CCMG practice guideline: laboratory guidelines for next-generation sequencing

PurposeThe purpose of this document is to provide guidance for the use of next-generation sequencing (NGS, also known as massively parallel sequencing or MPS) in Canadian clinical genetic laboratories for detection of genetic variants in genomic DNA and mitochondrial DNA for inherited disorders, as well as somatic variants in tumour DNA for acquired cancers. They are intended for Canadian clinical laboratories engaged in developing, validating and using NGS methods.Methods of statement developmentThe document was drafted by the Canadian College of Medical Geneticists (CCMG) Ad Hoc Working Group on NGS Guidelines to make recommendations relevant to NGS. The statement was circulated for comment to the CCMG Laboratory Practice and Clinical Practice committees, and to the CCMG membership. Following incorporation of feedback, the document was approved by the CCMG Board of Directors.DisclaimerThe CCMG is a Canadian organisation responsible for certifying medical geneticists and clinical laboratory geneticists, and for establishing professional and ethical standards for clinical genetics services in Canada. The current CCMG Practice Guidelines were developed as a resource for clinical laboratories in Canada and should not be considered to be inclusive of all information laboratories should consider in the validation and use of NGS for a clinical laboratory service.

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Using Machine Learning to Identify True Somatic Variants from Next-Generation Sequencing

Clinical Chemistry ◽

10.1373/clinchem.2019.308213 ◽

2019 ◽

Vol 66 (1) ◽

pp. 239-246 ◽

Cited By ~ 1

Author(s):

Chao Wu ◽

Xiaonan Zhao ◽

Mark Welsh ◽

Kellianne Costello ◽

Kajia Cao ◽

...

Keyword(s):

Machine Learning ◽

Next Generation Sequencing ◽

Clinical Laboratory ◽

Next Generation ◽

Single Nucleotide Variants ◽

Test Set ◽

Clinical Laboratories ◽

Bona Fide ◽

Validation Set ◽

Generation Sequencing

Abstract BACKGROUND Molecular profiling has become essential for tumor risk stratification and treatment selection. However, cancer genome complexity and technical artifacts make identification of real variants a challenge. Currently, clinical laboratories rely on manual screening, which is costly, subjective, and not scalable. We present a machine learning–based method to distinguish artifacts from bona fide single-nucleotide variants (SNVs) detected by next-generation sequencing from nonformalin-fixed paraffin-embedded tumor specimens. METHODS A cohort of 11278 SNVs identified through clinical sequencing of tumor specimens was collected and divided into training, validation, and test sets. Each SNV was manually inspected and labeled as either real or artifact as part of clinical laboratory workflow. A 3-class (real, artifact, and uncertain) model was developed on the training set, fine-tuned with the validation set, and then evaluated on the test set. Prediction intervals reflecting the certainty of the classifications were derived during the process to label “uncertain” variants. RESULTS The optimized classifier demonstrated 100% specificity and 97% sensitivity over 5587 SNVs of the test set. Overall, 1252 of 1341 true-positive variants were identified as real, 4143 of 4246 false-positive calls were deemed artifacts, whereas only 192 (3.4%) SNVs were labeled as “uncertain,” with zero misclassification between the true positives and artifacts in the test set. CONCLUSIONS We presented a computational classifier to identify variant artifacts detected from tumor sequencing. Overall, 96.6% of the SNVs received definitive labels and thus were exempt from manual review. This framework could improve quality and efficiency of the variant review process in clinical laboratories.

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The Application of Control Materials for Ongoing Quality Management of Next-Generation Sequencing in a Clinical Genetic Laboratory

Medicina ◽

10.3390/medicina57060543 ◽

2021 ◽

Vol 57 (6) ◽

pp. 543

Author(s):

Young-Kyu Min ◽

Kyung-Sun Park

Keyword(s):

Quality Control ◽

Next Generation Sequencing ◽

Cell Lines ◽

Method Development ◽

High Throughput Sequencing ◽

Massively Parallel Sequencing ◽

Material Selection ◽

Next Generation ◽

Clinical Genetic ◽

Generation Sequencing

Next-generation sequencing (NGS) has played an important role in detecting genetic variants with pathologic and therapeutic potential. The advantages of NGS, such as high-throughput sequencing capacity and massively parallel sequencing, have a significant impact on realization of genetic profiling in clinical genetic laboratories. These changes have enabled clinicians to execute precision medicine in diagnosis, prognosis, and treatment for patients. However, to adapt targeted gene panels in diagnostic use, analytical validation and ongoing quality control should be implemented and applied with both practical guidelines and appropriate control materials. Several guidelines for NGS quality control recommend usage of control materials such as HapMap cell lines, synthetic DNA fragments, and genetically characterized cell lines; however, specifications or applications of such usage are insufficient to guideline method development. This review focuses on what factors should be considered before control material selection for NGS assay and practical methods of how they could be developed in clinical genetic laboratories. This review also provides the detailed sources of critical information related to control materials.

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Targeted Next-Generation Sequencing for Human Leukocyte Antigen Typing in a Clinical Laboratory: Metrics of Relevance and Considerations for Its Successful Implementation

Archives of Pathology & Laboratory Medicine ◽

10.5858/arpa.2016-0537-ra ◽

2017 ◽

Vol 141 (6) ◽

pp. 806-812 ◽

Cited By ~ 19

Author(s):

Manish J. Gandhi ◽

Deborah Ferriola ◽

Yanping Huang ◽

Jamie L. Duke ◽

Dimitri Monos

Keyword(s):

Next Generation Sequencing ◽

Clinical Laboratory ◽

Human Leukocyte ◽

Hla Typing ◽

Successful Implementation ◽

Next Generation ◽

Human Leukocyte Antigen Typing ◽

Clinical Laboratories ◽

Exon 1 ◽

Generation Sequencing

Context.— Numerous feasibility studies to type human leukocyte antigens (HLAs) by next-generation sequencing (NGS) have led to the development of vendor-supported kits for HLA typing by NGS. Some clinical laboratories have introduced HLA-NGS, and many are investigating the introduction. Standards from accrediting agencies form the regulatory framework for introducing this test into clinical laboratories. Objectives.— To provide an assessment of metrics and considerations relevant to the successful implementation of clinical HLA-NGS typing, and to provide as a reference a validated HLA-NGS protocol used clinically since December 2013 at the Children's Hospital of Philadelphia (Philadelphia, Pennsylvania). Data Sources.— The HLA-NGS has been performed on 2532 samples. The initial 1046 and all homozygous samples were also typed by an alternate method. The HLA-NGS demonstrated 99.7% concordance with the alternate method. Ambiguous results were most common at the DPB1 locus because of a lack of phasing between exons 2 and 3 or the unsequenced exon 1 (533 of 2954 alleles; 18.04%) and the DRB1 locus because of not sequencing exon 1 (75 of 3972 alleles; 1.89%). No ambiguities were detected among the other loci. Except for 2 false homozygous samples, all homozygous samples (1891) demonstrated concordance with the alternate method. The article is organized to address the critical elements in the preanalytic, analytic, and postanalytic phases of introducing this assay into the clinical laboratory. Conclusions.— The results demonstrate that HLA typing by NGS is a highly accurate, reproducible, efficient method that provides more-complete sequencing information for the length of the HLA gene and can be the single methodology for HLA typing in clinical immunogenetics laboratories.

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Next-Generation Sequencing Informatics: Challenges and Strategies for Implementation in a Clinical Environment

Archives of Pathology & Laboratory Medicine ◽

10.5858/arpa.2015-0507-ra ◽

2016 ◽

Vol 140 (9) ◽

pp. 958-975 ◽

Cited By ~ 42

Author(s):

Somak Roy ◽

William A. LaFramboise ◽

Yuri E. Nikiforov ◽

Marina N. Nikiforova ◽

Mark J. Routbort ◽

...

Keyword(s):

Next Generation Sequencing ◽

Clinical Laboratory ◽

Cost Effective ◽

Small Degree ◽

Clinical Informatics ◽

Next Generation ◽

Clinical Environment ◽

Next Generation Sequencing Technology ◽

Clinical Laboratories ◽

Generation Sequencing

Context.—Next-generation sequencing (NGS) is revolutionizing the discipline of laboratory medicine, with a deep and direct impact on patient care. Although it empowers clinical laboratories with unprecedented genomic sequencing capability, NGS has brought along obvious and obtrusive informatics challenges. Bioinformatics and clinical informatics are separate disciplines with typically a small degree of overlap, but they have been brought together by the enthusiastic adoption of NGS in clinical laboratories. The result has been a collaborative environment for the development of novel informatics solutions. Sustaining NGS-based testing in a regulated clinical environment requires institutional support to build and maintain a practical, robust, scalable, secure, and cost-effective informatics infrastructure. Objective.—To discuss the novel NGS informatics challenges facing pathology laboratories today and offer solutions and future developments to address these obstacles. Data Sources.—The published literature pertaining to NGS informatics was reviewed. The coauthors, experts in the fields of molecular pathology, precision medicine, and pathology informatics, also contributed their experiences. Conclusions.—The boundary between bioinformatics and clinical informatics has significantly blurred with the introduction of NGS into clinical molecular laboratories. Next-generation sequencing technology and the data derived from these tests, if managed well in the clinical laboratory, will redefine the practice of medicine. In order to sustain this progress, adoption of smart computing technology will be essential. Computational pathologists will be expected to play a major role in rendering diagnostic and theranostic services by leveraging “Big Data” and modern computing tools.

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Point-Counterpoint: Should We Be Performing Metagenomic Next-Generation Sequencing for Infectious Disease Diagnosis in the Clinical Laboratory?

Journal of Clinical Microbiology ◽

10.1128/jcm.01739-19 ◽

2019 ◽

Vol 58 (3) ◽

Cited By ~ 10

Author(s):

Steve Miller ◽

Charles Chiu ◽

Kyle G. Rodino ◽

Melissa B. Miller

Keyword(s):

Next Generation Sequencing ◽

Clinical Laboratory ◽

Disease Diagnosis ◽

Metagenomic Sequencing ◽

Infectious Agents ◽

Next Generation ◽

Sequencing Data ◽

Clinical Laboratories ◽

Generation Sequencing ◽

Selection Of

INTRODUCTION With established applications of next-generation sequencing in inherited diseases and oncology, clinical laboratories are evaluating the use of metagenomics for identification of infectious agents directly from patient samples, to aid in the diagnosis of infections. Metagenomic next-generation sequencing for infectious diseases promises an unbiased approach to detection of microbes that does not depend on growth in culture or the targeting of specific pathogens. However, the issues of contamination, interpretation of results, selection of databases used for analysis, and prediction of antimicrobial susceptibilities from sequencing data remain challenges. In this Point-Counterpoint, Steve Miller and Charles Chiu discuss the pros of using direct metagenomic sequencing, while Kyle Rodino and Melissa Miller argue for the use of caution.

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Next-Generation Sequencing: An Emerging Tool for Drug Designing

Current Pharmaceutical Design ◽

10.2174/1381612825666190911155508 ◽

2019 ◽

Vol 25 (31) ◽

pp. 3350-3357 ◽

Cited By ~ 1

Author(s):

Pooja Tripathi ◽

Jyotsna Singh ◽

Jonathan A. Lal ◽

Vijay Tripathi

Keyword(s):

Next Generation Sequencing ◽

High Throughput ◽

Large Scale ◽

Massively Parallel Sequencing ◽

Genomic Research ◽

Biological Research ◽

Next Generation ◽

Human Welfare ◽

Drug Designing ◽

Generation Sequencing

Background: With the outbreak of high throughput next-generation sequencing (NGS), the biological research of drug discovery has been directed towards the oncology and infectious disease therapeutic areas, with extensive use in biopharmaceutical development and vaccine production. Method: In this review, an effort was made to address the basic background of NGS technologies, potential applications of NGS in drug designing. Our purpose is also to provide a brief introduction of various Nextgeneration sequencing techniques. Discussions: The high-throughput methods execute Large-scale Unbiased Sequencing (LUS) which comprises of Massively Parallel Sequencing (MPS) or NGS technologies. The Next geneinvolved necessarily executes Largescale Unbiased Sequencing (LUS) which comprises of MPS or NGS technologies. These are related terms that describe a DNA sequencing technology which has revolutionized genomic research. Using NGS, an entire human genome can be sequenced within a single day. Conclusion: Analysis of NGS data unravels important clues in the quest for the treatment of various lifethreatening diseases and other related scientific problems related to human welfare.

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Next-generation sequencing in the clinical genetic screening of patients with pheochromocytoma and paraganglioma

Endocrine Connections ◽

10.1530/ec-13-0009 ◽

2013 ◽

Vol 2 (2) ◽

pp. 104-111 ◽

Cited By ~ 32

Author(s):

Joakim Crona ◽

Alberto Delgado Verdugo ◽

Dan Granberg ◽

Staffan Welin ◽

Peter Stålberg ◽

...

Keyword(s):

Next Generation Sequencing ◽

Genetic Screening ◽

Bioinformatics Analysis ◽

Cost Effective ◽

Susceptibility Genes ◽

Next Generation ◽

Clinical Genetic ◽

Cost Effective Method ◽

Agilent Sureselect ◽

Generation Sequencing

BackgroundRecent findings have shown that up to 60% of pheochromocytomas (PCCs) and paragangliomas (PGLs) are caused by germline or somatic mutations in one of the 11 hitherto known susceptibility genes: SDHA, SDHB, SDHC, SDHD, SDHAF2, VHL, HIF2A (EPAS1), RET, NF1, TMEM127 and MAX. This list of genes is constantly growing and the 11 genes together consist of 144 exons. A genetic screening test is extensively time consuming and expensive. Hence, we introduce next-generation sequencing (NGS) as a time-efficient and cost-effective alternative.MethodsTumour lesions from three patients with apparently sporadic PCC were subjected to whole exome sequencing utilizing Agilent Sureselect target enrichment system and Illumina Hi seq platform. Bioinformatics analysis was performed in-house using commercially available software. Variants in PCC and PGL susceptibility genes were identified.ResultsWe have identified 16 unique genetic variants in PCC susceptibility loci in three different PCC, spending less than a 30-min hands-on, in-house time. Two patients had one unique variant each that was classified as probably and possibly pathogenic: NF1 Arg304Ter and RET Tyr791Phe. The RET variant was verified by Sanger sequencing.ConclusionsNGS can serve as a fast and cost-effective method in the clinical genetic screening of PCC. The bioinformatics analysis may be performed without expert skills. We identified process optimization, characterization of unknown variants and determination of additive effects of multiple variants as key issues to be addressed by future studies.

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Lavage of the Uterine Cavity for Molecular Detection of Müllerian Duct Carcinomas: A Proof-of-Concept Study

Journal of Clinical Oncology ◽

10.1200/jco.2015.61.3083 ◽

2015 ◽

Vol 33 (36) ◽

pp. 4293-4300 ◽

Cited By ~ 43

Author(s):

Elisabeth Maritschnegg ◽

Yuxuan Wang ◽

Nina Pecha ◽

Reinhard Horvat ◽

Els Van Nieuwenhuysen ◽

...

Keyword(s):

Next Generation Sequencing ◽

Tumor Tissue ◽

Massively Parallel Sequencing ◽

Uterine Cavity ◽

Mullerian Duct ◽

Next Generation ◽

Benign Lesions ◽

Cavity Detection ◽

Müllerian Duct ◽

Generation Sequencing

Purpose Type II ovarian cancer (OC) and endometrial cancer (EC) are generally diagnosed at an advanced stage, translating into a poor survival rate. There is increasing evidence that Müllerian duct cancers may exfoliate cells. We have established an approach for lavage of the uterine cavity to detect shed cancer cells. Patients and Methods Lavage of the uterine cavity was used to obtain samples from 65 patients, including 30 with OC, five with EC, three with other malignancies, and 27 with benign lesions involving gynecologic organs. These samples, as well as corresponding tumor tissue, were examined for the presence of somatic mutations using massively parallel sequencing (next-generation sequencing) and, in a subset, singleplex analysis. Results The lavage technique could be applied successfully, and sufficient amounts of DNA were obtained in all patients. Mutations, mainly in TP53, were identified in 18 (60%) of 30 lavage samples of patients with OC using next-generation sequencing. Singleplex analysis of mutations previously determined in corresponding tumor tissue led to further identification of six patients. Taken together, in 24 (80%) of 30 patients with OC, specific mutations could be identified. This also included one patient with occult OC. All five analyzed lavage specimens from patients with EC harbored mutations. Eight (29.6%) of 27 patients with benign lesions tested positive for mutations, six (75%) as a result of mutations in the KRAS gene. Conclusion This study proved that tumor cells from ovarian neoplasms are shed and can be collected via lavage of the uterine cavity. Detection of OC and EC and even clinically occult OC was achieved, making it a potential tool of significant promise for early diagnosis.

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