MEMBRANE PROTEOMICS OF BREAST CANCER CELL LINES

该子项目是利用NIH/NCRR资助的中心赠款提供的资源的许多研究子项目之一。子项目和研究者（PI）可能从另一个NIH来源获得了主要资金，因此可以在其他CRISP条目中表示。所列机构为中心，不一定是研究者所在机构。本研究的目的是研究乳腺癌细胞系蛋白质组，采用新的策略，结合基因组和功能数据库的可用性，进行差异蛋白质分析。我们将高通量蛋白质组（MS/MS）数据与1）转录表达和2）蛋白质-蛋白质相互作用数据相结合，以鉴定正常细胞系和癌细胞系之间差异调节的蛋白质网络。该MS/MS数据还用于开发准确的质量和时间（AMT）标签的集合，这使得能够在这些相同的细胞中定量比较同位素标记的蛋白质。 使用高通量LC-MS/MS技术和迭代搜索的8种形式的翻译后修饰（PTM），我们确定了一个功能多样的收集未修饰和修饰的蛋白质。从724，566个MS/MS谱中鉴定了2299个未修饰的蛋白质，包括与非癌细胞相比在癌细胞系中优先修饰的9个蛋白质。通过将该数据集映射到公开可用的蛋白质-蛋白质相互作用和mRNA丰度测量，我们分离出了几个功能相关蛋白质的网络，这些蛋白质似乎优先与癌症表型分离。我们确定了八个修饰蛋白和一个蛋白网络，其在癌症中的意义值得进一步研究和验证乳腺癌。 使用LC-FTICR的高质量准确度和先前从先前LC-MS/MS运行中鉴定的肽的集合，产生正常和癌性人上皮细胞中超过5000种多肽的AMT标签的集合。一种非癌细胞系（HMEC）和四种癌细胞系分别用18 O同位素标记，并与用16 O标记的蛋白质的参考混合物进行比较。在所有五种细胞系中检测到超过500种蛋白质的标记肽对。蛋白质丰度测量相关性差的基因表达数据获得这些相同的细胞系。在这些癌细胞系中鉴定了超过30种蛋白质，与非癌细胞系相比，其表达差异超过3倍。聚类分析也揭示了两个功能相关的蛋白质组具有相似的表达谱。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The purpose of this study is to investigate breast cancer cell-line proteomes using novel strategies for differential protein analyses coupled with the availability of genome and functional databases. We combined high-throughput proteome (MS/MS) data with 1) transcript expression and 2) protein-protein interaction data to identify networks of proteins differentially regulated in between normal and cancer cell lines. This MS/MS data was also used to develop a collection of accurate mass and time (AMT) tags, which enabled the quantitative comparison of isotopically labeled proteins among these same cells. Using high-throughput LC-MS/MS techniques and iterative searches for eight forms of post-translational modifications (PTMs) we identified a functionally diverse collection of unmodified and modified proteins. 2299 unmodified proteins were identified from 724,566 MS/MS spectra including nine proteins that were preferentially modified in cancer cell lines compared to non-cancerous cells. By mapping this dataset to publicly available protein-protein interaction and mRNA abundance measurements, we isolated several networks of functionally related proteins that appear to preferentially segregate with the cancer phenotype. We pinpointed eight modified proteins and one protein network whose significance in cancer warrants further investigation and validation in breast cancer. A collection of AMT tags for more than 5000 polypeptides in normal and cancerous human epithelial cells was generated using the high mass accuracy of LC-FTICR and the collection of peptides previously identified from prior LC-MS/MS runs. One non-cancer cell line (HMEC) and four cancer cell lines were individually labeled with 18O isotope and compared to a reference mixture of proteins labeled with 16O. Labeled peptide pairs were detected for more than 500 proteins among all five cell lines. Protein abundance measurements correlated poorly the gene expression data obtained for these same cell lines. More than 30 protein were identified in these cancer cell lines that had more than 3-fold difference in expression compared to the non-cancer cell line. Clustering analysis also revealed two functionally related protein groups with similar expression profiles.