biology of human and mouse as a tool to guide the modeling of human placental pathology.人类与小鼠的比较系统生物学作为指导人类胎盘病理学建模的工具
Mol Syst Biol. 2009;5:279. doi: 10.1038/msb.2009.37. Epub 2009 Jun 16.
5
Rational approach to implementation of prostate cancer antigen 3 into clinical care.将前列腺癌抗原3应用于临床护理的合理方法。
Cancer. 2009 Sep 1;115(17):3879-86. doi: 10.1002/cncr.24447.
6
Clinical collection and protein properties of expressed prostatic secretions as a source for biomarkers of prostatic disease.作为前列腺疾病生物标志物来源的前列腺分泌液的临床采集及蛋白质特性
J Proteomics. 2009 Aug 20;72(6):907-17. doi: 10.1016/j.jprot.2009.01.007. Epub 2009 Jan 20.
7
The use of PCA3 in the diagnosis of prostate cancer.PCA3 在前列腺癌诊断中的应用。
Nat Rev Urol. 2009 May;6(5):255-61. doi: 10.1038/nrurol.2009.40.
8
Serum proteomics using mass spectrometry.使用质谱法的血清蛋白质组学
Methods Mol Biol. 2009;520:107-28. doi: 10.1007/978-1-60327-811-9_8.
9
Automated 2D peptide separation on a 1D nano-LC-MS system.在一维纳升级液相色谱 - 质谱系统上进行二维肽段自动分离。
J Proteome Res. 2009 Mar;8(3):1610-6. doi: 10.1021/pr800986c.
10
2D-DIGE as a strategy to identify serum markers for the progression of prostate cancer.二维差异凝胶电泳作为一种识别前列腺癌进展血清标志物的策略。
J Proteome Res. 2009 Feb;8(2):942-57. doi: 10.1021/pr800570s.

直接表达的前列腺分泌物的深入蛋白质组学分析。

In-depth proteomic analyses of direct expressed prostatic secretions.

机构信息

Department of Microbiology and Molecular Cell Biology, Eastern Virginia Medical School, Norfolk, Virginia 23517, USA.

出版信息

J Proteome Res. 2010 May 7;9(5):2109-16. doi: 10.1021/pr1001498.

DOI:10.1021/pr1001498
PMID:20334419
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2869496/
Abstract

It is expected that clinically obtainable fluids that are proximal to organs contain a repertoire of secreted proteins and shed cells reflective of the physiological state of that tissue and thus represent potential sources for biomarker discovery, investigation of tissue-specific biology, and assay development. The prostate gland secretes many proteins into a prostatic fluid that combines with seminal vesicle fluids to promote sperm activation and function. Proximal fluids of the prostate that can be collected clinically are seminal plasma and expressed prostatic secretion (EPS) fluids. In the current study, MudPIT-based proteomics was applied to EPS obtained from nine men with prostate cancer and resulted in the confident identification of 916 unique proteins. Systematic bioinformatics analyses using publicly available microarray data of 21 human tissues (Human Gene Atlas), the Human Protein Atlas database, and other published proteomics data of shed/secreted proteins were performed to systematically analyze this comprehensive proteome. Therefore, we believe this data will be a valuable resource for the research community to study prostate biology and potentially assist in the identification of novel prostate cancer biomarkers. To further streamline this process, the entire data set was deposited to the Tranche repository for use by other researchers.

摘要

预计接近器官的临床可得液体含有一系列分泌蛋白和脱落细胞,反映了该组织的生理状态,因此代表了生物标志物发现、组织特异性生物学研究和检测方法开发的潜在来源。前列腺将许多蛋白质分泌到前列腺液中,这些液体会与精囊液结合,促进精子的激活和功能。可以从临床上收集的前列腺近端液体是精液和前列腺特异性分泌液(EPS)。在本研究中,基于 MudPIT 的蛋白质组学方法应用于从 9 名前列腺癌患者中获得的 EPS,结果鉴定出 916 种独特的蛋白质。使用 21 个人类组织(人类基因图谱)的公开微阵列数据、人类蛋白质图谱数据库和其他已发表的脱落/分泌蛋白的蛋白质组学数据进行系统的生物信息学分析,对这个全面的蛋白质组进行了系统分析。因此,我们相信这些数据将成为研究前列腺生物学的宝贵资源,并有可能有助于鉴定新型前列腺癌生物标志物。为了进一步简化这个过程,整个数据集被存入 Tranche 存储库,供其他研究人员使用。