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

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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.