Systematic Functional Characterization of RNA Editing in Endometrial Cancer

描述(申请人提供)：子宫内膜癌是美国最常见的妇科癌症。对这种疾病的研究工作主要集中在识别关键的遗传异常，如体细胞突变，但还没有建立有效的靶向治疗。相比之下，由RNA编辑引起的RNA水平的“突变”，这是一种重要的表观遗传控制，在子宫内膜癌乃至整个癌症中几乎没有受到关注。到目前为止，个体RNA编辑事件的重要性已经在几种癌症类型中得到了证明；然而，还没有尝试在任何一种癌症类型中进行全面的调查。值得注意的是，该研究小组的初步分析显示，主要RNA编辑酶的过度表达与子宫内膜癌患者较差的存活率显著相关。长期目标是阐明RNA编辑在子宫内膜癌病理生理学中的作用，并开发新的生物标记物或治疗策略。目前的目标是系统地识别“驱动”RNA编辑事件并阐明其 这种疾病的相关机制。中心假设是一些RNA编辑事件在子宫内膜肿瘤的发生和发展中起着至关重要的作用。其基本原理是，确定的关键的RNA编辑诱导的核苷酸变化将代表子宫内膜癌的有希望的生物标记物或治疗靶点，这样的研究将对肿瘤学的各个方面产生重大影响。在强大的初步数据的指导下，这一假说将通过追求两个特定的目标来验证：目的1.检测与子宫内膜癌中肿瘤过度编辑活动或临床变量相关的RNA编辑位点。将对癌症基因组图谱(TCGA)的测序数据进行分析，以确定在子宫内膜肿瘤中具有显著过度编辑活性或与重要临床变量相关的RNA编辑位点。观察到的RNA编辑模式随后将在TCGA样本和大量独立的内部子宫内膜肿瘤样本中使用正交方法进行验证。初步结果表明，这样的RNA编辑站点数量可观。目的2.确定子宫内膜肿瘤发病机制中的驱动RNA编辑事件。目标1中确定的RNA编辑事件的功能影响将通过使用高灵敏细胞活性分析的新的两步功能评估策略进行检查。与这些编辑事件相关的基因组异常将通过对TCGA/内部基因组数据的不平衡分析来确定。对于RNA编辑驱动事件，将使用选定的子宫内膜肿瘤细胞系中的功能蛋白质组学来确定其受影响的信号通路。这个项目是创新的，因为它代表了一种系统的方法，以确定关键的表观遗传学变化作为子宫内膜癌的分子基础。这一研究意义重大，因为所获得的知识将从纵向上促进对子宫内膜肿瘤发生的理解，并有助于开发和实施一类新的生物标记物或治疗靶点。此外，建立的计算和实验方法将很容易适用于其他类型的癌症。

DESCRIPTION (provided by applicant): Endometrial cancer is the most common gynecological cancer in the United States. Research efforts in this disease have focused on identifying key genetic aberrations such as somatic mutations, but no effective targeted therapies have been established. By contrast, "mutations" at the RNA level caused by RNA editing, an important epigenetic control, have received little attention in endometrial cancer and indeed, cancer in general. To date, the importance of individual RNA editing events has been documented in several cancer types; however a comprehensive investigation has not been attempted in any cancer type. Strikingly, the preliminary analyses by this research team reveal that the overexpression of major RNA editing enzymes significantly correlates with poor patient survival in endometrial cancer. The long-term goal is to elucidate the role of RNA editing in the pathophysiology of endometrial cancer and develop novel biomarkers or treatment strategies. The current objective is to systematically identify "driver" RNA editing events and elucidate their associated mechanisms in this disease. The central hypothesis is that some RNA editing events play a crucial role in the initiation and progression of endometrial tumors. The rationale is that the key RNA-editing-induced nucleotide changes identified will represent promising biomarkers or therapeutic targets for endometrial cancer and such a study will have major impacts across the breadth of oncology. Guided by strong preliminary data, this hypothesis will be tested by pursuing two specific aims: Aim 1. Detect RNA editing sites associated with tumor over-editing activity or clinical variables in endometrial cancer. The Cancer Genome Atlas (TCGA) sequencing data will be analyzed to identify RNA editing sites that have significant over-editing activity in endometrial tumors or correlate with important clinical variables. The observed patterns of RNA editing will then be validated using orthogonal approaches in both TCGA samples and a large, independent, in-house cohort of endometrial tumor samples. The preliminary results have demonstrated a substantial number of such RNA editing sites. Aim 2. Identify driver RNA editing events in the pathogenesis of endometrial tumors. The functional impact of RNA editing events identified in Aim 1 will be examined through a novel two-step functional assessment strategy using highly sensitive cell viability assays. The genomic aberrations associated with these editing events will be determined through disequilibrium analyses on TCGA/in-house genomics data. For the RNA editing driver events, functional proteomics in selected endometrial tumor cell lines will be used to identify their affected signaling pathways. This project is innovative because it represents a systematic approach to identifying key epigenetic changes as the molecular basis of endometrial cancer. It is significant because the knowledge gained will vertically advance the understanding of endometrial tumorigenesis and facilitate the development and implementation of a novel class of biomarkers or therapeutic targets. In addition, the computational and experimental methods established will be readily applicable to other cancer types.