Clinical Next-generation Sequencing Research Articles

Somatic genomic landscape of over 15,000 patients with advanced-stage cancer from clinical next-generation sequencing analysis of circulating tumor DNA.

LBA11501 Background: Next-generation sequencing (NGS) of circulating tumor DNA (ctDNA) enables non-invasive profiling of solid tumor cancers. Liquid biopsy studies to date have been limited to modest-size cohorts and case studies. Methods: Somatic genomic profiles of over 15,000 patients with advanced-stage clinical cancer were determined by a highly accurate, deep-coverage (15,000x) ctDNA NGS test targeting 70 genes (Guardant360). Frequencies of somatic ctDNA alterations per gene were compared to those previously described in tissue sequencing projects (e.g., TCGA). Accuracy of ctDNA sequencing (PPV) was assessed by comparing with matched tissue tests for 386 patients. Results: The cohort consisted of lung (37%), breast (14%), colorectal (10%) and other cancers (38%), with ctDNA clinical sensitivity of 86%, 83%, 85%, and 78%, respectively. Cancer-type-specific frequencies and mutual exclusivity patterns among major driver alterations largely recapitulated those seen in tissue sequencing studies. Mutation frequencies per codon correlated well between ctDNA and published tissue data, both for commonly altered tumor suppressors and for oncogenes (Pearson correlations: TP53, r = 0.94; KRAS, r = 0.99; PIK3CA, r = 0.99). The overall accuracy of ctDNA sequencing in comparison with matched tissue tests was 87% (336/386). The accuracy increased to 98% when blood and tumor were collected less than six months apart. Four distinct classes of clinical outcome benefits have been observed by liquid biopsy: 1) actionable mutations in cases with tissue QNS ( ALK fusion, or EGFR or BRAF activating mutations in lung; ERBB2 amp in gastric), 2) actionable resistance mutations at time of progression ( MET amp or EGFRT790M in lung), 3) evolution of sensitivity upon progression ( ERBB2-amplified metastatic breast cancer with triple negative primary), 4) under-genotyped tumors ( BRAFV600E or ERBB2indel in lung). Conclusions: Somatic alteration patterns in ctDNA samples largely agree with tissue alteration patterns, with the exception of resistance mutations. Clinical outcome benefits have been observed for patients treated based on ctDNA findings.

Navigating highly homologous genes in a molecular diagnostic setting: a resource for clinical next-generation sequencing.

Next-generation sequencing (NGS) is now routinely used to interrogate large sets of genes in a diagnostic setting. Regions of high sequence homology continue to be a major challenge for short-read technologies and can lead to false-positive and false-negative diagnostic errors. At the scale of whole-exome sequencing (WES), laboratories may be limited in their knowledge of genes and regions that pose technical hurdles due to high homology. We have created an exome-wide resource that catalogs highly homologous regions that is tailored toward diagnostic applications. This resource was developed using a mappability-based approach tailored to current Sanger and NGS protocols. Gene-level and exon-level lists delineate regions that are difficult or impossible to analyze via standard NGS. These regions are ranked by degree of affectedness, annotated for medical relevance, and classified by the type of homology (within-gene, different functional gene, known pseudogene, uncharacterized noncoding region). Additionally, we provide a list of exons that cannot be analyzed by short-amplicon Sanger sequencing. This resource can help guide clinical test design, supplemental assay implementation, and results interpretation in the context of high homology.Genet Med 18 12, 1282-1289.

Clinical next-generation sequencing in sarcomas.

11046Background: There are currently no FDA approved targeted therapies for sarcomas except GIST. Complicating this is the extreme diversity, heterogeneity, and rarity of these neoplasms. Few thera...

Somatic genomic landscape of over 15,000 patients with advanced-stage cancer from clinical next-generation sequencing analysis of circulating tumor DNA.

Somatic genomic landscape of over 15,000 patients with advanced-stage cancer from clinical next-generation sequencing analysis of circulating tumor DNA.

Plasmid-Based Materials as Multiplex Quality Controls and Calibrators for Clinical Next-Generation Sequencing Assays

Although next-generation sequencing technologies have been widely adapted for clinical diagnostic applications, an urgent need exists for multianalyte calibrator materials and controls to evaluate the performance of these assays. Control materials will also play a major role in the assessment, development, and selection of appropriate alignment and variant calling pipelines. We report an approach to provide effective multianalyte controls for next-generation sequencing assays, referred to as the control plasmid spiked-in genome (CPSG). Control plasmids that contain approximately 1000 bases of human genomic sequence with a specific mutation of interest positioned near the middle of the insert and a nearby 6-bp molecular barcode were synthesized, linearized, quantitated, and spiked into genomic DNA derived from formalin-fixed, paraffin-embedded-prepared hapmap cell lines at defined copy number ratios. Serial titration experiments demonstrated the CPSGs performed with similar efficiency of variant detection as formalin-fixed, paraffin-embedded cell line genomic DNA. Repetitive analyses of one lot of CPSGs 90 times during 18 months revealed that the reagents were stable with consistent detection of each of the plasmids at similar variant allele frequencies. CPSGs are designed to work across most next-generation sequencing methods, platforms, and data analysis pipelines. CPSGs are robust controls and can be used to evaluate the performance of different next-generation sequencing diagnostic assays,assess data analysis pipelines, and ensure robust assay performance metrics.

Clinical RNA sequencing in oncology: where are we?

The term next-generation sequencing (NGS) is becoming increasingly familiar to clinical oncologists and those patients who are exploring options for addressing the most aggressive and intractable forms of cancer. With few exceptions, the analyte of choice for clinical next-generation sequencing is DNA, and the primary motivation for the test is to uncover a genetic variant predictive of response to a targeted cancer therapy. McKinsey & Company (CA, USA) has estimated that by 2018 up to 70% of lung cancer patients and 60% of colorectal cancer patients will have some level of DNA sequencing performed on their tumors [1]. The benefits of targeted therapy for those patients with a qualifying mutation are significant – a recent study found treating lung cancer patients with targeted therapies could increase progression-free survival by 18 months [2]. Still, even the largest gene panels fail to match the majority of patients to the US FDA-approved therapy, and most patients that are given genetically targeted therapies eventually progress and then seek other treatment options. In comparison with DNA analysis, tumor RNA profiling has the potential to guide a much broader set of drugs and treatment approaches, including immunotherapy and chemotherapy. mRNA analysis can reveal tumor antigens and drug targets expressed by cancer cells, as well as the vital status of the tumor microenvironment, including immune response, the integrity of DNA repair mechanisms and engagement of angiogenesis and other cancer-related pathways. Moreover, for over a decade clinically established prognostic tests based on mRNA signatures, the best known being the Oncotype DX test from Genomic Health (CA, USA) for breast cancer [3,4], have been helping doctors and patients make decisions regarding whether to pursue chemotherapy. In this article, we outline our expectations for growth in RNA-based cancer diagnostics, particularly in immune oncology, and argue that those same forces that brought DNA sequencing into clinical laboratories – falling sequencing costs and a rapidly growing list of actionable markers – will lead to emergence of clinical RNA sequencing (RNA-Seq), despite the challenges.

Building a Robust Tumor Profiling Program: Synergy between Next-Generation Sequencing and Targeted Single-Gene Testing.

Next-generation sequencing (NGS) is a powerful platform for identifying cancer mutations. Routine clinical adoption of NGS requires optimized quality control metrics to ensure accurate results. To assess the robustness of our clinical NGS pipeline, we analyzed the results of 304 solid tumor and hematologic malignancy specimens tested simultaneously by NGS and one or more targeted single-gene tests (EGFR, KRAS, BRAF, NPM1, FLT3, and JAK2). For samples that passed our validated tumor percentage and DNA quality and quantity thresholds, there was perfect concordance between NGS and targeted single-gene tests with the exception of two FLT3 internal tandem duplications that fell below the stringent pre-established reporting threshold but were readily detected by manual inspection. In addition, NGS identified clinically significant mutations not covered by single-gene tests. These findings confirm NGS as a reliable platform for routine clinical use when appropriate quality control metrics, such as tumor percentage and DNA quality cutoffs, are in place. Based on our findings, we suggest a simple workflow that should facilitate adoption of clinical oncologic NGS services at other institutions.

The Pitfalls of Companion Diagnostics: Evaluation of Discordant EGFR Mutation Results from a Clinical Laboratory and a Central Laboratory

Accurate identification of somatic mutations in formalin-fixed, paraffin-embedded tumor tissue is required for enrollment into clinical trials for many novel targeted therapeutics, including trials requiring EGFR mutation status in non-small-cell lung carcinomas. Central clinical trial laboratories contracted to perform this analysis typically rely on US Food and Drug Administration-approved targeted assays to identify these mutations. We present two cases in which central laboratories inaccurately reported EGFR mutation status because of improper identification and isolation of tumor material and failure to accurately report assay limitations, resulting in enrollment denial. Such cases highlight the need for increased awareness by clinical trials of the limitation of these US Food and Drug Administration-approved assays and the necessity for a mechanism to reevaluate discordant results by alternative laboratory-developed procedures, including clinical next-generation sequencing.

Current practices and guidelines for clinical next-generation sequencing oncology testing

Next-generation sequencing (NGS) has been rapidly integrated into molecular pathology, dramatically increasing the breadth genomic of information available to oncologists and their patients. This review will explore the ways in which this new technology is currently applied to bolster care for patients with solid tumors and hematological malignancies, focusing on practices and guidelines for assessing the technical validity and clinical utility of DNA variants identified during clinical NGS oncology testing.

Effective quality management practices in routine clinical next-generation sequencing

Molecular technologies have allowed laboratories to detect and establish the profiles of human cancers by identifying a variety of somatic variants. In order to improve personalized patient care, we have established a next-generation sequencing (NGS) test to screen for somatic variants in primary or advanced cancers. In this study, we describe the laboratory quality management program for NGS testing, and also provide an overview of the somatic variants identified in over 1000 patient samples as well as their implications in clinical practice. Over the past one-and-a-half years, our laboratory received a total of 1028 formalin-fixed, paraffin-embedded (FFPE) tumor tissues, which consisted of non-small-cell lung carcinomas (NSCLCs), colon adenocarcinomas, glioma/glioblastomas, melanomas, breast carcinomas, and other tumor types. During this time period, we implemented a series of quality control (QC) checks that included (1) pre-DNA extraction, (2) DNA quantification, (3) DNA quality, (4) library quantification, (5) post-emulsification PCR, and (6) post-sequencing metrics. At least 10 ng of genomic DNA (gDNA) were used to prepare barcoded libraries using the AmpliSeq CHPv2. Samples were multiplexed and sequenced on Ion Torrent 318 chips using the Ion PGM System. Variants were identified using the Variant Caller Plugin, and annotation and functional predictions were performed using the Golden Helix SVS. A total of 1005 samples passed QC1-3, and following additional library preparation QC checkpoints, 877 samples were sequenced. Samples were classified into two categories: wild-type (127) and positive for somatic variants (750). Somatic variants were classified into clinically actionable (60%) and non-actionable (40%). The use of NGS in routine clinical laboratory practice allowed for the detection of tumor profiles that are essential for the selection of targeted therapies and identification of applicable clinical trials, contributing to the improvement of personalized patient care in oncology.

Current practices and guidelines for clinical next-generation sequencing oncology testing

Current practices and guidelines for clinical next-generation sequencing oncology testing

Clinical Next-Generation Sequencing for Somatic Mutation Detection- Advancements and Commercialization Strategies

Advancements in next-generation sequencing, variant-calling software, and mutation enrichment are facilitating the detection of rare genetic variants. In doing so, these methods have enabled identification of somatic disease, and more specifically cancer, representing as little as 0.01% of bulk genetic material. This improved sensitivity reduces false negative results, and in cancer, allows earlier detection. Such early detection will greatly improve monitoring and treatment of these diseases, especially in the context of liquid biopsies. This review aims to encapsulate the growing spectrum of technology and software currently being utilized to improve the sensitivity of somatic variant detection. Furthermore, industry adoption of these techniques will be summarized.

Interpretation of Clinical Next-Generation Sequencing Data: A Hurdle to Jump Over

Interpretation of Clinical Next-Generation Sequencing Data: A Hurdle to Jump Over

Identification of Genetic Hereditary Predisposition to Hematologic Malignancies By Clinical Next-Generation Sequencing

Introduction: Myelodysplastic syndrome (MDS) and acute leukemia (AL) are a clinically diverse and genetically heterogeneous group of hematologic malignancies. Familial forms of MDS/AL have been increasingly recognized in recent years, and can occur as a primary event or secondary to genetic syndromes, such as inherited bone marrow failure syndromes (IBMFS). It is critical to confirm a genetic diagnosis in patients with hereditary predisposition to hematologic malignancies in order to provide prognostic information and cancer risk assessment, and to aid in identification of at-risk or affected family members. In addition, a molecular diagnosis can help tailor medical management including informing the selection of family members for allogeneic stem cell transplantation donors. Until recently, clinical testing options for this diverse group of hematologic malignancy predisposition genes were limited to the evaluation of single genes by Sanger sequencing, which is a time consuming and expensive process. To improve the diagnosis of hereditary predisposition to hematologic malignancies, our CLIA-licensed laboratory has recently developed Next-Generation Sequencing (NGS) panel-based testing for these genes.Methods: Thirty six patients with personal and/or family history of aplastic anemia, MDS or AL were referred for clinical diagnostic testing. DNA from the referred patients was obtained from cultured skin fibroblasts or peripheral blood and was utilized for preparing libraries with the SureSelectXT Enrichment System. Libraries were sequenced on an Illumina MiSeq instrument and the NGS data was analyzed with a custom bioinformatic pipeline, targeting a panel of 76 genes associated with IBMFS and/or familial MDS/AL.Results: Pathogenic and highly likely pathogenic variants were identified in 7 out of 36 patients analyzed, providing a positive molecular diagnostic rate of 20%. Overall, 6 out of the 7 pathogenic changes identified were novel. In 2 unrelated patients with MDS, heterozygous pathogenic sequence changes were identified in the GATA2 gene. Heterozygous pathogenic changes in the following autosomal dominant genes were each identified in a single patient: RPS26 (Diamond-Blackfan anemia 10), RUNX1 (familial platelet disorder with propensity to myeloid malignancy), TERT (dyskeratosis congenita 4) and TINF2 (dyskeratosis congenita 3). In addition, one novel heterozygous sequence change (c.826+5_826+9del, p.?) in the Fanconi anemia associated gene FANCA was identified. . The RNA analysis demonstrated this variant causes skipping of exon 9 and results in a premature stop codon in exon 10. Further review of the NGS data provided evidence of an additional large heterozygous multi-exon deletion in FANCA in the same patient. This large deletion was confirmed using array-CGH (comparative genomic hybridization).Conclusions: This study demonstrates the effectiveness of using NGS technology to identify patients with a hereditary predisposition to hematologic malignancies. As many of the genes associated with hereditary predisposition to hematologic malignancies have similar or overlapping clinical presentations, analysis of a diverse panel of genes is an efficient and cost-effective approach to molecular diagnostics for these disorders. Unlike Sanger sequencing, NGS technology also has the potential to identify large exonic deletions and duplications. In addition, RNA splicing assay has proven to be helpful in clarifying the pathogenicity of variants suspected to affect splicing. This approach will also allow for identification of a molecular defect in patients who may have atypical presentation of disease. DisclosuresNo relevant conflicts of interest to declare.

Mutational Burden in Acute Myeloid Leukemia Is Largely Age Dependent

Risk stratification of acute myeloid leukemia (AML) is important for prognosis and for guiding treatment decisions. The National Comprehensive Cancer Network (NCCN) classifies AML into three risk categories (favorable, intermediate, or poor) based on recurrent cytogenetic or molecular abnormalities. Clinical next-generation sequencing (NGS) is beginning to clarify the relationship between these categories and the spectra of oncogenic mutations, and leading to the development of new targeted therapies. The role of NGS data in favorable risk disease and the interaction of the NCCN classification with other prognostic risk factors such as age are not fully understood.Here, we assess 32 favorable risk [12 inv(16), 2 t(8;21), and 18 normal karyotype NPM1 mutated/FLT3 ITD negative] and 88 poor risk (33 transformed from documented MDS, 47 with complex or monosomal karyotype without previous documented MDS, and 8 therapy-related with normal karyotype) cases of AML. Results of NGS using a 37 gene, myeloid neoplasm-specific panel were incorporated with conventional cytogenetics and FISH results, as well as clinical history including patient age and survival data. Genes were arranged into four functional groups: splicing, epigenetic, signaling, and transcription (see Table 1).Analysis of the mutational spectra categorized by NCCN risk category and by age reveals several patterns (see Table 1). TP53 mutations were associated with a low total mutation number, as previously reported. Core binding factor (CBF) AMLs were primarily seen in young patients (<60 years) and were associated with a predominance of signaling mutations, without splicing or epigenetic mutations. A similar pattern was seen in young patients with favorable risk, NPM1-positive cases as well as in young patients with non-TP53-mutated poor risk AML. Older patients (≥60 years) with non-TP53-mutation poor risk AML had a high number of splicing and epigenetic mutations, as expected, but so did older patients with favorable risk, NPM1-positive disease.For favorable risk and non-TP53-mutated poor risk AML, stratification by age (younger/older than 60 years) provided significant differentiation between total mutations and mutation categories superior to stratification by risk group (see Table 2). Stratifying mutation spectrum by age demonstrates no significant difference between younger and older poor risk TP53-mutated cases.To determine the degree to which the effect of age and risk category on survival is driven by the increased likelihood of splicing or epigenetic mutations, Cox regression analysis was performed on retrospective overall survival data for favorable risk and non-TP53-mutated poor risk cases. This analysis demonstrated the expected significant independent effects of risk category and age, but showed no significant independent effect of the presence of splicing or epigenetic mutations (see Table 3).These preliminary findings suggest that the mutation spectrum of AML is more a function of age than of NCCN risk category. Additionally, in our analysis, the primary effect of age on survival is independent of mutation profile.Table 1CategoryCBFNPM1 pos, FLT3-ITD neg, normal karyotypeKnown MDSComplex cytogenetics with no known history of MDSTreatment related, normal karyotypeTP53 mutated poor riskAge<60<60≥60<60≥60<60≥60<60≥60<60≥60N13513419917351120Total mutations1.2±0.32.6±0.43.5±0.22.8±0.83.5±0.32.0±0.32.8±0.50.3±0.33.4±1.21.7±0.21.9±0.3Mutations by gene groupSplicing1005013090214Epigenetic202162233170417Signaling3104538841742Transcription42022901001011: SRSF2, U2AF1, ZRSR2, SF3B12: DNMT3A, IDH1, IDH2, TET2, EZH2, ASXL13: FLT3, KIT, KRAS, NRAS, PTPN11, WT1, CBL, MYD884: GATA2, PHF6, RUNX1, BCOR, BCORL1, ETV6Table 2Data setTP53 -mutated Poor RiskFavorable Risk and Non-TP53 -mutated Poor RiskComparisonYounger vs. OlderYounger vs. OlderFavorable vs. Poor RiskTotal mutations, P value1NS< 0.0001NSMutations by gene group, P value2SplicingNS< 0.00010.04EpigeneticNS< 0.0001NSSignalingNS0.05NSTranscriptionNS0.010.03NS: Not significant.1: T-test2: Fisher's exact testTable 3P valueHazard RatioNCCN Risk Category (Favorable vs. Poor)<0.0013.637Age (< or ≥60)0.0382.006Presence of Splicing or Epigenetic Mutations0.7880.922Cox regression analysis of overall survival DisclosuresStrickland:Sunesis Pharmaceuticals: Other: Steering Committee and Advisory Board Participation; Boehringer-Ingelheim: Other: Advisory Board Particpation; Daiichi-Sankyo: Other: Advisory Board Particpation; Alexion Pharmaceuticals: Other: Advisory Board Particpation; Amgen: Other: Advisory Board Particpation. Daber:Archer Diagnostics: Membership on an entity's Board of Directors or advisory committees; BioReference Laboratories: Employment. Savona:Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding.

Identifying Inherited and Acquired Genetic Factors Involved in Poor Stem Cell Mobilization and Donor-Derived Malignancy

BackgroundMobilized peripheral blood (PB) stem cells (PBSC) are the most frequent source of hematopoietic stem cells (HSC) used for allogeneic HSC transplantation (HSCT). However, genetic factors contributing to donors who mobilize PBSC poorly are not well understood. We previously identified an undetected case of a familial myelodysplastic syndrome/acute leukemia (MDS/AL) predisposition syndrome in a donor with mild pre-donation thrombocytopenia who mobilized very poorly. Familial MDS/AL predisposition syndromes were identified in two other donors found to have hypocellular bone marrows after poor PBSC mobilization. Thus, we hypothesized that we could identify germline MDS/AL predisposition among poor mobilizing donors using a genomic screen of key hematopoietic genes.Patients and MethodsAmong 331 HLA-matched related HSC donors who underwent PBSC mobilization at The University of Chicago from 2001 to 2011, we defined those whose PB CD34+ cells/μl on day 5 post G-CSF administration fell within the lowest quartile as poor mobilizers (PM). Genomic DNA was available for 23 consented PM. This study was approved by The University of Chicago Institutional Review Board. Genomic DNAs isolated from donors' mobilized PBSC product were screened utilizing MarrowSeq, an next generation sequencing (NGS) assay targeting 142 genes involved in inherited and acquired bone marrow failure syndromes and hematologic malignancies. Potentially damaging variants were confirmed by Sanger sequencing. Clinical NGS panel testing was used to identify additional acquired mutations in one donor/recipient pair.ResultsAmong the 23 PM sequenced using MarrowSeq, deleterious mutations were identified in 2 (9%). The first, a 63 year old male donor with mild thrombocytopenia (platelet count 136 K/μL) and macrocytosis (MCV 107.8 fL) was previously reported by our group to have a deleterious germline TERT mutation (c.2908A>G; p.M970V; 48% allelic ratio), which was also identified in the recipient's leukemia. This donor required bone marrow harvest after two failed PBSC mobilization attempts and the recipient died 5 months post-HSCT due to complications of poor engraftment. The second was a 67 year old mildly thrombocytopenic male donor (platelet count 139 K/μl) with a deleterious TET2 mutation (c.3765C>G; p.Y1255*; 48% allelic ratio), which was not present in the recipient's skin fibroblasts, most consistent with the presence of clonal hematopoiesis of indeterminate potential (CHIP) in the donor. Follow-up of this donor six years after collection of these TET2-mutated PBSCs demonstrated persistent mild thrombocytopenia (platelet count 121 K/μl), but otherwise normal blood counts. The recipient achieved remission after reinduction chemotherapy for relapsed AML followed by matched-related HSCT. Post-HSCT, the recipient demonstrated persistent mild thrombocytopenia. Six years later, she developed transfusion-dependent anemia and refractory anemia with excess blasts-2. Karyotype and microsatellite marker analysis of the bone marrow were consistent with an MDS of male donor origin. NGS sequencing from the bone marrow demonstrated the same TET2 mutation found in the mobilized PBSC product used in the transplant and an additional acquired RUNX1 mutation (c.585del; p.T196Qfs*15). Additional data from NGS sequencing of donor and recipient samples over time will be presented.ConclusionsWe demonstrate that both inherited and acquired genetic factors in PBSC from apparently healthy donors can contribute to poor mobilization and donor-derived malignancy post-HSCT. To the best of our knowledge, this is the first example of clonal evolution of TET2-mutated CHIP within a donor resulting in a donor-derived leukemia within the HSCT recipient. Replicative stress to reconstitute hematopoiesis in the recipient and/or the recipient's damaged bone marrow microenvironment may be contributing factors to the development of this donor-derived leukemia while the donor remains well. This study suggests that PM with thrombocytopenia may carry inherited or acquired mutations in hematopoietic genes, and alternative donor options should be considered. Our study also raises concerns about whether we need to screen for CHIP in healthy donors with unexplained cytopenias, especially as donors of increasing age are utilized.This research was supported by the American Society of Hematology through the ASH HONORS Award. Disclosuresvan Besien:Miltenyi Biotec: Research Funding. Godley:Onconova: Research Funding.

Standards for Clinical Grade Genomic Databases.

Next-generation sequencing performed in a clinical environment must meet clinical standards, which requires reproducibility of all aspects of the testing. Clinical-grade genomic databases (CGGDs) are required to classify a variant and to assist in the professional interpretation of clinical next-generation sequencing. Applying quality laboratory standards to the reference databases used for sequence-variant interpretation presents a new challenge for validation and curation. To define CGGD and the categories of information contained in CGGDs and to frame recommendations for the structure and use of these databases in clinical patient care. Members of the College of American Pathologists Personalized Health Care Committee reviewed the literature and existing state of genomic databases and developed a framework for guiding CGGD development in the future. Clinical-grade genomic databases may provide different types of information. This work group defined 3 layers of information in CGGDs: clinical genomic variant repositories, genomic medical data repositories, and genomic medicine evidence databases. The layers are differentiated by the types of genomic and medical information contained and the utility in assisting with clinical interpretation of genomic variants. Clinical-grade genomic databases must meet specific standards regarding submission, curation, and retrieval of data, as well as the maintenance of privacy and security. These organizing principles for CGGDs should serve as a foundation for future development of specific standards that support the use of such databases for patient care.

Scalable and cost-effective NGS genotyping in the cloud.

BackgroundWhile next-generation sequencing (NGS) costs have plummeted in recent years, cost and complexity of computation remain substantial barriers to the use of NGS in routine clinical care. The clinical potential of NGS will not be realized until robust and routine whole genome sequencing data can be accurately rendered to medically actionable reports within a time window of hours and at scales of economy in the 10’s of dollars.ResultsWe take a step towards addressing this challenge, by using COSMOS, a cloud-enabled workflow management system, to develop GenomeKey, an NGS whole genome analysis workflow. COSMOS implements complex workflows making optimal use of high-performance compute clusters. Here we show that the Amazon Web Service (AWS) implementation of GenomeKey via COSMOS provides a fast, scalable, and cost-effective analysis of both public benchmarking and large-scale heterogeneous clinical NGS datasets.ConclusionsOur systematic benchmarking reveals important new insights and considerations to produce clinical turn-around of whole genome analysis optimization and workflow management including strategic batching of individual genomes and efficient cluster resource configuration.Electronic supplementary materialThe online version of this article (doi:10.1186/s12920-015-0134-9) contains supplementary material, which is available to authorized users.

Next-Generation Sequencing in Clinical Molecular Diagnostics of Cancer: Advantages and Challenges.

The application of next-generation sequencing (NGS) to characterize cancer genomes has resulted in the discovery of numerous genetic markers. Consequently, the number of markers that warrant routine screening in molecular diagnostic laboratories, often from limited tumor material, has increased. This increased demand has been difficult to manage by traditional low- and/or medium-throughput sequencing platforms. Massively parallel sequencing capabilities of NGS provide a much-needed alternative for mutation screening in multiple genes with a single low investment of DNA. However, implementation of NGS technologies, most of which are for research use only (RUO), in a diagnostic laboratory, needs extensive validation in order to establish Clinical Laboratory Improvement Amendments (CLIA) and College of American Pathologists (CAP)-compliant performance characteristics. Here, we have reviewed approaches for validation of NGS technology for routine screening of tumors. We discuss the criteria for selecting gene markers to include in the NGS panel and the deciding factors for selecting target capture approaches and sequencing platforms. We also discuss challenges in result reporting, storage and retrieval of the voluminous sequencing data and the future potential of clinical NGS.

Occult Specimen Contamination in Routine Clinical Next-Generation Sequencing Testing.

To evaluate the extent of human-to-human specimen contamination in clinical next-generation sequencing (NGS) data. Using haplotype analysis to detect specimen admixture, with orthogonal validation by short tandem repeat analysis, we determined the rate of clinically significant (>5%) DNA contamination in clinical NGS data from 296 consecutive cases. Haplotype analysis was performed using read haplotypes at common, closely spaced single-nucleotide polymorphisms in low linkage disequilibrium in the population, which were present in regions targeted by the clinical assay. Percent admixture was estimated based on frequencies of the read haplotypes at loci that showed evidence for contamination. We identified nine (3%) cases with at least 5% DNA admixture. Three cases were bone marrow transplant patients known to be chimeric. Six admixed cases were incidents of contamination, and the rate of contamination was strongly correlated with DNA yield from the tissue specimen. Human-human specimen contamination occurs in clinical NGS testing. Tools for detecting contamination in NGS sequence data should be integrated into clinical bioinformatics pipelines, especially as laboratories trend toward using smaller amounts of input DNA and reporting lower frequency variants. This study provides one estimate of the rate of clinically significant human-human specimen contamination in clinical NGS testing.