A comprehensive peptidome profiling technology for the identification of early detection biomarkers for lung adenocarcinoma.
A comprehensive peptidome profiling technology for the identification of early detection biomarkers for lung adenocarcinoma.
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DOI：
10.1371/journal.pone.0018567
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发表时间：
2011-04-12
期刊：
影响因子：
3.7
通讯作者：
Nakagawa H
中科院分区：
文献类型：
--
作者：
Ueda K;Saichi N;Takami S;Kang D;Toyama A;Daigo Y;Ishikawa N;Kohno N;Tamura K;Shuin T;Nakayama M;Sato TA;Nakamura Y;Nakagawa H
基于质谱的肽组学方法已经证明其在几个领域中的有用性，例如发现来自各种生物流体（包括血液和脑脊液）的生理活性肽或生物标志物候选物。然而，为了鉴定可再现且临床适用的生物标志物，人们迫切期待开发能够使用数百个临床样本进行快速、灵敏和定量分析的新技术。在这里，我们报告了一个整合肽组的方法，用于识别肺癌特异性血清肽生物标志物。它基于使用尺寸排阻色谱法对肽组级分（分子量为1，000 - 5，000）进行一步有效富集，并结合使用Expressionist Proteome Server平台对nano-LC/MS/MS数据集进行精确的无标记定量分析。我们将该方法应用于92个用我们的SOP（标准操作程序）良好管理的血清样本（30个健康对照和62个肺腺癌患者），并定量评估了检测到的3，537个肽信号。其中，118种肽在对照组和肺癌组之间显示出显著改变的血清水平（p <0.01 and fold change >5.0）。随后，我们通过MS/MS分析鉴定了肽序列，并通过96份独立制备的血清样本的基于MRM的相对定量分析进一步评估了基于Expressionist的定量结果的再现性及其诊断能力，发现APOA 4 273-283、FIBA 5-16和LBN 306-313应该是临床上有用的肺癌早期检测和肿瘤分期的生物标志物。我们的肽组分析技术可以提供大量临床样本的简单，高通量和可靠的定量，适用于使用任何类型的生物样本的多种肽组靶向生物标志物的发现。
The mass spectrometry-based peptidomics approaches have proven its usefulness in several areas such as the discovery of physiologically active peptides or biomarker candidates derived from various biological fluids including blood and cerebrospinal fluid. However, to identify biomarkers that are reproducible and clinically applicable, development of a novel technology, which enables rapid, sensitive, and quantitative analysis using hundreds of clinical specimens, has been eagerly awaited. Here we report an integrative peptidomic approach for identification of lung cancer-specific serum peptide biomarkers. It is based on the one-step effective enrichment of peptidome fractions (molecular weight of 1,000–5,000) with size exclusion chromatography in combination with the precise label-free quantification analysis of nano-LC/MS/MS data set using Expressionist proteome server platform. We applied this method to 92 serum samples well-managed with our SOP (standard operating procedure) (30 healthy controls and 62 lung adenocarcinoma patients), and quantitatively assessed the detected 3,537 peptide signals. Among them, 118 peptides showed significantly altered serum levels between the control and lung cancer groups (p<0.01 and fold change >5.0). Subsequently we identified peptide sequences by MS/MS analysis and further assessed the reproducibility of Expressionist-based quantification results and their diagnostic powers by MRM-based relative-quantification analysis for 96 independently prepared serum samples and found that APOA4 273–283, FIBA 5–16, and LBN 306–313 should be clinically useful biomarkers for both early detection and tumor staging of lung cancer. Our peptidome profiling technology can provide simple, high-throughput, and reliable quantification of a large number of clinical samples, which is applicable for diverse peptidome-targeting biomarker discoveries using any types of biological specimens.
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影响因子：
3.7
作者：
Ostroff RM;Bigbee WL;Franklin W;Gold L;Mehan M;Miller YE;Pass HI;Rom WN;Siegfried JM;Stewart A;Walker JJ;Weissfeld JL;Williams S;Zichi D;Brody EN
通讯作者：
Brody EN
临床生物标志物发现的靶向蛋白质组学策略。
影响因子：
6.6
作者：
Schiess R;Wollscheid B;Aebersold R
通讯作者：
Aebersold R
影响因子：
3.8
作者：
Albrethsen J;Bøgebo R;Gammeltoft S;Olsen J;Winther B;Raskov H
通讯作者：
Raskov H
影响因子：
3.8
作者：
Galdzicka, M;Patnala, S;Ginns, EI
通讯作者：
Ginns, EI
影响因子：
4.4
作者：
Ebert, Matthias P. A.;Niemeyer, Dagmar;Rocken, Christoph
通讯作者：
Rocken, Christoph