Matching Items (27)
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- All Subjects: Cancer
- Creators: Harrington Bioengineering Program
- Status: Published
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
Breast and other solid tumors exhibit high and varying degrees of intra-tumor heterogeneity resulting in targeted therapy resistance and other challenges that make the management and treatment of these diseases rather difficult. Due to the presence of admixtures of non-neoplastic cells with polyclonal cell populations, it is difficult to define cancer genomes in patient samples. By isolating tumor cells from normal cells, and enriching distinct clonal populations, clinically relevant genomic aberrations that drive disease can be identified in patients in vivo. An in-depth analysis of clonal architecture and tumor heterogeneity was performed in a stage II chemoradiation-naïve breast cancer from a sixty-five year old patient. DAPI-based DNA content measurements and DNA content-based flow sorting was used to to isolate nuclei from distinct clonal populations of diploid and aneuploid tumor cells in surgical tumor samples. We combined DNA content-based flow cytometry and ploidy analysis with high-definition array comparative genomic hybridization (aCGH) and next-generation sequencing technologies to interrogate the genomes of multiple biopsies from the breast cancer. The detailed profiles of ploidy, copy number aberrations and mutations were used to recreate and map the lineages present within the tumor. The clonal analysis revealed driver events for tumor progression (a heterozygous germline BRCA2 mutation converted to homozygosity within the tumor by a copy number event and the constitutive activation of Notch and Akt signaling pathways. The highlighted approach has broad implications in the study of tumor heterogeneity by providing a unique ultra-high resolution of polyclonal tumors that can advance effective therapies and clinical management of patients with this disease.
ContributorsLaughlin, Brady Scott (Author) / Ankeny, Casey (Thesis director) / Barrett, Michael (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor) / School for the Science of Health Care Delivery (Contributor)
Created2015-05
Description
The purpose of this project was to examine the viability of protein biomarkers in pre-symptomatic detection of lung cancer. Regular screening has been shown to vastly improve patient survival outcome. Lung cancer currently has the highest occurrence and mortality of all cancers and so a means of screening would be highly beneficial. In this research, the biomarker neuron-specific enolase (Enolase-2, eno2), a marker of small-cell lung cancer, was detected at varying concentrations using electrochemical impedance spectroscopy in order to develop a mathematical model of predicting protein expression based on a measured impedance value at a determined optimum frequency. The extent of protein expression would indicate the possibility of the patient having small-cell lung cancer. The optimum frequency was found to be 459 Hz, and the mathematical model to determine eno2 concentration based on impedance was found to be y = 40.246x + 719.5 with an R2 value of 0.82237. These results suggest that this approach could provide an option for the development of small-cell lung cancer screening utilizing electrochemical technology.
ContributorsEvans, William Ian (Author) / LaBelle, Jeffrey (Thesis director) / Spano, Mark (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
Description
One of the most prominent biological challenges for the field of drug delivery is the blood-brain barrier. This physiological system blocks the entry of or actively removes almost all small molecules into the central nervous system (CNS), including many drugs that could be used to treat diseases in the CNS. Previous studies have shown that activation of the adenosine receptor signaling pathway through the use of agonists has been demonstrated to increase BBB permeability. For example, regadenoson is an adenosine A2A receptor agonist that has been shown to disrupt the BBB and allow for increased drug uptake in the CNS. The goal of this study was to verify this property of regadenoson. We hypothesized that co-administration of regadenoson with a non-brain penetrant macromolecule would facilitate its entry into the central nervous system. To test this hypothesis, healthy mice were administered regadenoson or saline concomitantly with a fluorescent dextran solution. The brain tissue was either homogenized to measure quantity of fluorescent molecule, or cryosectioned for imaging with confocal fluorescence microscopy. These experiments did not identify any significant difference in the amount of fluorescence detected in the brain after regadenoson treatment. These results contradict those of previous studies and highlight potential differences in injection methodology, time windows, and properties of brain impermeant molecules.
ContributorsWohlleb, Gregory Michael (Author) / Sirianni, Rachael (Thesis director) / Stabenfeldt, Sarah (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2015-05
Description
The global population over the age of 60 is estimated to rise to 23% by 2050 only increase the prevalence of functional neurological disorders and stroke. Increase in cases of functional neurological disorders and strokes will place a greater burden on the healthcare industry, specifically physical therapy. Physical therapy is vital for a patient’s recovery of motor function which is time demanding and taxing on the physical therapist. Wearable robotics have been proven to improve functional outcomes in gait rehabilitation by providing controlled high dosage and high-intensity training. Accurate control strategies for assistive robotic exoskeletons are vital for repetitive high precisions assistance for cerebral plasticity to occur.
This thesis presents a preliminary determination and design of a control algorithm for an assistive ankle device developed by the ASU RISE Laboratory. The assistive ankle device functions by compressing a spring upon heel strike during gait, remaining compressed during mid-stance and then releasing upon initiation of heel-off. The relationship between surface electromyography and ground reactions forces were used for identification of user-initiated heel-off. The muscle activation of the tibialis anterior combined with the ground reaction forces of the heel pressure sensor generated potential features that will be utilized in the revised control algorithm for the assistive ankle device. Work on this project must proceed in order to test and validate the revised control algorithm to determine its accuracy and precision.
This thesis presents a preliminary determination and design of a control algorithm for an assistive ankle device developed by the ASU RISE Laboratory. The assistive ankle device functions by compressing a spring upon heel strike during gait, remaining compressed during mid-stance and then releasing upon initiation of heel-off. The relationship between surface electromyography and ground reactions forces were used for identification of user-initiated heel-off. The muscle activation of the tibialis anterior combined with the ground reaction forces of the heel pressure sensor generated potential features that will be utilized in the revised control algorithm for the assistive ankle device. Work on this project must proceed in order to test and validate the revised control algorithm to determine its accuracy and precision.
ContributorsGaytan-Jenkins, Daniel Rinaldo (Author) / Zhang, Wenlong (Thesis director) / Tyler, Jamie (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Glioblastoma multiforme (GBM) is an aggressive malignant brain tumor with a median prognosis of 14 months. Human hairless protein (HR) is a 130 kDa nuclear transcription factor that plays a critical role in skin and hair function but was found to be highly expressed in neural tissue as well. The expression of HR in GBM tumor cells is significantly decreased compared to the normal brain tissue and low levels of HR expression is associated with shortened patient survival. We have recently reported that HR is a DNA binding phosphoprotein, which binds to p53 protein and p53 responsive element (p53RE) in vitro and in intact cells. We hypothesized that HR can regulate p53 downstream target genes, and consequently affects cellular function and activity. To test the hypothesis, we overexpressed HR in normal human embryonic kidney HEK293 and GBM U87MG cell lines and characterized these cells by analyzing p53 target gene expression, viability, cell-cycle arrest, and apoptosis. The results revealed that the overexpressed HR not only regulates p53-mediated target gene expression, but also significantly inhibit cell viability, induced early apoptosis, and G2/M cell cycle arrest in U87MG cells, compared to mock groups. Translating the knowledge gained from this research on the connections between HR and GBM could aid in identifying novel therapies to circumvent GBM progression or improve clinical outcome.
ContributorsBrook, Lemlem Addis (Author) / Blattman, Joseph (Thesis director) / Hsieh, Jui-Cheng (Committee member) / Goldstein, Elliott (Committee member) / Harrington Bioengineering Program (Contributor) / School of Social Transformation (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Glioblastoma Multiforme (GBM) is an aggressive and deadly form of brain cancer with a median survival time of about a year with treatment. Due to the aggressive nature of these tumors and the tendency of gliomas to follow white matter tracks in the brain, each tumor mass has a unique growth pattern. Consequently it is difficult for neurosurgeons to anticipate where the tumor will spread in the brain, making treatment planning difficult. Archival patient data including MRI scans depicting the progress of tumors have been helpful in developing a model to predict Glioblastoma proliferation, but limited scans per patient make the tumor growth rate difficult to determine. Furthermore, patient treatment between scan points can significantly compound the challenge of accurately predicting the tumor growth. A partnership with Barrow Neurological Institute has allowed murine studies to be conducted in order to closely observe tumor growth and potentially improve the current model to more closely resemble intermittent stages of GBM growth without treatment effects.
ContributorsSnyder, Lena Haley (Author) / Kostelich, Eric (Thesis director) / Frakes, David (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
Description
This paper begins by exploring the prior research that has shown how eating a plant-based diet can affect the human body. Some of these effects include: improved mood, energy levels, gut health, alkalized urine pH, as well as, lowering the risk of hormonal imbalance, kidney stones, diabetes, cancer, and coronary artery disease. The worries that generally accompany eating a fully vegan diet, which include, malnutrition and protein deficiency, are also addressed in the background research. In attempt to build upon previous research, a weeklong experiment was conducted testing 3 different factors, which include: gut health, improved mood, and urine pH. Mood states were measured quantifiably using a POMS (profile of mood states) test. Gut health was measured using several factors, including consistency and frequency of bowel movements, as well as, GI discomfort. Two 24-hour urine samples were collected from each of the subjects to compare the pH of their urine before and after the study. The sample size of this study included 15 healthy, non-smoking, subjects, between 18-30 years of age. The subjects were split up into 3 stratified random samples, including, an omnivore control group, vegan control group, and experimental vegan group. The experimental vegans had eaten meat/eggs/dairy regularly for their whole lives before the start of the study, and had consented to eating a vegan diet for the entirety of one week. While the data from the control groups remained mostly constant as predicted, the results from the experimental group were shown to have a significantly better mood (P<0.05) after one week, as well as, a significantly higher urine pH (P < 0.025) than they did before the study. However, the experimental group did not show a significant change in stool frequency, consistency, or GI discomfort within one week. The vegan control group, which included subjects who had eaten a plant-based diet for 1-3 years, had much better gut health scores. This leads us to believe that the vegan gut microbiome takes much longer to transform into than just one week unlike urine pH and mood, which can take as little as one week. These findings warrant further investigation.
ContributorsMacias, Lindsey Kaori (Author) / Johnston, Carol (Thesis director) / Katsanos, Christos (Committee member) / Harrington Bioengineering Program (Contributor) / School of Nutrition and Health Promotion (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Nutritional support offered before and during chemotherapy treatment is proven to improve the outcomes of treatment (Bernhardson, 2016). This project seeks to examine current forms of nutritional support offered to patients, as well as the models of care and support teams in cancer treatment centers. The basis for this project incorporated personal experiences at M.D. Anderson Cancer Center in Gilbert, Arizona as well as research into the work of clinical oncology dietitians. An intense interest in food videos and blogs also informed this project, and was incorporated in the hope of providing chemotherapy patients a platform to discover recipes specific to their unique situation. The combination of this research was utilized to create several videos which demonstrated specific recipes beneficial for patients as well as creating a platform for this particular population. While nutritional support can take multiple forms, the focus of nutritional support surrounds symptom management. The common side effects of chemotherapy such as nausea, mucositis (mouth sores), and extreme weight loss were taken into account. Recipes were formulated to directly address these conditions and each recipe was broken down into the benefits of both macronutrients and micronutrients. In addition to formulating specific recipes and videos, barriers to proper nutritional support were examined and explained. These barriers include understaffing of clinical dietitians at cancer treatment centers, a patient's lack of transportation to and from treatments, as well as an overwhelming viewpoint that nutritional support is only required for extreme cases of malnutrition. Combatting these barriers and offering more forms of nutritional support will help to increase a patient's positive response to treatment, manage their symptoms, and improve their overall quality of life.
ContributorsMonteilh, Christina Eleanor (Author) / Levinson, Simin (Thesis director) / Martinelli, Sarah (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12