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

总结 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 进展事实上，我们对癌症基因组图谱（TCGA）转录组数据的分析表明，RBP，作为 在癌症中比转录因子更明显失调。我们提出了一个多方面的 一系列计算和实验研究，以系统地识别一组因果关系密切的限制性商业惯例 有助于癌症进展并表征其下游效应机制。在一个策略中， 我们建议通过首先在3'端发现它们的顺式调节识别元件来鉴定失调的RBP。 和显示动态mRNA表达的基因的5' UTR-肿瘤与正常样品之间，和 在TCGA的25个癌症队列中的每一个。这将使用信息理论来实现 算法，发现从头线性和结构RNA基序元件，具有高灵敏度和低假 发现率我们先前已经证明，这种RNA基序是调节细胞凋亡的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调节子（或RBP模块），其在癌症进展中具有疑似作用。为了 识别临床上重要的RBP模块，我们建议开发一个计算框架， 每个模块的表达在TCGA原发性肿瘤中对患者存活率分层的程度 样品我们的初步结果导致了许多这样的模块的发现与显着分层 多种癌症类型患者的生存率。对于最具临床预后的模块的子集，我们 将使用生物化学和基于CRISPR的平行遗传筛选来识别其同源RBP。中 作为一种互补策略，我们将通过计算从一个 在约250个RBP中的每一个的shRNA敲低后获得的ENCODE转录组数据的概要。在 为了确定在因果上导致癌症进展的RBP，我们建议开发一个平行的 CRISPR功能丧失筛选肿瘤形成和转移的小鼠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显示出显著的患者 存活分层和小鼠体内肿瘤效应。顶部验证 然后，RBP将单独表征其在各种体外和体内癌细胞中的作用。 表型最后，我们建议开发一个平行的小鼠体内CRISPR上位性平台， 确定RBP对肿瘤形成发挥作用的特定下游基因， 转移我们的综合计算/实验策略将扩大我们对一个分子的理解。 癌症通路失调的大部分未探索领域，并可能揭示工作中的新原理。 此外，我们对癌症进展的因果途径的关注将影响诊断、预后和预后。 我们在临床肿瘤学上的治疗精度。

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.