Cancer is a complex and diverse disease, and its range of associated mutations is vast. The combination of these genomic changes in an individual is referred to as their 'mutational landscape.' These landscapes vary based on the type of cancer, and even individuals with the same type of cancer can h
The researchers have devised a computational analysis method to detect and distinguish the functional impacts of somatic structural variations.
Scientists have already documented the mutational landscapes of several forms of cancer. Somatic structural variations have been found to account for over 50% of all cancer-causing mutations. These mutations occur in cells over time, such as through copying errors inThey are not inherited and are found only in affected cells and in their daughter cells. As we age, such genomic alterations become more numerous, and a person’s mutational landscape increasingly comes to resemble a unique mosaic.
With conventional sequencing methods, distinguishing such homologs – chromosomes that are similar in shape and structure but not identical – is nearly impossible. “By resolving the individual homologs within a cell, somatic SVs can be identified much better than with other methods,” explains Sanders.
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