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The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%., The goals, resources and design of the NHLBI Trans-Omics for Precision Medicine (TOPMed) programme are described, and analyses of rare variants detected in the first 53,831 samples provide insights into mutational processes and recent human evolutionary history.

SUMMARYHuman papillomavirus (HPV) causes 5% of all cancers and frequently integrates into host chromosomes, but the impacts of integration in tumorigenesis remain unclear. Analysis of 105 HPV-positive oropharyngeal cancers by whole genome sequencing detects viral integration in 77%, revealing five statistically significant integration hotspots near genes that regulate epithelial stem cell maintenance (i.e. SOX2, TP63, FGFR, MYC) and immune evasion (i.e. CD274). Somatic hyperamplification is enriched 16-fold near HPV integrants, and the extent of focal host genomic instability increases with local density of HPV integrants. Genes expressed at extreme outlier levels are increased 86-fold within +/- 150 kb of integrants. Across 95% of tumors with integration, host gene transcription is disrupted via intragenic integrants, chimeric transcription, outlier expression, gene breaking and/or de novo expression of noncoding or imprinted genes. We conclude that HPV integration contributes substantively to cancer development by causing extensive disruption of host genome structure and gene expression.

Human papillomavirus (HPV) causes 5% of all cancers and frequently integrates into host chromosomes. The HPV oncoproteins E6 and E7 are necessary but insufficient for cancer formation, indicating that additional secondary genetic events are required. Here, we investigate potential oncogenic impacts of virus integration. Analysis of 105 HPV-positive oropharyngeal cancers by whole-genome sequencing detects virus integration in 77%, revealing five statistically significant sites of recurrent integration near genes that regulate epithelial stem cell maintenance (i.e., SOX2, TP63, FGFR, MYC) and immune evasion (i.e., CD274). Genomic copy number hyperamplification is enriched 16-fold near HPV integrants, and the extent of focal host genomic instability increases with their local density. The frequency of genes expressed at extreme outlier levels is increased 86-fold within ±150 kb of integrants. Across 95% of tumors with integration, host gene transcription is disrupted via intragenic integrants, chimeric transcription, outlier expression, gene breaking, and/or de novo expression of noncoding or imprinted genes. We conclude that virus integration can contribute to carcinogenesis in a large majority of HPV-positive oropharyngeal cancers by inducing extensive disruption of host genome structure and gene expression.

Acute myeloid leukemias (AML) are characterized by mutations of tumor suppressor and oncogenes, involving distinct genes in adults and children. While certain mutations have been associated with the increased risk of AML relapse, the genomic landscape of primary chemotherapy-resistant AML is not well defined. As part of the TARGET initiative, we performed whole-genome DNA and transcriptome RNA and miRNA sequencing analysis of pediatric AML with failure of induction chemotherapy. We identified at least three genetic groups of patients with induction failure, including those with NUP98 rearrangements, somatic mutations of WT1 in the absence of apparent NUP98 mutations, and additional recurrent variants including those in KMT2C and MLLT10. Comparison of specimens before and after chemotherapy revealed distinct and invariant gene expression programs. While exhibiting overt therapy resistance, these leukemias nonetheless showed diverse forms of clonal evolution upon chemotherapy exposure. This included selection for mutant alleles of FRMD8, DHX32, PIK3R1, SHANK3, MKLN1, as well as persistence of WT1 and TP53 mutant clones, and elimination of FLT3, PTPN11, and NRAS mutant clones. These findings delineate genetic mechanisms of primary chemotherapy resistance in pediatric AML, which should inform improved approaches for its diagnosis and therapy.

Summary paragraphThe Trans-Omics for Precision Medicine (TOPMed) program seeks to elucidate the genetic architecture and disease biology of heart, lung, blood, and sleep disorders, with the ultimate goal of improving diagnosis, treatment, and prevention. The initial phases of the program focus on whole genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here, we describe TOPMed goals and design as well as resources and early insights from the sequence data. The resources include a variant browser, a genotype imputation panel, and sharing of genomic and phenotypic data via dbGaP. In 53,581 TOPMed samples, >400 million single-nucleotide and insertion/deletion variants were detected by alignment with the reference genome. Additional novel variants are detectable through assembly of unmapped reads and customized analysis in highly variable loci. Among the >400 million variants detected, 97% have frequency

Cancer genomes often harbor hundreds of somatic DNA rearrangement junctions, many of which cannot be easily classified into simple (e.g. deletion) or complex (e.g. chromothripsis) structural variant classes. Applying a novel genome graph computational paradigm to analyze the topology of junction copy number (JCN) across 2,778 tumor whole genome sequences, we uncovered three novel complex rearrangement phenomena: pyrgo, rigma, and tyfonas. Pyrgo are “towers” of low-JCN duplications associated with early replicating regions and superenhancers, enriched in breast and ovarian cancers. Rigma comprise “chasms” of low-JCN deletions at late-replicating fragile sites, enriched in gastrointestinal carcinomas. Tyfonas are “typhoons” of high-JCN junctions and fold-back inversions enriched in expressed protein-coding fusions and breakend hypermutation, frequently found in acral, but not cutaneous, melanomas. Clustering of tumors according to genome graph-derived features identified subgroups associated with DNA repair defects and poor prognosis.

Acute myeloid leukemias (AML) are characterized by mutations of tumor suppressor and oncogenes, involving distinct genes in adults and children. While certain mutations have been associated with the increased risk of AML relapse, the genomic landscape of primary chemotherapy resistant AML is not well defined. As part of the TARGET initiative, we performed whole-genome DNA and transcriptome (RNA and miRNA) sequencing analysis of pediatric AML with failure of induction chemotherapy. We identified at least three genetic groups of patients with induction failure, including those withNUP98rearrangements, somatic mutations ofWT1in the absence ofNUP98mutations, and additional recurrent variants including those inKMT2CandMLLT10.Comparison of specimens before and after chemotherapy revealed distinct and invariant gene expression programs. While exhibiting overt therapy resistance, these leukemias nonetheless showed diverse forms of clonal evolution upon chemotherapy exposure. This included selection for mutant alleles ofFRMD8,DHX32,PIK3R1,SHANK3,MKLN1, as well as persistence ofWT1andTP53mutant clones, and elimination or contraction ofFLT3,PTPN11, andNRASmutant clones. These findings delineate genetic mechanisms of primary chemotherapy resistance in pediatric AML, which should inform improved approaches for its diagnosis and therapy.

Background Prompted by the revolution in high-throughput sequencing and its potential impact for treating cancer patients, we initiated a clinical research study to compare the ability of different sequencing assays and analysis methods to analyze glioblastoma tumors and generate real-time potential treatment options for physicians. Methods A consortium of seven institutions in New York City enrolled 30 patients with glioblastoma and performed tumor whole genome sequencing (WGS) and RNA sequencing (RNA-seq; collectively WGS/RNA-seq); 20 of these patients were also analyzed with independent targeted panel sequencing. We also compared results of expert manual annotations with those from an automated annotation system, Watson Genomic Analysis (WGA), to assess the reliability and time required to identify potentially relevant pharmacologic interventions. Results WGS/RNAseq identified more potentially actionable clinical results than targeted panels in 90% of cases, with an average of 16-fold more unique potentially actionable variants identified per individual; 84 clinically actionable calls were made using WGS/RNA-seq that were not identified by panels. Expert annotation and WGA had good agreement on identifying variants [mean sensitivity = 0.71, SD = 0.18 and positive predictive value (PPV) = 0.80, SD = 0.20] and drug targets when the same variants were called (mean sensitivity = 0.74, SD = 0.34 and PPV = 0.79, SD = 0.23) across patients. Clinicians used the information to modify their treatment plan 10% of the time. Conclusion These results present the first comprehensive comparison of technical and machine augmented analysis of targeted panel and WGS/RNA-seq to identify potential cancer treatments.

Human papillomavirus (HPV) is a necessary but insufficient cause of a subset of oral squamous cell carcinomas (OSCCs) that is increasing markedly in frequency. To identify contributory, secondary genetic alterations in these cancers, we used comprehensive genomics methods to compare 149 HPV-positive and 335 HPV-negative OSCC tumor/normal pairs. Different behavioral risk factors underlying the two OSCC types were reflected in distinctive genomic mutational signatures. In HPV-positive OSCCs, the signatures of APOBEC cytosine deaminase editing, associated with anti-viral immunity, were strongly linked to overall mutational burden. In contrast, in HPV-negative OSCCs, T>C substitutions in the sequence context 5′-ATN-3′ correlated with tobacco exposure. Universal expression of HPV E6*1 and E7 oncogenes was a sine qua non of HPV-positive OSCCs. Significant enrichment of somatic mutations was confirmed or newly identified in PIK3CA, KMT2D, FGFR3, FBXW7, DDX3X, PTEN, TRAF3, RB1, CYLD, RIPK4, ZNF750, EP300, CASZ1, TAF5, RBL1, IFNGR1, and NFKBIA. Of these, many affect host pathways already targeted by HPV oncoproteins, including the p53 and pRB pathways, or disrupt host defenses against viral infections, including interferon (IFN) and nuclear factor kappa B signaling. Frequent copy number changes were associated with concordant changes in gene expression. Chr 11q (including CCND1) and 14q (including DICER1 and AKT1) were recurrently lost in HPV-positive OSCCs, in contrast to their gains in HPV-negative OSCCs. High-ranking variant allele fractions implicated ZNF750, PIK3CA, and EP300 mutations as candidate driver events in HPV-positive cancers. We conclude that virus-host interactions cooperatively shape the unique genetic features of these cancers, distinguishing them from their HPV-negative counterparts.

Next-generation DNA sequencing (NGS) technologies are currently being applied in both research and clinical settings for the understanding and management of disease. The goal is to use high-throughput sequencing to identify specific variants that drive tumorigenesis within each individual's tumor genomic profile. The significance of copy number and structural variants in glioblastoma makes it essential to broaden the search beyond oncogenic single nucleotide variants toward whole genome profiles of genetic aberrations that may contribute to disease progression. The heterogeneity of glioblastoma and its variability of cancer driver mutations necessitate a more robust examination of a patient's tumor genome. Here, we present patient whole genome sequencing (WGS) information to identify oncogenic structural variants that may contribute to glioblastoma pathogenesis. We provide WGS protocols and bioinformatics approaches to identify copy number and structural variations in 41 glioblastoma patient samples. We present how WGS can identify structural diversity within glioblastoma samples. We specifically show how to apply current bioinformatics tools to detect EGFR variants and other structural aberrations from DNA whole genome sequencing and how to validate those variants within the laboratory. These comprehensive WGS protocols can provide additional information directing more precise therapeutic options in the treatment of glioblastoma.

Next-generation DNA sequencing (NGS) technologies are currently being applied in both research and clinical settings for the understanding and management of disease. The goal is to use high-throughput sequencing to identify specific variants that drive tumorigenesis within each individual's tumor genomic profile. The significance of copy number and structural variants in glioblastoma makes it essential to broaden the search beyond oncogenic single nucleotide variants toward whole genome profiles of genetic aberrations that may contribute to disease progression. The heterogeneity of glioblastoma and its variability of cancer driver mutations necessitate a more robust examination of a patient's tumor genome. Here, we present patient whole genome sequencing (WGS) information to identify oncogenic structural variants that may contribute to glioblastoma pathogenesis. We provide WGS protocols and bioinformatics approaches to identify copy number and structural variations in 41 glioblastoma patient samples. We present how WGS can identify structural diversity within glioblastoma samples. We specifically show how to apply current bioinformatics tools to detect EGFR variants and other structural aberrations from DNA whole genome sequencing and how to validate those variants within the laboratory. These comprehensive WGS protocols can provide additional information directing more precise therapeutic options in the treatment of glioblastoma.

We developed and validated a clinical whole-genome and transcriptome sequencing (WGTS) assay that provides a comprehensive genomic profile of a patient's tumor. The ability to fully capture the mappable genome with sufficient sequencing coverage to precisely call DNA somatic single nucleotide variants, insertions/deletions, copy number variants, structural variants, and RNA gene fusions was analyzed. New York State's Department of Health next-generation DNA sequencing guidelines were expanded for establishing performance validation applicable to whole-genome and transcriptome sequencing. Whole-genome sequencing laboratory protocols were validated for the Illumina HiSeq X Ten platform and RNA sequencing for Illumina HiSeq2500 platform for fresh or frozen and formalin-fixed, paraffin-embedded tumor samples. Various bioinformatics tools were also tested, and CIs for sensitivity and specificity thresholds in calling clinically significant somatic aberrations were determined. The validation was performed on a set of 125 tumor normal pairs. RNA sequencing was performed to call fusions and to confirm the DNA variants or exonic alterations. Here, we present our results and WGTS standards for variant allele frequency, reproducibility, analytical sensitivity, and present limit of detection analysis for single nucleotide variant calling, copy number identification, and structural variants. We show that The New York Genome Center WGTS clinical assay can provide a comprehensive patient variant discovery approach suitable for directed oncologic therapeutic applications.

Reliable detection of somatic variations is of critical importance in cancer research. Here we present Lancet, an accurate and sensitive somatic variant caller, which detects SNVs and indels by jointly analyzing reads from tumor and matched normal samples using colored de Bruijn graphs. We demonstrate, through extensive experimental comparison on synthetic and real whole-genome sequencing datasets, that Lancet has better accuracy, especially for indel detection, than widely used somatic callers, such as MuTect, MuTect2, LoFreq, Strelka, and Strelka2. Lancet features a reliable variant scoring system, which is essential for variant prioritization, and detects low-frequency mutations without sacrificing the sensitivity to call longer insertions and deletions empowered by the local-assembly engine. In addition to genome-wide analysis, Lancet allows inspection of somatic variants in graph space, which augments the traditional read alignment visualization to help confirm a variant of interest. Lancet is available as an open-source program at https://github.com/nygenome/lancet.

Reliable detection of somatic variations is of critical importance in cancer research. Lancet is an accurate and sensitive somatic variant caller which detects SNVs and indels by jointly analyzing reads from tumor and matched normal samples using colored DeBruijn graphs. Extensive experimental comparison on synthetic and real whole-genome sequencing datasets demonstrates that Lancet has better accuracy, especially for indel detection, than widely used somatic callers, such as MuTect, MuTect2, LoFreq, Strelka, and Strelka2. Lancet features a reliable variant scoring system which is essential for variant prioritization and detects low frequency mutations without sacrificing the sensitivity to call longer insertions and deletions empowered by the local assembly engine. In addition to genome-wide analysis, Lancet allows inspection of somatic variants in graph space, which augments the traditional read alignment visualization to help confirm a variant of interest. Lancet is available as an open-source program at https://github.com/nygenome/lancet.

Genomic rearrangements are a hallmark of human cancers. Here, we identify the piggyBac transposable element derived 5 (PGBD5) gene as an active DNA transposase expressed in the majority of childhood solid tumors, including lethal rhabdoid tumors. Using assembly-based whole-genome DNA sequencing, we found previously undefined genomic rearrangements in human rhabdoid tumors. These rearrangements involved PGBD5-specific signal (PSS) sequences at their breakpoints, recurrently inactivating tumor suppressor genes. PGBD5 was physically associated with genomic PSS sequences that were also sufficient to mediate PGBD5-induced DNA rearrangements in rhabdoid tumor cells. Ectopic expression of PGBD5 in primary immortalized human cells was sufficient to promote cell transformation in vivo. This activity required specific catalytic residues in the PGBD5 transposase domain, as well as end-joining DNA repair, and induced structural rearrangements with PSS breakpoints. This defines PGBD5 as an oncogenic mutator and provides a plausible mechanism for site-specific DNA rearrangements in childhood and adult solid tumors.

Survival for children with acute myeloid leukemia (AML) remains low, with a primary induction remission failure rate of 10-15%. Although some mutations have been identified that are associated with increased relapse risk, the genomic landscape of pediatric AML resistant to primary chemotherapy is not well characterized. As part of the TARGET initiative (Therapeutically Applicable Research To Generate Effective Treatments), we assembled a cohort of 28 pediatric AML patients with primary chemotherapy resistance and failure of induction chemotherapy, uniformly treated as part of the COG AAML0531 study. We analyzed whole-genome DNA, mRNA, and miRNA sequence data obtained at diagnosis and after induction chemotherapy. At least three genetically distinct groups were apparent in this cohort, including those with NUP98 rearrangements, somatic mutations of WT1 in the absence of NUP98 variants, and additional recurrent variants including those in KMT2C and MLLT10. Comparisons of mutations before and after chemotherapy revealed both common and distinct gene expression programs. On chemotherapy exposure, these leukemias exhibited diverse forms of clonal evolution. We observed selection for mutant alleles of FRMD8, DHX32, PIK3R1, SHANK3, MKLN1, as well as persistence of WT1 and TP53 mutant clones, and elimination or contraction of FLT3, PTPN11, and NRAS mutant clones. These findings suggest diverse genetic mechanisms for primary chemotherapy resistance in pediatric AML, which should guide new approaches for its diagnosis and therapy. Citation Format: Nicole McNeer, John Philip, Heather Geiger, Rhonda E. Ries, Vincent-Philippe Lavallee, Michael Walsh, Minita Shah, Kanika Arora, Anne-Katrin Emde, Nicolas Robine, Todd A. Alonzo, E. Anders Kolb, Alan S. Gamis, Malcom Smith, Daniela Se Gerhard, Jaime Guidry-Auvil, Soheil Meshinchi, Alex Kentsis. Genetic mechanisms of primary chemotherapy resistance in pediatric acute myeloid leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2870.

Oncogenic Suspect Exposed It can be difficult logistically to study the genomics of rare variants of common cancers. Nevertheless, Honeyman et al. (p. 1010 ) studied fibrolamellar hepatocellular carcinoma (FL-HCC), a rare and poorly understood liver tumor that affects adolescents and young adults and for which there is no effective treatment. FL-HCCs from 15 patients all expressed a chimeric RNA transcript and protein containing sequences from a molecular chaperone fused in frame with sequences from the catalytic domain of protein kinase A. The chimeric protein retained kinase activity in vitro. Such recurrent gene fusions in cancer may signal a role in pathogenesis and provide an opportunity for therapeutic intervention.

Genomic rearrangements are a hallmark of childhood solid tumors, but their mutational causes remain poorly understood. Here, we identify the piggyBac transposable element derived 5 (PGBD5) gene as an enzymatically active human DNA transposase expressed in the majority of rhabdoid tumors, a lethal childhood cancer. Using assembly-based whole-genome DNA sequencing, we observed previously unknown somatic genomic rearrangements in primary human rhabdoid tumors. These rearrangements were characterized by deletions and inversions involving PGBD5-specific signal (PSS) sequences at their breakpoints, with some recurrently targeting tumor suppressor genes, leading to their inactivation. PGBD5 was found to be physically associated with human genomic PSS sequences that were also sufficient to mediate PGBD5-induced DNA rearrangements in rhabdoid tumor cells. We found that ectopic expression of PGBD5 in primary immortalized human cells was sufficient to promote penetrant cell transformation in vitro and in immunodeficient mice in vivo. This activity required specific catalytic residues in the PGBD5 transposase domain, as well as end-joining DNA repair, and induced distinct structural rearrangements, involving PSS-associated breakpoints, similar to those found in primary human rhabdoid tumors. This defines PGBD5 as an oncogenic mutator and provides a plausible mechanism for site-specific DNA rearrangements in childhood and adult solid tumors.

Purpose Patients with cancer who graciously consent for autopsy represent an invaluable resource for the study of cancer biology. To advance the study of tumor evolution, metastases, and resistance to treatment, we developed a next-generation rapid autopsy program integrated within a broader precision medicine clinical trial that interrogates pre- and postmortem tissue samples for patients of all ages and cancer types. Materials and Methods One hundred twenty-three (22%) of 554 patients who consented to the clinical trial also consented for rapid autopsy. This report comprises the first 15 autopsies, including patients with metastatic carcinoma (n = 10), melanoma (n = 1), and glioma (n = 4). Whole-exome sequencing (WES) was performed on frozen autopsy tumor samples from multiple anatomic sites and on non-neoplastic tissue. RNA sequencing (RNA-Seq) was performed on a subset of frozen samples. Tissue was also used for the development of preclinical models, including tumor organoids and patient-derived xenografts. Results Three hundred forty-six frozen samples were procured in total. WES was performed on 113 samples and RNA-Seq on 72 samples. Successful cell strain, tumor organoid, and/or patient-derived xenograft development was achieved in four samples, including an inoperable pediatric glioma. WES data were used to assess clonal evolution and molecular heterogeneity of tumors in individual patients. Mutational profiles of primary tumors and metastases yielded candidate mediators of metastatic spread and organotropism including CUL9 and PIGM in metastatic ependymoma and ANKRD52 in metastatic melanoma to the lung. RNA-Seq data identified novel gene fusion candidates. Conclusion A next-generation sequencing–based autopsy program in conjunction with a premortem precision medicine pipeline for diverse tumors affords a valuable window into clonal evolution, metastasis, and alterations underlying treatment. Moreover, such an autopsy program yields robust preclinical models of disease.

Objective:To analyze a glioblastoma tumor specimen with 3 different platforms and compare potentially actionable calls from each.Methods:Tumor DNA was analyzed by a commercial targeted panel. In addition, tumor-normal DNA was analyzed by whole-genome sequencing (WGS) and tumor RNA was analyzed by RNA sequencing (RNA-seq). The WGS and RNA-seq data were analyzed by a team of bioinformaticians and cancer oncologists, and separately by IBM Watson Genomic Analytics (WGA), an automated system for prioritizing somatic variants and identifying drugs.Results:More variants were identified by WGS/RNA analysis than by targeted panels. WGA completed a comparable analysis in a fraction of the time required by the human analysts.Conclusions:The development of an effective human-machine interface in the analysis of deep cancer genomic datasets may provide potentially clinically actionable calls for individual patients in a more timely and efficient manner than currently possible.ClinicalTrials.gov identifier:NCT02725684.

Genomic rearrangements are a hallmark of human cancers. Here, we identify the piggyBac transposable element derived 5 (PGBD5) gene as encoding an active DNA transposase expressed in the majority of childhood solid tumors, including lethal rhabdoid tumors. Using assembly-based whole-genome DNA sequencing, we found previously undefined genomic rearrangements in human rhabdoid tumors. These rearrangements involved PGBD5-specific signal (PSS) sequences at their breakpoints and recurrently inactivated tumor-suppressor genes. PGBD5 was physically associated with genomic PSS sequences that were also sufficient to mediate PGBD5-induced DNA rearrangements in rhabdoid tumor cells. Ectopic expression of PGBD5 in primary immortalized human cells was sufficient to promote cell transformation in vivo. This activity required specific catalytic residues in the PGBD5 transposase domain as well as end-joining DNA repair and induced structural rearrangements with PSS breakpoints. These results define PGBD5 as an oncogenic mutator and provide a plausible mechanism for site-specific DNA rearrangements in childhood and adult solid tumors.

Importance Understanding molecular mechanisms of response and resistance to anticancer therapies requires prospective patient follow-up and clinical and functional validation of both common and low-frequency mutations. We describe a whole-exome sequencing (WES) precision medicine trial focused on patients with advanced cancer. Objective To understand how WES data affect therapeutic decision making in patients with advanced cancer and to identify novel biomarkers of response. Design, Setting, and Patients Patients with metastatic and treatment-resistant cancer were prospectively enrolled at a single academic center for paired metastatic tumor and normal tissue WES during a 19-month period (February 2013 through September 2014). A comprehensive computational pipeline was used to detect point mutations, indels, and copy number alterations. Mutations were categorized as category 1, 2, or 3 on the basis of actionability; clinical reports were generated and discussed in precision tumor board. Patients were observed for 7 to 25 months for correlation of molecular information with clinical response. Main Outcomes and Measures Feasibility, use of WES for decision making, and identification of novel biomarkers. Results A total of 154 tumor-normal pairs from 97 patients with a range of metastatic cancers were sequenced, with a mean coverage of 95X and 16 somatic alterations detected per patient. In total, 16 mutations were category 1 (targeted therapy available), 98 were category 2 (biologically relevant), and 1474 were category 3 (unknown significance). Overall, WES provided informative results in 91 cases (94%), including alterations for which there is an approved drug, there are therapies in clinical or preclinical development, or they are considered drivers and potentially actionable (category 1-2); however, treatment was guided in only 5 patients (5%) on the basis of these recommendations because of access to clinical trials and/or off-label use of drugs. Among unexpected findings, a patient with prostate cancer with exceptional response to treatment was identified who harbored a somatic hemizygous deletion of the DNA repair gene FANCA and putative partial loss of function of the second allele through germline missense variant. Follow-up experiments established that loss of FANCA function was associated with platinum hypersensitivity both in vitro and in patient-derived xenografts, thus providing biologic rationale and functional evidence for his extreme clinical response. Conclusions and Relevance The majority of advanced, treatment-resistant tumors across tumor types harbor biologically informative alterations. The establishment of a clinical trial for WES of metastatic tumors with prospective follow-up of patients can help identify candidate predictive biomarkers of response.

Genomic rearrangements are a hallmark of childhood solid tumors, but their mutational causes remain poorly understood. Here, we identify the piggyBac transposable element derived 5 (PGBD5) gene as an enzymatically active human DNA transposase expressed in the majority of rhabdoid tumors, a lethal childhood cancer. Using assembly-based whole-genome DNA sequencing, we observed previously unknown somatic genomic rearrangements in primary human rhabdoid tumors. These rearrangements were characterized by deletions and inversions involving PGBD5-specific signal (PSS) sequences at their breakpoints, with some recurrently targeting tumor suppressor genes, leading to their inactivation. PGBD5 was found to be physically associated with human genomic PSS sequences that were also sufficient to mediate PGBD5-induced DNA rearrangements in rhabdoid tumor cells. We found that ectopic expression of PGBD5 in primary human cells was sufficient to promote penetrant cell transformation in vitro and in immunodeficient mice in vivo. This activity required specific catalytic residues in the PGBD5 transposase domain, as well as end-joining DNA repair, and induced distinct structural rearrangements, involving PSS-associated breakpoints, similar to those found in primary human rhabdoid tumors. Thus, PGBD5 defines a distinct class of oncogenic mutators and induces site-specific somatic DNA rearrangements in human cancer. Citation Format: Anton G. Henssen, Richard Koche, Jiali Zhuang, Eileen Jiang, Casie Reed, Amy Eisenberg, Eric Still, Elias Rodríguez-Fos, Santiago Gonzalez, Montserrat Puiggròs, Andrew N. Blackford, Christopher E. Mason, Elisa de Stanchina, Mithat Gönen, Anne-Katrin Emde, Minita Shah, Kanika Arora, Catherine Reeves, Nicholas D. Socci, Elizabeth Perlman, Cristina R. Antonescu, Charles W. Roberts, Hanno Steen, Elizabeth Mullen, Stephen P. Jackson, David Torrents, Zhiping Weng, Scott A. Armstrong, Alex Kentsis. Human PGBD5 DNA transposase promotes site-specific oncogenic mutations in rhabdoid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4888. doi:10.1158/1538-7445.AM2017-4888

Next Generation DNA Sequencing (NGS) technologies are currently being applied in the clinical setting for the treatment of disease. The goal is to use high-throughput sequencing to identify specific variants within each tumor and recommend personalized treatment approaches or clinical trials tailored to the individual’s disease and genomic profile. These assays are comprised of either predefined sequencing panels, where a handpicked set of clinically significant genes are examined within each patient, or are cancer type specific targeted sequencing protocols or whole exome platforms covering only the coding region of the patient’s genome. Whole genome sequencing allows hypothesis-free interrogation of both coding and non-coding regions of the genome revealing more potential therapeutic options than examining a small set of genes or genomic loci. The protocol eliminates sequence capture related bias observed in whole exome or panel sequencing. The New York Genome Center therefore has performed analytical validation of whole genome and transcriptome sequencing (WGTS) of patient derived tumors and matched normals for the purposes of clinical testing and have devised a clinical reporting strategy of significant driver and therapeutic associated mutations. Many clinical NGS guidelines are directed toward targeted panel or exome sequencing validation. Here, we expanded on New York State’s Department of Health NGS guidelines developing them into novel standards applicable to WGTS for the purposes of clinical test validation. We first sequenced a virtual tumor at very high coverage (300x) and downsampled to determine the optimum depth of sequencing necessary for high confidence somatic variant calling across the entire genome. We then validated whole genome sequencing laboratory protocols for DNA and RNA sequencing on a total of 50 specimens derived from fresh frozen (FF) and formalin-fixed paraffin-embedded (FFPE) tumor samples. We performed a series of experiments to assess the accuracy and reliability of the results based on our laboratory and bioinformatics protocols. We performed our validation on the 50 tumor normal pairs, a subset of which had known genomic profiles. Comparisons were also made for variant calling concordance and reproducibility between matched FF and FFPE tumors. Here, we present our validation results and clinical WGTS standards for depth of sequencing, reproducibility, sensitivity, and present limit of detection analysis for SNV calling, copy number identification and structural variants. RNA sequencing is performed to call fusion or exon skipping events and to confirm the DNA variants. The New York Genome Center WGTS clinical assay is intended to provide a more comprehensive patient variant discovery approach suitable for directed oncological therapeutic applications. Citation Format: Kazimierz O. Wrzeszczynski, Avinash Abhyankar, Vanessa Felice, Esra Dikoglu, Lukasz Kozon, Nicolas Robine, Anne-Katrin Emde, Olca Basturk, Umesh K. Bhanot, Alex Kentsis, Mahesh Mansukhani, Govind Bhagat, Vaidehi Jobanputra. Analytical validation of clinical whole genome and transcriptome sequencing of patient derived tumors: clinical application of whole genome sequencing for reporting targetable variants in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2714. doi:10.1158/1538-7445.AM2017-2714

Background Colorectal cancer is the second leading cause of cancer death in the United States, with over 50,000 deaths estimated in 2014. Molecular profiling for somatic mutations that predict absence of response to anti-EGFR therapy has become standard practice in the treatment of metastatic colorectal cancer; however, the quantity and type of tissue available for testing is frequently limited. Further, the degree to which the primary tumor is a faithful representation of metastatic disease has been questioned. As next-generation sequencing technology becomes more widely available for clinical use and additional molecularly targeted agents are considered as treatment options in colorectal cancer, it is important to characterize the extent of tumor heterogeneity between primary and metastatic tumors. Results We performed deep coverage, targeted next-generation sequencing of 230 key cancer-associated genes for 69 matched primary and metastatic tumors and normal tissue. Mutation profiles were 100% concordant for KRAS, NRAS, and BRAF, and were highly concordant for recurrent alterations in colorectal cancer. Additionally, whole genome sequencing of four patient trios did not reveal any additional site-specific targetable alterations. Conclusions Colorectal cancer primary tumors and metastases exhibit high genomic concordance. As current clinical practices in colorectal cancer revolve around KRAS, NRAS, and BRAF mutation status, diagnostic sequencing of either primary or metastatic tissue as available is acceptable for most patients. Additionally, consistency between targeted sequencing and whole genome sequencing results suggests that targeted sequencing may be a suitable strategy for clinical diagnostic applications. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0454-7) contains supplementary material, which is available to authorized users.

Current adjuvant therapeutic options for the treatment of Glioblastoma (GBM) are often determined by limited histological information. Additionally, most GBM clinical trials for targeted chemotherapeutic agents do not distinguish the genetic mutational tumor profiles of the patients recruited and have failed to reach successful treatment endpoints. The New York Genome Center (NYGC) has undertaken a glioblastoma clinical sequencing outcome pilot study to better determine personal treatment options for patients with GBM using integrated genomic data. During the initial phase of this study for 2015 NYGC has performed whole genome sequencing (WGS) on 10 primary GBM tumor-normal pairs, analyzed each patient's tumor for single nucleotide variants, structural variants and copy number alterations. In addition RNA sequencing and a DNA methylation assay were also performed on several of the patients. The patient's genomic profile was then compared to a database of known targeted therapeutic approaches. A final tumor board composed of NYGC scientists, GBM consortium scientists and treating oncologists then reviewed all data prior to identifying a final therapeutic strategy. Data from the first 10 patients revealed RB1 variants to be predominant in half of the patients. SNV's in NF1 or PIK3R1 were also discovered in 4 out of 10 samples. Remaining lower frequency variants occurred in TP53, PDGFRA, PTEN, PIK3CA, ERBB3, SMO, STAG2, ACVR1, NFKB1 and JAK3. Analysis of copy number alterations resulted in 8 of 10 patients containing the characteristic chromosome 7 amplification combined with chromosome 10 deletion, affecting EGFR and PTEN, respectively. Extreme amplification with potential double minute structural variation of EGFR containing the A289V mutation was observed in 2 of 10 samples. Two samples contained a potentially targetable over-amplification of the PDGFRA/KIT/KDR chromosome 4 locus. Predominant deletions resided in CDKN2A, ESR2, PTEN and FLT3. Hemizygous deletions of RB1 combined with RB1 nonsense or missense variants were observed in 4 samples. To date, RNA sequencing was performed on 5 patient samples. Most strikingly the combination of DNA and RNA sequencing revealed the presence of a putative activating MET exon skipping event in the extracellular domain. This MET variant was considered as a potential targetable variant. Therapeutic options resulting from WGS genomic profiles were the PI3K inhibitor BKM120 (60%), half of these had an additional aberration in MET and were recommended for the combinatorial trial NCT01870726. Drug recommendations for the treatment of GBM based on specific N = 1 patient genomic profiles were also made for nilotinib, vismodegib and palbociclib. Here, we present the first phase of the NYGC GBM clinical outcome study demonstrating how patient WGS information can provide more precise therapeutic options in the treatment of glioblastoma. Citation Format: Kazimierz O. Wrzeszczynski, Nicolas Robine, Vladimir Vacic, Anne-Katrin Emde, Bo-Juen Chen, Will Liao, Kanika Arora, Minita Shah, Ewa A. Grabowska, Vanessa Felice, Esra Dikoglu, Catherine Reeves, Mayu Frank, Vaidehi Jobanputra, Michael C. Zody, Toby Bloom, Robert B. Darnell. NYGC glioblastoma clinical outcomes pilot study: Discovering therapeutic potential in glioblastoma through integrative genomics. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4497.

Whole genome and targeted sequencing data have just started to revolutionize clinical care for cancer patients. Based on genetic variants in each tumor, clinicians can tailor treatment options for patients. While genomic sequencing data provide the landscapes of genetic variants, RNA-seq data can provide complementary information and allow us to interpret the functional effects of discovered variants. However, N-of-1 analysis with RNA-seq data poses several challenges, including integration with DNA data and normalization of gene expression. To tackle these challenges, we developed RNA analytics for integrative analysis for tumor samples in a clinical setting. For variant analysis, we use RNA to validate somatic variants (both SNVs and indels) and to elucidate potential functional effects of the variants. Because RNA-seq has different coverage patterns from WGS, we developed tools to calculate and compare variant allele frequency in both DNA and RNA data, which allows us to validate variants and evaluate allelic expression. Additionally, leveraging on RNA-seq, our tools look for evidence of aberrant splicing events, such as exon skipping and intron retention that are caused by genetic variants. These analyses not only provide an integrative view of the data, but also prioritize variants and potentially reveal variant effects. Because many cancers are driven by fusion genes and some fusion genes are recurrent in GBM, we use our data to detect gene fusion supported by RNA-Seq, and if possible by WGS. We use FusionCatcher and STAR-Fusion, coupled with OncoFuse to discover and annotate fusions in RNA-Seq. We subsequently look for supporting evidence by any of the structural variant callers we use. Gene expression quantification is most valuable as a comparative measurement. However, this is challenging for N-of-1 analysis, since such assessment requires proper normalization and comparison to a proper cohort. Batch-effects due to library preparation and other covariates exacerbate the issue of normalization. We tackle this issue with various normalization and correction strategies. Utilizing GC-bias correction, batch-effect adjustment, and public datasets, our analytic provides gene expression measurement that allows researcher to interpret whether the gene is up- or down-regulated compared to a cohort (such as TCGA). Our RNA analytics comprehensively utilize transcriptomic data and provides solutions to integrative analysis. We have applied our tools to sequence data from five glioblastoma patients and showed how RNA-seq can compliment WGS. Our integrative analysis helps identify an exon-skipping event in MET in one patient, which was validated with Sanger sequencing. The expression analysis also helps identify potential aberrant activity of the SMO pathway, possibly driven by a SMO missense mutation and loss of SUFU. Citation Format: Bo-Juen R. Chen, Nicolas Robine, Kazimierz Wrzeszczynski, Vladimir Vacic, Anne Katrin Emde, Kanika Arora, Minita Shah, Ewa A. Grabowska, Vanessa Felice, Esra Dikoglu, Catherine Reeves, Mayu Frank, Vaidehi Jobanputra, Michael C. Zody, Toby Bloom, Robert Darnell. RNA-Seq in the NYGC GBM Clinical Outcomes Pilot Study. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4498.

Motivation: The reliable detection of genomic variation in resequencing data is still a major challenge, especially for variants larger than a few base pairs. Sequencing reads crossing boundaries of structural variation carry the potential for their identification, but are difficult to map. Results: Here we present a method for ‘split’ read mapping, where prefix and suffix match of a read may be interrupted by a longer gap in the read-to-reference alignment. We use this method to accurately detect medium-sized insertions and long deletions with precise breakpoints in genomic resequencing data. Compared with alternative split mapping methods, SplazerS significantly improves sensitivity for detecting large indel events, especially in variant-rich regions. Our method is robust in the presence of sequencing errors as well as alignment errors due to genomic mutations/divergence, and can be used on reads of variable lengths. Our analysis shows that SplazerS is a versatile tool applicable to unanchored or single-end as well as anchored paired-end reads. In addition, application of SplazerS to targeted resequencing data led to the interesting discovery of a complete, possibly functional gene retrocopy variant. Availability: SplazerS is available from http://www.seqan.de/projects/ splazers. Contact: emde@inf.fu-berlin.de Supplementary information: Supplementary data are available at Bioinformatics online.

Motivation: Deep sequencing has become the method of choice for determining the small RNA content of a cell. Mapping the sequenced reads onto their reference genome serves as the basis for all further analyses, namely for identification and quantification. A method frequently used is Mega BLAST followed by several filtering steps, even though it is slow and inefficient for this task. Also, none of the currently available short read aligners has established itself for the particular task of small RNA mapping. Results: We present MicroRazerS, a tool optimized for mapping small RNAs onto a reference genome. It is an order of magnitude faster than Mega BLAST and comparable in speed with other short read mapping tools. In addition, it is more sensitive and easy to handle and adjust. Availability: MicroRazerS is part of the SeqAn C++ library and can be downloaded from http://www.seqan.de/projects/MicroRazerS.html. Contact: emde@inf.fu-berlin.de; grunert@molgen.mpg.de

Second-generation sequencing technologies deliver DNA sequence data at unprecedented high throughput. Common to most biological applications is a mapping of the reads to an almost identical or highly similar reference genome. Due to the large amounts of data, efficient algorithms and implementations are crucial for this task. We present an efficient read mapping tool called RazerS. It allows the user to align sequencing reads of arbitrary length using either the Hamming distance or the edit distance. Our tool can work either lossless or with a user-defined loss rate at higher speeds. Given the loss rate, we present an approach that guarantees not to lose more reads than specified. This enables the user to adapt to the problem at hand and provides a seamless tradeoff between sensitivity and running time. [RazerS is freely available at http://www.seqan.de/projects/razers.html.]

Motivation: Novel high-throughput sequencing technologies pose new algorithmic challenges in handling massive amounts of short-read, high-coverage data. A robust and versatile consensus tool is of particular interest for such data since a sound multi-read alignment is a prerequisite for variation analyses, accurate genome assemblies and insert sequencing. Results: A multi-read alignment algorithm for de novo or reference-guided genome assembly is presented. The program identifies segments shared by multiple reads and then aligns these segments using a consistency-enhanced alignment graph. On real de novo sequencing data obtained from the newly established NCBI Short Read Archive, the program performs similarly in quality to other comparable programs. On more challenging simulated datasets for insert sequencing and variation analyses, our program outperforms the other tools. Availability: The consensus program can be downloaded from http://www.seqan.de/projects/consensus.html. It can be used stand-alone or in conjunction with the Celera Assembler. Both application scenarios as well as the usage of the tool are described in the documentation. Contact: rausch@inf.fu-berlin.de

Motivation: Many multiple sequence alignment tools have been developed in the past, progressing either in speed or alignment accuracy. Given the importance and wide-spread use of alignment tools, progress in both categories is a contribution to the community and has driven research in the field so far. Results: We introduce a graph-based extension to the consistency-based, progressive alignment strategy. We apply the consistency notion to segments instead of single characters. The main problem we solve in this context is to define segments of the sequences in such a way that a graph-based alignment is possible. We implemented the algorithm using the SeqAn library and report results on amino acid and DNA sequences. The benefit of our approach is threefold: (1) sequences with conserved blocks can be rapidly aligned, (2) the implementation is conceptually easy, generic and fast and (3) the consistency idea can be extended to align multiple genomic sequences. Availability: The segment-based multiple sequence alignment tool can be downloaded from http://www.seqan.de/projects/msa.html. A novel version of T-Coffee interfaced with the tool is available from http://www.tcoffee.org. The usage of the tool is described in both documentations. Contact: rausch@inf.fu-berlin.de

Detection and characterization of somatic structural variants (SVs) and copy-number variants (CNVs) from whole genome sequencing remains a challenging part of cancer analysis. Many callers have been developed that use different detection strategies, but most methods suffer from high rates of false positives and false negatives, and agreement between different callers is usually low. We have developed a flexible pipeline that combines the results of multiple callers, filters calls to remove likely artifacts, and functionally annotates the resulting variants. We employ a diverse set of variant callers utilizing a combination of read depth, read pair, and split read detection methods: NBIC-seq (Xi et al., 2011), Crest (Wang et al., 2011), Delly (Rausch et al., 2012), and BreakDancer (Chen et al., 2009). To remove artifact calls due to mis-mapping, we apply filters that discard predicted SVs whose breakpoints exhibit certain sequence features (e.g. extensive mapping ambiguity, high repeat content). SVs corresponding to known germline variants (1000G, DGV, in-house database) are marked and removed as unlikely somatic variants: this greatly helps to prevent both sequencing protocol- and caller-specific artifacts as well as false positive somatic calls arising from missed calls in the matched germline sample. Finally, we employ our sensitive split read mapper SplazerS to identify SV breakpoints with base pair precision. In this step, we are also able to remove remaining germline variants for which we find split read support in the matched normal sample. The final predicted structural variants are annotated for overlap with SVs in COSMIC, overlap with known cancer genes and potential impact on gene structure. We use a public synthetic data set (DREAM challenge; Boutros et al., 2014) to demonstrate that using our selected ensemble of tools significantly improves sensitivity as compared to any single caller and that our filters effectively remove artifacts. Further, we show results from a set of colorectal cancer samples (Brannon et al., 2014) in which highly similar primary and metastatic tumors show excellent agreement in somatic SV calls in the absence of overlap between unrelated samples. Results from testing our pipeline on TCGA glioblastoma multiforme tumors, for which validated genomic rearrangements are available, will also be presented. In conclusion, our pipeline improves detection of SVs by integrating orthogonal calling methods and facilitates identification of clinically relevant SVs through effective filters and cancer-specific functional annotation. Citation Format: Minita Shah, Dayna M. Oschwald, Soren Germer, Michael C. Zody, Toby Bloom, Anne-Katrin Emde. An integrated pipeline for detecting and characterizing structural variation in cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4876. doi:10.1158/1538-7445.AM2015-4876

Background The elemental composition of peptides results in formation of distinct, equidistantly spaced clusters across the mass range. The property of peptide mass clustering is used to calibrate peptide mass lists, to identify and remove non-peptide peaks and for data reduction.