Advisory Committee Chair
Elliot J Lefkowitz
Advisory Committee Members
Thomas P Atkinson
Karin M Hardiman
Lewis Zhichang Shi
Date of Award
Degree Name by School
Doctor of Philosophy (PhD) Heersink School of Medicine
Understanding the molecular features underlying cancer health differences is crucial for developing effective therapeutic strategies. Multi-omics data analysis, integrating various molecular layers such as genomics, transcriptomics, epigenomics, proteomics, and metabolomics, provides a comprehensive approach to characterize the molecular landscape of cancer differences. By integrating diverse omics data, researchers can identify genetic variations, gene expression patterns, epigenetic modifications, and protein alterations that contribute to differences in cancer progression, and treatment response. These molecular features can serve as potential biomarkers for predicting patient outcomes and guiding personalized treatment strategies. Furthermore, multi-omics data analysis enables the identification of molecular subtypes specific to different populations, highlighting the heterogeneity of cancer and facilitating targeted therapies. Previous studies have unveiled the molecular characterization of cancer variations based on factors such as race/ethnicity, age, and gender. However, the molecular features of cancer differences among other factors have not been studied at the molecular level. Further research is necessary to comprehensively unravel the molecular features and mechanisms driving cancer differences across these additional factors, ultimately develop targeted interventions and address cancer differences effectively. iv The thesis presents a new framework for the comprehensive characterization of molecular differences in cancer with diverse factors. (i) molecular differences between cancer patients with normal weight and excess body fat. (ii) molecular differentiation between complete and incomplete responders to Neoadjuvant therapy in rectal cancer. In chapter 2, the content focuses on investigating the molecular characterizations of 14 cancer types with different body fat. We identify molecular alterations and pathways associated with overweight/obesity after balancing the other confounding factors. These include overweight/obesity-biased somatic mutations in cancer driver genes, copy number variations, alterations in DNA methylation patterns, dysregulated gene expression profiles, and immune cell infiltrations. In chapter 3, the content focuses on molecular characterizations of rectal cancer divergences in response to Neoadjuvant chemoradiation therapy. We explore the genomic and transcriptomic determinants of response to Neoadjuvant therapy (nCRT) in rectal cancer. The molecular characteristics classify subsets of rectal cancer with incomplete response to nCRT that display distinct molecular features. These differentiations underscore the need for tailored approaches to cancer management, considering the unique molecular characteristics of each patient subgroup. Finally, I summarize our contributions and demonstrate further directions in integrating multi-omics data for molecular characterizations to gain deeper insights into the molecular mechanisms driving cancer. These findings have significant implications for advancing cancer research, diagnostics, and therapeutics.
Huang, Fengyuan, "Unveiling the Molecular Features of Cancer Health Differences Through Multi-Omics Data Analysis" (2023). All ETDs from UAB. 426.
Available for download on Friday, March 01, 2024