A Tale of Three Transitions: Investigating Cancer Tumorigenesis, Metastasis, and Treatment via Omics Approaches

Abstract

Cancer develops through a series of evolutionary transitions in which cells undergo molecular alterations that enable tumor initiation, support metastatic dissemination, and modulate therapeutic intervention. Understanding the driving mechanisms of these transitions is essential for improving cancer prevention and treatment. Comprehensive methods in computational systems biology and advances in high-throughput sequencing provide new opportunities to study cancer progression in a systematic manner. In this dissertation, I investigate three critical transitions in cancer evolution using state-of-the-art omics modeling. First, I examine the alterations associated with early tumorigenesis in lung squamous cell carcinoma. By integrating transcriptomic data into context-specific genome-scale metabolic models, I identify dysregulations that may contribute to malignant precancer progression and highlight druggable drivers of early lung disease. Second, I characterize transcriptomic differences between primary and metastatic tumors across multiple cancer types with key normal tissue context. By comparing cancer gene expression profiles with their corresponding non-cancerous tissues, I identify molecular programs associated with metastatic adaptation in both classes of tumors. Finally, I evaluate a non-canonical, migration-restricting mechanism of the phosphodiesterase inhibitor Viagra using in-silico metabolic modeling, supporting its repurposing in combatting cancer. Altogether, this work demonstrates how systems-level approaches can reveal key molecular mechanisms underlying tumorigenesis, illuminating new paths to explore in cancer treatment.