Characterization and modeling of m6A RNA methylation in cancer

癌症中 m6A RNA 甲基化的表征和建模

• 批准号: 10027689
• 负责人: Han Liang
• 金额: $ 56.55万
• 依托单位: UNIVERSITY OF TX MD ANDERSON CAN CTR
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10027689
• 关键词: Alternative Splicing; Bioinformatics; Biological; Biological Markers; Biology; Biomedical Research; Cancer Biology; Cancer Patient; Cancer cell line; Chicago; Classification; Clinical; Clinical assessments; Colorectal Cancer; Communities; Computational Biology; Computer Analysis; Data; Databases; Development; Disease; Event; Expression Profiling; Genomics; Goals; Human; Investigation; Knowledge; Life Cycle Stages; Malignant Neoplasms; Malignant neoplasm of lung; Malignant neoplasm of urinary bladder; Messenger RNA; Mission; Modeling; Modification; Molecular; Molecular Abnormality; Outcome; Pathogenesis; Patients; Pattern; Phase; Play; Polyadenylation; Process; Protein Array; Proteins; Proteomics; Protocols documentation; Public Health; RNA; RNA Editing; RNA methylation; Reader; Research; Resources; Role; Sampling; Skin Cancer; Standardization; The Cancer Genome Atlas; Therapeutic; Tumor Subtype; United States National Institutes of Health; Universities; University of Texas M D Anderson Cancer Center; anticancer research; base; bioinformatics resource; biomedical resource; cancer biomarkers; cancer genomics; cancer initiation; cancer therapy; cancer type; clinically relevant; cohort; deep learning; disability; effective therapy; genome-wide; innovation; malignant breast neoplasm; methylation pattern; novel; potential biomarker; predictive modeling; prognostic; protein biomarkers; protein expression; therapeutic target; tumor; user-friendly

ABSTRACT The most abundant internal mRNA modification is N6-methyladenosine (m6A), and growing evidence has suggested its critical roles in cancer. However, the global patterns of m6A RNA modification and its regulators over large patient cohorts are not available. It remains unclear how m6A RNA modification contributes to cancer initiation/progression and how it may be used in cancer therapy. The objective is to systematically characterize the genome-wide patterns of m6A RNA modification and its regulators using well-characterized The Cancer Genome Atlas (TCGA) patient cohorts, elucidate their interactions with other molecular aberrations, and assess their potential clinical utility. The working hypothesis is that the dysregulation of m6A RNA methylation plays critical roles in cancer development and may represent potential biomarkers and therapeutic targets. We will pursue three specific aims: Aim #1. Generate the genome-wide profiles of m6A RNA methylation using TCGA sample cohorts. As part of an NCI Functional Proteomic Center, our team has unique access to these samples. We have developed a sensitive, robust m6A-seq protocol, and will apply it to ~1,000 patient samples from diverse cancer types, and generate high-quality, standardized m6A genome-wide profile data. Aim #2. Generate the protein expression profiles of m6A regulators using TCGA sample cohorts. Using the MD Anderson reverse-phase protein array platform, we will characterize the expression levels of ~30 protein markers (including both total and phosphorylated proteins) of 15 m6A regulators (five writers, two readers, and eight erasers) over ~8,000 samples of 31 cancer types as well as ~400 common cancer cell lines. Aim #3. Perform the integrative analysis and modeling of m6A RNA methylation data in a rich TCGA context. Using TCGA multi-dimensional molecular data, we will develop predictive models that quantify the effects of various factors involved in m6A RNA modification by deep learning. We will perform analyses to define m6A-based tumor subtypes, assess the clinical utility of m6A-related markers, and study the interactions of m6A with other molecular aberrations in diverse tumor contexts. Finally, we will build a publicly available, user-friendly database that will contain comprehensive information of the m6A data generated through Aim #1 and Aim #2. The expected outcome of this project is (i) the establishment of an integrated resource of m6A-related genomic and proteomic data based on the most widely used cancer patient cohorts, so that further investigation of such data can be conducted by the cancer research community fluently; and (ii) assessment of the biological and clinical utility of m6A RNA methylation for cancer therapy in a comprehensive way. This project is innovative because it will systematically assess the clinical relevance and functions of a key class of RNA modifications that are currently understudied in cancer research. These results will have an important positive impact because the knowledge gained will not only greatly advance our understanding of the role of m6A RNA methylation in cancer development, but also directly facilitate the development of a novel class of cancer biomarkers and therapeutic targets.

摘要 最丰富的内部mRNA修饰是N6-甲基腺苷(M6A)，越来越多的证据表明 暗示了它在癌症中的关键作用。然而，m6A RNA修饰的全球模式及其调节因子 没有大量的患者队列可用。目前尚不清楚m6A RNA修饰是如何导致癌症的 启动/进展以及如何将其用于癌症治疗。其目标是系统地描述 M6A RNA修饰的全基因组模式及其调控因子在肿瘤中的应用 基因组图谱(TCGA)患者队列，阐明它们与其他分子异常的相互作用，并评估 它们潜在的临床用途。工作假说是m6A rna甲基化的失调 在癌症发展中起关键作用，可能代表潜在的生物标记物和治疗靶点。我们会 追求三个具体目标：目标1.使用以下方法生成m6A RNA甲基化的全基因组图谱 TCGA样本队列。作为NCI功能蛋白质组中心的一部分，我们的团队拥有独特的访问权限 样本。我们已经开发了一种敏感、强大的M6A-SEQ方案，并将应用于约1000名患者样本 从不同的癌症类型，并生成高质量的，标准化的m6A全基因组概况数据。目标2. 使用TCGA样本队列生成m6A调节子的蛋白质表达谱。使用MD Anderson逆相蛋白质阵列平台上，我们将表征~30个蛋白质表达水平的标志物 (包括总蛋白和磷酸化蛋白)15个m6A调节子(5个作者、2个读者和8个 激光)超过31种癌症类型的8,000多个样本以及大约400种常见的癌细胞系。目标#3.执行 在丰富的TCGA背景下对m6A RNA甲基化数据进行综合分析和建模。使用TCGA 多维分子数据，我们将开发预测模型，量化各种因素的影响 通过深度学习参与m6A RNA的修饰。我们将进行分析以定义基于m6A的肿瘤 亚型，评估m6A相关标志物的临床应用，并研究m6A与其他分子的相互作用 在不同的肿瘤环境中的像差。最后，我们将建立一个公开可用的、用户友好的数据库，它将 包含通过目标#1和目标#2生成的m6A数据的全面信息。预期的 该项目的成果是：(I)建立了m6A相关基因组和蛋白质组的综合资源 基于最广泛使用的癌症患者队列的数据，以便可以进一步调查此类数据 由癌症研究界流利地进行；及(Ii)评估 M6A RNA甲基化用于癌症治疗的综合方法。这个项目是创新的，因为它将 系统评估目前正在进行的一类关键的RNA修饰的临床相关性和功能 在癌症研究方面研究不足。这些结果将产生重要的积极影响，因为 Gain不仅将极大地促进我们对m6A RNA甲基化在癌症发展中的作用的理解， 而且还直接促进了一类新型癌症生物标志物和治疗靶点的开发。