High-resolution copy number arrays in cancer and the problem of normal genome copy number variation.
High-resolution techniques for analysis of genome copy number (CN) enable the analysis of complex cancer somatic genetics. However, the analysis of these data is difficult, and failure to consider a number of issues in depth may result in false leads or unnecessary rejection of true positives. First, segmental duplications may falsely generate CN breakpoints in aneuploid samples. Second, even when tumor data were each normalized to matching lymphocyte DNA, we still observed copy number polymorphisms masquerading as somatic alterations due to allelic imbalance. We investigated a number of different solutions and determined that evaluating matching normal DNA, or at least using locally derived normal baseline data, were preferable to relying on current online databases because of poor cross-platform compatibility and the likelihood of excluding genuine small somatic alterations.
Gorringe
Kylie L
KL
VBCRC Cancer Genetics Laboratory, Peter MacCallum Cancer Centre, East Melbourne, Victoria, Australia.
Campbell
Ian G
IG
D002869:Chromosome Aberrations; D002874:Chromosome Mapping; D004273:DNA, Neoplasm / Q000378:metabolism; D018628:Gene Dosage; D015894:Genome, Human; D006801:Humans; D008957:Models, Genetic; D009369:Neoplasms / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis; D011110:Polymorphism, Genetic; D020641:Polymorphism, Single Nucleotide
D004273:DNA, Neoplasm