This thesis focuses on the development and application of a computational approach to investigate enhancer hijacking events in cancer genomics. Enhancer hijacking occurs when structural variations (SVs) lead to the misregulation of genes through the activation of distant enhancers, contributing to oncogene activation and tumor progression. We present a methodological framework for detecting these events, highlights case studies that illustrate the versatility and redundancy of enhancers, and explores how tumor cells exploit enhancer regions for their growth and survival. The thesis begins with an introduction to the biological significance of enhancers, their role in transcriptional regulation, and how enhancer hijacking can lead to cancer. Enhancers are regulatory elements that control the expression of genes, often located far from the genes they regulate. In cancer, SVs such as deletions, duplications, and translocations can bring enhancers into proximity with oncogenes, driving their aberrant expression. With this study we present a new approach to systematically identify these events, providing insights into their frequency and impact across different cancer types. A significant portion of the thesis is devoted to the development of the TERRA package, a computational tool designed to detect enhancer hijacking by integrating multiple genomic datasets. This package uses enhancers data, generates tissue-specific enhancer clusters, and maps SV breakpoints from cancer genomes to enhancers. By comparing enhancer activity with gene expression data, TERRA helps prioritize potential enhancer hijacking events that are likely to contribute to oncogenesis. We presented case studies to illustrate the practical application of the TERRA tool. These studies highlight different mechanisms of enhancer hijacking in cancer, including cases where a single enhancer is hijacked by multiple oncogenes and cases where multiple enhancers are co-opted to regulate a single oncogene. One of the prominent examples discussed is the hijacking of a prostate-specific enhancer cluster by several oncogenes in prostate cancer, emphasizing the versatility of enhancers in driving oncogenesis. Another example focuses on how multiple enhancers can co-opt a single oncogene, illustrating the redundancy and adaptability of these regulatory elements in cancer cells. In conclusion, this thesis provides a comprehensive framework for identifying and analyzing enhancer hijacking events in cancer. By integrating genomic data, enhancers genomic coordinates, and structural variations, the thesis offers new insights into the role of enhancers in cancer.
