Mate pair sequencing of whole-genome-amplified DNA following laser capture microdissection of prostate cancer - Abstract

High-throughput next-generation sequencing provides a revolutionary platform to unravel the precise DNA aberrations concealed within subgroups of tumour cells.

However, in many instances, the limited number of cells makes the application of this technology in tumour heterogeneity studies a challenge. In order to address these limitations, we present a novel methodology to partner laser capture microdissection (LCM) with sequencing platforms, through a whole-genome amplification (WGA) protocol performed in situ directly on LCM engrafted cells. We further adapted current Illumina mate pair (MP) sequencing protocols to the input of WGA DNA and used this technology to investigate large genomic rearrangements in adjacent Gleason Pattern 3 and 4 prostate tumours separately collected by LCM. Sequencing data predicted genome coverage and depths similar to unamplified genomic DNA, with limited repetition and bias predicted in WGA protocols. Mapping algorithms developed in our laboratory predicted high-confidence rearrangements and selected events each demonstrated the predicted fusion junctions upon validation. Rearrangements were additionally confirmed in unamplified tissue and evaluated in adjacent benign-appearing tissues. A detailed understanding of gene fusions that characterize cancer will be critical in the development of biomarkers to predict the clinical outcome. The described methodology provides a mechanism of efficiently defining these events in limited pure populations of tumour tissue, aiding in the derivation of genomic aberrations that initiate cancer and drive cancer progression.

Written by:
Murphy SJ, Cheville JC, Zarei S, Johnson SH, Sikkink RA, Kosari F, Feldman AL, Eckloff BW, Karnes RJ, Vasmatzis G   Are you the author?
Department of Molecular Medicine, Mayo Clinic, Medical Sciences Building 2, 200 First St., SW, Rochester, MN 55905, USA

Reference: DNA Res. 2012 Sep 18


PubMed Abstract
PMID: 22991452

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