cfSNV

Analysis of cell-free DNA (cfDNA)  has become a promising noninvasive approach in detecting cancer, identifying the tissue of origin, and monitoring. A fundamental task underlying these applications is SNV calling from cfDNA, which is hindered by the very low tumor content. Thus far, sensitive and accurate detection of low-frequency mutations (<5%) remains challenging for existing SNV callers. The EarlyDx founding team developed cfSNV, a novel method incorporating multi-layer error suppression and hierarchical mutation calling, to address this challenge. Furthermore, by leveraging cfDNA’s comprehensive coverage of the tumor’s clonal landscape, cfSNV can profile mutations in subclones. In both simulated and real patient data, cfSNV outperforms existing tools in sensitivity while maintaining high precision. cfSNV enhances the clinical utilities of cfDNA by improving mutation detection performance in medium-depth sequencing data, therefore making Whole-Exome Sequencing a viable option. As an example, we demonstrated that the tumor mutation profile from cfDNA WES data can provide an effective biomarker to predict immunotherapy outcomes.

For details, please refer to the following publications:

Li S. et al., Nature Communications 2021 Jul 7;12(1):4172 (link). 

Li S. et al. Nature Protocol. 2023 Feb 27. doi: 10.1038/s41596-023-00807-w (link).