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

Hou, Yong; Song, Liying; Zhu, Ping; Zhang, Bo; Tao, Ye; Xu, Xun; Li, Fuqiang; Wu, Kui; Liang, Jie; Шао, Ди; Wu, Huawei; Ye, Xiaofei; Wang, Hongzhi; Wu, Renhua; Jian, Min; Chen, Yan; Xie, Wei; Zhang, Ruren; Chen, Lei; Liu, Xin; Yao, Xiaotian; Zheng, Hancheng; Yu, Chang; Li, Qibin; Gong, Zhuolin; Mao, Mao; Xu, Yu; Yang, Lin; Li, Jingxiang; Wang, Wen; Zhang, Lu; Gu, Ning; Laurie, Goodman; Bolund, Lars; Kristiansen, Karsten; Wang, Jian; Yang, Huanming; Li, Yingrui; Zhang, Xiuqing; Wang, Jun

doi:10.1016/j.cell.2012.02.028

Cited by 495 publications

(542 citation statements)

References 40 publications

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“…When a 30% threshold for ADO is applied, the median ADO rate is reduced to 20% over the remaining cells based on all three methods. The ADO rate in the primary tumor cells was modestly higher than the median ADO rate of 15.6% observed in a control lymphoblastoid cell line and consistent with previous reports showing higher ADO rates in primary patient samples (12). These rates are also consistent with other single-cell primary sample cancer sequencing approaches using MDA and lower than approaches that have used PCR-based genome amplification (12)(13)(14)(15).…”

Section: Resultssupporting

confidence: 79%

Dissecting the clonal origins of childhood acute lymphoblastic leukemia by single-cell genomics

Gawad

Koh

Quake

2014

Proc. Natl. Acad. Sci. U.S.A.

276

313

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Many cancers have substantial genomic heterogeneity within a given tumor, and to fully understand that diversity requires the ability to perform single cell analysis. We performed targeted sequencing of a panel of single nucleotide variants (SNVs), deletions, and IgH sequences in 1,479 single tumor cells from six acute lymphoblastic leukemia (ALL) patients. By accurately segregating groups of cooccurring mutations into distinct clonal populations, we identified codominant clones in the majority of patients. Evaluation of intraclonal mutation patterns identified clone-specific punctuated cytosine mutagenesis events, showed that most structural variants are acquired before SNVs, determined that KRAS mutations occur late in disease development but are not sufficient for clonal dominance, and identified clones within the same patient that are arrested at varied stages in B-cell development. Taken together, these data order the sequence of genetic events that underlie childhood ALL and provide a framework for understanding the development of the disease at single-cell resolution.single-cell genomics | acute lymphoblastic leukemia | intratumor heterogeneity | clonal evolution | cytosine mutagenesis A more comprehensive understanding of how malignancies develop could facilitate the rational development of novel anticancer treatment and prevention strategies. Large projects that aim to comprehensively characterize somatic mutations in cancer samples have cataloged many of the recurrent genomic lesions in a wide variety of tumors (1). However, these studies do not measure the correlated cooccurrence of genomic lesions between different cells, which is required for understanding the clonal structure of a tumor as well as for rigorously determining temporal ordering of mutation acquisition. Other studies have provided some temporal resolution of mutation segregation patterns from diagnosis to disease recurrence, allowing for post hoc inference of intratumor clonal heterogeneity at diagnosis (2-5). However, approaches that rely on mutant allele frequencies to determine clonal structure require multiple samples from the same patient and are unable to resolve clones with mutations present at similar frequencies, which is a prerequisite to unambiguously determine the clonal structure and delineate the evolution of the disease (3-5). In principle, single cell genomics provides the most rigorous method to determine the clonal heterogeneity of tumors; as discussed below, there have been recent advances in this approach, but technical limitations have until now prevented it from fully addressing the questions of interest.Studies of pediatric acute lymphoblastic leukemias (ALL) have provided a limited ordering of the genetic events that underlie childhood leukemogenesis by studying prediagnostic samples. For example, ETV6 -RUNX1 translocations, which occur in about a third of patients under 10 y of age, have been shown to occur in utero by tracking the translocation back to neonatal blood spots (6, 7). In addition, a recent report ...

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Section: Resultssupporting

confidence: 79%

Dissecting the clonal origins of childhood acute lymphoblastic leukemia by single-cell genomics

Gawad

Koh

Quake

2014

Proc. Natl. Acad. Sci. U.S.A.

276

313

View full text Add to dashboard Cite

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“…Rather, it is a dynamic ensemble of subpopulations with different abnormalities undergoing molecular evolution [7][8][9] . Two fundamental principles of cancer signaling networks can explain why a binary driver/passenger classification may be too simplistic to accommodate the complex dynamic nature of tumors.…”

Section: From Genomic Lesions To Functional Network Perturbationsmentioning

confidence: 99%

Navigating cancer network attractors for tumor-specific therapy

et al. 2012

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“…It is important to bear in mind that these studies are based on the analysis of DNA from extractions from large numbers of cells, which only allows detection of CNVs if they are present in at least 5-10% of the cells 11,12 . In contrast, the recent development of new methods for the comprehensive study of the single cell genome [13][14][15][16] , epigenome 17 and transcriptome 18 is leading to a new understanding of cellular diversity. For instance, the study of single breast cancer cells revealed a significant number of de novo DNA copy number changes that appeared after only one cell cycle 15 and the analysis of large numbers of single cells has provided interesting insight in the evolution of genetically different cell populations within one tumour [14][15][16] .…”

mentioning

confidence: 99%

Low-grade chromosomal mosaicism in human somatic and embryonic stem cell populations

et al. 2014

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Current knowledge on chromosomal mosaicism in human cell cultures is mostly based on cytogenetic banding methods. The recent development of high-resolution full-genome analysis methods applicable to single cells is providing new insights into genetic and cellular diversity. Here we study the genetic content of 92 individual human cells, including fibroblasts, amniocytes and embryonic stem cells (hESCs), using single-cell array-based comparative genomic hybridization (aCGH). We find that human somatic and embryonic stem cell cultures show significant fractions of cells carrying unique megabase-scale chromosomal abnormalities, forming genetic mosaics that could not have been detected by conventional cytogenetic methods. These findings are confirmed by studying seven clonal hESC sub-lines by aCGH. Furthermore, fluorescent in situ hybridisation reveals an increased instability of the subtelomeric regions in hESC as compared to somatic cells. This genetic heterogeneity may have an impact on experimental results and, in the case of hESC, on their potential clinical use.

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

Cited by 495 publications

References 40 publications

Dissecting the clonal origins of childhood acute lymphoblastic leukemia by single-cell genomics

Dissecting the clonal origins of childhood acute lymphoblastic leukemia by single-cell genomics

Navigating cancer network attractors for tumor-specific therapy

Low-grade chromosomal mosaicism in human somatic and embryonic stem cell populations

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