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Somatic copy-number alterations (SCNAs) play a crucial role in the development of human cancer. However, it is not well understood what evolutionary mechanisms contribute to the global patterns of SCNAs in cancer genomes. Taking advantage of data recently available through The Cancer Genome Atlas, we performed a systematic analysis on genome-wide SCNA breakpoint data for eight cancer types. First, we observed a high degree of overall similarity among the SCNA breakpoint landscapes of different cancer types. Then, we compiled 19 genomic features and evaluated their effects on the observed SCNA patterns. We found that evolutionary indel and substitution rates between species (i.e. humans and chimpanzees) consistently show the strongest correlations with breakpoint frequency among all the surveyed features; whereas the effects of some features are quite cancer-type dependent. Focusing on SCNA breakpoint hotspots, we found that cancer-type-specific breakpoint hotspots and common hotspots show distinct patterns. Cancer-type-specific hotspots are enriched with known cancer genes but are poorly predicted from genomic features; whereas common hotspots show the opposite patterns. This contrast suggests that explaining high-frequency SCNAs in cancer may require different evolutionary models: positive selection driven by cancer genes, and non-adaptive evolution related to an intrinsically unstable genomic context. Our results not only present a systematic view of the effects of genetic factors on genome-wide SCNA patterns, but also provide deep insights into the evolutionary process of SCNAs in cancer.

Comparative analysis of somatic copy-number alterations across different human cancer types reveals two distinct classes of breakpoint hotspots