Integrated analysis of protein expression data from the Reverse Phase Protein Array (RPPA) platform

对反相蛋白阵列 (RPPA) 平台的蛋白表达数据进行集成分析

• 批准号: 9789028
• 负责人: Rehan Akbani
• 金额: $ 40.09万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-13 至 2021-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9789028
• 关键词: Algorithms; Award; Back; Biological; Cancer Center; Cancer Patient; Clinical; Communities; Competence; Computer software; Computing Methodologies; Contracts; DNA Methylation; Data; Data Analyses; Data Set; Data Sources; Deposition; Evolution; Excision; Feedback; Future; Galaxy; Genome; Genome Data Analysis Center; Goals; Infrastructure; Intervention; Investigation; Light; Malignant Neoplasms; Maps; Measures; Messenger RNA; Methodology; MicroRNAs; Molecular; Mutation; National Cancer Institute; Outcome; Pathway Analysis; Pathway interactions; Pattern; Performance; Phase; Phosphorylation; Process; Protein Analysis; Protein Array; Proteins; Proteomics; Quality Control; Research; Research Personnel; Running; Sampling; Software Tools; Specific qualifier value; Testing; Work; analysis pipeline; base; bioinformatics tool; biological systems; cancer genomics; cancer initiation; cancer therapy; clinically relevant; computerized tools; data warehouse; design; expectation; file format; improved; innovation; knowledge base; next generation; novel; novel therapeutic intervention; programs; protein expression; repository; secondary analysis; targeted treatment; therapy resistant; tool; tumor; working group

Project Summary/Abstract The National Cancer Institute has initiated, or will initiate, a number of large-scale cancer genomics programs under the aegis of the Center for Cancer Genomics (CCG). The overall goal of those programs is to help elucidate the mechanisms of cancer initiation, evolution, and resistance to therapy through detailed molecular characterization of tumor samples across multiple technological platforms. As most therapy targets are proteins, and protein phosphorylation is functionally important, accurate analysis of protein is critical to the effort. Consequently, MD Anderson was awarded the Genome Characterization Center contract to develop and apply a high-throughput reverse-phase protein array (RPPA) pipeline (Contact PD/PI Gordon Mills; PD/PI Rehan Akbani). The present proposal is for the establishment of a Specialized Genome Data Analysis Center (GDAC) at MD Anderson under the same auspices. As its first objective, the GDAC will directly support CCG projects by analyzing RPPA data for the Analysis Working Groups (AWGs). The GDAC will participate in discussions, solicit feedback from the AWGs, and suggest future directions for research. A second objective of the GDAC will be to enhance its current bioinformatic tools to improve the analysis and interpretation of RPPA data, whether developed under the aegis of the CCG or through other community approaches. Specifically, the aims of the GDAC are to (i) Extract high-quality, analysis-ready protein expression measures from the RPPA data; (ii) Cluster RPPA data and conduct integrated analysis by correlating RPPA data with clinical and other molecular data; (iii) Perform knowledge-based and independent pathway analysis of RPPA data to identify proteomic pathways that have been substantially altered in the set of cases in each CCG project; and (iv) Continue to develop innovative bioinformatic and computational tools and methodologies to improve the RPPA data analysis pipeline. The pipeline will be shared publicly for the benefit of other researchers. The GDAC will perform the stated tasks by continuing to develop a fully or semi-automated software pipeline using the Galaxy software infrastructure and their own software modules. A preliminary version of the pipeline, together with the necessary expertise for systems biological interpretation of the results, is already in place and will be available at the beginning of the performance period. Further enhancements of the pipeline will be implemented as the GDAC progresses. The pipeline will input raw or pre-processed RPPA data from a central data repository that is specified by the CCG; perform quality control; remove any batch effects; analyze the data using novel plus traditional algorithms; correlate the data with other molecular/clinical features; visualize the outcome; and then deposit the results back in the repository for use by the AWG. The GDAC will interact and collaborate with other components of the CCG consortium to discover biologically and clinically relevant findings that will shed light on the underlying mechanisms of cancer and offer potential avenues for novel therapeutic approaches.

项目概要/摘要 美国国家癌症研究所已经启动或将启动多个大规模癌症基因组学项目 在癌症基因组学中心 (CCG) 的支持下。这些计划的总体目标是帮助 通过详细的分子生物学阐明癌症发生、演变和治疗耐药的机制 跨多个技术平台对肿瘤样本进行表征。由于大多数治疗目标是 蛋白质，蛋白质磷酸化在功能上很重要，准确分析蛋白质对于 努力。因此，MD 安德森获得了基因组表征中心合同来开发和 应用高通量反相蛋白阵列 (RPPA) 管道（联系 PD/PI Gordon Mills；PD/PI 雷汉·阿克巴尼）。目前的建议是建立一个专门的基因组数据分析中心 (GDAC) 在 MD 安德森的同一赞助下。作为其首要目标，GDAC 将直接支持 CCG 通过为分析工作组 (AWG) 分析 RPPA 数据来开展项目。 GDAC 将参与 讨论，征求 AWG 的反馈，并提出未来的研究方向。第二个目标 GDAC 将增强其当前的生物信息工具，以改进 RPPA 的分析和解释 数据，无论是在 CCG 的支持下还是通过其他社区方法开发。 具体来说，GDAC 的目标是 (i) 提取高质量、可供分析的蛋白质表达 根据 RPPA 数据进行测量； (ii) 对RPPA数据进行聚类，并通过关联RPPA进行综合分析 临床数据和其他分子数据； (iii) 进行基于知识的独立途径分析 RPPA 数据来识别在每个病例组中发生显着改变的蛋白质组通路 CCG项目； (iv) 继续开发创新的生物信息和计算工具和方法 改进 RPPA 数据分析流程。该管道将​​公开共享，以造福其他人 研究人员。 GDAC 将通过继续开发全自动或半自动化的系统来执行规定的任务 使用 Galaxy 软件基础设施和自己的软件模块的软件管道。初步 管道的版本，以及对结果进行系统生物学解释所需的专业知识， 已经就位，并将在执行期开始时可用。进一步增强 该管道将​​随着 GDAC 的进展而实施。管道将输入原始或预处理的 RPPA 来自 CCG 指定的中央数据存储库的数据；执行质量控制；删除任何批次 影响；使用新颖和传统算法分析数据；将数据与其他分子/临床相关联 特征;可视化结果；然后将结果存回存储库以供 AWG 使用。这 GDAC 将与 CCG 联盟的其他组成部分进行互动和合作，以发现生物学和 临床相关的发现将揭示癌症的潜在机制并提供潜在的 新的治疗方法的途径。