4.8 Article

Identification and genetic analysis of cancer cells with PCR-activated cell sorting

期刊

NUCLEIC ACIDS RESEARCH
卷 42, 期 16, 页码 -

出版社

OXFORD UNIV PRESS
DOI: 10.1093/nar/gku606

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资金

  1. NSF [DBI-1253293]
  2. NIH [HG007233-01]
  3. Defense Advanced Research Projects Agency Living Foundries program [HR0011-12-C-0065]
  4. California Institute for Quantitative Biosciences (QB3)
  5. Rogers Family Foundation
  6. UCSF/Sandler Foundation Program for Breakthrough Biomedical Research
  7. University of California Proof of Concept Program
  8. Cancer Research Coordinating Committee of the University of California
  9. NSF
  10. Direct For Biological Sciences
  11. Div Of Biological Infrastructure [1253293] Funding Source: National Science Foundation

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Cell sorting is a central tool in life science research for analyzing cellular heterogeneity or enriching rare cells out of large populations. Although methods like FACS and FISH-FC can characterize and isolate cells from heterogeneous populations, they are limited by their reliance on antibodies, or the requirement to chemically fix cells. We introduce a new cell sorting technology that robustly sorts based on sequence-specific analysis of cellular nucleic acids. Our approach, PCR-activated cell sorting (PACS), uses TaqMan PCR to detect nucleic acids within single cells and trigger their sorting. With this method, we identified and sorted prostate cancer cells from a heterogeneous population by performing > 132 000 simultaneous single-cell TaqMan RT-PCR reactions targeting vimentin mRNA. Following vimentin-positive droplet sorting and downstream analysis of recovered nucleic acids, we found that cancer-specific genomes and transcripts were significantly enriched. Additionally, we demonstrate that PACS can be used to sort and enrich cells via TaqMan PCR reactions targeting single-copy genomic DNA. PACS provides a general new technical capability that expands the application space of cell sorting by enabling sorting based on cellular information not amenable to existing approaches.

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