Tumour evolution inferred by single-cell sequencing
Nicholas Navin,Jude Kendall,Jennifer Troge,Peter Andrews,Linda Rodgers,Jeanne McIndoo,Kerry Cook,Asya Stepansky,Dan Levy,Diane Esposito,Lakshmi Muthuswamy,Alexander Krasnitz,W. Richard McCombie,James W. Hicks,Michael Wigler +14 more
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TLDR
It is shown that with flow-sorted nuclei, whole genome amplification and next generation sequencing the authors can accurately quantify genomic copy number within an individual nucleus and indicate that tumours grow by punctuated clonal expansions with few persistent intermediates.Abstract:
Genomic analysis provides insights into the role of copy number variation in disease, but most methods are not designed to resolve mixed populations of cells. In tumours, where genetic heterogeneity is common, very important information may be lost that would be useful for reconstructing evolutionary history. Here we show that with flow-sorted nuclei, whole genome amplification and next generation sequencing we can accurately quantify genomic copy number within an individual nucleus. We apply single-nucleus sequencing to investigate tumour population structure and evolution in two human breast cancer cases. Analysis of 100 single cells from a polygenomic tumour revealed three distinct clonal subpopulations that probably represent sequential clonal expansions. Additional analysis of 100 single cells from a monogenomic primary tumour and its liver metastasis indicated that a single clonal expansion formed the primary tumour and seeded the metastasis. In both primary tumours, we also identified an unexpectedly abundant subpopulation of genetically diverse 'pseudodiploid' cells that do not travel to the metastatic site. In contrast to gradual models of tumour progression, our data indicate that tumours grow by punctuated clonal expansions with few persistent intermediates.read more
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Single-cell multiomics sequencing and analyses of human colorectal cancer
Shuhui Bian,Shuhui Bian,Yu Hou,Yu Hou,Xin Zhou,Xianlong Li,Xianlong Li,Jun Yong,Jun Yong,Yicheng Wang,Yicheng Wang,Wendong Wang,Jia Yan,Jia Yan,Boqiang Hu,Boqiang Hu,Hongshan Guo,Hongshan Guo,Jilian Wang,Shuai Gao,Shuai Gao,Y. J. Mao,Y. J. Mao,Ji Dong,Ji Dong,Ping Zhu,Ping Zhu,Dianrong Xiu,Liying Yan,Liying Yan,Lu Wen,Lu Wen,Jie Qiao,Fuchou Tang,Fuchou Tang,Wei Fu +35 more
TL;DR: This work demonstrates the feasibility of reconstructing genetic lineages and tracing their epigenomic and transcriptomic dynamics with single-cell multiomics sequencing and showed that DNA methylation levels are consistent within lineages but can differ substantially among clones.
Journal ArticleDOI
Intra-tumor Genetic Heterogeneity and Mortality in Head and Neck Cancer: Analysis of Data from The Cancer Genome Atlas
Edmund A. Mroz,Aaron M. Tward,Aaron M. Tward,Rebecca J. Hammon,Yin Ren,James W. Rocco,James W. Rocco,James W. Rocco +7 more
TL;DR: This study is the first to combine data from hundreds of patients, treated at multiple institutions, to document a relation between intra-tumor heterogeneity and overall survival in any type of cancer.
Journal ArticleDOI
Sources of PCR-induced distortions in high-throughput sequencing data sets
TL;DR: It is found that PCR stochasticity is the major force skewing sequence representation after amplification of a pool of unique DNA amplicons, and will have particular relevance to quantification of results from single cell sequencing, in which sequences are represented by only one or a few molecules.
Journal ArticleDOI
Progression from ductal carcinoma in situ to invasive breast cancer: Revisited
Catherine F. Cowell,Britta Weigelt,Rita A. Sakr,Charlotte K.Y. Ng,James W. Hicks,Tari A. King,Jorge S. Reis-Filho +6 more
TL;DR: The clinical challenge posed by DCIS, the contribution of the microenvironment and genetic aberrations to the progression from in situ to invasive breast cancer, the emerging evidence of the impact of intra‐tumor genetic heterogeneity on this process, and strategies to combat this heterogeneity are reviewed.
Journal ArticleDOI
Genomic analysis at the single-cell level.
TL;DR: A variety of approaches to single-cell genomic analysis are discussed, highlighting the importance of understanding the behavior and heterogeneity of the individual cells that constitute the system and their interactions.
References
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