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

威尔康奈尔医学-纽约约克基因组中心（WCM-NYGC）的功能和临床 肿瘤特征解读将对编码和非编码变体进行综合分析， 检测和阐明特定类型突变的功能，并评估其临床潜力。作为 在RFA中指定的情况下，我们选择关注两个核心竞争力：（1）编码突变， (2)非编码突变（种系）。我们将利用WCM在临床基因组学方面的专业知识， 在纽约州通过了第一个CLIA批准的全外显子组测序测试。我们将利用 NYGC的计算基础架构，拥有超过5，000个内核和10 Pb存储和数据管理 专业知识我们将把我们的GDAC集中在特定类别的突变上：（1）编码突变及其 临床相关性，包括与免疫治疗的相关性;（2）驱动非编码点突变， 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， 注释编码突变的临床和功能影响，包括免疫治疗。首先我们将 生成包含突变的临床解释的临床等级报告，可通过 自定义用户界面。这将使详细的统计数字和频率的临床 相关变种一个新的模块将有助于为知识库提供新的变体， 社区其次，我们将应用我们的分析管道来解开免疫景观 以及一种新的综合免疫评分，可以预测哪些患者更有可能对 免疫检查点阻断，一种在一部分癌症患者中显示出巨大影响的疗法。在 目的2，我们将诠释非编码突变对剪接的驱动作用和影响。一是 功能上表征基因（启动子，增强子）以外的遗传变异，使用 实验验证的FunSeq流水线。其次，我们将分析转录的后果， 使用整合RNA-Seq数据与预测的剪接改变的新的剪接位点改变 DNA测序的变体。在目标3中，我们将注释的驱动作用和转录的影响， 结构变化。我们将使用基于共识的 方法与基准的方法在我们的小组以及新的方法。此Aim的输出 将是全面的注释和功能分析的一个关键类的非编码事件。在 总之，建议的分析依赖于现有的管道和工具，将用于标准 和自动化的方式在WCM-NYGC计算基础设施。这些分析的目的是 是获得将影响临床和研究癌症的新知识和相关性 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.