The joint WCM-NYGC Center for Functional and Clinical Interpretation of Tumor Profiles

威尔·康奈尔医学-纽约基因组中心(WCM-NYGC) 肿瘤轮廓的解释将执行编码和非编码变体的综合分析，以 检测和揭示特定类别突变的功能，并评估其临床潜力。AS 在RFA中，我们选择专注于两个核心能力：(1)编码突变和 (2)非编码突变(生殖系)。我们将利用WCM在临床基因组学方面的专业知识来演示 由CLIA在纽约州批准的第一个完整外显子组测序测试。我们将利用 NYGC的计算基础设施，具有5,000个核心和10PB存储和数据管理 专业知识。我们将重点研究特定类别的突变：(1)编码突变及其 临床相关性，包括与免疫治疗的相关性；(2)驱动程序非编码点突变和 它们在转录调控中的作用；(3)结构变异的驱动作用。在目标1中，我们将 注释编码突变的临床和功能影响，包括免疫治疗。首先，我们会 生成包含突变的临床解释的临床分级报告，可通过 自定义用户界面。这将使详细的统计数字的数量和频率临床 相关变种。一个新的模块将帮助向知识库提供新的变体，并 社区。其次，我们将应用我们的分析管道来解开免疫格局 再加上一种新的综合免疫核心，可以预测哪些患者更有可能对 免疫检查点封锁，一种在部分癌症患者中显示出巨大影响的治疗方法。在……里面 目的2，我们将诠释非编码突变对剪接的驱动作用和影响。首先，我们将 从功能上表征基因(启动子、增强子)以外的遗传变异 经过实验验证的FunSeq管道。第二，我们将分析转录结果 利用一种新的整合RNA-Seq数据和预测剪接改变的剪接位点改变 DNA测序的变种。在目标3中，我们将注释驱动作用和转录影响 结构变化。我们将使用基于共识的方法对结构变异和基因融合进行注释 采用我们小组中的基准方法以及新的方法。这一目标的成果 将对一类关键的非编码事件进行全面的注释和功能分析。在……里面 总之，建议的分析依赖于将在标准中使用的现有管道和工具 和自动化的方式在WCM-NYGC计算基础设施上。这些分析的目的是 是获得新的知识和相关性，这将影响癌症的临床和研究 基因组学领域。WCM-NYGC团队将参与并响应合作伙伴 在这个网络中。

The Weill Cornell Medicine-New York Genome Center (WCM-NYGC) for Functional and Clinical Interpretation of Tumor Profiles will perform integrative analyses of coding and non-coding variants to detect and unravel the function of specific classes of mutations and assess their clinical potential. As specified in the RFA, we have chosen to focus on two Core Competencies: (1) coding mutations and (2) non-coding mutations (germline). We will use WCM’s expertise in clinical genomics demonstrated by the first CLIA approved Whole Exome Sequencing test in New York State. We will leverage NYGC’s computational infrastructure with > 5,000 cores and 10Pb storage and data management expertise. We will focus our GDAC on specific classes of mutations: (1) coding mutations and their clinical relevance including relevance to immunotherapy; (2) driver non-coding point mutations and their role in transcriptional regulation; (3) the driving role of structural variations. In Aim 1 we will annotate the clinical and functional impact of coding mutations including immunotherapy. First we will generate a clinical grade report containing clinical interpretation of mutations, viewable through a custom user interface. This will enable detailed statistics on number and frequency of clinically relevant variants. A new module will help contribute new variants to the knowledge base and community. Second, we will apply our analytical pipeline for unraveling the immune landscape together with a novel integrative immunoscore that predicts which patients are more likely to respond to immune checkpoint blockade, a therapy showing dramatic impact in a subset of cancer patients. In Aim 2, we will annotate the driving role and impact of non-coding mutations on splicing. First, we will functionally characterize genetic variants outside of genes (promoters, enhancers) using the experimentally validated FunSeq pipeline. Second, we will analyze the transcriptional consequence of splice site alterations using a novel for integrating RNA-Seq data with predicted splice-altering variants from DNA sequencing. In Aim 3 we will annotate the driving role and transcriptional impact of structural variations. We will annotate structural variants and gene fusions using a consensus-based approach with methods benchmarked in our group as well as novel methods. The output of this Aim will be comprehensive annotation and functional analysis of a critical class of non-coding events. In summary, the proposed analyses rely on existing pipelines and tools that will be used in a standard and automated way on the WCM-NYGC computational infrastructure. The objective of these analyses is to derive novel knowledge and correlation that will impact both clinical and research cancer genomics fields. The WCM-NYGC team will participate and be responsive to the cooperative partners in this Network.