Biomedical Engineering ETDs

Publication Date

Summer 7-7-2017

Abstract

Multiscale, hybrid computer modeling has emerged as a valuable tool in the fields of computational systems biology and mathematical oncology. In this work, we present an overview of the motivations for, and development and implementation of, three hybrid multiscale models of the mammary gland system and early stage ductal carcinoma in situ (DCIS) in the gland. Pubertal mammary gland development was described first using a two-dimensional, lattice-based hybrid agent-based model description of the mammary terminal end bud (TEB), and then with a three-dimensional lattice-free TEB model. Both models implement a discrete, agent-based description of the cell scale, and a continuum, finite element method description of tissue scale spatiotemporal molecular profiles, which are explicitly linked into a hybrid model. This lattice-free pubertal development TEB model was then transitioned into a post-menopausal early stage DCIS model, used for study of the phenotypic dynamics and molecular signaling disruptions involved in development of the DCIS tumor mass. Both TEB and DCIS models implemented simplified, literature-based cellular phenotypic developmental hierarchies and endocrine and paracrine signaling pathways. All models provided valuable insights into the effects of these aspects on the development of both the healthy gland and the pre-invasive DCIS cancer state, and results from model outputs were found to be within literature supported ranges. Cells of both healthy and cancerous phenotypes were found to be sensitive to changes in molecular signaling intensities and phenotypic hierarchies, which played an important part in overall development in both cases, with all cases demonstrating a greater effect of upstream estrogen paracrine signaling relative to the downstream AREG-FGF epithelial to stromal pathway also tested. Here, we provide detailed descriptions of these studies and results, as well as other useful discoveries, and also an overview of the modeling approaches, techniques, and rationale for their specific designs and implementations.

Language

English

Keywords

Mathematical Modeling, Hybrid Modeling, Agent-based Modeling, Mammary Gland

Document Type

Dissertation

Degree Name

Biomedical Engineering

Level of Degree

Doctoral

Department Name

Biomedical Engineering

First Committee Member (Chair)

Andrew P. Shreve

Second Committee Member

Vittorio Cristini

Third Committee Member

Jeffrey Brinker

Fourth Committee Member

Zhihui Wang

Project Sponsors

NSF, NIH, the Rochelle and Max Levit Chair in the Neurosciences, the University of Texas System STARS Award, he University of New Mexico Cancer Center Victor and Ruby Hansen Surface Professorship in Molecular Modeling of Cancer, the Houston Methodist Research Institute

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