Cancer is a complex and heterogeneous disease characterized by aberrant gene regulation. Gene regulation is fundamentally orchestrated by the 3D genome organization which involves chromatin looping, compartmentalization, and the formation of topologically associating domains (TADs). Structural variations (SVs), such as genomic rearrangements, deletions, inversions, and duplications, are commonly observed in cancer genomes. However, the impact of 3D genome plasticity and how SVs contribute to gene expression dysregulation in cancer remain largely unknown. In this study, we investigated the 3D genome architecture in two specific cancer types: Diffuse Intrinsic Pontine Glioma (DIPG) and Liposarcoma. Through comprehensive profiling of transcriptomes (RNA-seq), enhancer landscapes (ChIP-seq for H3K27Ac), and 3D genome organization (Hi-C) in both cell lines and tumor tissues, we presented novel insights into the regulatory networks and oncogenic mechanisms underlying these cancers. In the case of DIPG, we demonstrated distinct 3D genome and epigenome landscape for DIPG comparing to Glioblastoma (GBM), highlighting tumor-type specific regulatory networks associated with known oncogenes. Furthermore, we showed that inhibition or degradation of BRD proteins can alter the 3D genome structures, implicating potential therapeutic strategies. In Liposarcoma, we identified thousands of SV events from patient samples and discovered enhancer co-amplification and hijacking events as novel mechanisms in upregulating oncogenes such as MDM2, CDK4 and HMGA2. We also partially resolved the complex structure variations and reconstructed the local genome and the giant chromosome, shedding light on the intricate genomic landscape of Liposarcoma. Overall, these two studies provide a comprehensive resource for the DIPG and LPS research and offer insights into the role of altered enhancers and the 3D genome in gene dysregulation in cancer. Importantly, our findings highlight potential therapeutic targets for treatment of these cancers.

Creator

• Wang, Juan

DOI

• https://doi.org/10.21985/n2-eh1x-d192

Subject

• Bioinformatics
• Biology

Language

• en

Alternate Identifier

• http://dissertations.umi.com/northwestern:16734
• etdadmin_upload_1013045

Date created

• 2023-01-01

Resource type

• Dissertation

Rights statement

• In Copyright