Single-Cell Exome Sequencing and Monoclonal Evolution of a JAK2-Negative Myeloproliferative Neoplasm

Yong Hou1, 2, 3, 11, Luting Song1, 4, 5, 6, 11, Ping Zhu7, 11, Bo Zhang1, 11, Ye Tao1, 11, Xun Xu1, Fuqiang Li1, Kui Wu1, Jie Liang1, Di Shao1, Hanjie Wu1, Xiaofei Ye1, Chen Ye1, Renhua Wu1, Min Jian1, Yan Chen7, Wei Xie1, 3, Ruren Zhang1, 3, Lei Chen1, 4, 5, 6, Xin Liu1, Xiaotian Yao1, Hancheng Zheng1, Chang Yu1, Qibin Li1, Zhuolin Gong1, Mao Mao8, Xu Yang1, Lin Yang1, Jingxiang Li1, Wen Wang5, Zuhong Lu2, 3, Ning Gu2, 3, Goodman Laurie1, Lars Bolund1, Karsten Kristiansen1, 9, Jian Wang1, Huanming Yang1, Yingrui Li1, , , Xiuqing Zhang1, , , Jun Wang1, 9, 10, ,

Tumor heterogeneity presents a challenge for inferring clonal evolution and driver gene identification. Here, we describe a method for analyzing the cancer genome at a single-cell nucleotide level. To perform our analyses, we first devised and validated a high-throughput whole-genome single-cell sequencing method using two lymphoblastoid cell line single cells. We then carried out whole-exome single-cell sequencing of 90 cells from a JAK2-negative myeloproliferative neoplasm patient. The sequencing data from 58 cells passed our quality control criteria, and these data indicated that this neoplasm represented a monoclonal evolution. We further identified essential thrombocythemia （ET）-related candidate mutations such as SESN2 and NTRK1, which may be involved in neoplasm progression. This pilot study allowed the initial characterization of the disease-related genetic architecture at the single-cell nucleotide level. Further, we established a single-cell sequencing method that opens the way for detailed analyses of a variety of tumor types, including those with high genetic complex between patients.

Single-Cell Exome Sequencing Reveals Single-Nucleotide Mutation Characteristics of a Kidney Tumor

Xun Xu1, 2, 14, Yong Hou1, 3, 4, 14, Xuyang Yin1, 14, Li Bao1, 14, Aifa Tang5, 6, 14, Luting Song1, Fuqiang Li1, Shirley Tsang7, Kui Wu1, Hanjie Wu1, 8, Weiming He1, Liang Zeng1, Manjie Xing1, Renhua Wu1, Hui Jiang1, Xiao Liu1, Dandan Cao1, Guangwu Guo1, Xueda Hu1, Yaoting Gui9, Zesong Li5, 6, Wenyue Xie9, Xiaojuan Sun5, 6, Min Shi9, Zhiming Cai5, 6, 9, Bin Wang1, Meiming Zhong1, Jingxiang Li1, Zuhong Lu3, 4, Ning Gu3, 4, Xiuqing Zhang1, Laurie Goodman1, Lars Bolund1, 10, Jian Wang1, Huanming Yang1, Karsten Kristiansen1, 11, Michael Dean1, 13, , , Yingrui Li1, , , Jun Wang1, 11, 12, ,

Clear cell renal cell carcinoma （ccRCC） is the most common kidney cancer and has very few mutations that are shared between different patients. To better understand the intratumoral genetics underlying mutations of ccRCC, we carried out single-cell exome sequencing on a ccRCC tumor and its adjacent kidney tissue. Our data indicate that this tumor was unlikely to have resulted from mutations in VHL and PBRM1. Quantitative population genetic analysis indicates that the tumor did not contain any significant clonal subpopulations and also showed that mutations that had different allele frequencies within the population also had different mutation spectrums. Analyses of these data allowed us to delineate a detailed intratumoral genetic landscape at a single-cell level. Our pilot study demonstrates that ccRCC may be more genetically complex than previously thought and provides information that can lead to new ways to investigate individual tumors, with the aim of developing more effective cellular targeted therapies.