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通过差异肽展示对乳腺癌细胞进行表达谱分析。

Expression profiling of breast cancer cells by differential peptide display.

作者信息

Tammen Harald, Kreipe Hans, Hess Rüdiger, Kellmann Markus, Lehmann Ulrich, Pich Andreas, Lamping Norbert, Schulz-Knappe Peter, Zucht Hans-Dieter, Lilischkis Richard

机构信息

BioVisioN AG, Hannover, Germany.

出版信息

Breast Cancer Res Treat. 2003 May;79(1):83-93. doi: 10.1023/a:1023309621042.

DOI:10.1023/a:1023309621042
PMID:12779085
Abstract

Expression profiling of RNAs or proteins has become a promising means to investigate the heterogeneity of histopathologically defined classes of cancer. Peptides, representing degradation as well as processing products of proteins offer an even closer insight into cell physiology. Peptides are related to the turnover of cellular proteins and are capable to reflect disease-related changes in homoeostasis of the human body. Furthermore, peptides derived from tumor cells are potentially useful markers in the early detection of cancer. In this study, we introduced a method called differential peptide display (DPD) for separating, detecting, and identifying native peptides derived from whole cell extracts. This method is a highly standardized procedure, combining the power of reversed-phase chromatography with mass spectrometry. This technology is suitable to analyze cell lines, various tissue types and human body fluids. Peptide-based profiling of normal human mammary epithelial cells (HMEC) and the breast cancer cell line MCF-7 revealed complex peptide patterns comprising of up to 2300 peptides. Most of these peptides were common to both cell lines whereas about 8% differed in their abundance. Several of the differentially expressed peptides were identified as fragments of known proteins such as intermediate filament proteins, thymosins or Cathepsin D. Comparing cell lines with native tumors, overlapping peptide patterns were found between HMEC and a phylloides tumor (CP) on the one hand and MCF-7 cells and tissue from a invasive ductal carcinoma (DC) on the other hand.

摘要

RNA或蛋白质的表达谱分析已成为研究组织病理学定义的癌症类别的异质性的一种有前景的手段。肽作为蛋白质的降解产物和加工产物,能更深入地洞察细胞生理学。肽与细胞蛋白质的周转有关,能够反映人体稳态中与疾病相关的变化。此外,源自肿瘤细胞的肽在癌症早期检测中可能是有用的标志物。在本研究中,我们引入了一种称为差异肽展示(DPD)的方法,用于分离、检测和鉴定源自全细胞提取物的天然肽。该方法是一种高度标准化的程序,将反相色谱法与质谱法的优势结合在一起。这项技术适用于分析细胞系、各种组织类型和人体体液。对正常人乳腺上皮细胞(HMEC)和乳腺癌细胞系MCF-7进行基于肽的分析,发现了复杂的肽图谱,其中包含多达2300种肽。这些肽中的大多数在两个细胞系中都很常见,而约8%的肽在丰度上有所不同。一些差异表达的肽被鉴定为已知蛋白质的片段,如中间丝蛋白、胸腺素或组织蛋白酶D。将细胞系与天然肿瘤进行比较,一方面在HMEC和叶状肿瘤(CP)之间发现了重叠的肽图谱,另一方面在MCF-7细胞和浸润性导管癌(DC)的组织之间也发现了重叠的肽图谱。

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Breast Cancer Res Treat. 2003 May;79(1):83-93. doi: 10.1023/a:1023309621042.
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