@article{Potter20092013,
author = {Potter, Nicola E and Ermini, Luca and Papaemmanuil, Elli and Cazzaniga, Giovanni and Vijayaraghavan, Gowri and Titley, Ian and Ford, Anthony and Campbell, Peter and Kearney, Lyndal and Greaves, Mel}, 
title = {Single cell mutational profiling and clonal phylogeny in cancer},
year = {2013}, 
doi = {10.1101/gr.159913.113}, 
elocation-id = {gr.159913.113}, 
abstract ={The development of cancer is a dynamic evolutionary process in which intra-clonal, genetic diversity provides a substrate for clonal selection and a source of therapeutic escape. The complexity and topography of intra-clonal genetic architecture has major implications for biopsy-based prognosis and for targeted therapy. High depth, next generation sequencing (NGS) efficiently captures the mutational load of individual tumours or biopsies.  But, being a snapshot portrait of total DNA, it disguises the fundamental features of sub-clonal variegation of genetic lesions and of clonal phylogeny.
Single cell genetic profiling provides a potential resolution to this problem but methods developed to date all have limitations.  We present a novel solution to this challenge using leukaemic cells with known mutational spectra as a tractable model.  DNA from flow sorted single cells is screened using multiplex targeted Q-PCR within a micro-fluidic platform allowing unbiased single cell selection, high throughput and comprehensive analysis for all main varieties of genetic abnormalities: chimaeric gene fusions, copy number alterations and single nucleotide variants.  We show, in this proof of principle study, that the method has a low error rate and can provide detailed sub-clonal genetic architectures and phylogenies.}, 
URL = {http://genome.cshlp.org/content/early/2013/09/20/gr.159913.113.abstract}, 
eprint = {http://genome.cshlp.org/content/early/2013/09/20/gr.159913.113.full.pdf+html}, 
journal = {Genome Research} 
}