Research ArticleCancer

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

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Science Translational Medicine  17 Jun 2020:
Vol. 12, Issue 548, eaaz8084
DOI: 10.1126/scitranslmed.aaz8084

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INVARiable progress detecting tumor DNA

The analysis of tumor DNA in a patient’s blood offers a noninvasive way to detect cancer and monitor responses to therapy. The samples are much easier to obtain than a conventional biopsy, and they may be more representative of the variety of mutations found in a given tumor. Unfortunately, the sensitivity of circulating DNA analysis is limited by the amount of tumor DNA in the blood and by the methods of detection. A pipeline for integration of variant reads (INVAR) designed by Wan et al. offers a way to use a patient’s individual tumor sequencing data to monitor for signs of relapse with greater sensitivity.


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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