Integrative Analysis and Visualization Platform for Cancer Regulatory Genomics

PROJECT SUMMARY Recent advancements in next-generation sequencing technologies have resulted in the generation of vast quantities of publicly accessible data that are specific to cancer. This wealth of information has significantly enhanced our comprehension of disease mechanisms. It is now evident that alterations in epigenetic and genetic factors can disrupt the interactions between regulatory elements and their target genes, leading to abnormal gene regulation. Numerous studies conducted on distinct cancer types have yielded promising outcomes, unveiling previously unknown cancer subtypes characterized by distinctive enhancer landscapes. Moreover, these studies have identified clinically relevant regulatory elements that have implications for prognosis and treatment. Nevertheless, the majority of cancer analyses tend to concentrate on specific cancer subtypes and fail to capitalize on the entire breadth of available data encompassing both tumorigenic and normal tissue and cell types. As members of the ENCODE project, we have created the Registry of candidate cis-Regulatory Elements, an extensive compilation of nearly one million potential enhancers, promoters, and insulators in the human genome. These elements have been characterized across over 800 human cell types, offering valuable insights into non-coding regions. However, it's important to note that the Registry lacks clinical data, and all experimental findings were obtained from healthy individuals, which limits its applicability in cancer research. To address this limitation, we propose the development of a regulatory-element–target-gene atlas, which will enable researchers to explore the connections between regulatory elements and genes associated with cancer (Aim 1). Drawing upon our expertise in regulatory genomics and three-dimensional chromatin architecture, we will perform extensive analysis to identify germline variants, somatic mutations, and other genetic aberrations that affect cCREs and predict their effects on molecular phenotypes (Aim 2). Finally, to enhance accessibility to these tools, we will establish a new cloud-based computational notebook-based environment equipped with modular and customizable components for integrative data visualization. This environment will be flexible and user-friendly, allowing researchers to easily access and utilize cancer-specific genomic data (Aim 3). Finally, we will collaborate with ITCR members and perform community outreach (Aim 4).Together, these tools will simplify and improve the accessibility of cancer-specific genomic data.