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Sensitive detection of tumor mutations from blood and its application to immunotherapy prognosis

Cell-free DNA (cfDNA) is attractive for many applications, including cancer detection, locating, and monitoring. A fundamental task underlying these applications is the SNV calling from cfDNA, which, however, faces a new challenge, namely, the generally very low tumor content in cfDNA. Thus all existing callers fail to achieve satisfactory performance. Here we present cfSNV, a method incorporating multi-layer error suppression and hierarchical mutation calling, to address this important challenge. Furthermore, by leveraging cfDNA’s comprehensive coverage of clonal landscape, for the first time cfSNV can profile mutations even in subclones. In both simulated and real patient data, cfSNV vastly outperforms existing tools, showing tens of times increase in sensitivity in detecting mutations with low allele frequency while maintaining high precision. cfSNV can enhance the clinical utilities of cfDNA by dramatically reducing the required sequencing depth and therefore reduce the cost by magnitudes, and further make the Whole-Exome-Sequencing of cfDNA a viable option. As an example, we demonstrate that cfDNA-WES allows a new biomarker to effectively select patients for immunotherapy.

Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data

Dataset ID Description Technology Samples
EGAD00001006096 HiSeq X Ten Illumina HiSeq 3000 83
Publications Citations
Sensitive detection of tumor mutations from blood and its application to immunotherapy prognosis.
Nat Commun 12: 2021 4172
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