Large-scale Sequencing Projects Research Articles

Modeling cancer driver events in vitro using barrier bypass-clonal expansion assays and massively parallel sequencing

The information on candidate cancer driver alterations available from public databases is often descriptive and of limited mechanistic insight, which poses difficulties for reliable distinction between true driver and passenger events. To address this challenge, we performed in-depth analysis of whole-exome sequencing data from cell lines generated by a barrier bypass-clonal expansion (BBCE) protocol. The employed strategy is based on carcinogen-driven immortalization of primary mouse embryonic fibroblasts and recapitulates early steps of cell transformation. Among the mutated genes were almost 200 COSMIC Cancer Gene Census genes, many of which were recurrently affected in the set of 25 immortalized cell lines. The alterations affected pathways regulating DNA damage response and repair, transcription and chromatin structure, cell cycle and cell death, as well as developmental pathways. The functional impact of the mutations was strongly supported by the manifestation of several known cancer hotspot mutations among the identified alterations. We identified a new set of genes encoding subunits of the BAF chromatin remodeling complex that exhibited Ras-mediated dependence on PRC2 histone methyltransferase activity, a finding that is similar to what has been observed for other BAF subunits in cancer cells. Among the affected BAF complex subunits, we determined Smarcd2 and Smarcc1 as putative driver candidates not yet fully identified by large-scale cancer genome sequencing projects. In addition, Ep400 displayed characteristics of a driver gene in that it showed a mutually exclusive mutation pattern when compared with mutations in the Trrap subunit of the TIP60 complex, both in the cell line panel and in a human tumor data set. We propose that the information generated by deep sequencing of the BBCE cell lines coupled with phenotypic analysis of the mutant cells can yield mechanistic insights into driver events relevant to human cancer development.

Genomic profiling using a 435-gene panel provides a vision for precision medicine in Japanese gastric cancer.

e15592 Background: Molecular heterogeneity represents a significant hurdle in realizing precision medicine for gastric cancer (GC). Large-scale whole exome sequencing projects have identified distinct molecular subtypes to help define the heterogeneity of GC. However, it remains unclear whether the targeted gene panel-based sequencing can provide optimum targeted therapies and clinical utility in GC. The aim of this study is to generate comprehensive genomic profiling data and classify Japanese GC into actionable clusters associated with targeted therapies. Methods: FFPE tumor tissues were obtained from surgical or biopsy specimens of 207 Japanese patients with GC. Extracted DNA was subjected to genomic sequencing for 435 cancer related genes including 69 druggable genes with FDA approved targeted therapies. Somatic mutations, copy number alterations (SCNA), microsatellite instability (MSI) and Epstein-Barr virus (EBV) infection were evaluated using sequencing data. Results: Genomic sequencing identified at least one alteration of 435 genes in 194 pts (94%), and that of 69 druggable genes in 141 pts (68%). The most frequently altered druggable gene was ERBB2 (14%), following BRCA2 (11%) and ATM (10%). We successfully classified 207 tumors into four molecular subtypes, similar to the previously report; EBV (4%), MSI (8%), chromosomal instability (58%) and genomically stable subtype (30%). Frequent alterations of druggable genes ( > 5%) were widely observed through these subtypes. To discover the novel classifications associated with targeted therapies, we classified 207 tumors using mutation rate and hierarchical clustering. We identified a hypermutated group (n = 32), and a remaining non-hypermutated group (n = 175) which were sub-divided into six clusters including five actionable ones; ERBB2 (n = 25), CDKN2A and CDKN2B (n = 10), KRAS (n = 10), BRCA2 (n = 9) and ATM cluster (n = 12). Interestingly, we experienced a case of unresectable GC with a remarkable response for anti-HER2 therapy in the ERBB2 cluster. Conclusions: Genomic sequencing using a 435-gene panel has the potential to provide the information of optimum targeted therapies for upcoming precision medicine in Japanese GC.

Pancreatic Cancer Genomes: Implications for Clinical Management and Therapeutic Development.

Pancreatic cancer has become the third leading cause of cancer-related death, with little improvement in outcomes despite decades of research. Surgery remains the only chance of cure, yet only 20% of patients will be alive at 5 years after pancreatic resection. Few chemotherapeutics provide any improvement in outcome, and even then, for approved therapies, the survival benefits are marginal. Genomic sequencing studies of pancreatic cancer have revealed a small set of consistent mutations found in most pancreatic cancers and beyond that, a low prevalence for targetable mutations. This may explain the failure of conventional clinical trial designs to show any meaningful survival benefit, except in small and undefined patient subgroups. With the development of next-generation sequencing technology, genomic sequencing and analysis can be performed in a clinically meaningful turnaround time. This can identify therapeutic targets in individual patients and personalize treatment selection. Incorporating preclinical discovery and molecularly guided therapy into clinical trial design has the potential to significantly improve outcomes in this lethal malignancy. In this review, we discuss the findings of recent large-scale genomic sequencing projects in pancreatic cancer and the potential relevance of these data to therapeutic development. Clin Cancer Res; 23(7); 1638-46. ©2017 AACRSee all articles in this CCR Focus section, "Pancreatic Cancer: Challenge and Inspiration."

DNA Compass: a secure, client-side site for navigating personal genetic information.

MotivationMillions of individuals have access to raw genomic data using direct-to-consumer companies. The advent of large-scale sequencing projects, such as the Precision Medicine Initiative, will further increase the number of individuals with access to their own genomic information. However, querying genomic data requires a computer terminal and computational skill to analyze the data—an impediment for the general public.ResultsDNA Compass is a website designed to empower the public by enabling simple navigation of personal genomic data. Users can query the status of their genomic variants for over 1658 markers or tens of millions of documented single nucleotide polymorphisms (SNPs). DNA Compass presents the relevant genotypes of the user side-by-side with explanatory scientific resources. The genotype data never leaves the user’s computer, a feature that provides improved security and performance. More than 12 000 unique users, mainly from the general genetic genealogy community, have already used DNA Compass, demonstrating its utility.Availability and ImplementationDNA Compass is freely available on https://compass.dna.land.

Abstract CS1-1: The genomics of metastatic breast cancer: What are we learning?

Abstract Over the past decade, genomic characterization of tumors from cancer patients obtained through large-scale sequencing projects has shed enormous light on the molecular underpinnings of cancer. These discoveries have, in turn, led to the development of novel therapies and preventive measures that have already revolutionized cancer care. Despite this tremendous progress, our understanding of the genomics of metastatic breast cancer – and in particular cancers that have developed resistance to therapies – remains incomplete. In this presentation, we will discuss recent and ongoing studies that focus on the genomics of metastatic breast cancer, and how the learnings from these studies are influencing precision medicine strategies for patients with advanced breast cancer. We will focus on how genomic and molecular characterization of metastatic tumor samples from patients can shed light on the biology of metastatic breast cancer and can enable the development of strategies to overcome or prevent drug resistance. We will discuss the landscape of mutations in metastatic breast cancer, the potential clinical impact of genomic profiling, and the incorporation of genomic information into clinical care and clinical trials. We will also discuss how partnering directly with patients, in projects such as The Metastatic Breast Cancer Project (mbcproject.org), enables rapid identification of large numbers of patients willing to share tumors, saliva, and medical records to accelerate this research. Citation Format: Wagle N. The genomics of metastatic breast cancer: What are we learning? [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr CS1-1.

Assessment of Whole-Exome Sequence Data in Attempted Suicide within a Bipolar Disorder Cohort

Suicidal behavior is a complex and devastating phenotype with a heritable component that has not been fully explained by existing common genetic variant analyses. This study represents the first large-scale DNA sequencing project designed to assess the role of rare functional genetic variation in suicidal behavior risk. To accomplish this, whole-exome sequencing data for ∼19,000 genes were generated for 387 bipolar disorder subjects with a history of suicide attempt and 631 bipolar disorder subjects with no prior suicide attempts. Rare functional variants were assessed in all exome genes as well as pathways hypothesized to contribute to suicidal behavior risk. No result survived conservative Bonferroni correction, though many suggestive findings have arisen that merit additional attention. In addition, nominal support for past associations in genes, such as BDNF, and pathways, such as the hypothalamic-pituitary-adrenal axis, was also observed. Finally, a novel pathway was identified that is driven by aldehyde dehydrogenase genes. Ultimately, this investigation explores variation left largely untouched by existing efforts in suicidal behavior, providing a wealth of novel information to add to future investigations, such as meta-analyses.

De Novo Mutations in EBF3 Cause a Neurodevelopmental Syndrome

Early B cell factor 3 (EBF3) is an atypical transcription factor that is thought to influence the laminar formation of the cerebral cortex. Here, we report that de novo mutations in EBF3 cause a complex neurodevelopmental syndrome. The mutations were identified in two large-scale sequencing projects: the UK Deciphering Developmental Disorders (DDD) study and the Canadian Clinical Assessment of the Utility of Sequencing and Evaluation as a Service (CAUSES) study. The core phenotype includes moderate to severe intellectual disability, and many individuals exhibit cerebellar ataxia, subtle facial dysmorphism, strabismus, and vesicoureteric reflux, suggesting that EBF3 has a widespread developmental role. Pathogenic de novo variants identified in EBF3 include multiple loss-of-function and missense mutations. Structural modeling suggested that the missense mutations affect DNA binding. Functional analysis of mutant proteins with missense substitutions revealed reduced transcriptional activities and abilities to form heterodimers with wild-type EBF3. We conclude that EBF3, a transcription factor previously unknown to be associated with human disease, is important for brain and other organ development and warrants further investigation.

Mycotoxins: A Fungal Genomics Perspective.

The chemical and enzymatic diversity in the fungal kingdom is staggering. Large-scale fungal genome sequencing projects are generating a massive catalog of secondary metabolite biosynthetic genes and pathways. Fungal natural products are a boon and bane to man as valuable pharmaceuticals and harmful toxins. Understanding how these chemicals are synthesized will aid the development of new strategies to limit mycotoxin contamination of food and feeds as well as expand drug discovery programs. A survey of work focused on the fumonisin family of mycotoxins highlights technological advances and provides a blueprint for future studies of other fungal natural products. Expressed sequence tags led to the discovery of new fumonisin genes (FUM) and hinted at a role for alternatively spliced transcripts in regulation. Phylogenetic studies of FUM genes uncovered a complex evolutionary history of the FUM cluster, as well as fungi with the potential to synthesize fumonisin or fumonisin-like chemicals. The application of new technologies (e.g., CRISPR) could substantially impact future efforts to harness fungal resources.

Loss of Function Cohesin Complex Gene Mutations Create Neomorphic Cell States Advantageous to Oncogenesis

Multiple large scale sequencing projects have identified a significant number of mutations in Acute Myeloid Leukaemia (AML) and high-risk Myelodysplastic syndromes (MDS) patients. Emerging from this are those affecting members of the cohesin complex, predominantly STAG2, and it has been highlighted that the poorer overall survival of this chromatin structure group is second only to patients carrying mutations affecting TP53. The Cohesin complex is an evolutionary conserved, multimeric protein complex consisting of SMC1, SMC3, RAD21 and STAG1/ STAG2. The complex plays a pivotal role during mitosis, ensuring sister chromatid cohesion however, substantial data exists highlighting roles in DNA damage repair, homologous recombination and most significantly, contribution to long-range interactions between cis-regulatory elements of the genome.Here, we have used the CRISPR/Cas9 genome editing system to create an isogenic model featuring a premature stop codon within STAG2 at a region which presents as highly mutated in patient data sets. This stop codon generates a loss of function phenotype due to the haplo-insufficient X-linked nature of the STAG2 gene. Following model validation, the impact on genome wide distribution of the cohesin complex was assessed using ChIP-Seq for STAG1, STAG2, SMC3 & the transcriptional insulator CTCF.A modest increase in overall CTCF binding from ~67,000 to ~72,000 high confidence peaks was observed, despite a ~7-fold decrease in enrichment, indicating decreased global insulator activity as a result of the inactivating STAG2 mutation. As expected, compensation between the STAG members was observed at a number of sites within transcriptionally active topologically associated domains, with an increase in STAG1 binding peaks (~17,000 to >25,000 sites) within the mutant model, despite no changes in average global enrichment. This data was integrated with RNA-seq of the isogeneic parental and mutant cells to determine the transcriptional impact of changes in cohesin complex binding on gene expression within active and repressive domains.Assessment of the active and repressive super-enhancer associated marks H3K27ac and H3K27me3 showed increased global levels of both marks without increase in the polycomb repressive complex 2 member, EZH2 total protein levels. These findings indicate that increased H3K27ac and H3K27me3 marks, in this model, are due to altered domain boundaries, associated with local activation of both H3K9ac and H3K9me3, leading to aberrant gene expression and consequently a neomorphic state within these mutant cells.With recent further stratification of de-novo AML, secondary AML and high-risk MDS emerging, this study on the aberrant and non-canonical nature of the cohesin complex provides avenues for an attractive therapeutic target and personalised treatment approach for patients within the chromatin subgroup. DisclosuresNo relevant conflicts of interest to declare.

GenBank.

GenBank® (www.ncbi.nlm.nih.gov/genbank/) is a comprehensive database that contains publicly available nucleotide sequences for 370 000 formally described species. These sequences are obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole genome shotgun (WGS) and environmental sampling projects. Most submissions are made using the web-based BankIt or the NCBI Submission Portal. GenBank staff assign accession numbers upon data receipt. Daily data exchange with the European Nucleotide Archive (ENA) and the DNA Data Bank of Japan (DDBJ) ensures worldwide coverage. GenBank is accessible through the NCBI Nucleotide database, which links to related information such as taxonomy, genomes, protein sequences and structures, and biomedical journal literature in PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. Recent updates include changes to policies regarding sequence identifiers, an improved 16S submission wizard, targeted loci studies, the ability to submit methylation and BioNano mapping files, and a database of anti-microbial resistance genes.

Genetics of restless legs syndrome

At the outset of genetic studies in restless legs syndrome (RLS), the disorder was assumed to be a classical monogenic disorder that runs in families. However, years of family studies did not reveal any causally-related genes or genetic variants. The advent of high-throughput genotyping technology led to a change; genome-wide association studies in large case−control samples became feasible, which led to the identification of first genetic risk variants for RLS. Variants detected by this approach are common ones, which that individually confer only a minor increase in risk of disease. Overall, the currently known risk variants in six genomic loci account for only a small proportion of the genetically determined susceptibility to RLS. Additional risk loci and individual variants remain to be discovered. First studies indicate that rare genetic variants are also important contributors in RLS. These are expected to have a larger impact on the phenotype and may thus prove to be excellent candidates for functional studies and, in the long-term, targets for developing therapeutics or preventive measures. To enable their discovery, large-scale studies including tens of thousands of affected individuals may be needed. Next-generation sequencing technologies such as whole exome or whole genome sequencing will be essential for this endeavor. Even though the number of known risk variants is still limited, they have been indispensable in terms of deciphering the underlying pathophysiology of RLS, providing the molecular starting points for animal models and in vitro studies to understand disease mechanisms. In addition, genetic risk variants can be valuable tools for disentangling the phenotypic complexity observed in RLS. Testing RLS risk variants for associations with periodic limb movements (PLMs) identified a significant role of some of the variants and suggested PLMs as an endophenotype in RLS. Further advances in genetics research in RLS will be driven by large-scale sequencing projects and the identification of additional common, but also rarer risk variants with larger effects on disease risk. Another uncharted territory in RLS research epigenetic effect on gene activity. Overall, genetic studies continue to hold great potential for understanding biology of the disease.

Quantifying unobserved protein-coding variants in human populations provides a roadmap for large-scale sequencing projects.

As new proposals aim to sequence ever larger collection of humans, it is critical to have a quantitative framework to evaluate the statistical power of these projects. We developed a new algorithm, UnseenEst, and applied it to the exomes of 60,706 individuals to estimate the frequency distribution of all protein-coding variants, including rare variants that have not been observed yet in the current cohorts. Our results quantified the number of new variants that we expect to identify as sequencing cohorts reach hundreds of thousands of individuals. With 500K individuals, we find that we expect to capture 7.5% of all possible loss-of-function variants and 12% of all possible missense variants. We also estimate that 2,900 genes have loss-of-function frequency of <0.00001 in healthy humans, consistent with very strong intolerance to gene inactivation.

Impact of post-alignment processing in variant discovery from whole exome data.

BackgroundGATK Best Practices workflows are widely used in large-scale sequencing projects and recommend post-alignment processing before variant calling. Two key post-processing steps include the computationally intensive local realignment around known INDELs and base quality score recalibration (BQSR). Both have been shown to reduce erroneous calls; however, the findings are mainly supported by the analytical pipeline that incorporates BWA and GATK UnifiedGenotyper. It is not known whether there is any benefit of post-processing and to what extent the benefit might be for pipelines implementing other methods, especially given that both mappers and callers are typically updated. Moreover, because sequencing platforms are upgraded regularly and the new platforms provide better estimations of read quality scores, the need for post-processing is also unknown. Finally, some regions in the human genome show high sequence divergence from the reference genome; it is unclear whether there is benefit from post-processing in these regions.ResultsWe used both simulated and NA12878 exome data to comprehensively assess the impact of post-processing for five or six popular mappers together with five callers. Focusing on chromosome 6p21.3, which is a region of high sequence divergence harboring the human leukocyte antigen (HLA) system, we found that local realignment had little or no impact on SNP calling, but increased sensitivity was observed in INDEL calling for the Stampy + GATK UnifiedGenotyper pipeline. No or only a modest effect of local realignment was detected on the three haplotype-based callers and no evidence of effect on Novoalign. BQSR had virtually negligible effect on INDEL calling and generally reduced sensitivity for SNP calling that depended on caller, coverage and level of divergence. Specifically, for SAMtools and FreeBayes calling in the regions with low divergence, BQSR reduced the SNP calling sensitivity but improved the precision when the coverage is insufficient. However, in regions of high divergence (e.g., the HLA region), BQSR reduced the sensitivity of both callers with little gain in precision rate. For the other three callers, BQSR reduced the sensitivity without increasing the precision rate regardless of coverage and divergence level.ConclusionsWe demonstrated that the gain from post-processing is not universal; rather, it depends on mapper and caller combination, and the benefit is influenced further by sequencing depth and divergence level. Our analysis highlights the importance of considering these key factors in deciding to apply the computationally intensive post-processing to Illumina exome data.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1279-z) contains supplementary material, which is available to authorized users.

MuSE: accounting for tumor heterogeneity using a sample-specific error model improves sensitivity and specificity in mutation calling from sequencing data.

Subclonal mutations reveal important features of the genetic architecture of tumors. However, accurate detection of mutations in genetically heterogeneous tumor cell populations using next-generation sequencing remains challenging. We develop MuSE (http://bioinformatics.mdanderson.org/main/MuSE), Mutation calling using a Markov Substitution model for Evolution, a novel approach for modeling the evolution of the allelic composition of the tumor and normal tissue at each reference base. MuSE adopts a sample-specific error model that reflects the underlying tumor heterogeneity to greatly improve the overall accuracy. We demonstrate the accuracy of MuSE in calling subclonal mutations in the context of large-scale tumor sequencing projects using whole exome and whole genome sequencing.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-1029-6) contains supplementary material, which is available to authorized users.

Sequencing Circulating Cell-Free DNA: The Potential to Refine Precision Cancer Medicine.

Most cancer treatments benefit only a minority of the patients who receive them. This is particularly true for molecularly targeted drugs, unless we know which patients to target. The completion of the first human reference genome in 2003 and the introduction of massively parallel sequencing (MPS)2 technology in 2004 ushered in the “genomic era” of cancer research and triggered the concept of precision cancer medicine, in which treatment is tailored to the genetic make-up of an individual's tumor. Since then, efforts from large-scale cancer genome sequencing projects, such as The Cancer Genome Atlas, have led to the discovery of many important cancer genes [for example, isocitrate dehydrogenase 1 ( IDH 1)3 and isocitrate dehydrogenase 2 ( IDH2 ) for glioblastoma multiforme and acute myeloid leukemia, respectively] as well as new targets for therapy. Today, affordable targeted MPS-based assays have become commonplace in the clinical research setting, particularly in cancer centers with early-phase drug development programs, as molecular screening tools to triage patients for molecularly targeted therapies. Molecular testing is traditionally conducted with tumor tissue derived from a diagnostic biopsy or an archival resection sample. However, the existence of intratumoral, intermetastatic, and intrametastatic genetic heterogeneity implies that the genomic analysis of a single tissue sample may represent an incomplete view of the genetic landscape of the tumor. The presence of genetic heterogeneity is particularly relevant in patients with heavily pretreated advanced cancers. In such cases, the current molecular profile of the disease may be substantially different from that of the archival tissue obtained several years prior. Recent studies evaluating the clonal relationships among primary and metastatic cancers have demonstrated that seeding metastases require very few additional driver or founder mutations beyond those found in the primary tumors. However, as the metastatic lesion grows, it acquires new mutations with each cell division, providing …

The Pokeweed Leaf mRNA Transcriptome and Its Regulation by Jasmonic Acid.

The American pokeweed plant, Phytolacca americana, is recognized for synthesizing pokeweed antiviral protein (PAP), a ribosome inactivating protein (RIP) that inhibits the replication of several plant and animal viruses. The plant is also a heavy metal accumulator with applications in soil remediation. However, little is known about pokeweed stress responses, as large-scale sequencing projects have not been performed for this species. Here, we sequenced the mRNA transcriptome of pokeweed in the presence and absence of jasmonic acid (JA), a hormone mediating plant defense. Trinity-based de novo assembly of mRNA from leaf tissue and BLASTx homology searches against public sequence databases resulted in the annotation of 59 096 transcripts. Differential expression analysis identified JA-responsive genes that may be involved in defense against pathogen infection and herbivory. We confirmed the existence of several PAP isoforms and cloned a potentially novel isoform of PAP. Expression analysis indicated that PAP isoforms are differentially responsive to JA, perhaps indicating specialized roles within the plant. Finally, we identified 52 305 natural antisense transcript pairs, four of which comprised PAP isoforms, suggesting a novel form of RIP gene regulation. This transcriptome-wide study of a Phytolaccaceae family member provides a source of new genes that may be involved in stress tolerance in this plant. The sequences generated in our study have been deposited in the SRA database under project # SRP069141.

Evolutionary aspects of plant photoreceptors.

Plant photoreceptors link environmental light cues with physiological responses, determining how individual plants complete their life cycles. Structural and functional evolution of photoreceptors has co-occurred as plants diversified and faced the challenge of new light environments, during the transition of plants to land and as substantial plant canopies evolved. Large-scale comparative sequencing projects allow us for the first time to document photoreceptor evolution in understudied clades, revealing some surprises. Here we review recent progress in evolutionary studies of three photoreceptor families: phytochromes, phototropins and neochromes.

On Sample Size and Power Calculation for Variant Set-Based Association Tests.

Sample size and power calculations are an important part of designing new sequence-based association studies. The recently developed SEQPower and SPS programs adopted computationally intensive Monte Carlo simulations to empirically estimate power for a series of variant set association (VSA) test methods including the sequence kernel association test (SKAT). It is desirable to develop methods that can quickly and accurately compute power without intensive Monte Carlo simulations. We will show that the computed power for SKAT based on the existing analytical approach could be inflated especially for small significance levels, which are often of primary interest for large-scale whole genome and exome sequencing projects. We propose a new χ(2) -approximation-based approach to accurately and efficiently compute sample size and power. In addition, we propose and implement a more accurate "exact" method to compute power, which is more efficient than the Monte Carlo approach though generally involves more computations than the χ(2) approximation method. The exact approach could produce very accurate results and be used to verify alternative approximation approaches. We implement the proposed methods in publicly available R programs that can be readily adapted when planning sequencing projects.

GenBank.

GenBank® (www.ncbi.nlm.nih.gov/genbank/) is a comprehensive database that contains publicly available nucleotide sequences for over 340 000 formally described species. Recent developments include a new starting page for submitters, a shift toward using accession.version identifiers rather than GI numbers, a wizard for submitting 16S rRNA sequences, and an Identical Protein Report to address growing issues of data redundancy. GenBank organizes the sequence data received from individual laboratories and large-scale sequencing projects into 18 divisions, and GenBank staff assign unique accession.version identifiers upon data receipt. Most submitters use the web-based BankIt or standalone Sequin programs. Daily data exchange with the European Nucleotide Archive (ENA) and the DNA Data Bank of Japan (DDBJ) ensures worldwide coverage. GenBank is accessible through the nuccore, nucest, and nucgss databases of the Entrez retrieval system, which integrates these records with a variety of other data including taxonomy nodes, genomes, protein structures, and biomedical journal literature in PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP.

Abstract 4743: A population-based approach to address clinical cancer care: The national genomics platform

Abstract Our understanding of the genetic basis for cancer is advancing at a rapid rate due to the application of next generation sequencing (NGS) technologies. It is becoming common to sequence tumors and patients in an attempt to find actionable mutations that could offer the patient a more targeted and effective treatment. However, the genomics of cancer is very complex and only a handful of actionable mutations have been characterized. Larger-scale studies are needed to understand the pathogenic spectrum of cancer variants and deliver reliable clinical decision-making support to providers. Several large-scale sequencing projects are underway to collect NGS data on tumors (e.g. TCGA, ICGC, and TARGET) but a national platform for analysis, interpretation, and reporting does not exist. We propose that a consolidated informatics platform for the collection of outcomes data with genomics and clinical data would accelerate research and provide patients with the opportunity for personalized cancer treatment. In addition, with 1,665,540 new cancer cases predicted in the US for 2014, a national-scale genomics platform is needed, capable of sequencing 3 million genomes per year, storing exabytes of data, while supporting over 20,000 oncologists, researchers, and analysts. At Lockheed Martin, we deliver highly scalable and reliable information systems for a variety of missions and citizen services. Here, we will present our vision for a national cancer genomics platform to include NGS data collection, cost-efficient storage, scalable and modular processing pipelines, and collaborative analytics and data sharing capabilities, within a compliant privacy and security framework. In conclusion, by leveraging the scale of clinical cancer sequencing and capturing these data into a case management system for translational research, this platform provides data at-scale needed for finding actionable mutations, designing effective treatments and implementing prevention strategies, faster. Citation Format: Ogan Abaan, Amrita Basu, Noah Brown, Bret Light, David Deal, Michael Hultner. A population-based approach to address clinical cancer care: The national genomics platform. [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 4743. doi:10.1158/1538-7445.AM2015-4743