Detection of copy number aberrations in cholangiocarcinoma using shallow whole genome sequencing of plasma DNA.

2018 ◽  
Vol 36 (4_suppl) ◽  
pp. 293-293 ◽  
Author(s):  
Maria Farooq ◽  
Jan B. Egan ◽  
Bradon McDonald ◽  
Havell Markus ◽  
Tania Contente-Cuomo ◽  
...  
Keyword(s):  
Healthy Volunteers ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Whole Genome ◽  
Sequencing Data ◽  
Plasma Dna ◽  
Copy Number Aberrations ◽  
Ctdna Analysis ◽  
Tumor Genotyping

293 Background: Cholangiocarcinoma (CCA) is a deadly cancer with ~20% five year survival. Obtaining tissue to confirm diagnosis of CCA is often challenging. This also limits the use of tumor genotyping that could guide potential molecularly targeted treatment (such as FGFR inhibitors for a subset of cases). We investigated whether circulating tumor DNA (ctDNA) analysis in plasma is feasible for noninvasive tumor genotyping in patients with advanced CCA. Methods: We collected and processed plasma samples for ctDNA analysis from 17 patients with CCA at presentation and from 11 healthy volunteers. Following cell-free DNA extraction and quality assessment using digital PCR, we performed low-pass, shallow whole genome sequencing (sWGS). We analyzed sequencing data to identify copy number aberrations and quantify tumor fraction in plasma using recently published computational approaches. Results: Median total cfDNA concentration in patients with CCA was 7,003 genome equivalents (GEs)/mL plasma (range: 1,512- 107,707 GEs/mL) and significantly higher than healthy volunteers (two tailed t-test p < 0.04, median: 1,658 GEs/mL, range: 661-4,938 GEs/mL). We successfully sequenced all tumor libraries, generating a median of 173 million paired-end reads. ctDNA was detectable in 10/17 samples using sWGS. In these 10 samples, median tumor fraction in plasma DNA was 7.1% (range: 3.9%-44.6%). We found recurrent copy number aberrations expected in CCA including 1q gain in 80%, 7p gain in 50%, 1p loss in 70% and 3p loss in 50% of cases. Conclusions: ctDNA analysis for noninvasive tumor genotyping is feasible in patients with advanced cholangiocarcinoma. On-going work is focused on expanding these results using targeted and whole-exome sequencing.

scholarly journals Identification of Medium-Sized Copy Number Alterations in Whole-Genome Sequencing

2014 ◽  
Vol 13s3 ◽  
pp. CIN.S14023
Author(s):  
Hatice Gulcin Ozer ◽  
Aisulu Usubalieva ◽  
Adrienne Dorrance ◽  
Ayse Selen Yilmaz ◽  
Michael Caligiuri ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Copy Number Alterations ◽  
Sequencing Data ◽  
Entire Genome ◽  
Multiple Challenges ◽  
Cost Efficient

The genome-wide discoveries such as detection of copy number alterations (CNA) from high-throughput whole-genome sequencing data enabled new developments in personalized medicine. The CNAs have been reported to be associated with various diseases and cancers including acute myeloid leukemia. However, there are multiple challenges to the use of current CNA detection tools that lead to high false-positive rates and thus impede widespread use of such tools in cancer research. In this paper, we discuss these issues and propose possible solutions. First, since the entire genome cannot be mapped due to some regions lacking sequence uniqueness, current methods cannot be appropriately adjusted to handle these regions in the analyses. Thus, detection of medium-sized CNAs is also being directly affected by these mappability problems. The requirement for matching control samples is also an important limitation because acquiring matching controls might not be possible or might not be cost efficient. Here we present an approach that addresses these issues and detects medium-sized CNAs in cancer genomes by (1) masking unmappable regions during the initial CNA detection phase, (2) using pool of a few normal samples as control, and (3) employing median filtering to adjust CNA ratios to its surrounding coverage and eliminate false positives.

scholarly journals SECNVs: A Simulator of Copy Number Variants and Whole-Exome Sequences from Reference Genomes

2019 ◽  
Author(s):  
Yue Xing ◽  
Alan R. Dabney ◽  
Xiao Li ◽  
Guosong Wang ◽  
Clare A. Gill ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Copy Number Variants ◽  
Whole Genome ◽  
Sequencing Data ◽  
Software Applications ◽  
Exome Sequencing Data ◽  
Whole Exome ◽  
Whole Exome Sequencing Data

AbstractCopy number variants are insertions and deletions of 1 kb or larger in a genome that play an important role in phenotypic changes and human disease. Many software applications have been developed to detect copy number variants using either whole-genome sequencing or whole-exome sequencing data. However, there is poor agreement in the results from these applications. Simulated datasets containing copy number variants allow comprehensive comparisons of the operating characteristics of existing and novel copy number variant detection methods. Several software applications have been developed to simulate copy number variants and other structural variants in whole-genome sequencing data. However, none of the applications reliably simulate copy number variants in whole-exome sequencing data. We have developed and tested SECNVs (Simulator of Exome Copy Number Variants), a fast, robust and customizable software application for simulating copy number variants and whole-exome sequences from a reference genome. SECNVs is easy to install, implements a wide range of commands to customize simulations, can output multiple samples at once, and incorporates a pipeline to output rearranged genomes, short reads and BAM files in a single command. Variants generated by SECNVs are detected with high sensitivity and precision by tools commonly used to detect copy number variants. SECNVs is publicly available at https://github.com/YJulyXing/SECNVs.

scholarly journals Cell-free tumour DNA analysis detects copy number alterations in gastro-oesophageal cancer patients

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0245488
Author(s):  
Karin Wallander ◽  
Jesper Eisfeldt ◽  
Mats Lindblad ◽  
Daniel Nilsson ◽  
Kenny Billiau ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Oesophageal Cancer ◽  
Copy Number ◽  
Dna Analysis ◽  
Tissue Sample ◽  
Whole Genome ◽  
Copy Number Alterations ◽  
Plasma Dna ◽  
Low Coverage

Background Analysis of cell-free tumour DNA, a liquid biopsy, is a promising biomarker for cancer. We have performed a proof-of principle study to test the applicability in the clinical setting, analysing copy number alterations (CNAs) in plasma and tumour tissue from 44 patients with gastro-oesophageal cancer. Methods DNA was isolated from blood plasma and a tissue sample from each patient. Array-CGH was applied to the tissue DNA. The cell-free plasma DNA was sequenced by low-coverage whole-genome sequencing using a clinical pipeline for non-invasive prenatal testing. WISECONDOR and ichorCNA, two bioinformatic tools, were used to process the output data and were compared to each other. Results Cancer-associated CNAs could be seen in 59% (26/44) of the tissue biopsies. In the plasma samples, a targeted approach analysing 61 regions of special interest in gastro-oesophageal cancer detected cancer-associated CNAs with a z-score >5 in 11 patients. Broadening the analysis to a whole-genome view, 17/44 patients (39%) had cancer-associated CNAs using WISECONDOR and 13 (30%) using ichorCNA. Of the 26 patients with tissue-verified cancer-associated CNAs, 14 (54%) had corresponding CNAs in plasma. Potentially clinically actionable amplifications overlapping the genes VEGFA, EGFR and FGFR2 were detected in the plasma from three patients. Conclusions We conclude that low-coverage whole-genome sequencing without prior knowledge of the tumour alterations could become a useful tool for cell-free tumour DNA analysis of total CNAs in plasma from patients with gastro-oesophageal cancer.

scholarly journals A Bioinformatics Pipeline for Estimating Mitochondria DNA Copy Number and Heteroplasmy Levels from Whole Genome Sequencing Data

2021 ◽  
Author(s):  
Stephanie L Battle ◽  
Daniela Puiu ◽  
Eric Boerwinkle ◽  
Kent Taylor ◽  
Jerome Rotter ◽  
...  
Keyword(s):  
Mitochondrial Genome ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Dna Molecules ◽  
Sequencing Data ◽  
Bioinformatics Pipeline ◽  
Accurate Identification

Mitochondrial diseases are a heterogeneous group of disorders that can be caused by mutations in the nuclear or mitochondrial genome. Mitochondrial DNA variants may exist in a state of heteroplasmy, where a percentage of DNA molecules harbor a variant, or homoplasmy, where all DNA molecules have a variant. The relative quantity of mtDNA in a cell, or copy number (mtDNA-CN), is associated with mitochondrial function, human disease, and mortality. To facilitate accurate identification of heteroplasmy and quantify mtDNA-CN, we built a bioinformatics pipeline that takes whole genome sequencing data and outputs mitochondrial variants, and mtDNA-CN. We incorporate variant annotations to facilitate determination of variant significance. Our pipeline yields uniform coverage by remapping to a circularized chrM and recovering reads falsely mapped to nuclear-encoded mitochondrial sequences. Notably, we construct a consensus chrM sequence for each sample and recall heteroplasmy against the sample's unique mitochondrial genome. We observe an approximately 3-fold increased association with age for heteroplasmic variants in non-homopolymer regions and, are better able to capture genetic variation in the D-loop of chrM compared to existing software. Our bioinformatics pipeline more accurately captures features of mitochondrial genetics than existing pipelines that are important in understanding how mitochondrial dysfunction contributes to disease.

scholarly journals Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing

2018 ◽  
Author(s):  
Isidro Cortés-Ciriano ◽  
June-Koo Lee ◽  
Ruibin Xi ◽  
Dhawal Jain ◽  
Youngsook L. Jung ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Human Cancer ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
End Joining ◽  
Cancer Types ◽  
Non Homologous End Joining

SummaryChromothripsis is a newly discovered mutational phenomenon involving massive, clustered genomic rearrangements that occurs in cancer and other diseases. Recent studies in cancer suggest that chromothripsis may be far more common than initially inferred from low resolution DNA copy number data. Here, we analyze the patterns of chromothripsis across 2,658 tumors spanning 39 cancer types using whole-genome sequencing data. We find that chromothripsis events are pervasive across cancers, with a frequency of >50% in several cancer types. Whereas canonical chromothripsis profiles display oscillations between two copy number states, a considerable fraction of the events involves multiple chromosomes as well as additional structural alterations. In addition to non-homologous end-joining, we detect signatures of replicative processes and templated insertions. Chromothripsis contributes to oncogene amplification as well as to inactivation of genes such as mismatch-repair related genes. These findings show that chromothripsis is a major process driving genome evolution in human cancer.

scholarly journals ascatNgs: Identifying Somatically Acquired Copy-Number Alterations from Whole-Genome Sequencing Data

2016 ◽  
Vol 56 (1) ◽  
pp. 15.9.1-15.9.17 ◽  
Author(s):  
Keiran M. Raine ◽  
Peter Van Loo ◽  
David C. Wedge ◽  
David Jones ◽  
Andrew Menzies ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Copy Number ◽  
Whole Genome Sequencing Data ◽  
Whole Genome ◽  
Copy Number Alterations ◽  
Sequencing Data

scholarly journals Performance of copy number variants detection based on whole-genome sequencing by DNBSEQ platforms

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Junhua Rao ◽  
Lihua Peng ◽  
Xinming Liang ◽  
Hui Jiang ◽  
Chunyu Geng ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Technology Use ◽  
Copy Number ◽  
Massively Parallel Sequencing ◽  
Copy Number Variants ◽  
Whole Genome ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Cnv Detection

Abstract Background DNBSEQ™ platforms are new massively parallel sequencing (MPS) platforms that use DNA nanoball technology. Use of data generated from DNBSEQ™ platforms to detect single nucleotide variants (SNVs) and small insertions and deletions (indels) has proven to be quite effective, while the feasibility of copy number variants (CNVs) detection is unclear. Results Here, we first benchmarked different CNV detection tools based on Illumina whole-genome sequencing (WGS) data of NA12878 and then assessed these tools in CNV detection based on DNBSEQ™ sequencing data from the same sample. When the same tool was used, the CNVs detected based on DNBSEQ™ and Illumina data were similar in quantity, length and distribution, while great differences existed within results from different tools and even based on data from a single platform. We further estimated the CNV detection power based on available CNV benchmarks of NA12878 and found similar precision and sensitivity between the DNBSEQ™ and Illumina platforms. We also found higher precision of CNVs shorter than 1 kbp based on DNBSEQ™ platforms than those based on Illumina platforms by using Pindel, DELLY and LUMPY. We carefully compared these two available benchmarks and found a large proportion of specific CNVs between them. Thus, we constructed a more complete CNV benchmark of NA12878 containing 3512 CNV regions. Conclusions We assessed and benchmarked CNV detections based on WGS with DNBSEQ™ platforms and provide guidelines for future studies.

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