ORCID ID
Graduation Date
Fall 12-19-2025
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Programs
Molecular Genetics & Cell Biology
First Advisor
Daryl J Murry
Second Advisor
David Oupicky
Third Advisor
Kyle Hewitt
Fourth Advisor
Jered Garrison
Abstract
Cellular metabolism is emerging as a crucial regulator of both pathological and physiological processes, critically influencing cancer progression, reproductive function and tissue remodeling. In cancer, the rewiring of metabolism supports cancer initiation, proliferation, immune evasion, metastasis and therapy resistance. Conventional cancer therapies are often hindered by resistance and relapse, highlighting the need for novel strategies to effectively treat cancers. Similarly, in ovarian physiology metabolic cues govern processes such as follicular development and luteal regression. While research over the past decade has explored some aspects of metabolic control, the complexity among these dynamic systems further demands high-resolution tools for in-depth insights. In this context, metabolomics has emerged as a robust tool that enables comprehensive profiling of metabolites, reflecting the real-time physiological state of biological systems. Metabolomics provides an unbiased functional readout of cellular phenotypes and responses to interventions with extreme accuracy and precision.
The central aim of this dissertation is to understand how metabolic reprogramming underlies tumorigenesis and reproductive physiology and to evaluate how novel drug candidates and regulatory proteins modulate these pathways. Using metabolomics, we investigate how various metabolic networks – including nucleotide metabolism, glycolysis, TCA cycle, and amino acid biosynthesis are altered in response to novel therapeutics and genetic perturbations. This work is organized into four chapters, each exploring a distinct biological context within the overarching theme of metabolic vulnerability and intervention.
In chapter 1, we use lipidomics to evaluate the impact of polymeric hydroxychloroquine on PDAC metabolism. By linking metabolic rewiring to suppression of protumorigenic lipid metabolites, this study demonstrates how metabolomics can reveal the suppression of lipid mediators following PCQ treatment, particularly in metabolically rigid tumors like PDAC. In chapter 2, we employed untargeted metabolomics to evaluate the metabolic consequences of treating OS cell lines with MO-OH-Nap tropolone. This study highlights how metabolomics can uncover context-specific vulnerabilities, guiding personalized therapeutic approaches in heterogenous tumors like osteosarcoma. Next, in chapter 3, we used metabolomics to map the metabolic reprogramming downstream of YAP and TAZ activation. This study offers novel insights into the metabolic determinants of ovarian physiology with implications for conditions like PCOS and provides detailed analysis of how transcriptional cues influence metabolic output. In chapter 4, we shift focus to transcriptional regulation of metabolism in PDAC through ELK3. Findings from this study underscore how metabolomics can uncover the metabolic consequences of transcription factor activity and identifying new targets like ELK3 for therapeutic intervention in metabolically plastic cancers such as PDAC.
Metabolomics has played a central role in revealing the metabolic hallmarks of disease progression, therapeutic response and genetic regulation. From targeting lipid signaling in PDAC, disrupting nucleotide metabolism in OS modulating redox and amino acid pathways in ovarian cells, to reversing glycolytic addiction through ELK3 suppression, metabolic profiling has been central to this dissertation. Collectively, this dissertation demonstrates the pivotal role of metabolic reprogramming and positions metabolomics as a cornerstone of next-generation biomedical research.
Recommended Citation
Kollala, Sai Sundeep, "Assessment of Cellular Metabolism in Disease Progression and Prevention" (2025). Theses & Dissertations. 994.
https://digitalcommons.unmc.edu/etd/994
Comments
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