Specialized RNA analysis center for integrative genomic analyses

用于综合基因组分析的专业 RNA 分析中心

基本信息

批准号：
10458037
负责人：
KATHERINE A. HOADLEY
金额：
$ 35.52万
依托单位：
UNIV OF NORTH CAROLINA CHAPEL HILL
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-01 至 2026-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10458037
关键词：
Address Adopted American Association of Cancer Research Area Artificial Intelligence Automobile Driving Award Awareness B-Lymphocytes Back Biological Assay Biological Markers Blood capillaries Candidate Disease Gene Cells Center for Translational Science Activities Characteristics Classification Clinical Clinical Trials Clinical Trials Cooperative Group Color Communities Companions Competence Complex Contracts DNA DNA sequencing Data Data Analyses Data Commons Disease Emerging Technologies Epigenetic Process Event Evolution Explosion Eye Gene Expression Profile Gene Fusion Generations Genetic Fingerprintings Genetic Transcription Genome Genome Data Analysis Center Genome Data Analysis Network Genomic approach Genomics Genotype Goals Head and Neck Cancer Heterogeneity Immunogenomics Individual Knowledge Laboratories Leadership Malignant Neoplasms Manuscripts Methods MicroRNAs Modeling Molecular Morphology Mutation Oligonucleotide Microarrays Outcome Paraffin Pathogenesis Patient Care Patients Phenotype Plant Roots Play Production Productivity Proteins Proteomics Quality Control RNA RNA Splicing RNA analysis Recording of previous events Recurrence Reporting Research Research Personnel Rewards Role Sampling Science Slide Supervision T-Cell Receptor T-Lymphocyte Techniques Technology The Cancer Genome Atlas Tissues Translational Research U-Series Cooperative Agreements Variant Viral Work analytical tool bench to bedside cancer classification career data integration data sharing experience genetic signature genomic data genomic platform hazard improved innovation mRNA Expression malignant breast neoplasm molecular subtypes nano-string neural network next generation next generation sequencing novel petabyte precision medicine programs response skills technique development tool transcriptome sequencing transcriptomics translational study treatment response tumor tumorigenesis variant detection viral RNA viral detection

项目摘要

ABSTRACT Projects like The Cancer Genome Atlas (TCGA) have generated a tremendous amount of data characterizing the genomic events in cancer and highlighting the deep complexity and significant heterogeneity that can make precision medicine challenging. Molecular subtyping has helped to identify groups of samples with shared genomic characteristics that can be used for clinical decisions. RNA expression has played a strong role in molecular subtyping over the last twenty years. Integration of RNA expression data with other data types that are being generated as part of the Genome Data Analysis Network have improved our knowledge of tumorigenesis and separating driving events from passenger events. Our team has over a 20 year history of innovation in expression technologies, innovating across generations of assays and projects. We propose to apply our knowledge, experience, and methods to address the projects that will be addressed in this cooperative agreement including clinical trial samples from ALCHEMIST or the Clinical Trials Sequencing Program. We propose to address four specific areas of research including `expression/mRNA analysis', `Spatial genomics data analysis', `data integration', and “clinical outcomes.” We will provide 1) analysis of RNA sequencing and expression data, 2) normalization and analysis methods of spatial transcriptomics data, 3) integrative genomic approaches for cancer classification and characterization, and 4) analysis of biomarkers for association with clinical and other molecular features. We will provide our data to other GDACs and work collaboratively with them to integrate our analyses and generate data for sharing with the larger scientific community through the Genome Data Commons.

抽象的癌症基因组图谱 (TCGA) 等项目已经生成了大量的数据特征癌症中的基因组事件，并强调了深刻的复杂性和显着的异质性，可以使精准医学具有挑战性。可用于临床决策的基因组特征发挥了重要作用。过去二十年的分子亚型分析将 RNA 表达数据与其他数据类型相整合。作为基因组数据分析网络的一部分而生成，提高了我们的知识我们的团队在肿瘤发生以及将驾驶事件与乘客事件分开方面拥有 20 多年的历史。我们建议表达技术的创新，跨代的检测和项目的创新。应用我们的知识、经验和方法来解决本报告中将要解决的项目合作协议，包括来自 ALCHEMIST 或临床试验测序的临床试验样本我们建议解决四个具体的研究领域，包括“表达/mRNA 分析”、 “空间基因组数据分析”、“数据整合”和“临床结果”。我们将提供 1) RNA 分析。测序和表达数据，2) 空间转录组数据的归一化和分析方法，3) 用于癌症分类和表征的综合基因组方法，以及 4) 生物标志物分析我们将向其他 GDAC 和工作提供我们的数据。与他们合作整合我们的分析并生成数据以与更大的科学界共享通过基因组数据共享社区。