Limitations
Unlike karyotypes obtained from conventional cytogenetics, virtual karyotypes are reconstructed by computer programs using signals obtained from disrupted DNA. In essence, the computer program will correct translocations when it lines up the signals in chromosomal order. Therefore, virtual karyotypes cannot detect balanced translocations and inversions. They also can only detect genetic aberrations in regions of the genome that are represented by probes on the array. In addition, virtual karyotypes generate a relative copy number normalized against a diploid genome, so tetraploid genomes will be condensed into a diploid space unless renormalization is performed. Renormalization requires an ancillary cell-based assay, such as FISH, if one is using arrayCGH. For karyotypes obtained from SNP-based arrays, tetraploidy can often be inferred from the maintenance of heterozygosity within a region of apparent copy number loss. Low-level mosaicism or small subclones may not be detected by virtual karyotypes because the presence of normal cells in the sample will dampen the signal from the abnormal clone. The exact point of failure, in terms of the minimal percentage of neoplastic cells, will depend on the particular platform and algorithms used. Many copy number analysis software programs used to generate array-based karyotypes will falter with less than 25–30% tumor/abnormal cells in the sample. However, in oncology applications this limitation can be minimized by tumor enrichment strategies and/or software optimized for use with oncology samples. The analysis algorithms are evolving rapidly, and some are even designed to thrive on ‘normal clone contamination’, so it is anticipated that this limitation will continue to dissipate.
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