• Medientyp: E-Artikel
  • Titel: Abstract 2220: Analyzing cancer with single cell resolution using droplet technology
  • Beteiligte: Samuels, Michael L.; Kennedy, Scott
  • Erschienen: American Association for Cancer Research (AACR), 2010
  • Erschienen in: Cancer Research, 70 (2010) 8_Supplement, Seite 2220-2220
  • Sprache: Englisch
  • DOI: 10.1158/1538-7445.am10-2220
  • ISSN: 0008-5472; 1538-7445
  • Schlagwörter: Cancer Research ; Oncology
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  • Anmerkungen:
  • Beschreibung: <jats:title>Abstract</jats:title> <jats:p>Cancers develop and grow in the complex environments present in normal tissue, and tumor cells are composed of heterogeneous mixtures of both clonal transformed cells and other cell types. We demonstrate the use of microfluidic-generated single cell microdroplets in workflows that capture both phenotypic and genomic information from individual cells, enabling analysis of tumors with single cell resolution. This transformative new tool will allow for more thorough examinations of the variations that influence the predisposition and composition of cancers, and the cellular responses to therapeutic and prevention agents. Uniform picoliter-nanoliter volume aqueous droplets suspended in an immiscible oil provide unique opportunities for fluorescence-based analytical techniques, including sorting relevant sub-populations at rates of several hundred cells per second, coupled directly to single cell genomic characterization. We use a defined set of control samples to perform low-bias single cell whole genome amplification (WGA) within the sorted microdroplets, and show how following this with droplet PCR-based targeted amplification (of many thousands of selected genomic loci using a cancer-focused droplet primer library) provides an automated sample preparation method for any Next Gen sequencing platform. Single cell microdroplet technology results in a cost-effective method to gain sequence information from phenotypically selected individual cells, addressing cancer gene discovery and validation by powering the larger studies required to classify driver or passenger mutations and analyzing how epigenomic features (such as cytosine methylation) regulate transcriptional changes that can underlie cancer development.</jats:p> <jats:p>Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2220.</jats:p>
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