Clinical application of tumour-in-normal contamination assessment from whole genome sequencing.
Jonathan MitchellSalvatore MiliteJack BartramSusan WalkerNadezda VolkovaOlena YavorskaMagdalena ZarowieckiJane ChalkerRebecca ThomasLuca VagoAlona SosinskyGiulio CaravagnaPublished in: Nature communications (2024)
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 [Formula: see text] 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.
Keyphrases
- drinking water
- risk assessment
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- end stage renal disease
- high resolution
- single cell
- electronic health record
- copy number
- newly diagnosed
- induced apoptosis
- chronic kidney disease
- liver failure
- climate change
- dna methylation
- big data
- prognostic factors
- squamous cell carcinoma
- dendritic cells
- intensive care unit
- label free
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- preterm infants
- smoking cessation
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- young adults
- oxidative stress
- quality improvement
- genome wide
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- clinical evaluation