Copy number variants (CNVs) are recognized to be part of the natural genetic variation in humans. Although there is still work to do to fully understand biology involved, it is likely that CNVs are responsible for a considerable proportion of phenotypic variation between individuals. On the other hand, copy number alterations (CNAs) are somatic changes in copy number that are characteristic of the genome of cancerous cells. These CNAs can affect cancer genes such as tumor suppressor genes and oncogenes.
Both somatic copy number alterations (CNAs) and germline copy number variants (CNVs) that are prevalent in healthy individuals can appear as recurrent changes in comparative genomic hybridization (CGH) analyses of tumors. This represent a challenge during the analysis since researchers are keen to identify regions that are frequently gained or lost in patients with a particular cancer.
What strategies can be implemented to distinguish between CNA and CNV changes?
One possible solution would be to collect data from healthy and tumor tissue samples from the same individual and run a matched paired analysis.
When performing matched paired analysis, generally a tumor sample is compared to its matched normal sample to identify only those events in the tumor that are not present in the normal tissue. Two files are loaded for each sample: data from the tumor tissue and the data from the matched normal tissue. (i.e. normal tissue from the same patient). The two files are combined into one result after the values in the normal sample are subtracted from the corresponding probes in the tumor sample. In the resulting profile, the Log ratios and B-Allele Frequencies (BAF) are shown after subtraction.
In BioDiscovery Nexus Copy Number software, researchers can perform matched paired analysis by loading both the tumor and normal data for each sample. After the values from the normal sample are subtracted from the tumor sample, these corrected probe level values are used to perform segmentation and calling.