Li Jun, Akbani Rehan, Zhao Wei, Lu Yiling, Weinstein John N, Mills Gordon B, Liang Han
Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Cancer Res. 2017 Nov 1;77(21):e51-e54. doi: 10.1158/0008-5472.CAN-17-0369.
Reverse-phase protein arrays (RPPA) represent a powerful functional proteomic approach to elucidate cancer-related molecular mechanisms and to develop novel cancer therapies. To facilitate community-based investigation of the large-scale protein expression data generated by this platform, we have developed a user-friendly, open-access bioinformatic resource, The Cancer Proteome Atlas (TCPA, http://tcpaportal.org), which contains two separate web applications. The first one focuses on RPPA data of patient tumors, which contains >8,000 samples of 32 cancer types from The Cancer Genome Atlas and other independent patient cohorts. The second application focuses on the RPPA data of cancer cell lines and contains >650 independent cell lines across 19 lineages. Many of these cell lines have publicly available, high-quality DNA, RNA, and drug screening data. TCPA provides various analytic and visualization modules to help cancer researchers explore these datasets and generate testable hypotheses in an effective and intuitive manner. .
反相蛋白质阵列（RPPA）是一种强大的功能蛋白质组学方法，用于阐明癌症相关分子机制并开发新型癌症疗法。为了促进基于社区对该平台产生的大规模蛋白质表达数据的研究，我们开发了一个用户友好、开放获取的生物信息资源——癌症蛋白质组图谱（TCPA，http://tcpaportal.org），它包含两个独立的网络应用程序。第一个专注于患者肿瘤的RPPA数据，其中包含来自癌症基因组图谱和其他独立患者队列的32种癌症类型的8000多个样本。第二个应用程序专注于癌细胞系的RPPA数据，包含19个谱系的650多个独立细胞系。这些细胞系中的许多都有公开可用的高质量DNA、RNA和药物筛选数据。TCPA提供各种分析和可视化模块，以帮助癌症研究人员有效且直观地探索这些数据集并生成可检验的假设。
