Genome instability is a hallmark of cancer, resulting in the accumulation of various types of alterations. Somatic structural variations (SVs) in cancer can shuffle DNA content in the genome, relocate regulatory elements, and alter genome organization. Enhancer hijacking occurs when SVs relocate distal enhancers to activate proto-oncogenes. However, most enhancer hijacking studies have only focused on protein-coding genes. Here, we develop a computational algorithm “HYENA” to identify candidate oncogenes (both protein-coding and non-coding) activated by enhancer hijacking based on tumor whole-genome and transcriptome sequencing data. HYENA detects genes whose elevated expression is associated with somatic SVs by using a rank-based regression model. We systematically analyzed 1,146 tumors across 25 types of adult tumors and identify a total of 108 candidate oncogenes including many non-coding genes. A long non-coding RNA TOB1-AS1 is activated by various types of SVs in 10% of pancreatic cancers through altered 3D genome structure. We find that high expression of TOB1-AS1 can promote cell invasion and metastasis. With CRISPR activation screens, we identified more potential oncogene candidates that can promote cancer cell growth or migration while confirming the known oncogenes. Applying HYENA to neuroblastoma samples, we identified 5 oncogene candidates activated by enhancer hijacking with default parameters and 58 candidates when gene copy information is excluded in the model. These genes may reveal new disease biology for neuroblastoma and potential new markers for risk level classification. In summary, our study highlights the contribution of genetic alterations in non-coding regions to tumorigenesis and tumor progression, and identified putative oncogenes activated by enhancer hijacking in multiple tumor types.