Suppr超能文献

用于生物标志物鉴定的无标记液相色谱-质谱联用方法。

Label-free LC-MS method for the identification of biomarkers.

作者信息

Higgs Richard E, Knierman Michael D, Gelfanova Valentina, Butler Jon P, Hale John E

机构信息

Lilly Corporate Center, Indianapolis, IN, USA.

出版信息

Methods Mol Biol. 2008;428:209-30. doi: 10.1007/978-1-59745-117-8_12.

Abstract

Pharmaceutical companies and regulatory agencies are pursuing biomarkers as a means to increase the productivity of drug development. Quantifying differential levels of proteins from complex biological samples like plasma or cerebrospinal fluid is one specific approach being used to identify markers of drug action, efficacy, toxicity, etc. Academic investigators are also interested in markers that are diagnostic or prognostic of disease states. We report a comprehensive, fully automated, and label-free approach to relative protein quantification including: sample preparation, proteolytic protein digestion, LCMS/MS data acquisition, de-noising, mass and charge state estimation, chromatographic alignment, and peptide quantification via integration of extracted ion chromatograms. Additionally, we describe methods for transformation and normalization of the quantitative peptide levels in multiplexed measurements to improve precision for statistical analysis. Lastly, we outline how the described methods can be used to design and power biomarker discovery studies.

摘要

制药公司和监管机构正在寻求生物标志物,以此作为提高药物研发效率的一种手段。对血浆或脑脊液等复杂生物样本中的蛋白质差异水平进行定量,是用于识别药物作用、疗效、毒性等标志物的一种具体方法。学术研究人员也对疾病状态的诊断或预后标志物感兴趣。我们报告了一种全面、全自动且无需标记的相对蛋白质定量方法,包括:样品制备、蛋白水解消化、液相色谱-质谱/质谱数据采集、去噪、质量和电荷状态估计、色谱对齐以及通过提取离子色谱图积分进行肽段定量。此外,我们描述了在多重测量中对定量肽段水平进行转换和归一化的方法,以提高统计分析的精度。最后,我们概述了所描述的方法如何用于设计和推动生物标志物发现研究。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验