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BioinformaticsNature Communications
Peer-reviewed journal article

Clinical application of tumour-in-normal contamination assessment from whole genome sequencing

Jonathan MitchelliD, Salvatore MiliteiD, Jack Luke BartramiD, Susan WalkeriD, Nadezda V. VolkovaiD, Olena Yavorska, Magdalena ZarowieckiiD, Jane ChalkeriD, Rebecca Thomas, Luca VagoiD, Alona SosinskyiD, Giulio CaravagnaiD

Abstract

The unexpected contamination of normal samples with tumour cells reduces variant detection sensitivity, compromising downstream analyses in canonical tumour-normal analyses. Leveraging whole-genome sequencing data available at Genomics England, we develop a tool for normal sample contamination assessment, which we validate in silico and against minimal residual disease testing. From a systematic review of 771 patients with haematological malignancies and sarcomas, we find contamination across a range of cancer clinical indications and DNA sources, with highest prevalence in saliva samples from acute myeloid leukaemia patients, and sorted CD3+ T-cells from myeloproliferative neoplasms. Further exploration reveals 108 hotspot mutations in genes associated with haematological cancers at risk of being subtracted by standard variant calling pipelines. Our work highlights the importance of contamination assessment for accurate somatic variants detection in research and clinical settings, especially with large-scale sequencing projects being utilised to deliver accurate data from which to make clinical decisions for patient care.

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02 /Specification & Classification

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