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.

项目总结/文摘