Validation of a next generation sequencing panel for detection of hotspot cancer mutations in a clinical laboratory

2017 ◽  
Vol 213 (2) ◽  
pp. 98-105 ◽  
Author(s):  
Reza Shahsiah ◽  
Jenefer DeKoning ◽  
Saeed Samie ◽  
Seyed Ziaeddin Latifzadeh ◽  
Zahra Mehdizadeh Kashi
Keyword(s):  
Next Generation Sequencing ◽  
Clinical Laboratory ◽  
Next Generation ◽  
Cancer Mutations ◽  
Generation Sequencing

scholarly journals Next-generation sequencing as a clinical laboratory tool for describing different microbiotas: an urgent need for future paediatric practice

2021 ◽  
pp. archdischild-2021-321683
Author(s):  
Richard Hansen ◽  
Mona Bajaj-Elliott ◽  
Georgina L Hold ◽  
Konstantinos Gerasimidis ◽  
Tariq H Iqbal ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Clinical Laboratory ◽  
Next Generation ◽  
Paediatric Practice ◽  
Laboratory Tool ◽  
Generation Sequencing

scholarly journals Implementation of Cloud based Next Generation Sequencing data analysis in a clinical laboratory

2014 ◽  
Vol 7 (1) ◽  
pp. 314 ◽  
Author(s):  
Getiria Onsongo ◽  
Jesse Erdmann ◽  
Michael D Spears ◽  
John Chilton ◽  
Kenneth B Beckman ◽  
...  
Keyword(s):  
Data Analysis ◽  
Next Generation Sequencing ◽  
Clinical Laboratory ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
Generation Sequencing ◽  
Sequencing Data Analysis

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

2019 ◽  
Vol 66 (1) ◽  
pp. 239-246 ◽  
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.

scholarly journals Digital PCR—An Emerging Technology with Broad Applications in Microbiology

2019 ◽  
Vol 66 (1) ◽  
pp. 117-123 ◽  
Author(s):  
Stephen J Salipante ◽  
Keith R Jerome
Keyword(s):  
Next Generation Sequencing ◽  
Quantitative Pcr ◽  
Clinical Microbiology ◽  
Clinical Laboratory ◽  
Digital Pcr ◽  
Emerging Technology ◽  
Next Generation ◽  
Powerful Technique ◽  
Advantages And Disadvantages ◽  
Generation Sequencing

Abstract BACKGROUND The PCR and its variant, quantitative PCR (qPCR), have revolutionized the practice of clinical microbiology. Continued advancements in PCR have led to a new derivative, digital PCR (dPCR), which promises to address certain limitations inherent to qPCR. CONTENT Here we highlight the important technical differences between qPCR and dPCR, and the potential advantages and disadvantages of each. We then review specific situations in which dPCR has been implemented in clinical microbiology and the results of such applications. Finally, we attempt to place dPCR in the context of other emerging technologies relevant to the clinical laboratory, including next-generation sequencing. SUMMARY dPCR offers certain clear advantages over traditional qPCR, but these are to some degree offset by limitations of the technology, at least as currently practiced. Laboratories considering implementation of dPCR should carefully weigh the potential advantages and disadvantages of this powerful technique for each specific application planned.

scholarly journals Using a Next Generation Sequencing Panel to Discover the Obscure Causes of Hereditary Hemolytic Anemias

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 2433-2433 ◽  
Author(s):  
Archana M Agarwal ◽  
N. Scott Reading ◽  
Kimberly Frizzell ◽  
Wei Shen ◽  
Shelly Sorrells ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Hemolytic Anemia ◽  
Clinical Laboratory ◽  
Single Gene ◽  
Cytoskeletal Proteins ◽  
Next Generation ◽  
Pathogenic Variants ◽  
Late Morbidity ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing

Abstract Hereditary hemolytic anemias are a heterogeneous group of disorders with consequences ranging from non-anemic hemolysis to severe life-threatening anemia. However, the late morbidity in patients without transfusions is often underappreciated because of erythropoietic compensatory stimulation inducing hematopoiesis by erythroferrone/hepcidin axis. Principal causes of hereditary hemolytic anemias are germline mutations of red cell cytoskeleton (e.g. hereditary spherocytosis and elliptocytosis/pyropoikilocytosis) or enzyme deficiencies (e.g. Glucose 6 phosphate dehydrogenase deficiency and pyruvate kinase deficiency). Routine morphological and biochemical analysis may be inconclusive and misleading particularly in transfusion-dependent infants and children. Molecular studies have not been extensively used to diagnose these disorders due to the complex genetic nature of these disorders, and multi-gene disorders. In these cases, patients may undergo multiple rounds of single gene testing, which can be very costly and time consuming. The advent of next generation sequencing (NGS) methods in the clinical laboratory has made diagnosing complex genetic disorders feasible. Our diagnostic panel includes 28 genes encoding cytoskeletal proteins and enzymes, and covers the complete coding region, splice site junctions, and, where appropriate, deep intronic or regulatory regions. Targeted gene capture and library construction for next-generation sequencing (NGS) was performed using Sure Select kit (Agilent Technologies, Santa Clara, USA). Prior to sequencing on the Illumina Next Seq, (Illumina Inc) instrument, indexed samples are quantified using qPCR and then pooled. Samples were sequenced using 2x150 paired end sequencing. We now report the first 68 patients evaluated using our NGS panel. The age of the patients ranged from newborn to 62 years. These patients presented with symptoms ranging from mild lifelong anemia to severe hemolytic anemia with extreme hyperbilirubinemia. Genetic variants were classified using the American College of Medical Genetics (ACMG) guidelines. We identified pathogenic variants in 11 patients and likely pathogenic variants in 12 others, the majority of these were novel. Many variants with unknown significance were also identified that could potentially contribute to disease. The most commonly mutated genes were SPTB and SPTA1, encoding spectrin subunits. Some complex interactions were uncovered i.e. SPTA1 mutations along with alpha LELY leading to hereditary pyropoikilocytosis; Spectrin variants along with Gilbert syndrome causing severe hyperbilirubinemia in neonates; and Spectrin variants in combination with PKLR and G6PD variants. Our results demonstrate that many patients with hemolytic anemia harbor complex combinations of known and novel mutations in RBC cytoskeleton/enzyme genes, but their clinical significance is further augmented by polymorphisms of UGT1A1 gene contributing to severe neonatal hyperbilirubinemia and its consequences. To conclude, next-generation sequencing provides a cost-effective and relatively rapid approach to molecular diagnosis, especially in instances where traditional testing failed. We have used this technology successfully to determine the molecular causes of hemolytic anemia in many cases with no prior family history. Disclosures Yaish: Octapharma: Other: Study investigator.

scholarly journals Assuring the quality of next-generation sequencing in clinical laboratory practice

2012 ◽  
Vol 30 (11) ◽  
pp. 1033-1036 ◽  
Author(s):  
Amy S Gargis ◽  
Lisa Kalman ◽  
Meredith W Berry ◽  
David P Bick ◽  
David P Dimmock ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Clinical Laboratory ◽  
Next Generation ◽  
Laboratory Practice ◽  
Generation Sequencing

scholarly journals How Do Advanced Molecular Tests Compare to Routine Clinical Laboratory Evaluation of CSF in Meningoencephalitis? A Study in 10 Urban Emergency Departments Across the USA

2017 ◽  
Vol 4 (suppl_1) ◽  
pp. S8-S9 ◽  
Author(s):  
Toby L Merlin ◽  
Scott Chancey ◽  
Yueli Zheng ◽  
Brad Bowzard ◽  
Leah Fischer ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Pilot Study ◽  
Emergency Departments ◽  
Clinical Laboratory ◽  
Targeted Sequencing ◽  
Laboratory Evaluation ◽  
Next Generation ◽  
Molecular Tests ◽  
Causative Agents ◽  
Generation Sequencing

Abstract Background The EMERGEncy ID Net Study Group is investigating whether advanced molecular tests (AMT) increase the detection of causative agents in the CSF of patients presenting with meningoencephalitis (ME). We report findings from a pilot study using AMT on 18 CSF samples from 10 US Urban Emergency Departments. The purpose of the pilot was to compare the performance of these four AMT to established clinical laboratory methods. Methods We investigated four AMT: (1) BioFire FilmArray ME Panel targeting 14 causative agents; (2) an in-house target-directed next generation sequencing assay targeting 25 agents; (3) a microarray capable of detecting >2,500 agents; and (4) deep metagenomic next generation sequencing. For targeted sequencing, loci from 12 DNA-based and 13 RNA-based pathogens were amplified from the extracts by multiplex PCR. All sequencing was performed on an Illumina MiSeq using 500 cycle v2 Reagent Kits. Reads from the targeted sequencing were aligned to the 25 specific reference target sequences using Bowtie2 while metagenomics reads were processed with the taxonomic sequence classifying software Kraken. For microarray analysis, Lawrence Livermore Microbial Detection Array v2 arrays were hybridized with Cy3-labeled DNA or cDNA. Scanned images of arrays were analyzed by CLiMax 3.1. Results Eight CSF samples had results positive for well-established causes of ME from prior testing (Table). The pilot study demonstrated none of the four AMT detected all causative agents in the eight CSF samples known to have well-established causes of ME. BioFire and targeted sequencing performed best, both detecting 6/8, metagenomics deep sequencing detected 3/8, and microarray detected 1/8. Conclusion Despite the sophistication of AMT, they cannot detect pathogens they do not target, that are present in small numbers, or that have been eliminated from the CSF by the immune response. Despite the theoretical potential for microarray and metagenomic sequencing to detect thousands of different agents, the agents probably must be present at high levels for detection. Disclosures All authors: No reported disclosures.

Next generation sequencing of non-muscle invasive bladder cancer to reveal potential biomarkers and rational therapeutic targets.

2017 ◽  
Vol 35 (6_suppl) ◽  
pp. 302-302
Author(s):  
Eugene J. Pietzak ◽  
Eugene K. Cha ◽  
Aditya Bagrodia ◽  
Esther N. Drill ◽  
Gopa Iyer ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Cox Regression ◽  
Clinical Laboratory ◽  
Genetic Alterations ◽  
Gene Panel ◽  
Next Generation ◽  
Cox Regression Analysis ◽  
Bcg Therapy ◽  
Pre Treatment ◽  
Generation Sequencing

302 Background: We examined a cohort of index pre-treatment NMIBC tumors using Next Generation Sequencing to identify genetic alterations with potential clinical implications. Methods: 105 patients on a prospective IRB-approved protocol had their pre-treatment index NMIBC tumor and matched germline DNA sequenced with a 341 cancer-associated gene panel in a CLIA-certified clinical laboratory. A genitourinary pathologist reviewed representative H&E slides to confirm grade, stage, and urothelial histology. Restaging TUR was performed in all HGT1 tumors. Results: To characterize the genomic landscape of NMIBC, we analyzed 105 tumors across the disease spectrum including LGTa (n = 23), HGTis (n = 12), HGTa (n = 32) and HGT1 (n = 38). The most frequently altered genes in NMIBC were the TERT promoter (74%), FGFR3 (50%), KDM6A (47%), ARID1A (28%), PIK3CA (27%), KMT2D (24%), STAG2 (21%), and CDKN2A (17%). 81% of tumors had inactivating alterations in a chromatin-modifying gene. Alterations in the RTK/RAS/PIK3 pathway occurred in 83% of tumors, including 58% of high-grade NMIBC having alterations in either ERBB2 or FGFR3. Of the 105 patients, 62 were treated uniformly with a 6-week induction course of BCG without maintenance. We investigated all genes altered on the 341-gene panel in at least 5 patients for their association with recurrence after BCG therapy in this 62 patient cohort. On cox-regression analysis, only truncating mutations in the chromatin-modifying gene ARID1A were associated with recurrence after BCG (HR = 3.14 [95%CI = 1.51, 6.51] p = 0.002). This remained significant when adjusting for multiple comparisons (p = 0.04) and when including ARID1A missense mutations of unknown significance (p = 0.002). Conclusions: Next Generation Sequencing of index pre-treatment NMIBC tumors identified an association between ARID1A mutations and recurrence after BCG therapy. Further investigation is needed to determine whether ARID1A mutations are a potential predictive/prognostic biomarker or therapeutic target. Moreover, most NMIBC tumors had at least one potentially “actionable” alteration that could serve as a target in rationally designed trials of intravesical or systemic therapy.

scholarly journals Bioinformatics for Clinical Next Generation Sequencing

2015 ◽  
Vol 61 (1) ◽  
pp. 124-135 ◽  
Author(s):  
Gavin R Oliver ◽  
Steven N Hart ◽  
Eric W Klee
Keyword(s):  
Next Generation Sequencing ◽  
Service Providers ◽  
Clinical Laboratory ◽  
Work Flow ◽  
Next Generation ◽  
Sequencing Data ◽  
Regulatory Requirements ◽  
Bioinformatics Analyses ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing

Abstract BACKGROUND Next generation sequencing (NGS)-based assays continue to redefine the field of genetic testing. Owing to the complexity of the data, bioinformatics has become a necessary component in any laboratory implementing a clinical NGS test. CONTENT The computational components of an NGS-based work flow can be conceptualized as primary, secondary, and tertiary analytics. Each of these components addresses a necessary step in the transformation of raw data into clinically actionable knowledge. Understanding the basic concepts of these analysis steps is important in assessing and addressing the informatics needs of a molecular diagnostics laboratory. Equally critical is a familiarity with the regulatory requirements addressing the bioinformatics analyses. These and other topics are covered in this review article. SUMMARY Bioinformatics has become an important component in clinical laboratories generating, analyzing, maintaining, and interpreting data from molecular genetics testing. Given the rapid adoption of NGS-based clinical testing, service providers must develop informatics work flows that adhere to the rigor of clinical laboratory standards, yet are flexible to changes as the chemistry and software for analyzing sequencing data mature.

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