Literature DB >> 22385957

Single-cell exome sequencing and monoclonal evolution of a JAK2-negative myeloproliferative neoplasm.

Yong Hou1, Luting Song, Ping Zhu, Bo Zhang, Ye Tao, Xun Xu, Fuqiang Li, Kui Wu, Jie Liang, Di Shao, 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.   

Abstract

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. Copyright Â
© 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22385957     DOI: 10.1016/j.cell.2012.02.028

Source DB:  PubMed          Journal:  Cell        ISSN: 0092-8674            Impact factor:   41.582


  260 in total

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5.  Calibrating genomic and allelic coverage bias in single-cell sequencing.

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7.  Assessing intratumor heterogeneity and tracking longitudinal and spatial clonal evolutionary history by next-generation sequencing.

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Review 8.  Clonal expansion in non-cancer tissues.

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Journal:  Nat Rev Cancer       Date:  2021-02-24       Impact factor: 60.716

9.  Tumour heterogeneity in the clinic.

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Journal:  Nature       Date:  2013-09-19       Impact factor: 49.962

10.  Genome-wide detection of single-nucleotide and copy-number variations of a single human cell.

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