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- All Subjects: Cancer
- Creators: School of Mathematical and Statistical Sciences
- 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
Description
This paper explores how marginalist economics defines and inevitably constrains Victorian sensation fiction's content and composition. I argue that economic intuition implies that sensationalist heroes and antagonists, writers and readers all pursued a fundamental, "rational" aim: the attainment of pleasure. So although "sensationalism" took on connotations of moral impropriety in the Victorian age, sensation fiction primarily involves experiences of pain on the page that excite the reader's pleasure. As such, sensationalism as a whole can be seen as a conformist product, one which mirrors the effects of all commodities on the market, rather than as a rebellious one. Indeed, contrary to modern and contemporary critics' assumptions, sensation fiction may not be as scandalous as it seems.
ContributorsFischer, Brett Andrew (Author) / Bivona, Daniel (Thesis director) / Looser, Devoney (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Economics Program in CLAS (Contributor) / School of Politics and Global Studies (Contributor) / Department of English (Contributor)
Created2014-12
Description
Through collection of survey data on the characteristics of college debaters, disparities in participation and success for women and racial and ethnic minorities are measured. This study then uses econometric tools to assess whether there is an in-group judging bias in college debate that systematically disadvantages female and minority participants. Debate is used as a testing ground for competing economic theories of taste-based and statistical discrimination, applied to a higher education context. The study finds persistent disparities in participation and success for female participants. Judges are more likely to vote for debaters who share their gender. There is also a significant disparity in the participation of racial and ethnic minority debaters and judges, as well as female judges.
ContributorsVered, Michelle Nicole (Author) / Silverman, Daniel (Thesis director) / Symonds, Adam (Committee member) / Dillon, Eleanor (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Politics and Global Studies (Contributor)
Created2014-12
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
Despite the 40-year war on cancer, very limited progress has been made in developing a cure for the disease. This failure has prompted the reevaluation of the causes and development of cancer. One resulting model, coined the atavistic model of cancer, posits that cancer is a default phenotype of the cells of multicellular organisms which arises when the cell is subjected to an unusual amount of stress. Since this default phenotype is similar across cell types and even organisms, it seems it must be an evolutionarily ancestral phenotype. We take a phylostratigraphical approach, but systematically add species divergence time data to estimate gene ages numerically and use these ages to investigate the ages of genes involved in cancer. We find that ancient disease-recessive cancer genes are significantly enriched for DNA repair and SOS activity, which seems to imply that a core component of cancer development is not the regulation of growth, but the regulation of mutation. Verification of this finding could drastically improve cancer treatment and prevention.
ContributorsOrr, Adam James (Author) / Davies, Paul (Thesis director) / Bussey, Kimberly (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of Life Sciences (Contributor)
Created2015-05
Description
According to the Tax Policy Center, a joint project of the Brookings Institution and Urban Institute, the Earned Income Tax Credit (EITC) will provide 26 million households with 60 billion dollars of reduced taxes and refunds in 2015 \u2014 resources that serve to lift millions of families above the federal poverty line. Responding to the popularity of EITC programs and recent discussion of its expansion for childless adults, I select three comparative case studies of state-level EITC reform from 2005 to 2013. Each state represents a different kind of policy reform: the creation of a supplemental credit in Connecticut, credit reduction in New Jersey, and finally credit expansion for childless adults in Maryland. For each case study, I use Current Population Survey panel data from the March Supplement to complete a differences-in-differences (DD) analysis of EITC policy changes. Specifically, I analyze effects of policy reform on total earned income, employment and usual hours worked. For comparison groups, I construct unique counterfactual populations of northeastern U.S. states, using people of color with less than a college degree as my treatment group for their increased sensitivity to EITC policy reform. I find no statistically significant effects of policy creation in Connecticut, significant decreases in employment and hours worked in New Jersey, and finally, significant increases in earnings and hours worked in Maryland. My work supports the findings of other empirical work, suggesting that awareness of new supplemental EITC programs is critical to their effectiveness while demonstrating that these types of programs can affect the labor supply and outcomes of eligible groups.
ContributorsRichard, Katherine Rose (Author) / Dillon, Eleanor Wiske (Thesis director) / Silverman, Daniel (Committee member) / Herbst, Chris (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Economics Program in CLAS (Contributor)
Created2015-05
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