Hydro-Seq enables contamination-free high-throughput single-cell RNA-sequencing for circulating tumor cells

Yu-Heng Cheng, Yu-Chih Chen, Eric Lin, Riley Brien, Seungwon Jung, Yu-Ting Chen, Woncheol Lee, Zhijian Hao, Saswat Sahoo, Hyun Min Kang, Jason Cong, Monika Burness, Sunitha Nagrath, Max S. Wicha and Euisik Yoon ()
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Yu-Heng Cheng: University of Michigan
Yu-Chih Chen: University of Michigan
Eric Lin: University of Michigan
Riley Brien: University of Michigan
Seungwon Jung: University of Michigan
Yu-Ting Chen: Computer Science Department UCLA, Boelter Hall
Woncheol Lee: University of Michigan
Zhijian Hao: University of Michigan
Saswat Sahoo: University of Michigan
Hyun Min Kang: University of Michigan
Jason Cong: Computer Science Department UCLA, Boelter Hall
Monika Burness: University of Michigan
Sunitha Nagrath: University of Michigan
Max S. Wicha: University of Michigan
Euisik Yoon: University of Michigan

Nature Communications, 2019, vol. 10, issue 1, 1-11

Abstract: Abstract Molecular analysis of circulating tumor cells (CTCs) at single-cell resolution offers great promise for cancer diagnostics and therapeutics from simple liquid biopsy. Recent development of massively parallel single-cell RNA-sequencing (scRNA-seq) provides a powerful method to resolve the cellular heterogeneity from gene expression and pathway regulation analysis. However, the scarcity of CTCs and the massive contamination of blood cells limit the utility of currently available technologies. Here, we present Hydro-Seq, a scalable hydrodynamic scRNA-seq barcoding technique, for high-throughput CTC analysis. High cell-capture efficiency and contamination removal capability of Hydro-Seq enables successful scRNA-seq of 666 CTCs from 21 breast cancer patient samples at high throughput. We identify breast cancer drug targets for hormone and targeted therapies and tracked individual cells that express markers of cancer stem cells (CSCs) as well as of epithelial/mesenchymal cell state transitions. Transcriptome analysis of these cells provides insights into monitoring target therapeutics and processes underlying tumor metastasis.

Date: 2019
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DOI: 10.1038/s41467-019-10122-2

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