Abstract 5391: Low frequency variant detection and tissue-of-origin exploration using liquid biopsies

2017 ◽  
Author(s):  
Justin S. Lenhart ◽  
Ashley Wood ◽  
Sukhinder Sandhu ◽  
Cassie Schumacher ◽  
Laurie Kurihara ◽  
...  
Keyword(s):  
Low Frequency ◽  
Liquid Biopsies ◽  
Variant Detection ◽  
Tissue Of Origin

scholarly journals MAESTRO affords ‘breadth and depth’ for mutation testing

2021 ◽  
Author(s):  
Gregory Gydush ◽  
Erica Nguyen ◽  
Jin H. Bae ◽  
Justin Rhoades ◽  
Sarah C. Reed ◽  
...  
Keyword(s):  
Residual Disease ◽  
Low Frequency ◽  
Mutation Testing ◽  
Liquid Biopsies ◽  
Cancer Genome Sequencing ◽  
Large Numbers ◽  
Powerful Approach ◽  
Sequencing Studies ◽  
Duplex Sequencing ◽  
Parallel Mutation

AbstractThe ability to assay large numbers of low-abundance mutations is crucial in biomedicine. Yet, the technical hurdles of sequencing multiple mutations at extremely high depth and accuracy remain daunting. For sequencing low-level mutations, it’s either ‘depth or breadth’ but not both. Here, we report a simple and powerful approach to accurately track thousands of distinct mutations with minimal reads. Our technique called MAESTRO (minor allele enriched sequencing through recognition oligonucleotides) employs massively-parallel mutation enrichment to empower duplex sequencing—one of the most accurate methods—to track up to 10,000 low-frequency mutations with up to 100-fold less sequencing. In example use cases, we show that MAESTRO could enable mutation validation from cancer genome sequencing studies. We also show that it could track thousands of mutations from a patient’s tumor in cell-free DNA, which may improve detection of minimal residual disease from liquid biopsies. In all, MAESTRO improves the breadth, depth, accuracy, and efficiency of mutation testing.

Genomic alterations in appendiceal carcinoma using circulating DNA.

2019 ◽  
Vol 37 (4_suppl) ◽  
pp. 658-658
Author(s):  
Walid Labib Shaib ◽  
Ali Roberts ◽  
Mehmet Akce ◽  
Christina Wu ◽  
Olatunji B. Alese ◽  
...  
Keyword(s):  
Low Frequency ◽  
Circulating Tumor Dna ◽  
Plasma Samples ◽  
Single Nucleotide Variants ◽  
Liquid Biopsies ◽  
Genomic Alterations ◽  
Synonymous Mutations ◽  
Molecular Alterations ◽  
Uncertain Significance ◽  
Brca1 Brca2

658 Background: Appendiceal cancers (AC) comprise around 0.5% of all gastrointestinal neoplasia. The genomic landscape of AC has not been well studied. The yield of circulating tumor DNA (ctDNA) from the plasma of patients with AC has not been reported. The aim of this study is to confirm the feasibility of NGS using ctDNA and characterize common alternations in the genomic profile of AC. Methods: The molecular alterations in 372 plasma samples from 303 patients with AC using clinical-grade NGS of ctDNA (Guardant 360) across multiple institutions, was evaluated. The test detects single nucleotide variants in 54 -73 genes, copy number amplifications, fusions, and indels in selected genes. Results: A total of 303 AC patients were evaluated; 169 female (56%). Median age was 56.8 (range: 25-83). ctDNA NGS testing was done on 372 plasma samples; 48 patients had testing performed twice, 9 three times, and 1 was tested four times. Genomic alterations were defined in 207 (55.6%) samples with a total of 288 alterations identified after excluding variants of uncertain significance (VUSs) and synonymous mutations. TP53 associated genes were most commonly altered (n = 96, 33.3%), followed by KRAS (n = 41, 14.2%), APC (n = 19, 6.6%), EGFR (n = 15, 5.2%), BRAF (n = 13, 4.5%), NF1 (n = 13, 4.5%), MYC (n = 9, 3.1%), GNAS (n = 8, 2.7%), PI3CA (n = 7, 2.4%), MET (n = 6, 2.08%), ATM in 6 (1.6%). Other genomic alterations of low frequency, but clinically relevant: AR (n = 4, 1.39%), TERT (n = 4, 1.39%), ERBB2 (n = 4, 1.39%), SMAD4 (n = 3, 1.04%), CDK4 (n = 2, 0.69%), NRAS (n = 2, 0.69%), FGFR1 (n = 2, 0.69%), FGFR2 (n = 2, 0.69%), PTEN (n = 2, 0.69%), RB1 (n = 2, 0.69%), and CDK6, CDKN2A, BRCA1, BRCA2, JAK2, IDH2, MAPK, NTRK1, CDH1, ARID1A, and PDGFRA were all reported once. Conclusions: Evaluation of ctDNA was feasible among individuals with AC. The frequency of genomic alterations in ctDNA testing is similar to those previously reported in tissue NGS. Liquid biopsies are non-invasive methods that can provide personalized options for targeted therapies in patients with AC.

Abstract 2230: Low frequency variant detection in cell free DNA by applying molecular identifiers to targeted NGS

2018 ◽  
Author(s):  
Ashley Wood ◽  
Sukhinder Sandhu ◽  
Mida Pezeshkian ◽  
Vanessa Kelchner ◽  
Jordan RoseFigura ◽  
...  
Keyword(s):  
Low Frequency ◽  
Cell Free Dna ◽  
Free Dna ◽  
Targeted Ngs ◽  
Variant Detection

scholarly journals Accurate, Efficient and User-Friendly Mutation Calling and Sample Identification for TILLING Experiments

2021 ◽  
Vol 12 ◽  
Author(s):  
Juanita Gil ◽  
Juan Sebastian Andrade-Martínez ◽  
Jorge Duitama
Keyword(s):  
Reverse Genetics ◽  
High Throughput Sequencing ◽  
Natural Populations ◽  
Low Frequency ◽  
Low Frequencies ◽  
Pooled Data ◽  
Variant Detection ◽  
Similar Accuracy ◽  
User Friendly ◽  
Sample Identification

TILLING (Targeting Induced Local Lesions IN Genomes) is a powerful reverse genetics method in plant functional genomics and breeding to identify mutagenized individuals with improved behavior for a trait of interest. Pooled high throughput sequencing (HTS) of the targeted genes allows efficient identification and sample assignment of variants within genes of interest in hundreds of individuals. Although TILLING has been used successfully in different crops and even applied to natural populations, one of the main issues for a successful TILLING experiment is that most currently available bioinformatics tools for variant detection are not designed to identify mutations with low frequencies in pooled samples or to perform sample identification from variants identified in overlapping pools. Our research group maintains the Next Generation Sequencing Experience Platform (NGSEP), an open source solution for analysis of HTS data. In this manuscript, we present three novel components within NGSEP to facilitate the design and analysis of TILLING experiments: a pooled variants detector, a sample identifier from variants detected in overlapping pools and a simulator of TILLING experiments. A new implementation of the NGSEP calling model for variant detection allows accurate detection of low frequency mutations within pools. The samples identifier implements the process to triangulate the mutations called within overlapping pools in order to assign mutations to single individuals whenever possible. Finally, we developed a complete simulator of TILLING experiments to enable benchmarking of different tools and to facilitate the design of experimental alternatives varying the number of pools and individuals per pool. Simulation experiments based on genes from the common bean genome indicate that NGSEP provides similar accuracy and better efficiency than other tools to perform pooled variants detection. To the best of our knowledge, NGSEP is currently the only tool that generates individual assignments of the mutations discovered from the pooled data. We expect that this development will be of great use for different groups implementing TILLING as an alternative for plant breeding and even to research groups performing pooled sequencing for other applications.

scholarly journals Sensitive detection of tumor mutations from blood and its application to immunotherapy prognosis

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Shuo Li ◽  
Zorawar S. Noor ◽  
Weihua Zeng ◽  
Mary L. Stackpole ◽  
Xiaohui Ni ◽  
...  
Keyword(s):  
Mutation Detection ◽  
Low Frequency ◽  
Sequencing Data ◽  
Viable Option ◽  
Real Patient ◽  
Free Dna ◽  
Whole Exome ◽  
Mutation Profile ◽  
Tissue Of Origin ◽  
Error Suppression

AbstractCell-free DNA (cfDNA) is attractive for many applications, including detecting cancer, identifying the tissue of origin, and monitoring. A fundamental task underlying these applications is SNV calling from cfDNA, which is hindered by the very low tumor content. Thus sensitive and accurate detection of low-frequency mutations (<5%) remains challenging for existing SNV callers. Here we present cfSNV, a method incorporating multi-layer error suppression and hierarchical mutation calling, to address this challenge. Furthermore, by leveraging cfDNA’s comprehensive coverage of tumor clonal landscape, cfSNV can profile mutations in subclones. In both simulated and real patient data, cfSNV outperforms existing tools in sensitivity while maintaining high precision. cfSNV enhances the clinical utilities of cfDNA by improving mutation detection performance in medium-depth sequencing data, therefore making Whole-Exome Sequencing a viable option. As an example, we demonstrate that the tumor mutation profile from cfDNA WES data can provide an effective biomarker to predict immunotherapy outcomes.

scholarly journals QQ-SNV: single nucleotide variant detection at low frequency by comparing the quality quantiles

2015 ◽  
Vol 16 (1) ◽  
Author(s):  
Koen Van der Borght ◽  
Kim Thys ◽  
Yves Wetzels ◽  
Lieven Clement ◽  
Bie Verbist ◽  
...  
Keyword(s):  
Low Frequency ◽  
Single Nucleotide Variant ◽  
Single Nucleotide ◽  
Variant Detection

scholarly journals VirVarSeq: a low-frequency virus variant detection pipeline for Illumina sequencing using adaptive base-calling accuracy filtering

2014 ◽  
Vol 31 (1) ◽  
pp. 94-101 ◽  
Author(s):  
Bie M.P. Verbist ◽  
Kim Thys ◽  
Joke Reumers ◽  
Yves Wetzels ◽  
Koen Van der Borght ◽  
...  
Keyword(s):  
Illumina Sequencing ◽  
Low Frequency ◽  
Virus Variant ◽  
Base Calling ◽  
Variant Detection
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