Genome Nexus: A Comprehensive Resource for the Annotation and Interpretation of Genomic Variants in Cancer

PURPOSE Interpretation of genomic variants in tumor samples still presents a challenge in research and the clinical setting. A major issue is that information for variant interpretation is fragmented across disparate databases, and aggregation of information from these requires building extensive infrastructure. To this end, we have developed Genome Nexus, a one-stop shop for variant annotation with a user-friendly interface for cancer researchers and clinicians. METHODS Genome Nexus (1) aggregates variant information from sources that are relevant to cancer research and clinical applications, (2) allows high-performance programmatic access to the aggregated data via a unified application programming interface, (3) provides a reference page for individual cancer variants, (4) provides user-friendly tools for annotating variants in patients, and (5) is freely available under an open source license and can be installed in a private cloud or local environment and integrated with local institutional resources. RESULTS Genome Nexus is available at https://www.genomenexus.org. It displays annotations from more than a dozen resources including those that provide variant effect information (variant effect predictor), protein sequence annotation (Uniprot, Pfam, and dbPTM), functional consequence prediction (Polyphen-2, Mutation Assessor, and SIFT), population prevalences (gnomAD, dbSNP, and ExAC), cancer population prevalences (Cancer hotspots and SignalDB), and clinical actionability (OncoKB, CIViC, and ClinVar). We describe several use cases that demonstrate the utility of Genome Nexus to clinicians, researchers, and bioinformaticians. We cover single-variant annotation, cohort analysis, and programmatic use of the application programming interface. Genome Nexus is unique in providing a user-friendly interface specific to cancer that allows high-performance annotation of any variant including unknown ones. CONCLUSION Interpretation of cancer genomic variants is improved tremendously by having an integrated resource for annotations. Genome Nexus is freely available under an open source license. Genome Nexus (genomenexus.org): a one-stop shop to annotate and interpret genomic variants in cancer.

[1]  B. Taylor,et al.  The context-specific role of germline pathogenicity in tumorigenesis , 2021, Nature Genetics.

[2]  Gregory M. Cooper,et al.  CADD: predicting the deleteriousness of variants throughout the human genome , 2018, Nucleic Acids Res..

[3]  J. Flowers,et al.  Origins and geographic diversification of African rice (Oryza glaberrima) , 2018, bioRxiv.

[4]  Dong Xu,et al.  G2S: a web-service for annotating genomic variants on 3D protein structures , 2018, Bioinform..

[5]  Peter W. Laird,et al.  Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer , 2018, Cell.

[6]  Bruce D. Gelb,et al.  ClinGen’s RASopathy Expert Panel Consensus Methods for Variant Interpretation , 2018, Genetics in Medicine.

[7]  Michael P. Schroeder,et al.  Cancer Genome Interpreter annotates the biological and clinical relevance of tumor alterations , 2017, Genome Medicine.

[8]  Moriah H Nissan,et al.  OncoKB: A Precision Oncology Knowledge Base. , 2017, JCO precision oncology.

[9]  Donavan T. Cheng,et al.  Mutational Landscape of Metastatic Cancer Revealed from Prospective Clinical Sequencing of 10,000 Patients , 2017, Nature Medicine.

[10]  Steven J. M. Jones,et al.  CIViC is a community knowledgebase for expert crowdsourcing the clinical interpretation of variants in cancer , 2017, Nature Genetics.

[11]  C. Sander,et al.  3D clusters of somatic mutations in cancer reveal numerous rare mutations as functional targets , 2017, Genome Medicine.

[12]  Cathy H. Wu,et al.  UniProt: the universal protein knowledgebase , 2016, Nucleic Acids Research.

[13]  Raymond Dalgleish,et al.  HGVS Recommendations for the Description of Sequence Variants: 2016 Update , 2016, Human mutation.

[14]  Benjamin J. Ainscough,et al.  High-performance web services for querying gene and variant annotation , 2016, Genome Biology.

[15]  F. Cunningham,et al.  The Ensembl Variant Effect Predictor , 2016, bioRxiv.

[16]  Ricardo Villamarín-Salomón,et al.  ClinVar: public archive of interpretations of clinically relevant variants , 2015, Nucleic Acids Res..

[17]  James Y. Zou Analysis of protein-coding genetic variation in 60,706 humans , 2015, Nature.

[18]  Tatiana A. Tatusova,et al.  Gene: a gene-centered information resource at NCBI , 2014, Nucleic Acids Res..

[19]  Mingming Jia,et al.  COSMIC: exploring the world's knowledge of somatic mutations in human cancer , 2014, Nucleic Acids Res..

[20]  Benjamin E. Gross,et al.  Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal , 2013, Science Signaling.

[21]  Hannah Carter,et al.  CRAVAT: cancer-related analysis of variants toolkit , 2013, Bioinform..

[22]  I. Adzhubei,et al.  Predicting Functional Effect of Human Missense Mutations Using PolyPhen‐2 , 2013, Current protocols in human genetics.

[23]  Tom R. Gaunt,et al.  Predicting the Functional, Molecular, and Phenotypic Consequences of Amino Acid Substitutions using Hidden Markov Models , 2012, Human mutation.

[24]  Benjamin E. Gross,et al.  The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. , 2012, Cancer discovery.

[25]  C. Sander,et al.  Predicting the functional impact of protein mutations: application to cancer genomics , 2011, Nucleic acids research.

[26]  H. Hakonarson,et al.  ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data , 2010, Nucleic acids research.

[27]  Jonathan M. Mudge,et al.  The consensus coding sequence (CCDS) project: Identifying a common protein-coding gene set for the human and mouse genomes. , 2009, Genome research.

[28]  Michael R. Green,et al.  F-Box Protein FBXO31 Mediates Cyclin D1 Degradation to Induce G1 Arrest Following DNA Damage , 2009, Nature.

[29]  Hsien-Da Huang,et al.  dbPTM: an information repository of protein post-translational modification , 2005, Nucleic Acids Res..

[30]  H. Berman,et al.  The Protein Data Bank. , 2002, Acta crystallographica. Section D, Biological crystallography.

[31]  M. Roussel,et al.  Glycogen synthase kinase-3beta regulates cyclin D1 proteolysis and subcellular localization. , 1998, Genes & development.

[32]  N. Socci,et al.  Accelerating Discovery of Functional Mutant Alleles in Cancer. , 2018, Cancer discovery.

[33]  AACR Project GENIE: Powering Precision Medicine through an International Consortium. , 2017, Cancer discovery.

[34]  S. Henikoff,et al.  Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm , 2009, Nature Protocols.

[35]  Cathy H. Wu,et al.  UniProt: the Universal Protein knowledgebase , 2004, Nucleic Acids Res..

[36]  Elizabeth M. Smigielski,et al.  dbSNP: the NCBI database of genetic variation , 2001, Nucleic Acids Res..