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Single-Cell Exome Sequencing and Monoclonal Evolution of a JAK2-Negative Myeloproliferative Neoplasm
Author(s) -
Yong Hou,
Luting Song,
Ping Zhu,
Bo Zhang,
Ye Tao,
Xun Xu,
Fuqiang Li,
Kui Wu,
Jie Liang,
Ди Шао,
Hanjie Wu,
Xiaofei Ye,
Chen Ye,
Renhua Wu,
Min Jian,
Yan Chen,
Wei Xie,
Ruren Zhang,
Lei Chen,
Xin Liu,
Xiaotian Yao,
Hancheng Zheng,
Chang Yu,
Qibin Li,
Zhuolin Gong,
Mao Mao,
Xu Yang,
Lin Yang,
Jingxiang Li,
Wen Wang,
Zuhong Lu,
Ning Gu,
Goodman Laurie,
Lars Bolund,
Karsten Kristiansen,
Jian Wang,
Huanming Yang,
Yingrui Li,
Xiuqing Zhang,
Jun Wang
Publication year - 2012
Publication title -
cell
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 26.304
H-Index - 776
eISSN - 1097-4172
pISSN - 0092-8674
DOI - 10.1016/j.cell.2012.02.028
Subject(s) - biology , exome sequencing , myeloproliferative neoplasm , exome , monoclonal antibody , cancer research , monoclonal , neoplasm , somatic evolution in cancer , genetics , myeloproliferative disorders , computational biology , mutation , immunology , cancer , gene , bone marrow , myelofibrosis , antibody
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.

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