I'd suggest taking a look at a paper like Characterizing complex structural variation in germline and somatic genomes. It sounds like you have done a basic read count based analysis. You may want to look at PEM methods as well as split-read methods to be complete. Since you have a single cancer tumor/normal, you'll want to identify genes that appear to be activated or inactivated by somatic SNVs and small indels and structural rearrangements, not just those with copy number changes. I'd suggest a focus on those techniques since they are likely to be more actionable in the setting of a single sample. As you increase your sample size, you can then apply techniques such as GISTIC to define better regions of shared copy number states. Note GSEA on copy number data from a single sample is not likely to be fruitful since the vast majority of genes in such copy number variable regions are likely passengers and perhaps only half of them are even expressed.