• Login
    View Item 
    •   Home
    • The Christie Research Publications Repository
    • All Christie Publications
    • View Item
    •   Home
    • The Christie Research Publications Repository
    • All Christie Publications
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of ChristieCommunitiesTitleAuthorsIssue DateSubmit DateSubjectsThis CollectionTitleAuthorsIssue DateSubmit DateSubjects

    My Account

    LoginRegister

    Local Links

    The Christie WebsiteChristie Library and Knowledge Service

    Statistics

    Display statistics

    Low-cost and clinically applicable copy number profiling using repeat DNA

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Name:
    35978291.pdf
    Size:
    1.993Mb
    Format:
    PDF
    Description:
    Identified with Open Access button
    Download
    Authors
    Abujudeh, S.
    Zeki, S. S.
    van Lanschot, M. C. J.
    Pusung, M.
    Weaver, Jamie M
    Li, X.
    Noorani, A.
    Metz, A. J.
    Bornschein, J.
    Bower, L.
    Miremadi, A.
    Fitzgerald, R. C.
    Morrissey, E. R.
    Lynch, A. G.
    Show allShow less
    Affiliation
    Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, CB2 0RE, UK.
    Issue Date
    2022
    
    Metadata
    Show full item record
    Abstract
    Background: Somatic copy number alterations (SCNAs) are an important class of genomic alteration in cancer. They are frequently observed in cancer samples, with studies showing that, on average, SCNAs affect 34% of a cancer cell's genome. Furthermore, SCNAs have been shown to be major drivers of tumour development and have been associated with response to therapy and prognosis. Large-scale cancer genome studies suggest that tumours are driven by somatic copy number alterations (SCNAs) or single-nucleotide variants (SNVs). Despite the frequency of SCNAs and their clinical relevance, the use of genomics assays in the clinic is biased towards targeted gene panels, which identify SNVs but provide limited scope to detect SCNAs throughout the genome. There is a need for a comparably low-cost and simple method for high-resolution SCNA profiling. Results: We present conliga, a fully probabilistic method that infers SCNA profiles from a low-cost, simple, and clinically-relevant assay (FAST-SeqS). When applied to 11 high-purity oesophageal adenocarcinoma samples, we obtain good agreement (Spearman's rank correlation coefficient, rs=0.94) between conliga's inferred SCNA profiles using FAST-SeqS data (approximately £14 per sample) and those inferred by ASCAT using high-coverage WGS (gold-standard). We find that conliga outperforms CNVkit (rs=0.89), also applied to FAST-SeqS data, and is comparable to QDNAseq (rs=0.96) applied to low-coverage WGS, which is approximately four-fold more expensive, more laborious and less clinically-relevant. By performing an in silico dilution series experiment, we find that conliga is particularly suited to detecting SCNAs in low tumour purity samples. At two million reads per sample, conliga is able to detect SCNAs in all nine samples at 3% tumour purity and as low as 0.5% purity in one sample. Crucially, we show that conliga's hidden state information can be used to decide when a sample is abnormal or normal, whereas CNVkit and QDNAseq cannot provide this critical information. Conclusions: We show that conliga provides high-resolution SCNA profiles using a convenient, low-cost assay. We believe conliga makes FAST-SeqS a more clinically valuable assay as well as a useful research tool, enabling inexpensive and fast copy number profiling of pre-malignant and cancer samples.
    Citation
    Abujudeh S, Zeki SS, van Lanschot MCJ, Pusung M, Weaver JMJ, Li X, et al. Low-cost and clinically applicable copy number profiling using repeat DNA. BMC genomics. 2022 Aug 17;23(1):599. PubMed PMID: 35978291. Pubmed Central PMCID: PMC9386984. Epub 2022/08/18. eng.
    Journal
    BMC Genomics
    URI
    http://hdl.handle.net/10541/625572
    DOI
    10.1186/s12864-022-08681-8
    PubMed ID
    35978291
    Additional Links
    https://dx.doi.org/10.1186/s12864-022-08681-8
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.1186/s12864-022-08681-8
    Scopus Count
    Collections
    All Christie Publications

    entitlement

    Related articles

    • A Validation Framework for Somatic Copy Number Detection in Targeted Sequencing Panels.
    • Authors: Chandramohan R, Reuther J, Gandhi I, Voicu H, Alvarez KR, Plon SE, Lopez-Terrada DH, Fisher KE, Parsons DW, Roy A
    • Issue date: 2022 Jul
    • Breast and prostate cancers harbor common somatic copy number alterations that consistently differ by race and are associated with survival.
    • Authors: Chen Y, Sadasivan SM, She R, Datta I, Taneja K, Chitale D, Gupta N, Davis MB, Newman LA, Rogers CG, Paris PL, Li J, Rybicki BA, Levin AM
    • Issue date: 2020 Aug 20
    • Accurity: accurate tumor purity and ploidy inference from tumor-normal WGS data by jointly modelling somatic copy number alterations and heterozygous germline single-nucleotide-variants.
    • Authors: Luo Z, Fan X, Su Y, Huang YS
    • Issue date: 2018 Jun 15
    • SAAS-CNV: A Joint Segmentation Approach on Aggregated and Allele Specific Signals for the Identification of Somatic Copy Number Alterations with Next-Generation Sequencing Data.
    • Authors: Zhang Z, Hao K
    • Issue date: 2015 Nov
    • Unbiased Detection of Somatic Copy Number Aberrations in cfDNA of Lung Cancer Cases and High-Risk Controls with Low Coverage Whole Genome Sequencing.
    • Authors: Taylor F, Bradford J, Woll PJ, Teare D, Cox A
    • Issue date: 2016
    DSpace software (copyright © 2002 - 2023)  DuraSpace
    Quick Guide | Contact Us
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.