Subclonal identification of driver mutations and copy number variations from single-cell DNA sequencing of tumors.

BACKGROUND Single-cell sequencing elucidates unique insights in understanding intratumor heterogeneity and clonal evolution. Both chromosomal structural change/copy number alteration/variation (CNA/CNV) and driver gene mutation events appear somatically at the early stages of oncogenesis and are critical in cancer initiation, tumor progression and therapy response. Previously, we have developed a high-throughput single-cell DNA analysis platform that leverages droplet microfluidics and a multiplex-PCR based targeted DNA sequencing approach. The platform demonstrates high sensitivity detection of single nucleotide variants (SNVs) and indels in the same cells and generation of high-resolution maps of clonal architecture based on mutational profiling. METHODS Here, we present a dynamic solution that we developed to simultaneously characterize point mutations, small indels and gene-level CNVs from the same single-cell. With improved biochemistry, we develop novel data analysis algorithms to detect amplification or loss of function in oncogenes and/or tumor suppressors reliably. Either using Loss of Heterozygosity (LOH) or the mutation profiles we generate a baseline control population and then estimate the ploidy by normalizing the read counts to the median of the normal population. We enable multiple visualizations of the copy number estimates in karyotype plots and line plots projected on snv clones. RESULTS We validated this method on clinical samples and admixture samples with cell lines mixed at known ratios. CNV alone confidently detects subclones while when combined with mutational analysis, rare subclones of ∼1% prevalence was detected. Integration of CNVs and SNVs facilitates more accurate reconstruction of tumor evolution to better understand cancer progression mechanisms as well for quality control of gene edited cells, to further advance cancer research and therapy.