Kyu-Tae Kim1,8,†, Hye Won Lee2,3,7,†, Hae-Ock Lee1,6,†, Sang Cheol Kim1, Yun Jee Seo2,4, Woosung Chung1,7, Hye Hyeon Eum1,8, Do-Hyun Nam2,4,7, Junhyong Kim10,9, Kyeung Min Joo2,5,7* and Woong-Yang Park1,6,7,*
1 Samsung Genome Institute, Samsung Medical Center, Seoul, South Korea
2 Institute for Refractory Cancer Research, Samsung Medical Center, Seoul, South Korea
3 Department of Urology, Samsung Medical Center, Sungkyunkwan University, Seoul, South Korea
4 Department of Neurosurgery, Samsung Medical Center, Sungkyunkwan University, Seoul, South Korea
5 Department of Anatomy and Cell Biology, Sungkyunkwan University, Seoul, South Korea
6 Department of Molecular Cell Biology, Sungkyunkwan University, Seoul, South Korea
7 Samsung Advanced Institute for Health Science and Technology (SAIHST), Sungkyunkwan University, Seoul, South Korea
8 Department of Biomedical Sciences, College of Medicine, Seoul National University, Seoul, South Korea
9 Department of Biology, University of Pennsylvania, Philadelphia 19104, PA, USA
10 Penn Program in Single Cell Biology, University of Pennsylvania, Philadelphia 19104, PA, USA
* Corresponding authors: Kyeung M Joo, Woong-Yang Park
† Equal contributors
Abstract (provisional)
Background Intra-tumoral genetic and functional heterogeneity correlates with cancer clinical prognoses. However, the mechanisms by which intra-tumoral heterogeneity impacts therapeutic outcome remain poorly understood. RNA sequencing (RNA-seq) of single tumor cells can provide comprehensive information about gene expression and single-nucleotide variations in individual tumor cells, which may allow for the translation of heterogeneous tumor cell functional responses into customized anti-cancer treatments. Results We isolated 34 patient-derived xenograft (PDX) tumor cells from a lung adenocarcinoma patient tumor xenograft. Individual tumor cells were subjected to single cell RNA-seq for gene expression profiling and expressed mutation profiling. Fifty tumor-specific SNVs, including KRAS G12D , were observed to be heterogeneous in individual PDX cells. Semi-supervised clustering, based on KRAS G12D mutant expression and a risk score representing expression of 69 lung adenocarcinoma-prognostic genes, classified PDX cells into four groups. PDX cells that survived in vitro anti-cancer drug treatment displayed transcriptome signatures consistent with the group characterized by KRAS G12D and low risk score. Conclusions Single-cell RNA-seq on viable PDX cells identified a candidate tumor cell subgroup associated with anti-cancer drug resistance. Thus, single-cell RNA-seq is a powerful approach for identifying unique tumor cell-specific gene expression profiles which could facilitate the development of optimized clinical anti-cancer strategies.