The use of technical replication for detection of low-level somatic mutations in next-generation sequencing.
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ABSTRACT:
SUBMITTER: Kim J
PROVIDER: S-EPMC6400950 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Next-generation DNA sequencing promises to revolutionize clinical medicine and basic research. However, while this technology has the capacity to generate hundreds of billions of nucleotides of DNA sequence in a single experiment, the error rate of ~1% results in hundreds of millions of sequencing mistakes. These scattered errors can be tolerated in some applications but become extremely problematic when "deep sequencing" genetically heterogeneous mixtures, such as tumors or mixed microbial populations. To overcome limitations in sequencing accuracy, we have developed a method termed Duplex Sequencing. This approach greatly reduces errors by independently tagging and sequencing each of the two strands of a DNA duplex. As the two strands are complementary, true mutations are found at the same position in both strands. In contrast, PCR or sequencing errors result in mutations in only one strand and can thus be discounted as technical error. We determine that Duplex Sequencing has a theoretical background error rate of less than one artifactual mutation per billion nucleotides sequenced. In addition, we establish that detection of mutations present in only one of the two strands of duplex DNA can be used to identify sites of DNA damage. We apply the method to directly assess the frequency and pattern of random mutations in mitochondrial DNA from human cells.
| S-EPMC3437896 | biostudies-other
Project description:This is a prospective, single-center, clinical study.This study is to evaluate the feasibility of genetic susceptibility screening based on the detection of tumor tissue mutations by a NGS panel.
| 2330960 | ecrin-mdr-crc
Project description:BACKGROUND:Targeted next generation sequencing (NGS) technology to assess the mutational status of multiple genes on formalin-fixed, paraffin embedded (FFPE) tumors is rapidly being adopted in clinical settings, where quality control (QC) practices are required. Establishing reliable FFPE QC materials for NGS can be challenging and/or expensive. Here, we established a reliable and cost-effective FFPE QC material for routine utilization in the Ion AmpliSeq™ Cancer Hotspot Panel v2 (CHP2) assay. METHODS:The performance characteristics of the CHP2 assay were determined by sequencing various cell line mixtures and 55 different FFPE tumors on the Ion Torrent PGM platform. A FFPE QC material was prepared from a mixture of cell lines derived from different cancers, comprising single nucleotide variants and small deletions on actionable genes at different allelic frequencies. RESULTS:The CHP2 assay performed with high precision and sensitivity when custom variant calling pipeline parameters where established. In addition, all expected somatic variants in the QC material were consistently called at variant frequencies ranging from 9.1 % (CV = 11.1 %) to 37.9 % (CV = 2.8 %). CONCLUSIONS:The availability of a reliable and cost-effective QC material is instrumental in assessing the performance of this or any targeted NGS assay that detects somatic variants in fixed solid tumor specimens.
| S-EPMC4573924 | biostudies-other
Project description:PurposePrimary central nervous system lymphomas (PCNSL) have recurrent genomic alterations. The main objective of our study was to demonstrate that targeted sequencing of circulating cell-free DNA (cfDNA) released by PCNSL at the time of diagnosis could identify somatic mutations by next-generation sequencing (NGS).Patients and methodsPlasmacfDNA and matched tumor DNA (tDNA) from 25 PCNSL patients were sequenced using an Ion Torrent Personal Genome Machine (Life Technologies®). First, patient-specific targeted sequencing of identified somatic mutations in tDNA was performed. Then, a second sequencing targeting MYD88 c.T778C was performed and compared to plasma samples from 25 age-matched control patients suffering from other types of cancer.ResultsAccording to the patient-specific targeted sequencing, eight patients (32% [95% CI 15-54%]) had detectable somatic mutations in cfDNA. Considering MYD88 sequencing, six patients had the specific c.T778C alteration detected in plasma. Using a control group, the sensitivity was 24% [9-45%] and the specificity was 100%. Tumor volume or deep brain structure involvement did not influence the detection of somatic mutations in plasma.ConclusionThis pilot study provided evidence that somatic mutations can be detected by NGS in the cfDNA of a subset of patients suffering from PCNSL.
| S-EPMC5564634 | biostudies-literature
Project description:The overall prevalence of germline BRCA1/2 mutations is estimated between 11% and 15% of all ovarian cancers. Individuals with germline BRCA1/2 alterations treated with the PARP1 inhibitors (iPARP1) tend to respond better than patients with wild-type BRCA1/2. Additionally, also somatic BRCA1/2 alterations induce the sensitivity to iPARP1. Therefore, the detection of both germline and somatic BRCA1/2 mutations is required for effective iPARP1 treatment. The aim of this study was to identify the frequency and spectrum of germline and somatic BRCA1/2 alterations in a group of Polish patients with ovarian serous carcinoma. In total, 100 formalin-fixed paraffin-embedded (FFPE) ovarian serous carcinoma tissues were enrolled to the study. Mutational analysis of BRCA1/2 genes was performed by using next-generation sequencing. The presence of pathogenic variants was confirmed by Sanger sequencing. In addition, to confirm the germline or somatic status of the mutation, the nonneoplastic tissue was analyzed by bidirectional Sanger sequencing. In total, 27 (28% of patient samples) mutations (20 in BRCA1 and 7 in BRCA2) were identified. For 22 of 27 patients, nonneoplastic cells were available and sequencing revealed the somatic character of two BRCA1 (2/16; 12.5%) and two BRCA2 (2/6; 33%) mutations. Notably, we identified six novel frameshift or nonsense BRCA1/2 mutations. The heterogeneity of the detected mutations confirms the necessity of simultaneous analysis of BRCA1/2 genes in all patients diagnosed with serous ovarian carcinoma. Moreover, the use of tumor tissue for mutational analysis allowed the detection of both somatic and germline BRCA1/2 mutations.
| S-EPMC4867663 | biostudies-literature
Project description:BackgroundSomatic variant callers are used to find mutations in sequencing data from cancer samples. They are very sensitive and have high recall, but also may produce low precision data with a large proportion of false positives. Further ad hoc filtering is commonly performed after variant calling and before further analysis. Improving the filtering of somatic variants in a reproducible way represents an unmet need. We have developed Filters for Next Generation Sequencing (FiNGS), software written specifically to address these filtering issues.ResultsDeveloped and tested using publicly available sequencing data sets, we demonstrate that FiNGS reliably improves upon the precision of default variant caller outputs and performs better than other tools designed for the same task.ConclusionsFiNGS provides researchers with a tool to reproducibly filter somatic variants that is simple to both deploy and use, with filters and thresholds that are fully configurable by the user. It ingests and emits standard variant call format (VCF) files and will slot into existing sequencing pipelines. It allows users to develop and implement their own filtering strategies and simple sharing of these with others.
| S-EPMC7890800 | biostudies-literature
Project description:BackgroundAllele specific real-time PCR and next-generation sequencing (NGS) are widely used to detect somatic mutation in non-small cell lung cancer (NSCLC). Both methods commonly use formalin-fixed paraffin-embedded (FFPE) tissues as diagnostic materials. Real-time PCR has the advantage of being easy to use and more tolerant of variable DNA quality, but has limited multiplex capability. NGS, in contrast, allows simultaneous analysis of many genomic loci while revealing the exact sequence changes; it is, however, more technically demanding and more expensive to employed. A challenge for both platforms is the varied limit of detection (LoD) for target genomic loci, even within the same gene. The variability of detection sensitivity may be problematic if well-known actionable somatic mutations are missed.CasesWe compared LoDs between real-time PCR and targeted NGS tests for some commonly observed EGFR mutations in NSCLC specimens.ConclusionsThe FDA-approved real-time PCR test was superior to the NGS in detecting low level EGFR exon 19 deletion (near 1% variant allele fraction (VAF)). The cancer hotspot NGS detects low level EGFR c.2369C > T, p.T790M (2-5% VAF) better than the FDA-approved real-time PCR method. We conclude that the real-time PCR and hotspot NGS methods have complementary strengths in accurately determining clinically important EGFR mutations in NSCLC.
| S-EPMC6656700 | biostudies-literature
Project description:BackgroundGiven the modest responses to everolimus, a mTOR inhibitor, in multiple tumor types, there is a pressing need to identify predictive biomarkers for this drug. Using targeted ultra-deep sequencing, we aimed to explore genomic alterations that confer extreme sensitivity to everolimus.ResultsWe collected formalin-fixed paraffin-embedded tumor/normal pairs from 39 patients (22 with exceptional clinical benefit, 17 with no clinical benefit) who were treated with everolimus across various tumor types (13 gastric cancers, 15 renal cell carcinomas, 2 thyroid cancers, 2 head and neck cancer, and 7 sarcomas). Ion AmpliSeqTM Comprehensive Cancer Panel was used to identify alterations across all exons of 409 target genes. Tumors were sequenced to a median coverage of 552x. Cancer genomes are characterized by 219 somatic single-nucleotide variants (181 missense, 9 nonsense, 7 splice-site) and 22 frameshift insertions/deletions, with a median of 2.1 mutations per Mb (0 to 12.4 mutations per Mb). Overall, genomic alterations with activating effect on mTOR signaling were identified in 10 of 22 (45%) patients with clinical benefit and these include MTOR, TSC1, TSC2, NF1, PIK3CA and PIK3CG mutations. Recurrently mutated genes in chromatin remodeling genes (BAP1; n = 2, 12%) and receptor tyrosine kinase signaling (FGFR4; n = 2, 12%) were noted only in patients without clinical benefit.ConclusionsRegardless of different cancer types, mTOR-pathway-activating mutations confer sensitivity to everolimus. Targeted sequencing of mTOR pathway genes facilitates identification of potential candidates for mTOR inhibitors.
| S-EPMC4891139 | biostudies-literature
Project description:Identification of somatic single nucleotide variants (SNVs) in tumour genomes is a necessary step in defining the mutational landscapes of cancers. Experimental designs for genome-wide ascertainment of somatic mutations now routinely include next-generation sequencing (NGS) of tumour DNA and matched constitutional DNA from the same individual. This allows investigators to control for germline polymorphisms and distinguish somatic mutations that are unique to the tumour, thus reducing the burden of labour-intensive and expensive downstream experiments needed to verify initial predictions. In order to make full use of such paired datasets, computational tools for simultaneous analysis of tumour-normal paired sequence data are required, but are currently under-developed and under-represented in the bioinformatics literature.In this contribution, we introduce two novel probabilistic graphical models called JointSNVMix1 and JointSNVMix2 for jointly analysing paired tumour-normal digital allelic count data from NGS experiments. In contrast to independent analysis of the tumour and normal data, our method allows statistical strength to be borrowed across the samples and therefore amplifies the statistical power to identify and distinguish both germline and somatic events in a unified probabilistic framework.The JointSNVMix models and four other models discussed in the article are part of the JointSNVMix software package available for download at http://compbio.bccrc.casshah@bccrc.caSupplementary data are available at Bioinformatics online.
| S-EPMC3315723 | biostudies-literature
Project description:Somatic structural variants (SVs), which are variants that typically impact >50 nucleotides, play a significant role in cancer development and evolution but are notoriously more difficult to detect than small variants from short-read next-generation sequencing (NGS) data. This is due to a combination of challenges attributed to the purity of tumour samples, tumour heterogeneity, limitations of short-read information from NGS and sequence alignment ambiguities. In spite of active development of SV detection tools (callers) over the past few years, each method has inherent advantages and limitations. In this review, we highlight some of the important factors affecting somatic SV detection and compared the performance of seven commonly used SV callers. In particular, we focus on the extent of change in sensitivity and precision for detecting different SV types and size ranges from samples with differing variant allele frequencies and sequencing depths of coverage. We highlight the reasons for why some SV callers perform well in some settings but not others, allowing our evaluation findings to be extended beyond the seven SV callers examined in this paper. As the importance of large SVs become increasingly recognized in cancer genomics, this paper provides a timely review on some of the most impactful factors influencing somatic SV detection that should be considered when choosing SV callers.
| S-EPMC8138798 | biostudies-literature