Edwards Nathan J, Oberti Mauricio, Thangudu Ratna R, Cai Shuang, McGarvey Peter B, Jacob Shine, Madhavan Subha, Ketchum Karen A
‡ESAC, Inc., Rockville, Maryland 20850, United States.
J Proteome Res. 2015 Jun 5;14(6):2707-13. doi: 10.1021/pr501254j. Epub 2015 May 4.
The Clinical Proteomic Tumor Analysis Consortium (CPTAC), under the auspices of the National Cancer Institute's Office of Cancer Clinical Proteomics Research, is a comprehensive and coordinated effort to accelerate the understanding of the molecular basis of cancer through the application of proteomic technologies and workflows to clinical tumor samples with characterized genomic and transcript profiles. The consortium analyzes cancer biospecimens using mass spectrometry, identifying and quantifying the constituent proteins and characterizing each tumor sample's proteome. Mass spectrometry enables highly specific identification of proteins and their isoforms, accurate relative quantitation of protein abundance in contrasting biospecimens, and localization of post-translational protein modifications, such as phosphorylation, on a protein's sequence. The combination of proteomics, transcriptomics, and genomics data from the same clinical tumor samples provides an unprecedented opportunity for tumor proteogenomics. The CPTAC Data Portal is the centralized data repository for the dissemination of proteomic data collected by Proteome Characterization Centers (PCCs) in the consortium. The portal currently hosts 6.3 TB of data and includes proteomic investigations of breast, colorectal, and ovarian tumor tissues from The Cancer Genome Atlas (TCGA). The data collected by the consortium is made freely available to the public through the data portal.
临床蛋白质组肿瘤分析联盟(CPTAC)在美国国立癌症研究所癌症临床蛋白质组学研究办公室的支持下,通过将蛋白质组学技术和工作流程应用于具有特征性基因组和转录组图谱的临床肿瘤样本,为加速理解癌症的分子基础开展了一项全面且协调的工作。该联盟使用质谱分析法分析癌症生物样本,识别并定量其中的组成蛋白质,以及描绘每个肿瘤样本的蛋白质组特征。质谱分析法能够高度特异性地识别蛋白质及其异构体,精确地相对定量对比生物样本中蛋白质的丰度,并在蛋白质序列上定位翻译后蛋白质修饰,如磷酸化。来自同一临床肿瘤样本的蛋白质组学、转录组学和基因组学数据的结合为肿瘤蛋白质基因组学提供了前所未有的机遇。CPTAC数据门户是联盟中蛋白质组特征分析中心(PCC)所收集的蛋白质组学数据的集中存储库。该门户目前拥有6.3 TB的数据,包括来自癌症基因组图谱(TCGA)的乳腺癌、结直肠癌和卵巢癌肿瘤组织的蛋白质组学研究。联盟收集的数据通过数据门户向公众免费提供。