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

基本信息

批准号：
10350659
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
项目类别：
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/10350659
关键词：
3&apos Untranslated Regions 5&apos Untranslated Regions Algorithms Area Binding Binding Proteins Binding Sites Biochemical Biological Biology Breast cancer metastasis CRISPR screen Cells Clinical Clinical Oncology Clinical stratification Clustered Regularly Interspaced Short Palindromic Repeats Collaborations Computer Analysis Data Diagnosis Diagnostic Elements Exhibits Gene Proteins Genes Genetic Epistasis Genetic Screening Genetic Transcription Goals Human Genome In Vitro Individual Knowledge Laboratories Malignant Neoplasms Maps Mediating Messenger RNA Molecular Molecular Genetics 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 The Cancer Genome Atlas Therapeutic Intervention Tissue-Specific Gene Expression Transcript Universities Untranslated RNA Work Xenograft Model base 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 prognostic small hairpin RNA transcription factor transcriptome tumor tumor growth tumor progression tumorigenesis

项目摘要

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 RNA 结合蛋白 (RBP) 失调在癌症中的重要作用事实上，我们对癌症基因组图谱 (TCGA) 转录组数据的分析表明，RBP 与一个群体，在癌症中比转录因子更加失调。我们提出了一个多方面的研究。一组计算和实验研究，系统地识别因果关系的一组 RBP 在一种策略中，有助于癌症进展并表征其下游效应机制。我们建议通过首先发现其 3' 中的顺式调节识别元件来识别失调的 RBP 以及显示动态 mRNA 表达的基因的 5' UTR——无论是在肿瘤样本还是正常样本之间，以及 TCGA 中 25 个癌症队列中的每一个都将使用信息论来完成。算法从头发现线性和结构 RNA 基序元素，具有高灵敏度和低错误率我们之前已经表明，此类 RNA 基序是调节 RBP 的结合位点。 mRNA，其子集调节肿瘤稳定性和转移。构成一个孤儿 RBP 调节子（或 RBP 模块），其在癌症进展中具有可疑作用。为了确定临床上重要的 RBP 模块，我们建议开发一个计算框架来量化每个模块的表达对 TCGA 原发肿瘤患者生存进行分层的程度我们的初步结果发现了许多具有显着分层的此类模块。对于大多数临床预后模块的子集，我们研究了多种癌症类型的患者生存率。将使用生化和基于 CRISPR 的平行遗传筛选来鉴定其同源 RBP。作为补充策略，我们将从计算中识别出此类临床预后 RBP 模块获得大约 250 个 RBP 的 shRNA 敲低后的 ENCODE 转录组数据概要。为了确定导致癌症进展的 RBP，我们建议开发一个并行的 CRISPR 功能丧失筛选小鼠肿瘤形成和转移异种移植模型中的所有 RBP。然后，我们将对前 20 个 RBP 进行更集中的 CRISPR 筛选，这些 RBP 均显示出重要的患者我们的初步综合筛选中的生存分层和小鼠体内肿瘤效应。然后将分别表征 RBP 在各种体外和体内癌细胞中的作用最后，我们建议开发一个平行的小鼠体内 CRISPR 上位平台以有效地实现。确定 RBP 通过其对肿瘤形成发挥作用的特定下游基因，以及我们的综合计算/实验策略将扩展我们对转移的分子理解。癌症途径失调的很大程度上尚未探索的领域，并可能揭示工作中的新原理。此外，我们对癌症进展因果途径的关注将影响诊断、预后和我们对待临床肿瘤学的治疗精度。