Title |
Single-cell epigenomic variability reveals functional cancer heterogeneity
|
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Published in |
Genome Biology, January 2017
|
DOI | 10.1186/s13059-016-1133-7 |
Pubmed ID | |
Authors |
Ulrike M. Litzenburger, Jason D. Buenrostro, Beijing Wu, Ying Shen, Nathan C. Sheffield, Arwa Kathiria, William J. Greenleaf, Howard Y. Chang |
Abstract |
Cell-to-cell heterogeneity is a major driver of cancer evolution, progression, and emergence of drug resistance. Epigenomic variation at the single-cell level can rapidly create cancer heterogeneity but is difficult to detect and assess functionally. We develop a strategy to bridge the gap between measurement and function in single-cell epigenomics. Using single-cell chromatin accessibility and RNA-seq data in K562 leukemic cells, we identify the cell surface marker CD24 as co-varying with chromatin accessibility changes linked to GATA transcription factors in single cells. Fluorescence-activated cell sorting of CD24 high versus low cells prospectively isolated GATA1 and GATA2 high versus low cells. GATA high versus low cells express differential gene regulatory networks, differential sensitivity to the drug imatinib mesylate, and differential self-renewal capacity. Lineage tracing experiments show that GATA/CD24hi cells have the capability to rapidly reconstitute the heterogeneity within the entire starting population, suggesting that GATA expression levels drive a phenotypically relevant source of epigenomic plasticity. Single-cell chromatin accessibility can guide prospective characterization of cancer heterogeneity. Epigenomic subpopulations in cancer impact drug sensitivity and the clonal dynamics of cancer evolution. |
X Demographics
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Country | Count | As % |
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United States | 4 | 16% |
Belgium | 1 | 4% |
Austria | 1 | 4% |
Montenegro | 1 | 4% |
France | 1 | 4% |
Germany | 1 | 4% |
Spain | 1 | 4% |
Unknown | 11 | 44% |
Demographic breakdown
Type | Count | As % |
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Scientists | 13 | 52% |
Members of the public | 11 | 44% |
Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United Kingdom | 1 | <1% |
United States | 1 | <1% |
Sweden | 1 | <1% |
Unknown | 273 | 99% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 61 | 22% |
Researcher | 43 | 16% |
Student > Master | 32 | 12% |
Student > Bachelor | 26 | 9% |
Professor | 14 | 5% |
Other | 36 | 13% |
Unknown | 64 | 23% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 95 | 34% |
Agricultural and Biological Sciences | 62 | 22% |
Computer Science | 11 | 4% |
Medicine and Dentistry | 11 | 4% |
Immunology and Microbiology | 6 | 2% |
Other | 20 | 7% |
Unknown | 71 | 26% |