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    ctDNA monitoring using patient-specific sequencing and integration of variant reads

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    Author
    Wan, JCM; Heider, K; Gale, D; Murphy, S; Fisher, E; Mouliere, F; Ruiz-Valdepenas, A; Santonja, A; Morris, J; Chandrananda, D; ...
    Date
    2020-06-17
    Source Title
    Science Translational Medicine
    Publisher
    AMER ASSOC ADVANCEMENT SCIENCE
    University of Melbourne Author/s
    Chandrananda, Sandunie
    Affiliation
    Sir Peter MacCallum Department of Oncology
    Metadata
    Show full item record
    Document Type
    Journal Article
    Citations
    Wan, J. C. M., Heider, K., Gale, D., Murphy, S., Fisher, E., Mouliere, F., Ruiz-Valdepenas, A., Santonja, A., Morris, J., Chandrananda, D., Marshall, A., Gill, A. B., Chan, P. Y., Barker, E., Young, G., Cooper, W. N., Hudecova, I., Marass, F., Mair, R. ,... Rosenfeld, N. (2020). ctDNA monitoring using patient-specific sequencing and integration of variant reads. SCIENCE TRANSLATIONAL MEDICINE, 12 (548), https://doi.org/10.1126/scitranslmed.aaz8084.
    Access Status
    Access this item via the Open Access location
    URI
    http://hdl.handle.net/11343/254094
    DOI
    10.1126/scitranslmed.aaz8084
    Open Access URL
    http://wrap.warwick.ac.uk/138534/1/WRAP-ctDNA-monitoring-patient-specific-sequencing-integration-variant-reads-Marshall-2020.pdf
    Abstract
    Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to parts per million. This resulted in median area under the curve (AUC) values of 0.98 in advanced cancers and 0.80 in early-stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that INVAR may be applied without requiring personalized sequencing panels so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

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