Identification of community-consensus clinically relevant variants and development of single molecule molecular inversion probes using the CIViC database

Clinical targeted sequencing panels are important for identifying actionable variants for cancer patients, however, there are currently no strategies to create impartial and rationally-designed panels to accommodate rapidly growing knowledge within the field. Here we use the Clinical Interpretations of Variants in Cancer database (CIViC) in conjunction with single-molecule molecular inversion probe (smMIP) capture to identify and design probes targeting clinically relevant variants in cancer. In total, 2,027 smMIPs were designed to target 111 eligible CIViC variants. The total genomic region covered by the CIViC smMIPs reagent was 61.5 kb. When compared to existing genome or exome sequencing results (n = 27 cancer samples from 5 tumor types), CIViC smMIP sequencing demonstrated a 95% sensitivity for variant detection (n = 61/64 variants). Variant allele frequency for variants identified on both sequencing platforms were highly concordant (Pearson correlation = 0.885; n = 61 variants). Moreover, for individuals with paired tumor/normal samples (n = 12), 182 clinically relevant variants missed by original sequencing were discovered by CIViC smMIPs sequencing. This design paradigm demonstrates the utility of an open-sourced database built on attendant community contributions for each variant with peer-reviewed interpretations. Use of a public repository for variant identification, probe development, and variant annotation could provide a transparent approach to build a dynamic next-generation sequencing–based oncology panel.

[1]  Elaine R. Mardis,et al.  The $ 1 , 000 genome , the $ 100 , 000 analysis ? , 2019 .

[2]  Obi L. Griffith,et al.  Standard operating procedure for somatic variant refinement of sequencing data with paired tumor and normal samples , 2018, Genetics in Medicine.

[3]  Alex H. Wagner,et al.  Recurrent WNT pathway alterations are frequent in relapsed small cell lung cancer , 2018, Nature Communications.

[4]  J. Szustakowski,et al.  STK11/LKB1 Mutations and PD-1 Inhibitor Resistance in KRAS-Mutant Lung Adenocarcinoma. , 2018, Cancer discovery.

[5]  B. Wood,et al.  Ultrasensitive detection of acute myeloid leukemia minimal residual disease using single molecule molecular inversion probes , 2017, Haematologica.

[6]  H. Chaturvedi,et al.  FoundationOne as a relevant tool for comprehensive genomic profiling and assessment of tumor mutation burden in the era of precision oncology in India. , 2017 .

[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]  Marina N Nikiforova,et al.  Guidelines for Validation of Next-Generation Sequencing-Based Oncology Panels: A Joint Consensus Recommendation of the Association for Molecular Pathology and College of American Pathologists. , 2017, The Journal of molecular diagnostics : JMD.

[10]  Christina A. Castellani,et al.  VarScan2 analysis of de novo variants in monozygotic twins discordant for schizophrenia , 2017, Psychiatric genetics.

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

[12]  Mingming Jia,et al.  COSMIC: somatic cancer genetics at high-resolution , 2016, Nucleic Acids Res..

[13]  A. Hoischen,et al.  Reliable Next-Generation Sequencing of Formalin-Fixed, Paraffin-Embedded Tissue Using Single Molecule Tags. , 2016, The Journal of molecular diagnostics : JMD.

[14]  A. Gonzalez-Perez,et al.  Rational design of cancer gene panels with OncoPaD , 2016, Genome Medicine.

[15]  S. Patterson,et al.  The clinical trial landscape in oncology and connectivity of somatic mutational profiles to targeted therapies , 2016, Human Genomics.

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

[17]  Obi L. Griffith,et al.  Optimizing cancer genome sequencing and analysis. , 2015, Cell systems.

[18]  Obi L. Griffith,et al.  Genome Modeling System: A Knowledge Management Platform for Genomics , 2015, PLoS Comput. Biol..

[19]  Donavan T. Cheng,et al.  Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT): A Hybridization Capture-Based Next-Generation Sequencing Clinical Assay for Solid Tumor Molecular Oncology. , 2015, The Journal of molecular diagnostics : JMD.

[20]  F. Collins,et al.  A new initiative on precision medicine. , 2015, The New England journal of medicine.

[21]  Benjamin M. Good,et al.  Organizing knowledge to enable personalization of medicine in cancer , 2014, Genome Biology.

[22]  Jane C Weeks,et al.  Physicians' attitudes about multiplex tumor genomic testing. , 2014, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[23]  Ira M. Hall,et al.  SAMBLASTER: fast duplicate marking and structural variant read extraction , 2014, Bioinform..

[24]  Travis E. Abbott,et al.  Using SomaticSniper to Detect Somatic Single Nucleotide Variants. , 2014, Current protocols in bioinformatics.

[25]  Deanna M. Church,et al.  ClinVar: public archive of relationships among sequence variation and human phenotype , 2013, Nucleic Acids Res..

[26]  Renato Martins,et al.  Validation and implementation of targeted capture and sequencing for the detection of actionable mutation, copy number variation, and gene rearrangement in clinical cancer specimens. , 2014, The Journal of molecular diagnostics : JMD.

[27]  Emily H Turner,et al.  Actionable, pathogenic incidental findings in 1,000 participants' exomes. , 2013, American journal of human genetics.

[28]  Marc S. Williams,et al.  ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing , 2013, Genetics in Medicine.

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

[30]  Heng Li Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM , 2013, 1303.3997.

[31]  A. Sivachenko,et al.  Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples , 2013, Nature Biotechnology.

[32]  Wendy S. W. Wong,et al.  Strelka: accurate somatic small-variant calling from sequenced tumor-normal sample pairs , 2012, Bioinform..

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

[34]  Christopher A. Miller,et al.  VarScan 2: somatic mutation and copy number alteration discovery in cancer by exome sequencing. , 2012, Genome research.

[35]  Ken Chen,et al.  SomaticSniper: identification of somatic point mutations in whole genome sequencing data , 2012, Bioinform..

[36]  E. Mardis The $1,000 genome, the $100,000 analysis? , 2010, Genome Medicine.

[37]  M. DePristo,et al.  The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. , 2010, Genome research.

[38]  Kai Ye,et al.  Pindel: a pattern growth approach to detect break points of large deletions and medium sized insertions from paired-end short reads , 2009, Bioinform..

[39]  Gonçalo R. Abecasis,et al.  The Sequence Alignment/Map format and SAMtools , 2009, Bioinform..

[40]  Richard Durbin,et al.  Sequence analysis Fast and accurate short read alignment with Burrows – Wheeler transform , 2009 .

[41]  John D. Hunter,et al.  Matplotlib: A 2D Graphics Environment , 2007, Computing in Science & Engineering.

[42]  David Haussler,et al.  The UCSC genome browser database: update 2007 , 2006, Nucleic Acids Res..

[43]  Terrence S. Furey,et al.  The UCSC Genome Browser Database: update 2006 , 2005, Nucleic Acids Res..

[44]  L. Harris,et al.  The HER2 extracellular domain as a prognostic and predictive factor in breast cancer. , 2002, Clinical breast cancer.