Medicine and Health Sciences Commons^™

Immune Landscape Of Early Liver Metastatic Lesions In A Novel Immunocompetent Murine Colorectal Cancer Metastasis Model, Alaa Mohamed

Dissertations and Theses (Open Access)

Colorectal cancer minimal residual disease (MRD) represents a major clinical problem for colorectal cancer patients, with failure rates of surgery and adjuvant chemotherapy between 5% to 40% depending on stage of disease. In our study, we simulated MRD using genetically engineered organoids with precise somatic editing of APC and TP53, creating a murine model that mimics human liver metastatic colorectal cancer. By implementing a meticulously timed experimental metastatic model, we could detect microscopic tumor lesions. Through genomic and transcriptomic analyses, we pinpointed the importance of macrophages, particularly those expressing high levels of CSF1R, in these microscopic metastatic focal lesions. We …

Unraveling Epigenetic Mechanisms That Regulate Breast Cancer Lung Metastatic Relapse By Rewiring The Immune Microenvironment, Jayanta Mondal

Dissertations and Theses (Open Access)

Metastasis accounts for >90% of cancer-related deaths and thwarting metastasis is widely considered to be the “Holy Grail” of cancer treatment. Breast cancer is the most common cause of cancer-related death among women and is characterized by its proclivity to spread to distant secondary organs like the lungs, and the brain. These disseminated tumor cells lie dormant at the secondary site and can undergo metastatic relapse. Epigenetic alterations are a predominant hallmark of cancer, however, its role in facilitating reawakening of dormant cancer cells and the subsequent metastatic relapse remains to be elucidated. To address this gap of knowledge, we …

Developing Novel Therapies Targeting The Tumor Microenvironment Of Aggressive Breast Cancer, Lan T H Phi

Dissertations and Theses (Open Access)

Triple-negative breast cancer (TNBC) and inflammatory breast cancer (IBC) are the most aggressive breast cancer subtypes. The tumor microenvironment (TME) is critical in driving these aggressive breast cancers' clinical phenotype and aggressiveness. Therefore, we explored novel actionable targets and complementary therapies targeting the TME to improve the outcomes of patients with these cancers.

In this thesis, we identified AXL as a potential therapeutic target in IBC due to its role in generating an immunosuppressive TME. Indeed, inhibiting the AXL pathway suppresses IBC tumor growth and reduces M2 macrophage populations in various mouse models. Mechanistically, AXL facilitates the polarization of M2 …

Impact Of Tumor Cell Expressed Cd38 On Metastasis And Immune Evasion In Breast Cancer, Tanvi Visal

Dissertations and Theses (Open Access)

Triple-negative breast cancer (TNBC) is a highly metastatic breast cancer subtype. The epithelial-to-mesenchymal transition (EMT) of cancer cells is a key feature of the metastatic cascade and is not a binary process but often generates malignant cells with both epithelial (E) and mesenchymal (M) traits known as hybrid EM cells. Recent studies highlight the enhanced metastatic potential of the hybrid EM cells. However, molecular insights and targetable vulnerabilities within hybrid EM remain elusive. We discovered that hybrid EM murine tumors are enriched in CD38, an immunesuppressive molecule associated with worse clinical outcomes in liquid malignancies but relatively understudied in solid …

Relationship Between Processing Body Formation, Epithelial-To-Mesenchymal Transition, And Invasion In Lung Adenocarcinoma, Amanda Warner

Dissertations and Theses (Open Access)

Lung cancer is the leading cause of cancer-related deaths in the United States, largely due to its ability to metastasize. Epithelial-to-mesenchymal transition (EMT) is a process that enhances the ability of cells to lose their cell-cell contacts, invade, and enter the blood stream which are essential during metastasis. Many transcriptional gene programs are altered during EMT such as activation of mesenchymal transcription factors, like ZEB1, and enhanced response to the TGFβ1 cytokine. In oncogenic contexts, TGFβ1 enhances the formation of processing-bodies (P-bodies) where P-body proteins are required for invasion in multiple cancerous cell lines. P-bodies are a type of ribonucleoprotein …

Rod Photoreceptor Regeneration In A Zebrafish Model With Retinitis Pigmentosa, Eyad Shihabeddin

Dissertations and Theses (Open Access)

A cellular hallmark of inherited retinal degenerative diseases is progressive loss of photoreceptors until one is completely blind. Unlike mammalian models, Zebrafish have the ability to naturally regenerate their neurons after injury or disease is detected. We have generated a zebrafish model with the most common autosomal dominant form of the inherited retinal degenerative disease known as Retinitis Pigmentosa. We utilize immunohistochemistry, single-cell RNA sequencing, several analysis tools, behavioral assays and oligonucleotides to characterize our zebrafish model and identify the transcription factors necessary for rod photoreceptor regeneration. We show that our zebrafish model has continuous degeneration and regeneration of rod …

Automated Radiotherapy Treatment Planning For Breast Cancer: A Robust To Ol For Global Deployment, Hana Baroudi

Dissertations and Theses (Open Access)

Breast cancer incidence continues to rise worldwide, particularly in low- and middle-income countries, where limitations in resources already constrain access to timely care. Radiotherapy is a cornerstone of breast cancer management, proven to significantly lower both recurrence and mortality. However, a growing shortage of radiation staff worldwide threatens the prompt delivery of these treatments.This thesis proposes an automated solution to address the limited accessibility of radiotherapy planning in breast cancer management by developing an end-to-end automated treatment planning model and evaluating its performance and limitations across diverse patient populations.

An automated contouring model was trained using data from 104 whole-breast …

Development Of Lineal Energy Spectrum-Based Biological Effects Models For Protons, Joseph M. Decunha, Fada Guan, David Grosshans, Zhongxing Liao, Dragan Mirkovic, Oleg Vassiliev, Radhe Mohan

Dissertations and Theses (Open Access)

In this dissertation, methods are developed and described to allow for the rapid calculation of microdosimetric spectra (specifically, lineal energy) for protons. SuperTrack, a GPU-accelerated tool for calculation of microdosimetric spectra was developed and is capable of computing lineal energy spectra up to 5000x faster than using Geant4 directly. Proton lineal energy spectra generated by SuperTrack are indistinguishable from those generated by Geant4. With SuperTrack, large libraries of lineal energy spectra for monoenergetic protons spanning 0-300 MeV have been developed. The proton lineal energy spectra calculated by SuperTrack have been compared to experimental measurements made by a tissue equivalent proportional …

Overcoming Resistance To Cdk4/6-Targeted Therapy Using Jak2/Stat3 Inhibitor In Triple-Negative Breast Cancer, Chuling Zhuang

Dissertations and Theses (Open Access)

Breast cancer is the most common type of cancer diagnosed in women, with nearly 30% of cases becoming metastatic accounting for over 90% of breast cancer-related deaths. Among different breast cancer subtypes, triple-negative breast cancer (TNBC) has the worst prognosis and the highest propensity to metastasize. However, TNBC patients have limited treatment options due to their lack of actionable drug targets while therapeutic resistances result in high rates of recurrence and metastasis. Cyclin-dependent kinase 4 and 6 (CDK4/6) are major cell cycle regulators that control G1 to S phase transition and aberrant hyperactivation of the CDK4/6 pathway results in uncontrolled …

Elucidating The Multi-Omics Of Early-Onset Colorectal Cancer, Jumanah Alshenaifi

Dissertations and Theses (Open Access)

The incidence and mortality rates of sporadic early-onset colorectal cancer have increased in recent decades, but there is no clear etiological basis for this trend. EOCRC is commonly defined as colon and rectal cancers diagnosed before the age of 50 years. The rising incidence of EOCRC has made it the second most common cancer and the third leading cause of cancer death in this age group. The rising incidence of EOCRC is also documented internationally in more than 20 countries across different continents. Clinically, EOCRC has a distinct, more aggressive clinical profile than LOCRC. While approximately 15% of EOCRC cases …

Combined Inhibition Of Lysine-Specific Demethylase 1 And Kinase Signaling As A Preclinical Treatment Strategy In Glioblastoma, Lea Stitzlein

Dissertations and Theses (Open Access)

Glioblastoma is the most common primary malignant brain tumor in adults, with limited treatment options resulting in a poor prognosis. Lysine-specific demethylase 1 (LSD1) is overexpressed in glioblastoma and contributes to tumor growth and treatment resistance. Inhibitors of LSD1 have shown preclinical promise but have had limited clinical development for glioblastoma. Given the frequent kinase pathway alterations in glioblastoma, the interplay between LSD1 inhibition and kinase signaling pathways was investigated to identify vulnerabilities that could be exploited through rationally designed combination therapies. We hypothesized that LSD1 inhibitors would activate kinase signaling pathways, such as MAPK, and the addition of kinase …

The Influence Of Scientific, Genetic, And Health Literacy On Carrier Screening Decision-Making, Brenna D. Albracht

Dissertations and Theses (Open Access)

For those wishing to assess their reproductive risks and make informed decisions in their reproductive planning, carrier screening for autosomal recessive and X-linked conditions, as well as cell-free DNA (cfDNA) screening for aneuploidy, are recommended during pregnancy. Despite similarities in purpose, sample requirements, insurance coverage, and safety, a lower percentage of individuals elect carrier screening than cfDNA screening, suggesting there may be a disconnect in what patients perceive as valuable information for their pregnancy. Previous studies have attempted to explain the factors associated with carrier screening uptake or decline; however, no models have yet accounted for a patient’s literacy level …

Achieving The Practice-Based Competencies: Are More Than 50 Cases Needed?, Farren Lopez

Dissertations and Theses (Open Access)

Genetic counseling graduate programs are required to provide didactic coursework and fieldwork experiences to foster development of the practice-based competencies (PBCs) in trainees. Currently, every graduating trainee must log a minimum of 50 participatory encounters to demonstrate readiness for entry-level practice of the PBCs. Previous studies have noted that many trainees exceed the 50-case standard, raising the question of whether this minimum satisfies the training needs of every student. To assess the perceived number of encounters needed for graduates to independently perform the PBCs, a survey was administered to 2023 and 2024 graduates of North American genetic counseling training programs. …

Uncovering A Fundamental Mechanism Underlying Female Oocyte Quality And Rasopathies Using C. Elegans As A Model System, Han Bit Baek

Dissertations and Theses (Open Access)

Signaling pathways are molecular networks that allow cells to communicate between and within themselves. They are crucial for the coordination of diverse cellular processes and are the molecular mechanism in which cells sense and respond to their environment. RAS (Rat Sarcoma) is a small GTPase that transmits extracellular growth factor signals through a downstream kinase cascade and ERK (Extracellular-signal regulated kinase) is the terminal kinase, and it controls cellular processes such as proliferation, differentiation, and survival by phosphorylating its downstream effectors. This post translational modification regulates the effector by modulating its activity, levels, and/or interaction with other molecules. Given the …

Exploring The Immunologic Consequences Of Atrx Deficiency In Glioma, Benjamin Whitfield

Dissertations and Theses (Open Access)

ATRX is a key chromatin regulator that is frequently mutated across multiple cancer types. One of the most common ATRX-mutated tumor types is the adult-type glioma, IDH-mutant, Astrocytoma. It is known that ATRX mutation leads to increases in DNA damage, replication stress, and global epigenetic regulation at a cell level; however, less is known about the impact of ATRX mutation on immune signaling. Furthermore, little is known about the interaction of ATRX loss with gain-of-function mutations in IDH. In this paper we set out to explore the impact of ATRX loss on immune signaling in gliomas, both in the context …

Investigating Prefrontal Cortex Neuronal Signatures Of Opioid-Induced Risk-Taking Behavior, Cana Quave

Dissertations and Theses (Open Access)

Opioid use disorder occurs alongside impaired risk-related decision-making, but the underlying neural correlates are unclear. We developed an approach-avoidance conflict task using a modified conditioned place preference procedure to study neural signals of risky opioid seeking in the prefrontal cortex, a region implicated in executive decision-making. Following morphine conditioned place preference, rats underwent a conflict test in which fear-inducing cat odor was introduced in the previously drug-paired side of the apparatus. While the saline-exposed control group avoided cat odor, the morphine group included two subsets of rats that either maintained a preference for the paired side despite the presence of …

Automated To Ols For Contour Review In Radiotherapy, Barbara Marquez

Dissertations and Theses (Open Access)

Peer review of organ-at-risk and target volume delineation is essential for patient safety and optimization of treatment outcomes. Peer review makes a substantial impact on patient outcomes, reporting notable rates of plan changes when reviewed and worse survival when patient cases are not reviewed. In around half of revised cases, target volume change is the required cause for modification (related to tumor control); in one in ten cases, it is normal tissue sparing (related to treatment toxicity). Essentially all North American institutions with accredited residency training programs hold peer review to some capacity. However, accessibility to practicing routine peer review …

An Investigation Into The Potential Of Cell Therapies For Acute Myeloid Leukemia (Aml) Treatment, Amanda Eckstrom

Dissertations and Theses (Open Access)

Despite recent advances in acute myeloid leukemia (AML) treatment, curative rates remain poor with high rates of relapse and many patients are unable to tolerate the intensive chemotherapy standard of care regimen. Cell therapies have shown great success against hematologic malignancies but face several challenges including treatment-related toxicities and human-leukocyte antigen (HLA) matching. Natural killer (NK) cells and gamma delta (γδ) T cells offer alternative effector cell options for cell therapies that do not require HLA-matching and have shown low toxicity in previous studies. In this project, we sought to evaluate FT538 induced pluripotent stem cell-derived NK (iPSC-NK) and donor-derived …

Evaluating Triage To Genetic Counseling Using An Online Reproductive Genetics Module, Grace Ra

Dissertations and Theses (Open Access)

The American College of Obstetricians and Gynecologists recommends genetic screening for all pregnant women. As clinical recommendations broaden and demand for prenatal screening increases, obstetric practitioners report time constraints and lack of genetics knowledge as challenges to providing sufficient pretest education. These challenges in offering routine screening are further compounded by the inequities in access to genetic counseling and testing. Thus, alternative education and service delivery models have emerged to meet the demands for prenatal genetics education and help mitigate challenges surrounding access. At UTHealth Houston, an online triage and education module, the Prenatal Genetics Education Program (PGEP), was created …

Denial Of Inpatient Genetic Testing: A Study On Outpatient Yield And Outcomes, Cindy Y. Canales

Dissertations and Theses (Open Access)

This study investigates the difference in diagnostic yield between patients approved for inpatient genetic testing compared to those denied inpatient testing and the effect of an earlier diagnosis on outcomes and medical/clinical care. In the literature, research has explored the impact of a diagnostic delay for patients with genetics conditions, assessed the utility of genetic testing in the inpatient setting, and described the impact to care of an earlier diagnosis. However, gaps remain on research exploring the diagnostic yields of inpatient versus outpatient settings and the potential impact to care an inpatient genetic testing request denial may pose. This is …

Leveraging Observational And Rct Data For Understanding Interventions’ Efficacy: Applications In Progressive And Acute Neurological Diseases, Yaobin Ling

Dissertations and Theses (Open Access)

The advancement of drug repurposing for progressive and acute neurological diseases is hampered by the limitations of randomized clinical trials (RCTs) and observational data. This dissertation presents a comprehensive framework to integrate data-driven insights from multiple sources, including observational studies, RCTs, and synthetic data generation, to overcome these challenges.

The first study focuses on estimating treatment effects on the population level, which investigates the effects of routine and high-dose influenza vaccines on the risk of Alzheimer’s Disease and Related Dementias (ADRD) through a trial emulation framework applied to health claims data, addressing biases inherent in observational studies. The second study …

Standardizing Social Determinants Of Health Factors From Heterogeneous Sources To Improve Data Fairness, Yifang Dang

Dissertations and Theses (Open Access)

Social Determinants of Health (SDoH) significantly influence health outcomes, yet their representation in computational models remains fragmented. This dissertation addresses this gap by constructing an SDoH ontology (SDoHO), leveraging it to improve large language model (LLM) performance, and using LLMs to extract new knowledge and enrich the ontology. The overarching goal is to establish a feedback loop where ontology development enhances LLM-based extraction, and LLM-derived insights refine and expand the ontology. The methodology is structured across three aims: (1) ontology construction, (2) ontology-assisted LLM enhancement, and (3) LLM-driven ontology enrichment, with a focus on Alzheimer’s Disease and Related Dementias (ADRD). …

Computer-Aided Integrated Rehabilitation For Post-Stroke Patients Using Deep Learning Techniques, Kaichen Tang

Dissertations and Theses (Open Access)

Stroke is a leading cause of long-term disability, often requiring intensive rehabilitation and frequent clinical assessments such as the Fugl-Meyer Assessment. However, traditional in-person evaluations are resource-heavy and difficult to scale, limiting access for many patients. Additionally, monitoring vital signs like blood pressure and oxygen saturation typically depends on specialized equipment, leading to fragmented care and incomplete recovery insights. Even when assessments and monitoring are available, patients often struggle to maintain high-quality, intensive exercise routines without supervision, further limiting rehabilitation outcomes.

To address these challenges, this dissertation proposes an AI-driven, smartphone-based framework that integrates automated motor function assessment, non-invasive vital …

Leveraging And Advancing The Foundation Models For Clinical Trajectory Analysis Based On Electronic Health Record Data, Jianping He

Dissertations and Theses (Open Access)

Enhancements in foundation models have provided significant potentials for clinical applications. This dissertation leverages and advances foundation models for a range of clinical tasks using electronic health record (EHR) data, demonstrating their applicability in Clinical Temporal Relation Extraction (CTRE), disease prediction, and patients trajectory analysis.

Aim 1 is to efficiently adapt large language models (LLMs) for CTRE in both full data and few-shot settings. This study leveraged four LLMs: GatorTron-Base, GatorTron-Large, LLaMA3.1, and MeLLaMA. The proposed fine-tuning strategies include: (a) standard fine-tuning; (b) hard-prompting; (c) soft-prompting; (d) Low-Rank Adaptation (LoRA). We found that nearly all proposed fine-tuning strategies outperformed existing …

Precision Drug Dosing And Disease Risk Prediction: Advanced Deep Learning Artificial Intelligence Approaches For Precision Medicine Using Structured Electronic Health Records Data, Bingyu Mao

Dissertations and Theses (Open Access)

Advancements in precision medicine increasingly rely on data-driven approaches to improve clinical decision-making. This work presents three interconnected studies that leverage deep learning, reinforcement learning, and comparative modeling to address key challenges in precision drug dosing and disease risk prediction. Together, these contributions offer novel computational frameworks that enhance model performance, improve dosing strategies, and guide model selection for clinical predictive tasks.

To improve individualized vancomycin therapeutic drug monitoring (TDM), the first study introduces PKRNN-2CM, a novel deep learning framework that integrates a two-compartment pharmacokinetic (PK) model with recurrent neural networks (RNNs). While one-compartment models are commonly used in clinical …

Computational Methods For Enhancing The Quality And Interoperability Of Biomedical Terminologies, Xubing Hao

Dissertations and Theses (Open Access)

Biomedical ontologies or terminologies not only serve as a part of the metadata standards for describing data in the FAIR Data Principles (Findable, Accessible, Interoperable, Reusable), but also play a vital role in downstream applications such as cohort identification from electronic health records (EHR). However, there are two critical barriers that may lead to ambiguity, complexity, and inaccuracies in such ontology-based downstream applications. The first barrier is the quality of the ontology. Despite efforts by ontology curators to ensure ontology accuracy and comprehensiveness, errors and inconsistencies are unavoidable. The second barrier is the semantic heterogeneity since human experts may use …

Advancing Genetic Association Discovery In Brain Mri Using Unsupervised And Self-Supervised Deep Learning: Exploring Learning Dynamics, Region-Specific Features, And Spatially Resolved Representations, Sheikh Muhammad Saiful Islam

Dissertations and Theses (Open Access)

Deep learning has unlocked significant potential for advancing the discovery of genetic associations in imaging genetics, particularly in brain imaging using T1-weighted Magnetic Resonance Imaging (MRI). Traditional methods for this task often relied on hand-crafted or semi-automated feature extraction, followed by genetic association studies utilizing these features. While effective, these approaches are limited by their lack of data-driven exploration and the generation of features with limited informativeness.

Unsupervised deep learning, in particular, has emerged as a powerful alternative, addressing some of these limitations by enabling automated and data-driven feature discovery. Recent research in this domain has primarily focused on adapting …

Harnessing Knowledge And Data For Clinical Information Extraction In The Era Of Large Language Models, Yan Hu

Dissertations and Theses (Open Access)

The rapid digitization of healthcare records has led to the widespread adoption of Electronic Health Records (EHRs), which contain rich, unstructured clinical notes. These notes hold valuable information for patient care and clinical research, but their complexity and unstructured nature pose significant challenges for effective utilization. Clinical Information Extraction (IE) aims to bridge this gap by transforming unstructured text into structured data, enabling automated analysis. Traditional Natural Language Processing (NLP) techniques, such as Named Entity Recognition (NER), have been widely used for clinical IE, but recent advancements in Large Language Models (LLMs) like GPT-3.5, GPT-4, and LLaMA have opened new …

Accelerating Drug Repurposing And Target Discovery Using Deep Learning, Kohong Lin

Dissertations and Theses (Open Access)

Drug discovery is a long-lasting and expensive process. Computational approaches, particularly deep learning techniques, offer the potential to accelerate this process by integrating diverse perspectives from drug discovery theories and capturing intricate patterns within large, multimodal datasets. This dissertation explores deep learning methodologies to accelerate drug repurposing and genetic target discovery. The first aim focuses on integrating multimodal data, including chemical structures, disease genetics, and systems biology, into comprehensive disease knowledge graphs, followed by applying graph neural networks (GNNs) to prioritize repurposable drug candidates. The second aim is to develop a heterogeneous GNN-based approach capable of modelling distinct semantic relationships …

Addressing The Public Health Concern Of Maternal Mortality In Houston, Texas, Lucy Couture

Dissertations and Theses (Open Access)

Maternal mortality remains a pressing public health concern in the United States, with disproportionate consequences for marginalized communities. Despite being a developed nation, the U.S. reports one of the highest maternal mortality rates among its peers, with approximately 80% of maternal deaths deemed preventable. Texas reflects this national crisis, particularly affecting Black women, whose maternal mortality rate is significantly higher than that of other racial and ethnic groups. This thesis explores maternal mortality trends in Houston, Texas, analyzing the roles of systemic inequities, social determinants of health, and disparities in access to quality care. Drawing on data from the Texas …