scholarly journals Clinical Validation of a Myeloid Next-Generation Sequencing Panel for Single-Nucleotide Variants, Insertions/Deletions, and Fusion Genes

2020 ◽  
Vol 22 (2) ◽  
pp. 208-219 ◽  
Author(s):  
Iyare Izevbaye ◽  
Li Y. Liang ◽  
Cheryl Mather ◽  
Soufiane El-Hallani ◽  
Remegio Maglantay ◽  
...  
2016 ◽  
Vol 140 (10) ◽  
pp. 1085-1091 ◽  
Author(s):  
Eric J. Duncavage ◽  
Haley J. Abel ◽  
Jason D. Merker ◽  
John B. Bodner ◽  
Qin Zhao ◽  
...  

Context.—Most current proficiency testing challenges for next-generation sequencing assays are methods-based proficiency testing surveys that use DNA from characterized reference samples to test both the wet-bench and bioinformatics/dry-bench aspects of the tests. Methods-based proficiency testing surveys are limited by the number and types of mutations that either are naturally present or can be introduced into a single DNA sample. Objective.—To address these limitations by exploring a model of in silico proficiency testing in which sequence data from a single well-characterized specimen are manipulated electronically. Design.—DNA from the College of American Pathologists reference genome was enriched using the Illumina TruSeq and Life Technologies AmpliSeq panels and sequenced on the MiSeq and Ion Torrent platforms, respectively. The resulting data were mutagenized in silico and 26 variants, including single-nucleotide variants, deletions, and dinucleotide substitutions, were added at variant allele fractions (VAFs) from 10% to 50%. Participating clinical laboratories downloaded these files and analyzed them using their clinical bioinformatics pipelines. Results.—Laboratories using the AmpliSeq/Ion Torrent and/or the TruSeq/MiSeq participated in the 2 surveys. On average, laboratories identified 24.6 of 26 variants (95%) overall and 21.4 of 22 variants (97%) with VAFs greater than 15%. No false-positive calls were reported. The most frequently missed variants were single-nucleotide variants with VAFs less than 15%. Across both challenges, reported VAF concordance was excellent, with less than 1% median absolute difference between the simulated VAF and mean reported VAF. Conclusions.—The results indicate that in silico proficiency testing is a feasible approach for methods-based proficiency testing, and demonstrate that the sensitivity and specificity of current next-generation sequencing bioinformatics across clinical laboratories are high.


2020 ◽  
Vol 2 (3) ◽  
Author(s):  
Ross G Murphy ◽  
Aideen C Roddy ◽  
Shambhavi Srivastava ◽  
Esther Baena ◽  
David J Waugh ◽  
...  

Abstract Combining alignment-free methods for phylogenetic analysis with multi-regional sampling using next-generation sequencing can provide an assessment of intra-patient tumour heterogeneity. From multi-regional sampling divergent branching, we validated two different lesions within a patient’s prostate. Where multi-regional sampling has not been used, a single sample from one of these areas could misguide as to which drugs or therapies would best benefit this patient, due to the fact these tumours appear to be genetically different. This application has the power to render, in a fraction of the time used by other approaches, intra-patient heterogeneity and decipher aberrant biomarkers. Another alignment-free method for calling single-nucleotide variants from raw next-generation sequencing samples has determined possible variants and genomic locations that may be able to characterize the differences between the two main branching patterns. Alignment-free approaches have been applied to relevant clinical multi-regional samples and may be considered as a valuable option for comparing and determining heterogeneity to help deliver personalized medicine through more robust efforts in identifying targetable pathways and therapeutic strategies. Our study highlights the application these tools could have on patient-aligned treatment indications.


2020 ◽  
Vol 66 (8) ◽  
pp. 1084-1092 ◽  
Author(s):  
Eddy N de Boer ◽  
Lennart F Johansson ◽  
Kim de Lange ◽  
Anneke G Bosga-Brouwer ◽  
Eva van den Berg ◽  
...  

Abstract Background Measuring minimal residual disease (MRD), the persistence of leukemic cells after treatment, is important for monitoring leukemia recurrence. The current methods for monitoring MRD are flow cytometry, to assess aberrant immune phenotypes, and digital droplet PCR (ddPCR), to target genetic aberrations such as single-nucleotide variants and gene fusions. We present the performance of an RNA-based next-generation sequencing (NGS) method for MRD gene fusion detection compared with ddPCR. This method may have advantages, including the capacity to analyze different genetic aberrations and patients in 1 experiment. In particular, detection at the RNA level may be highly sensitive if the genetic aberration is highly expressed. Methods We designed a probe-based NGS panel targeting the breakpoints of 11 fusion genes previously identified in clinical patients and 2 fusion genes present in cell lines. Blocking probes were added to prevent nonspecific enrichment. Each patient RNA sample was diluted in background RNA, depleted for rRNA and globin mRNA, converted to cDNA, and prepared for sequencing. Unique sequence reads, identified by unique molecular identifiers, were aligned directly to reference transcripts. The same patient and cell-line samples were also analyzed with ddPCR for direct comparison. Results Our NGS method reached a maximum sensitivity of 1 aberrant cell in 10 000 cells and was mostly within a factor of 10 compared with ddPCR. Conclusions Our detection limit was below the threshold of 1:1000 recommended by European Leukemia Net. Further optimizations are easy to implement and are expected to boost the sensitivity of our method to diagnostically obtained ddPCR thresholds.


2010 ◽  
Vol 26 (6) ◽  
pp. 730-736 ◽  
Author(s):  
Rodrigo Goya ◽  
Mark G.F. Sun ◽  
Ryan D. Morin ◽  
Gillian Leung ◽  
Gavin Ha ◽  
...  

2013 ◽  
Vol 14 (1) ◽  
pp. 225 ◽  
Author(s):  
Jiawen Bian ◽  
Chenglin Liu ◽  
Hongyan Wang ◽  
Jing Xing ◽  
Priyanka Kachroo ◽  
...  

2012 ◽  
Vol 41 (1) ◽  
pp. e16-e16 ◽  
Author(s):  
Michael Forster ◽  
Peter Forster ◽  
Abdou Elsharawy ◽  
Georg Hemmrich ◽  
Benjamin Kreck ◽  
...  

2017 ◽  
Vol 141 (6) ◽  
pp. 751-758 ◽  
Author(s):  
Elizabeth P. Garcia ◽  
Alissa Minkovsky ◽  
Yonghui Jia ◽  
Matthew D. Ducar ◽  
Priyanka Shivdasani ◽  
...  

Context.— The analysis of somatic mutations across multiple genes in cancer specimens may be used to aid clinical decision making. The analytical validation of targeted next-generation sequencing panels is important to assess accuracy and limitations. Objective.— To report the development and validation of OncoPanel, a custom targeted next-generation sequencing assay for cancer. Design.— OncoPanel was designed for the detection of single-nucleotide variants, insertions and deletions, copy number alterations, and structural variants across 282 genes with evidence as drivers of cancer biology. We implemented a validation strategy using formalin-fixed, paraffin-embedded, fresh or frozen samples compared with results obtained by clinically validated orthogonal technologies. Results.— OncoPanel achieved 98% sensitivity and 100% specificity for the detection of single-nucleotide variants, and 84% sensitivity and 100% specificity for the detection of insertions and deletions compared with single-gene assays and mass spectrometry–based genotyping. Copy number detection achieved 86% sensitivity and 98% specificity compared with array comparative genomic hybridization. The sensitivity of structural variant detection was 74% compared with karyotype, fluorescence in situ hybridization, and polymerase chain reaction. Sensitivity was affected by inconsistency in the detection of FLT3 and NPM1 alterations and IGH rearrangements due to design limitations. Limit of detection studies demonstrated 98.4% concordance across triplicate runs for variants with allele fraction greater than 0.1 and at least 50× coverage. Conclusions.— The analytical validation of OncoPanel demonstrates the ability of targeted next-generation sequencing to detect multiple types of genetic alterations across a panel of genes implicated in cancer biology.


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