Matching Items (26)
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- All Subjects: Cancer
- Creators: Harrington Bioengineering Program
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
DescriptionMy main goal for my thesis is in conjunction with the research I started in the summer of 2010 regarding the creation of a TBI continuous-time sensor. Such goals include: characterizing the proteins in sensing targets while immobilized, while free in solution, and while in free solution in the blood.
ContributorsHaselwood, Brittney (Author) / LaBelle, Jeffrey (Thesis director) / Pizziconi, Vincent (Committee member) / Cook, Curtiss (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2011-12
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
The purpose of this project is to explore the benefit of using prodrugs in chemotherapy, as well as to explain the concept of angiogenesis and the importance of this process to tumor development. Angiogenesis is the formation of new blood capillaries that are necessary for the survival of a tumor, as a tumor cannot grow larger than 1-2 mm3 without developing its own blood supply. Vascular disrupting agents, such as iodocombstatin, a derivative of combretastatin, can be used to effectively cut off the blood supply to a growing neoplasm, effectively inhibiting the supply of oxygen and nutrients needed for cell division Thus, VDAs have a very important implication in terms of the future of chemotherapy. A prodrug, defined as an agent that is inactive in the body until metabolized to yield the drug itself, was synthesized by combining iodocombstatin with a β-glucuronide linker. The prodrug is theoretically hydrolyzed in the body to afford the active drug by β-glucuronidase, an enzyme that is produced five times as much by cancer cells as by normal cells. This effectively creates a “magic-bullet” form of chemotherapy, known as Direct Enzyme Prodrug Therapy (DEPT).
ContributorsClark, Caroline Marie (Author) / Pettit, George Robert (Thesis director) / Melody, Noeleen (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2015-05
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
In this paper, β-estradiol was characterized utilizing electrochemical impedance spectroscopy (EIS) techniques for the purpose of developing a multi-marker fertility sensor. β-estradiol was immobilized onto the surface of gold disk electrodes to find the optimal binding frequency of estradiol and its respective antibody, anti-17β-estradiol, which was determined to be 37.46Hz. At this frequency a logarithmic relationship between concentration and impedance (Z/ohm) was established creating a concentration calibration curve with a slope of 211 ohm/ln(pg mL-1), an R-squared value of 0.986 and a lower limit of detection of 742 fg mL-1. The specificity and cross-reactivity of the antibody with other hormones was tested through interferent and non-target experiments. Signal-to-noise ratio analysis verified that anti-17β-estradiol exhibited minimal chemical reactions with other hormones (SNR< 3) in non-target experiments. Additionally, there were minimal changes in the amount of signal collected during interferent testing, with albumin and follicle stimulating hormone having SNR values greater than 3. These results, along with the unique frequency response of the antibody-target binding reaction, allow for the possibility of using anti-17β-estradiol and β-estradiol for detecting multiple fertility biomarkers on a single sensor.
ContributorsSmith, Victoria Ann (Author) / LaBelle, Jeffrey (Thesis director) / Spano, Mark (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
Description
Diabetes mellitus is a disease characterized by many chronic and acute conditions. With the prevalence and cost quickly increasing, we seek to improve on the current standard of care and create a rapid, label free sensor for glycated albumin (GA) index using electrochemical impedance spectroscopy (EIS). The antibody, anti-HA, was fixed to gold electrodes and a sine wave of sweeping frequencies was induced with a range of HA, GA, and GA with HA concentrations. Each frequency in the impedance sweep was analyzed for highest response and R-squared value. The frequency with both factors optimized is specific for both the antibody-antigen binding interactions with HA and GA and was determined to be 1476 Hz and 1.18 Hz respectively in purified solutions. The correlation slope between the impedance response and concentration for albumin (0 \u2014 5400 mg/dL of albumin) was determined to be 72.28 ohm/ln(mg/dL) with an R-square value of 0.89 with a 2.27 lower limit of detection. The correlation slope between the impedance response and concentration for glycated albumin (0 \u2014 108 mg/dL) was determined to be -876.96 ohm/ln(mg/dL) with an R-squared value of 0.70 with a 0.92 mg/dL lower limit of detection (LLD). The above data confirms that EIS offers a new method of GA detection by providing unique correlation with albumin as well as glycated albumin. The unique frequency response of GA and HA allows for modulation of alternating current signals so that several other markers important in the management of diabetes could be measured with a single sensor. Future work will be necessary to establish multimarker sensing on one electrode.
ContributorsEusebio, Francis Ang (Author) / LaBelle, Jeffrey (Thesis director) / Pizziconi, Vincent (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
Description
Currently, the management of diabetes mellitus (DM) involves the monitoring of only blood glucose using self-monitoring blood glucose devices (SMBGs) followed by taking interventional steps, if needed. To increase the amount of information that diabetics can have to base DM care decisions off of, the development of an insulin biosensor is explored. Such a biosensor incorporates electrochemical impedance spectroscopy (EIS) to ensure an extremely sensitive platform. Additionally, anti-insulin antibody was immobilized onto the surface of a gold disk working electrode to ensure a highly specific sensing platform as well. EIS measurements were completed with a 5mV sine wave that was swept through the frequency spectrum of 100 kHz to 1 Hz on concentrations of insulin ranging from 0 pM to 100 μM. The frequency at which the interaction between insulin and its antibody was optimized was determined by finding out at which frequency the R2 and slope of the impedance-concentration plot were best. This frequency, otherwise known as the optimal binding frequency, was determined to be 459 Hz. Three separate electrodes were developed and the impedance data for each concentration measured at 459 Hz was averaged and plotted against the LOG (pM insulin) to construct the calibration curve. The response was calculated to be 263.64 ohms/LOG(pM insulin) with an R2 value of 0.89. Additionally, the average RSD was determined to be 19.24% and the LLD was calculated to be 8.47 pM, which is well below the physiological normal range. These results highlight the potential success of developing commercial point-of-care insulin biosensors or multi-marker devices operating with integrated insulin detection.
ContributorsDecke, Zachary William (Author) / LaBelle, Jeffrey (Thesis director) / Pizziconi, Vincent (Committee member) / Cook, Curtiss (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2013-05