Abstract 437: Leveraging new methods in single-cell copy number analysis and clonotype detection to uncover and characterize hidden subclones within standard cell lines

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Abstract Single-cell sequencing is an important and powerful tool for improving our understanding of cancer heterogeneity. While previous reports have largely focused on single-cell RNA-seq, we examined the utility of novel approaches for single-cell copy-number analysis and clonotype detection using 10x Chromium™ Technology capable of processing thousands of single cells. In contrast to bulk sequencing, this technology is able to call cell clonotypes down to 1% of 1,000 cell inputs, while providing detection of CNVs down to 100 Kb events on clones consisting of 10 or more cells. As a pilot study, we processed 300 single cells from COLO829 through the system, generating a barcoded short-read library, which was sequenced to a raw depth of approximately 600 million reads. Previous efforts had characterized COLO829 by bulk whole-genome sequencing of tumor/normal cell-line lineages grown and sequenced across four laboratories to help establish tumor/normal reference standards. We used barcode-aware bioinformatic analysis to recover reads derived from single cells, analyzing them in 20 Kb cassettes of reads providing both regional copy number and genome-wide ploidy estimates. This high resolution of CNV detection is enabled by aggregation of reads across cells within the same clone. Somewhat surprisingly, we find the presence of multiple clones within a single cell line growth evident by large-scale copy number changes, in some cases spanning entire chromosome arms. We show an ability to better resolve absolute copy number, whereas previous analysis approaches on bulk sequencing have lagged due to a reliance on indirect inferences. Consideration of prior publications on this cell line are consistent with the undescribed existence of clonal heterogeneity in these, and when considered with these data provide greater insight into copy number-driven events. Overall, our results suggest that single-cell copy number provides unique and important insight into larger-scale events, providing unique and distinct insight into cancer heterogeneity. Citation Format: Enrique I. Velazquez Villarreal, Vijay Kumar, Yifeng Yin, John D. Carpten, David W. Craig. Leveraging new methods in single-cell copy number analysis and clonotype detection to uncover and characterize hidden subclones within standard cell lines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 437.