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J Pathol. 2008 Nov;216(3):307-16. doi: 10.1002/path.2413.

Microdissection molecular copy-number counting (microMCC)--unlocking cancer archives with digital PCR.

Author information

1
Centre for Respiratory Research, Department of Medicine, Royal Free and University College Medical School, The Rayne Institute, London WC1E 6JJ, UK.

Abstract

Most cancer genomes are characterized by the gain or loss of copies of some sequences through deletion, amplification or unbalanced translocations. Delineating and quantifying these changes is important in understanding the initiation and progression of cancer, in identifying novel therapeutic targets, and in the diagnosis and prognosis of individual patients. Conventional methods for measuring copy-number are limited in their ability to analyse large numbers of loci, in their dynamic range and accuracy, or in their ability to analyse small or degraded samples. This latter limitation makes it difficult to access the wealth of fixed, archived material present in clinical collections, and also impairs our ability to analyse small numbers of selected cells from biopsies. Molecular copy-number counting (MCC), a digital PCR technique, has been used to delineate a non-reciprocal translocation using good quality DNA from a renal carcinoma cell line. We now demonstrate microMCC, an adaptation of MCC which allows the precise assessment of copy number variation over a significant dynamic range, in template DNA extracted from formalin-fixed paraffin-embedded clinical biopsies. Further, microMCC can accurately measure copy number variation at multiple loci, even when applied to picogram quantities of grossly degraded DNA extracted after laser capture microdissection of fixed specimens. Finally, we demonstrate the power of microMCC to precisely interrogate cancer genomes, in a way not currently feasible with other methodologies, by defining the position of a junction between an amplified and non-amplified genomic segment in a bronchial carcinoma. This has tremendous potential for the exploitation of archived resources for high-resolution targeted cancer genomics and in the future for interrogating multiple loci in cancer diagnostics or prognostics.

PMID:
18773450
DOI:
10.1002/path.2413
[Indexed for MEDLINE]

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