Abstract

The recent application of genome-wide, single nucleotide polymorphism (SNP) microarrays to investigate DNA copy number aberrations in cancer has provided unparalleled sensitivity for identifying genomic changes. In some instances the complexity of these changes makes them difficult to interpret, particularly when tumour samples are contaminated with normal (stromal) tissue. Current automated scoring algorithms require considerable manual data checking and correction, especially when assessing uncultured tumour specimens. To address these limitations we have developed a visual tool to aid in the analysis of DNA copy number data. Simulated DNA Copy Number (SiDCoN) is a spreadsheet-based application designed to simulate the appearance of B-allele and logR plots for all known types of tumour DNA copy number changes, in the presence or absence of stromal contamination. The system allows the user to determine the level of stromal contamination, as well as specify up to 3 different DNA copy number aberrations for up to 5000 data points (representing individual SNPs). This allows users great flexibility to assess simple or complex DNA copy number combinations. We demonstrate how this utility can be used to estimate the level of stromal contamination within tumour samples and its application in deciphering the complex heterogeneous copy number changes we have observed in a series of tumours. We believe this tool will prove useful to others working in the area, both as a training tool, and to aid in the interpretation of complex copy number changes.

Highlights

  • Single nucleotide polymorphism (SNP) microarrays provide data on both genotype and signal intensity, the combination of which can be used to generate information on chromosomal segment copy number

  • Across a chromosomal region the relative B-allele intensity sits around 0.5 and the logR is expected to be close to zero; equal proportions of sample and reference DNA resulting in a ratio of 1 and a log2 value of zero

  • We propose that at the site of any of the simple copy number changes seen in tumours (LOH, NLOH & 3nAMP) the degree of shift can be used to estimate the percentage of cells that have a normal 2n genotype

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Summary

Introduction

Single nucleotide polymorphism (SNP) microarrays provide data on both genotype and signal intensity, the combination of which can be used to generate information on chromosomal segment copy number. When compared to cancer cell lines, DNA from a tumour biopsy often generates a distinctively different pattern (Ballele & logR) for a variety of the common copy number changes observed when using SNP microarrays.

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