Reliability of liquid biopsy analysis: an inter-laboratory comparison of circulating tumor DNA extraction and sequencing with different platforms.

作者: Thibaud Koessler , Viola Paradiso , Salvatore Piscuoglio , Ronny Nienhold , Liza Ho

DOI: 10.1038/S41374-020-0459-7

关键词: Circulating tumor DNAAllele frequencyGood laboratory practiceComputational biologyPersonalized medicineInter-laboratoryDeep sequencingComputer scienceLiquid biopsyReliability (statistics)

摘要: Liquid biopsy, the analysis of circulating tumor DNA (ctDNA), is a promising tool in oncology, especially personalized medicine. Although its main applications currently focus on selection and adjustment therapy, ctDNA may also be used to monitor residual disease, establish prognosis, detect relapses, possibly screen at-risk individuals. CtDNA represents small variable proportion cell-free (ccfDNA) which itself present at low concentration normal individuals so analyzing technically challenging. Various commercial systems have recently appeared market, but it remains difficult for practitioners compare their performance determine whether they yield comparable results. As first step toward establishing national guidelines analyses, four laboratories Switzerland joined comparative exercise assess ccfDNA extraction by sequencing. Extraction was performed using six distinct methods yielded equally high quality, suitable Sequencing synthetic samples containing predefined amounts eight mutations three different systems, with similar In all laboratories, were easily identified down 1% allele frequency, whereas detection 0.1% proved Linearity excellent cases while molecular superior one system this did not impact sensitivity. This study led several additional conclusions: First, should concentrate principles good laboratory practice rather than recommend particular system. Second, essential that thoroughly validate every aspect sequencing, respect initial amount average sequencing depth. Finally, as software critical mutation detection, variant callers underlying algorithms various types mutations.

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