Matching Items (8)
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- All Subjects: Cancer
- Creators: Kuang, Yang
- Creators: Nikkhah, Mehdi
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
Description
Cancer is one of the leading causes of death globally according to the World Health Organization. Although improved treatments and early diagnoses have reduced cancer related mortalities, metastatic disease remains a major clinical challenge. The local tumor microenvironment plays a significant role in cancer metastasis, where tumor cells respond and adapt to a plethora of biochemical and biophysical signals from stromal cells and extracellular matrix (ECM) proteins. Due to these complexities, there is a critical need to understand molecular mechanisms underlying cancer metastasis to facilitate the discovery of more effective therapies. In the past few years, the integration of advanced biomaterials and microengineering approaches has initiated the development of innovative platform technologies for cancer research. These technologies enable the creation of biomimetic in vitro models with physiologically relevant (i.e. in vivo-like) characteristics to conduct studies ranging from fundamental cancer biology to high-throughput drug screening. In this review article, we discuss the biological significance of each step of the metastatic cascade and provide a broad overview on recent progress to recapitulate these stages using advanced biomaterials and microengineered technologies. In each section, we will highlight the advantages and shortcomings of each approach and provide our perspectives on future directions.
ContributorsPeela, Nitish (Author) / Nikkhah, Mehdi (Thesis director) / LaBaer, Joshua (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Glioblastoma multiforme (GBM) is a malignant, aggressive and infiltrative cancer of the central nervous system with a median survival of 14.6 months with standard care. Diagnosis of GBM is made using medical imaging such as magnetic resonance imaging (MRI) or computed tomography (CT). Treatment is informed by medical images and includes chemotherapy, radiation therapy, and surgical removal if the tumor is surgically accessible. Treatment seldom results in a significant increase in longevity, partly due to the lack of precise information regarding tumor size and location. This lack of information arises from the physical limitations of MR and CT imaging coupled with the diffusive nature of glioblastoma tumors. GBM tumor cells can migrate far beyond the visible boundaries of the tumor and will result in a recurring tumor if not killed or removed. Since medical images are the only readily available information about the tumor, we aim to improve mathematical models of tumor growth to better estimate the missing information. Particularly, we investigate the effect of random variation in tumor cell behavior (anisotropy) using stochastic parameterizations of an established proliferation-diffusion model of tumor growth. To evaluate the performance of our mathematical model, we use MR images from an animal model consisting of Murine GL261 tumors implanted in immunocompetent mice, which provides consistency in tumor initiation and location, immune response, genetic variation, and treatment. Compared to non-stochastic simulations, stochastic simulations showed improved volume accuracy when proliferation variability was high, but diffusion variability was found to only marginally affect tumor volume estimates. Neither proliferation nor diffusion variability significantly affected the spatial distribution accuracy of the simulations. While certain cases of stochastic parameterizations improved volume accuracy, they failed to significantly improve simulation accuracy overall. Both the non-stochastic and stochastic simulations failed to achieve over 75% spatial distribution accuracy, suggesting that the underlying structure of the model fails to capture one or more biological processes that affect tumor growth. Two biological features that are candidates for further investigation are angiogenesis and anisotropy resulting from differences between white and gray matter. Time-dependent proliferation and diffusion terms could be introduced to model angiogenesis, and diffusion weighed imaging (DTI) could be used to differentiate between white and gray matter, which might allow for improved estimates brain anisotropy.
ContributorsAnderies, Barrett James (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Stepien, Tracy (Committee member) / Harrington Bioengineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Magnetic resonance imaging (MRI) data of metastatic brain cancer patients at the Barrow Neurological Institute sparked interest in the radiology department due to the possibility that tumor size distributions might mimic a power law or an exponential distribution. In order to consider the question regarding the growth trends of metastatic brain tumors, this thesis analyzes the volume measurements of the tumor sizes from the BNI data and attempts to explain such size distributions through mathematical models. More specifically, a basic stochastic cellular automaton model is used and has three-dimensional results that show similar size distributions of those of the BNI data. Results of the models are investigated using the likelihood ratio test suggesting that, when the tumor volumes are measured based on assuming tumor sphericity, the tumor size distributions significantly mimic the power law over an exponential distribution.
ContributorsFreed, Rebecca (Co-author) / Snopko, Morgan (Co-author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / WPC Graduate Programs (Contributor) / School of Accountancy (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
After more than 40 years since the signing of the National Cancer Act in 1970, cancer remains a formidable challenge. Cancer is currently the second most common cause of death in the United States, and worldwide cancer cases are projected to rise 50% between 2012 and 2030 [1-2]. While researchers have dramatically expanded our understanding of the biology of cancer, they have also revealed the staggering complexity and difficulty of developing successful treatments for the disease. More complex assays involving three dimensional cell culture offer the potential to model complex interactions, such as those involving the extracellular matrix (ECM), chemical concentration gradients, and the impact of vascularization of a tissue mass. Modern cancer assays thus promise to be both more accurate and more complex than previous models. One promising newly developed type of assay is microfluidics. Microfluidic devices consist of a silicone polymer stamp bonded to a glass slide. The stamp is patterned to produce a network of channels for cell culture. These devices allow manipulation of liquids on a sub-millimeter level, allowing researchers to produce a tightly controlled 3D microenvironment for cell culture. Our lab previously developed a microfluidic device to measure cancer cell invasion in response to a variety of signals and conditions. The small volume associated with microfluidics offers a number of advantages, but simultaneously make it impractical to use certain traditional cell analysis procedures, such as Western Blotting. As a result, measuring protein expression of cells in the microfluidic device was a continuing challenge. In order to expand the utility of microfluidic devices, it was therefore very enticing to develop a means of measuring protein expression inside the device. One possible solution was identified in the technique of In-Cell-Western blotting (ICW). ICW consists of using infrared-fluorescently stained antibodies to stain a protein of interest. This signal is measured using an infrared laser scanner, producing images that can be analyzed to quantitatively measure protein expression. ICW has been well validated in traditional 2D plate culture conditions, but has not been applied in conjunction with microfluidic devices. This project worked to evaluate In-Cell-Western blotting for use in microfluidic devices as a method of quantifying protein expression in situ.
ContributorsKratz, Alexander Franz (Author) / Nikkhah, Mehdi (Thesis director) / Truong, Danh (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Prostate cancer is the second most common kind of cancer in men. Fortunately, it has a 99% survival rate. To achieve such a survival rate, a variety of aggressive therapies are used to treat prostate cancers that are caught early. Androgen deprivation therapy (ADT) is a therapy that is given in cycles to patients. This study attempted to analyze what factors in a group of 79 patients caused them to stick with or discontinue the treatment. This was done using naïve Bayes classification, a machine-learning algorithm. The usage of this algorithm identified high testosterone as an indicator of a patient persevering with the treatment, but failed to produce statistically significant high rates of prediction.
ContributorsMillea, Timothy Michael (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Over time, tumor treatment resistance inadvertently develops when androgen de-privation therapy (ADT) is applied to metastasized prostate cancer (PCa). To combat tumor resistance, while reducing the harsh side effects of hormone therapy, the clinician may opt to cyclically alternates the patient’s treatment on and off. This method,known as intermittent ADT, is an alternative to continuous ADT that improves the patient’s quality of life while testosterone levels recover between cycles. In this paper,we explore the response of intermittent ADT to metastasized prostate cancer by employing a previously clinical data validated mathematical model to new clinical data from patients undergoing Abiraterone therapy. This cell quota model, a system of ordinary differential equations constructed using Droop’s nutrient limiting theory, assumes the tumor comprises of castration-sensitive (CS) and castration-resistant (CR)cancer sub-populations. The two sub-populations rely on varying levels of intracellular androgen for growth, death and transformation. Due to the complexity of the model,we carry out sensitivity analyses to study the effect of certain parameters on their outputs, and to increase the identifiability of each patient’s unique parameter set. The model’s forecasting results show consistent accuracy for patients with sufficient data,which means the model could give useful information in practice, especially to decide whether an additional round of treatment would be effective.
ContributorsBennett, Justin Klark (Author) / Kuang, Yang (Thesis director) / Kostelich, Eric (Committee member) / Phan, Tin (Committee member) / School of Mathematical and Statistical Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Tumor-stroma interactions significantly influence cancer cell metastasis and disease progression. These interactions partly comprise crosstalk between tumor and stromal fibroblasts, but the key molecular mechanisms within the crosstalk governing cancer invasion are still unclear. Here we develop a 3D in vitro organotypic microfluidic to model tumor-stroma interaction by mimicking the spatial organization of the tumor microenvironment on a chip. We co-culture breast cancer and patient-derived fibroblast cells in 3D tumor and stroma regions respectively and combine functional assessments, including cancer cell migration, with transcriptome profiling to unveil the molecular influence of tumor-stroma crosstalk on invasion. This led to the observation that cancer associated fibroblasts enhanced invasion in 3D by inducing the expression of a novel gene of interest, GPNMB, in breast cancer cells resulting in increased migration speed. Importantly, knockdown of GPNMB blunted the influence of CAFs on enhancing cancer invasion. Overall, these results demonstrate the ability of our model to recapitulate patient specific tumor microenvironment to investigate cellular and molecular consequences of tumor-stroma interactions.
ContributorsBarrientos, Eric Salvador (Author) / Nikkhah, Mehdi (Thesis director) / Veldhuizen, Jaime (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Stromal cells play an important role in facilitating disease progression of ductal carcinoma. Cancer associated fibroblasts (CAFs) are an important component of the extracellular matrix (ECM) which constitutes the microenvironment of breast tumor cells. They are known to participate in chemotherapeutic drug resistance by modulating various biochemical and biophysical factors that contribute to increased matrix stiffness and collagen I density of the tumor-adjacent stroma. To address these issues in terms of patient treatment, anti-cancer drug regimes have been assembled to incorporate both chemotherapeutic as well as anti-fibrotic drugs to both target tumor cells while also diminishing the elastic modulus of the microenvironment by targeting CAFs. The quantitative assessment of these drug regimes on tumor progression is missing in terms of CAFs role alone.
A high density 3D tumor model was utilized to recapitulate the tumor microenvironment of ductal carcinoma in vitro. The tumor model consisted of MDA-MB-231 tumors seeded within micromolded collagen wells, chemically immobilized upon a surface treated PDMS substrate. CAFs were seeded within the greater collagen structure from which the microwells were formed. The combinatorial effect of anti-fibrotic drug (Tranilast) and chemotherapy drug (Doxorubicin) were studied within 3D co culture conditions. Specifically, the combinatorial effects of the drugs on tumor cell viability, proliferation, and invasion were examined dynamically upon coculture with CAFs using the microengineered model.
The results of the study showed that the combinatorial effects of Tranilast and Doxorubicin significantly decreased the proliferative ability of tumor cells, in addition to significantly decreasing the ability of tumor cells to remain viable and invade their surrounding stroma, compared to control conditions.
A high density 3D tumor model was utilized to recapitulate the tumor microenvironment of ductal carcinoma in vitro. The tumor model consisted of MDA-MB-231 tumors seeded within micromolded collagen wells, chemically immobilized upon a surface treated PDMS substrate. CAFs were seeded within the greater collagen structure from which the microwells were formed. The combinatorial effect of anti-fibrotic drug (Tranilast) and chemotherapy drug (Doxorubicin) were studied within 3D co culture conditions. Specifically, the combinatorial effects of the drugs on tumor cell viability, proliferation, and invasion were examined dynamically upon coculture with CAFs using the microengineered model.
The results of the study showed that the combinatorial effects of Tranilast and Doxorubicin significantly decreased the proliferative ability of tumor cells, in addition to significantly decreasing the ability of tumor cells to remain viable and invade their surrounding stroma, compared to control conditions.
ContributorsSilva, Casey Rudolph (Author) / Nikkhah, Mehdi (Thesis director) / Saini, Harpinder (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05