Exploiting public genomic and transcriptomic data to uncover cancer-RNA editing relationships

利用公共基因组和转录组数据揭示癌症-RNA 编辑关系

基本信息

批准号：
10643949
负责人：
Xinshu Grace Xiao
金额：
$ 38.22万
依托单位：
UNIVERSITY OF CALIFORNIA LOS ANGELES
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-07-01 至 2027-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10643949
关键词：
3&apos Untranslated Regions ADAR1 Address Adenosine Affect Amino Acid Sequence Base Sequence Bioinformatics Cancer Control Cancer Patient Cells Code Collection Complement DNA Sequence Alteration DRADA2b protein Data Data Set Double-Stranded RNA Enzymes Epithelium Future Gene Expression Genes Genomics Goals Heterogeneity Human Immune Response Genes Immune response Immunotherapy Inosine Interferon Activation Interferons Label Malignant Neoplasms Mammals Mesenchymal Cell Neoplasm Methodology Methods Modification Molecular Mutation Natural Immunity Nucleotides Organism Outcome Pathway interactions Patients Pattern Phenotype Proteins Proteomics RNA RNA Editing RNA Sequences RNA analysis RNA-Binding Proteins Regulation Reporting Research Role Sampling Site Structure Technology Transcript Untranslated RNA Validation Work cancer cell cancer risk cancer type cell type genetic architecture human disease immunoregulation insertion/deletion mutation insight mRNA Stability neuropsychiatric disorder novel posttranscriptional prevent response secondary analysis success transcriptome transcriptome sequencing transcriptomics treatment response tumor

3&apos Untranslated Regions ADAR1 Address Adenosine Affect Amino Acid Sequence Base Sequence Bioinformatics Cancer Control Cancer Patient Cells Code Collection Complement DNA Sequence Alteration DRADA2b protein Data Data Set Double-Stranded RNA Enzymes Epithelium Future Gene Expression Genes Genomics Goals Heterogeneity Human Immune Response Genes Immune response Immunotherapy Inosine Interferon Activation Interferons Label Malignant Neoplasms Mammals Mesenchymal Cell Neoplasm Methodology Methods Modification Molecular Mutation Natural Immunity Nucleotides Organism Outcome Pathway interactions Patients Pattern Phenotype Proteins Proteomics RNA RNA Editing RNA Sequences RNA analysis RNA-Binding Proteins Regulation Reporting Research Role Sampling Site Structure Technology Transcript Untranslated RNA Validation Work cancer cell cancer risk cancer type cell type genetic architecture human disease immunoregulation insertion/deletion mutation insight mRNA Stability neuropsychiatric disorder novel posttranscriptional prevent response secondary analysis success transcriptome transcriptome sequencing transcriptomics treatment response tumor

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项目摘要

Project Summary This project aims to better understand the regulation and function of RNA editing in cancer through analysis of existing omics data sets. RNA editing is a prevalent type of RNA modification where the RNA sequences are altered through insertion, deletion or substitution of nucleotides. In mammals, the most common type of RNA editing is adenosine to inosine (A-to-I) editing. Catalyzed by the ADAR enzymes, A-to-I editing is the most prevalent type of RNA editing in human, occurring in the majority of human transcripts. In the past few decades, great progress was made to understand the critical function of a small number of A-to-I editing sites in cancer-related genes, most of which alter protein-coding sequences. Owing to the recent advances in RNA-sequencing (RNA-seq) technologies and bioinformatic methodologies, an unprecedented number of A-to-I editing sites have been cataloged for various organisms. Importantly, widespread aberrant RNA editing has been reported in a number of cancer types. In addition, increasing evidence supports that ADAR and RNA editing levels are associated with patient survival or response to therapy. However, many questions remain, the most significant ones including the unclear mechanisms through which ADAR and RNA editing contribute to cancer-related pathways and the unknown regulatory mechanisms underlying aberrant RNA editing in cancer. In this project, we propose to extend our recent successes at developing and applying bioinformatic approaches in RNA editing studies to address the above challenges. We will capitalize on the large collection of RNA-seq data sets derived from different types of cancer samples. We will develop and apply novel methodologies to make full use of these data sets, complemented by further bioinformatic prediction and experimental validations, to predict and validate the molecular function of RNA editing and related regulatory mechanisms. This work will allow a previously unattained level of understanding of the molecular basis of RNA editing and provide new insights to the involvement of RNA editing in human cancer.

项目摘要该项目旨在更好地了解RNA编辑在癌症中的调节和功能通过分析现有的OMIC数据集。 RNA编辑是一种普遍的RNA 修改RNA序列通过插入，缺失或取代而改变核苷酸。在哺乳动物中，最常见的RNA编辑类型是腺苷的腺苷（A-TO-I）编辑。由ADAR酶催化，A-to-I编辑是最普遍的RNA 在人类中进行编辑，发生在大多数人类笔录中。在过去的几十年中，很棒取得了进展，以了解少数A到I编辑站点的关键功能与癌症相关的基因，其中大多数改变了蛋白质编码序列。由于最近 RNA测序（RNA-SEQ）技术和生物信息学方法论的进步各种生物已经对空前的A到I编辑站点进行了分类。重要的是，已经报道了多种癌症类型的广泛异常RNA编辑。此外，越来越多的证据支持ADAR和RNA编辑水平与患者生存或对治疗的反应。但是，仍然存在许多问题，这是最重要的其中包括ADAR和RNA编辑有助于的不明确机制与癌症相关的途径和未知的调节机制异常RNA 癌症编辑。在这个项目中，我们建议扩大我们在开发和开发方面取得的最新成功在RNA编辑研究中应用生物信息学方法来应对上述挑战。我们将利用大量从不同类型的癌症得出的RNA-seq数据集样品。我们将开发并应用新颖的方法来充分利用这些数据集，以进一步的生物信息学预测和实验验证进行补充，以预测和验证RNA编辑和相关调节机制的分子功能。这项工作将允许以前未经鉴定的理解RNA编辑的分子基础并为RNA编辑在人类癌症中的参与提供新的见解。