Frequent extrachromosomal oncogene amplification drives aggressive tumors

2019 ◽  
Author(s):  
Hoon Kim ◽  
Nam Nguyen ◽  
Kristen Turner ◽  
Sihan Wu ◽  
Jihe Liu ◽  
...  
Keyword(s):  
Copy Number ◽  
Computational Analysis ◽  
Chromatin Accessibility ◽  
Tissue Type ◽  
Whole Genome Sequencing Data ◽  
Tumor Evolution ◽  
Sequencing Data ◽  
Oncogene Amplification ◽  
Significant Enrichment ◽  
Aggressive Tumors

Extrachromosomal DNA (ecDNA) amplification promotes high oncogene copy number, intratumoral genetic heterogeneity, and accelerated tumor evolution1–3, but its frequency and clinical impact are not well understood. Here we show, using computational analysis of whole-genome sequencing data from 1,979 cancer patients, that ecDNA amplification occurs in at least 26% of human cancers, of a wide variety of histological types, but not in whole blood or normal tissue. We demonstrate a highly significant enrichment for oncogenes on amplified ecDNA and that the most common recurrent oncogene amplifications arise on ecDNA. EcDNA amplifications resulted in higher levels of oncogene transcription compared to copy number matched linear DNA, coupled with enhanced chromatin accessibility. Patients whose tumors have ecDNA-based oncogene amplification showed increase of cell proliferation signature activity, greater likelihood of lymph node spread at initial diagnosis, and significantly shorter survival, even when controlled for tissue type, than do patients whose cancers are not driven by ecDNA-based oncogene amplification. The results presented here demonstrate that ecDNA-based oncogene amplification plays a central role in driving the poor outcome for patients with some of the most aggressive forms of cancers.

scholarly journals Decomposing the subclonal structure of tumors with two-way mixture models on copy number aberrations

2018 ◽  
Author(s):  
An-Shun Tai ◽  
Chien-Hua Peng ◽  
Shih-Chi Peng ◽  
Wen-Ping Hsieh
Keyword(s):  
Head And Neck Cancer ◽  
Head And Neck ◽  
Neck Cancer ◽  
Copy Number ◽  
Tumor Heterogeneity ◽  
Tumor Evolution ◽  
Depth Information ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
Copy Number Aberrations

AbstractMultistage tumorigenesis is a dynamic process characterized by the accumulation of mutations. Thus, a tumor mass is composed of genetically divergent cell subclones. With the advancement of next-generation sequencing (NGS), mathematical models have been recently developed to decompose tumor subclonal architecture from a collective genome sequencing data. Most of the methods focused on single-nucleotide variants (SNVs). However, somatic copy number aberrations (CNAs) also play critical roles in carcinogenesis. Therefore, further modeling subclonal CNAs composition would hold the promise to improve the analysis of tumor heterogeneity and cancer evolution. To address this issue, we developed a two-way mixture Poisson model, named CloneDeMix for the deconvolution of read-depth information. It can infer the subclonal copy number, mutational cellular prevalence (MCP), subclone composition, and the order in which mutations occurred in the evolutionary hierarchy. The performance of CloneDeMix was systematically assessed in simulations. As a result, the accuracy of CNA inference was nearly 93% and the MCP was also accurately restored. Furthermore, we also demonstrated its applicability using head and neck cancer samples from TCGA. Our results inform about the extent of subclonal CNA diversity, and a group of candidate genes that probably initiate lymph node metastasis during tumor evolution was also discovered. Most importantly, these driver genes are located at 11q13.3 which is highly susceptible to copy number change in head and neck cancer genomes. This study successfully estimates subclonal CNAs and exhibit the evolutionary relationships of mutation events. By doing so, we can track tumor heterogeneity and identify crucial mutations during evolution process. Hence, it facilitates not only understanding the cancer development but finding potential therapeutic targets. Briefly, this framework has implications for improved modeling of tumor evolution and the importance of inclusion of subclonal CNAs.

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 Conservation of copy number profiles during engraftment and passaging of patient-derived cancer xenografts

2019 ◽  
Author(s):  
Xing Yi Woo ◽  
Jessica Giordano ◽  
Anuj Srivastava ◽  
Zi-Ming Zhao ◽  
Michael W. Lloyd ◽  
...  
Keyword(s):  
Microarray Data ◽  
Copy Number ◽  
Dynamic Range ◽  
Human Cancer ◽  
Tumor Evolution ◽  
Copy Number Alterations ◽  
Recurrence Analysis ◽  
Late Passage ◽  
Significant Enrichment ◽  
Pdx Models

ABSTRACTPatient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, impacting the accuracy of PDX modeling of human cancer. Here we exhaustively analyze copy number alterations (CNAs) in 1451 PDX and matched patient tumor (PT) samples from 509 PDX models. CNA inferences based on DNA sequencing and microarray data displayed substantially higher resolution and dynamic range than gene expression-based inferences, and they also showed strong CNA conservation from PTs through late-passage PDXs. CNA recurrence analysis of 130 colorectal and breast PT/PDX-early/PDX-late trios confirmed high-resolution CNA retention. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multi-region samples within patients. Our study demonstrates the lack of systematic copy number evolution driven by the PDX mouse host.

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 High plasma salivary α-amylase, but not high AMY1 copy number, associated with low obesity rate in Qatari adults: cross-sectional study

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Neyla Al-Akl ◽  
Richard I. Thompson ◽  
Abdelilah Arredouani
Keyword(s):  
Copy Number ◽  
High Plasma ◽  
Cross Sectional Study ◽  
Normal Weight ◽  
Whole Genome Sequencing Data ◽  
Obesity Prevalence ◽  
Sequencing Data ◽  
Cross Sectional ◽  
Prevalence Of Obesity ◽  
The Relationship

Abstract The relationship between salivary α-amylase activity (psAAa) or AMY1 copy number and the risk of obesity remains controversial. We aimed to assess this relationship in a cohort from Qatar, where obesity affects 43% of adults. The relationship was investigated cross-sectionally in 923 Qatari adults from the Qatar biobank cohort. AMY1 CN was estimated form whole genome sequencing data. The associations with obesity prevalence were assessed by linear and logistic regressions. We found no difference in AMY1 CN between obese and normal-weight individuals. However, the psAAa was significantly lower in obese individuals. Significant inverse correlations were found between adiposity markers and psAAa in both sexes, but were marginally stronger in men. A significant effect of high psAAa, but not AMY1 CN, on reduced obesity rates was identified in men (OR per psAAa unit 0.957 [95% CI 0.937–0.977], p < 0.001, with psAAa ranging between 5 to 66 U/L). A significantly higher prevalence of obesity was observed in the lowest quartile of psAAa in men (75% (Q1) vs. 36% (Q4), p < 0.001) and women (74% (Q1) vs 56% (Q4), p = 0.009). Our findings suggest that high psAAa, but not AMY1 CN, has a potential positive benefit against obesity in the Qatari population.

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 Remarkably stable copy-number profiles in osteosarcoma revealed using single-cell DNA sequencing

2021 ◽  
Author(s):  
Sanjana Rajan ◽  
Simone Zaccaria ◽  
Matthew V. Cannon ◽  
Maren Cam ◽  
Amy C. Gross ◽  
...  
Keyword(s):  
Dna Sequencing ◽  
Single Cell ◽  
Genomic Instability ◽  
Copy Number ◽  
Fitness Landscape ◽  
Clonal Evolution ◽  
Response To Therapy ◽  
Tumor Evolution ◽  
Sequencing Data ◽  
Recurrent Mutations

AbstractOsteosarcoma is an aggressive malignancy characterized by high genomic complexity. Identification of few recurrent mutations in protein coding genes suggests that somatic copy-number aberrations (SCNAs) are the genetic drivers of disease. Models around genomic instability conflict-it is unclear if osteosarcomas result from pervasive ongoing clonal evolution with continuous optimization of the fitness landscape or an early catastrophic event followed by stable maintenance of an abnormal genome. We address this question by investigating SCNAs in 12,019 tumor cells obtained from expanded patient tissues using single-cell DNA sequencing, in ways that were previously impossible with bulk sequencing. Using the CHISEL algorithm, we inferred allele- and haplotype-specific SCNAs from whole-genome single-cell DNA sequencing data. Surprisingly, we found that, despite extensive genomic aberrations, cells within each tumor exhibit remarkably homogeneous SCNA profiles with little sub-clonal diversification. Longitudinal analysis between two pairs of patient samples obtained at distant time points (early detection, relapse) demonstrated remarkable conservation of SCNA profiles over tumor evolution. Phylogenetic analysis suggests that the bulk of SCNAs was acquired early in the oncogenic process, with few new events arising in response to therapy or during adaptation to growth in distant tissues. These data suggest that early catastrophic events, rather than sustained genomic instability, drive formation of these extensively aberrant genomes. Overall, we demonstrate the power of combining single-cell DNA sequencing with an allele- and haplotype-specific SCNA inference algorithm to resolve longstanding questions regarding genetics of tumor initiation and progression, questioning the underlying assumptions of genomic instability inferred from bulk tumor data.

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
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