Abstract A38: Optimization of whole-genome amplification for analysis of single cells using next-generation sequencing

The accurate analysis of both genotypic variation in tumors and tumor evolution due to selective pressure is important in determining treatment options in the clinic. Next generation sequencing (NGS) of single cells from solid tumors and circulating tumor cells has the potential to dramatically increase the amount of genotypic detail obtained from these samples. For the analysis of single cells the challenge is to employ whole genome amplification (WGA) to obtain enough DNA for analysis while minimizing amplification bias and maintaining copy accuracy. We are developing tools for single cell sequencing to improve these parameters while also increasing sample throughput. Initially, three commercially available WGA methods were tested on 5-10 genome quantities of HCT-15 genomic DNA. Using the Ion Torrent AmpliSeq Cancer Hotspot Panel, the amplification accuracy, amplicon coverage and DNA yield were determined. When compared to controls significant differences were observed in the three WGA methods ability to accurately amplify DNA. The most accurate kit produced a specificity and sensitivity of 98.5% and 100% respectively. This protocol also produced a substantial DNA yield of 25 µgs and although, the average amplicon coverage indicated some bias, greater than 99% of the amplicons had at least 100-fold coverage. This WGA kit was then tested on single cells from a human breast cancer; an ER/PR/Her2 negative spindle cell metaplastic carcinoma. To obtain single cells the tumor was grown in a PDX mouse model and index sorted using a BD FACSAria II flow cytometer. The WGA produced an average DNA yield of 2.7± 0.8 µg, with 100-fold amplicon coverage of 92±7%. For the variants identified, the amplification bias differed by as much as 3,000 reads/variant. We are now taking steps to improve WGA of single cells and will report on these efforts in detail. To date when monitoring variant allele frequency and coverage depth in the triple negative tumor, KRAS and MET mutations were identified in single cells, as well as in the bulk sample. Interestingly, a TP53 mutation was identified only in single cells. This data supports the utility of WGA and single cell analysis to identify mutations, some having clinically relevant role for targeted therapy. Citation Format: Terry J. Amiss, Frances Tong, Eileen Snowden, Richard Kelly, Rainer Blaesius, Nick Herrmann, Friedrich Hahn, Warren Porter, Mitchell Ferguson, Chen Chang, Daphne Clancy, Stewart Jurgensen. Optimization of whole