Mapping the regulatory landscape of RNA binding proteins and their causal roles in tumorigenesis and patient survival

绘制 RNA 结合蛋白的调控格局及其在肿瘤发生和患者生存中的因果作用

• 批准号: 10549731
• 负责人: Saeed F Tavazoie
• 金额: $ 53.62万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-02-12 至 2026-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10549731
• 关键词: 3' Untranslated Regions; 5' Untranslated Regions; Algorithms; Area; Binding; Binding Proteins; Binding Sites; Biochemical; Biological; Biology; Breast cancer metastasis; CRISPR screen; Cell Proliferation; Cells; Clinical; Clinical Oncology; Clinical stratification; Clustered Regularly Interspaced Short Palindromic Repeats; Collaborations; Computer Analysis; Data; Diagnosis; Diagnostic; Elements; Exhibits; Gene Proteins; Genes; Genetic; Genetic Epistasis; Genetic Screening; Goals; Human Genome; In Vitro; Individual; Knowledge; Laboratories; Malignant Neoplasms; Maps; Mediating; Messenger RNA; MicroRNAs; Molecular; Mus; Neoplasm Metastasis; Orphan; Pathway interactions; Patients; Phenotype; Play; Positioning Attribute; Precision therapeutics; Primary Neoplasm; Process; RNA; RNA Sequences; RNA-Binding Proteins; Recording of previous events; Regulatory Element; Regulatory Pathway; Regulon; Research; Role; Sampling; Stratification; Technology; The Cancer Genome Atlas; Therapeutic Intervention; Tissue-Specific Gene Expression; Transcript; Universities; Untranslated RNA; Work; Xenograft Model; cancer cell; cancer type; clinical prognostic; clinically relevant; clinically significant; cohort; computer framework; computer studies; experimental study; genetic regulatory protein; in vivo; knock-down; large datasets; loss of function; mRNA Expression; mRNA Stability; novel; patient stratification; posttranscriptional; prognostic; small hairpin RNA; transcription factor; transcriptome; tumor; tumor growth; tumor progression; tumorigenesis

Summary Our preliminary results support a prominent role for dysregulation of RNA binding proteins (RBPs) in cancer progression. In fact, our analysis of the cancer genome atlas (TCGA) transcriptome data shows that RBPs, as a group, are significantly more dysregulated in cancer than transcription factors. We propose a multi-faceted set of computational and experimental studies to systematically identify the set of RBPs that causally contribute to cancer progression and to characterize their downstream effector mechanisms. In one strategy, we propose to identify dysregulated RBPs by first discovering their cis-regulatory recognition elements in the 3’ and 5’ UTR of genes that show dynamic mRNA expression—both between tumor vs. normal samples, and across each of the 25 cancer cohorts in TCGA. This will be accomplished using information-theoretic algorithms that discover de novo linear and structural RNA motif elements with high sensitivity and low false discovery rates. We have previously shown that such RNA motifs are the binding sites for RBPs that modulate mRNA stability, a subset of which regulate tumorigenesis and metastasis. The genes harboring these motifs constitute an orphan RBP regulon (or RBP module) with a suspected role in cancer progression. In order to identify clinically significant RBP modules, we propose to develop a computational framework that quantifies the degree to which the expression of each module stratifies patient survival across the TCGA primary tumor samples. Our preliminary results have led to the discovery of many such modules with remarkable stratification of patient survival across multiple cancer types. For the subset of the most clinically prognostic modules, we will identify their cognate RBPs using both biochemical and CRISPR-based parallel genetic screens. In a complementary strategy, we will computationally identify such clinically prognostic RBP modules from a compendium of ENCODE transcriptome data obtained following shRNA knockdowns of each of ~250 RBPs. In order to identify RBPs that causally contribute to cancer progression, we propose to develop a parallel CRISPR loss-of-function screen for all RBPs in mouse xenograft models of tumor formation and metastasis. We will then conduct a more focused CRISPR screen on the top ~20 RBPs that show both significant patient survival stratification and mouse in vivo tumor effects in our primary comprehensive screen. The top validated RBPs will then be individually characterized for their roles in a variety of in vitro and in vivo cancer cell phenotypes. Finally, we propose to develop a parallel mouse in vivo CRISPR epistasis platform to efficiently determine the specific downstream genes through which the RBP exerts its effects on tumor formation and metastasis. Our integrated computational/experimental strategy will expand our molecular understanding of a largely unexplored domain of cancer pathway dysregulation and potentially reveal new principles at work. Furthermore, our focus on causal pathways of cancer progression will impact the diagnostic, prognostic, and therapeutic precision with which we approach clinical oncology.

概括 我们的初步结果支持癌症RNA结合蛋白（RBP）失调的重要作用 进展。实际上，我们对癌症基因组图集（TCGA）转录组数据的分析表明，RBPS，AS 一组在癌症中比转录因子更大的失调。我们提出了一个多方面的 一组计算和实验研究，以系统地识别有因果的RBP 有助于癌症进展并表征其下游效应子机制。在一个策略中， 我们建议通过首先在3'中发现其顺式调节识别元素来识别失调的RBP。 5'UTR的基因表达动态mRNA表达 - 肿瘤与正常样品之间的基因和 在TCGA中的25个癌症队列中的每一个中。这将使用信息理论完成 发现从头线性和结构RNA图案元素具有高灵敏度和低假的算法 发现率。我们先前已经表明，这种RNA基序是调节的RBP的结合位点 mRNA稳定性，其中一个子集调节肿瘤发生和转移。携带这些图案的基因 构成孤儿RBP调节（或RBP模块），可疑在癌症进展中作用。为了 确定具有临床意义的RBP模块，我们建议开发一个量化的计算框架 每个模块的表达在跨TCGA原发性肿瘤中的患者生存分层的程度 样品。我们的初步结果导致发现了许多具有显着分层的模块 多种癌症类型的患者生存。对于最临床预后模块的子集，我们 将使用生化和基于CRISPR的平行遗传筛选来识别其同源RBP。在 互补策略，我们将在计算上确定从一个临床预后的RBP模块 在约250 rbps中的每个shrna敲低之后获得的编码转录组数据的汇编。在 为了识别有因果关系促进癌症进展的RBP，我们建议发展一个平行 在肿瘤形成和转移的小鼠Xenographic模型中，所有RBP的功能丧失屏幕。 然后，我们将在顶部大约20个RBP上进行更集中的CRISPR屏幕，这两者都显示出重要的患者 在我们的主要综合筛查中，生存分层和小鼠体内肿瘤的影响。最高验证 然后，RBP将以各种体外和体内癌细胞中的作用来单独表征 表型。最后，我们建议在Vivo CRISPR上位平台中开发平行的鼠标以有效 确定RBP对肿瘤形成的影响的特定下游基因 转移。我们集成的计算/实验策略将扩大我们对 癌症途径失调的大部分意外领域，并有可能揭示工作中的新原则。 此外，我们对癌症进展的因果途径的关注将影响诊断，预后和 我们处理临床肿瘤学的治疗精度。