Date of Award

12-2024

Document Type

Campus Access Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Integrative Biosciences

First Advisor

Changmeng Cai

Second Advisor

Kourosh Zarringhalam

Third Advisor

Jill Macoska, Ozgun Babur, Shuai Gao

Abstract

Metastatic castration-resistant prostate cancer (mCRPC) is a heterogeneous disease, characterized by diverse drivers of progression and mechanisms of therapeutic resistance. Super-Enhancers (SEs) are large clusters of enhancers that can robustly drive transcription. SEs are frequently found at key oncogenic driver genes and play a significant role in cancer occurrence and progression. This research aims to evaluate whether SE landscape can predict the aggressiveness of prostate cancer and distinguish unique subtypes of mCRPC. Using Super-Enhancer Analysis for Lineages (SEAL) on published high-throughput chromatin structure data, I examined SEs across samples representing various stages of prostate cancer progression. Compared to SEs in normal prostate and primary prostate cancer, mCRPC samples exhibited a distinct SE program. Notably, five distinct SE programs were identified within mCRPC: three linked to androgen receptor (AR)-dependent CRPC (designated AR-1, AR-2, and AR-3) and two associated with AR-independent neuroendocrine (NEPC) and double-negative (DNPC) subtypes. For each subtype, top SE-driven genes with elevated expression were identified. Within the AR-dependent subtypes, AR-1 and AR-2 were particularly aggressive with higher tumor growth, showing enrichment in epithelial-mesenchymal transition (EMT) and metabolic pathways, respectively. Importantly, TWIST1 and HNF1A were identified as top SE-driven transcriptional drivers in AR-1 and AR-2 SE subtypes, respectively. In public mCRPC patient datasets, distinct TWIST1+ and HNF1A+ tumor subsets emerged within the AR-dependent subgroup, with patients showing high HNF1A expression displaying poor clinical outcomes. Furthermore, HNF1A was involved in glycolysis process and tumor development, indicating its role in metabolic reprogramming of tumor cells. Overall, this study demonstrates that distinct SE landscapes in mCRPC are associated with tumor progression, therapy resistance, and lineage plasticity. The molecular classifications defined by SEs may guide therapeutic decisions and facilitate the identification of key oncogenic drivers within each CRPC subtype.

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Liu, Mingyu - PhD_Dissertation_Signature_Page.pdf (268 kB)

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