Matching Items (8)
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- All Subjects: Oncology
- All Subjects: cancer research
- Creators: Maley, Carlo
- Creators: Gardner, Carl
Description
Macrostomum lignano is characterized by its elevated regenerative ability conferred by its high percentage of stem cells (the highest recorded for any animal). M. lignano is already used as a model organism for addressing fundamental questions of stem cell biology, aging, regeneration, and reproduction, but not yet cancer.
M. lignano larvae were isolated into separate wells of 24-well plates. After reaching maturity (30 days), the experimental plates were exposed to 5 Gys of X-rays every 4 days for a total of a 25 Gy exposure. We observed phenotypes that may be attributed to the acute effect of irradiation (e.g. blisters) but we recorded two types of phenotypes that may be a result of long-term effects of exposure to radiation. We observed enlarged testis and dark regions/masses that appeared statistically significantly more frequently in the treated animals (Fisher exact test, p=0.0026). Preliminary histological analyses of the enlarged testis suggest a benign testis enlargement due to an aberrant growth of the testes and an accumulation of aberrant spermatozoa. Importantly, we found that, similar to cancer, the dark masses can grow in size over time and the histological analysis confirms that the observed masses are composed of cells completely different from surrounding normal cells. Notably, we observed that those masses can develop and then completely disappear through an observed method of ejection. M. lignano offer the unique possibility to study in vivo cancer development in a simple organism that can easily be cultured in the lab in large numbers.
M. lignano larvae were isolated into separate wells of 24-well plates. After reaching maturity (30 days), the experimental plates were exposed to 5 Gys of X-rays every 4 days for a total of a 25 Gy exposure. We observed phenotypes that may be attributed to the acute effect of irradiation (e.g. blisters) but we recorded two types of phenotypes that may be a result of long-term effects of exposure to radiation. We observed enlarged testis and dark regions/masses that appeared statistically significantly more frequently in the treated animals (Fisher exact test, p=0.0026). Preliminary histological analyses of the enlarged testis suggest a benign testis enlargement due to an aberrant growth of the testes and an accumulation of aberrant spermatozoa. Importantly, we found that, similar to cancer, the dark masses can grow in size over time and the histological analysis confirms that the observed masses are composed of cells completely different from surrounding normal cells. Notably, we observed that those masses can develop and then completely disappear through an observed method of ejection. M. lignano offer the unique possibility to study in vivo cancer development in a simple organism that can easily be cultured in the lab in large numbers.
ContributorsGerman, Adriana (Author) / Fortunato, Angelo (Thesis director) / Maley, Carlo (Committee member) / School of Life Sciences (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
A big part of understanding cancer is understanding the cellular environment itthrives in by analyzing it from a microecological perspective. Humans and other species
are affected by different cancer types, and this highlights the notion that there may be a
correlation between specific tissues and neoplasia prevalence. Research shows that
humans are the most susceptible to adenocarcinomas and carcinomas which include the
following tissues: lungs, breast, prostate, and pancreas. Furthermore, research shows that
adenocarcinoma accounts for 38.5% of all lung cancer cases, 20% of small cell
carcinomas, and 2.9% of large cell carcinoma. The incidence of the most common cancer
types in humans is consistently increasing annually. This study analyzes trends of tissue-specific cancers across species to examine possible contributors to vulnerability to
cancer. I predicted that adenocarcinomas would be the most prevalent cancer type across
the tree of life. To test this hypothesis, I reviewed over 130 species that reported equal to
or greater than 50 individual necropsy pathology records across 4 classes (Mammalia,
amphibia, Reptilia, Aves) and ranked them by neoplasia prevalence. This information was
then organized in tables in descending order. The study’s resulting tables and data
concluded that the hypothesis was correct. I found that across all species
adenocarcinomas were the most common cancer type and account for 30.4% of
malignancies reported among species. Future research should investigate how organ size
contributes to neoplasia prevalence.
ContributorsPERAZA, ASHLEY (Author) / Maley, Carlo (Thesis advisor) / Boddy, Amy (Thesis advisor) / Baciu, Cristina (Committee member) / Arizona State University (Publisher)
Created2022
Description
Public education and involvement with evolutionary theory has long been limited by both the complexity of the subject and societal pushback. Furthermore, effective and engaging evolution education has become an elusive feat that often fails to reflect the types of questions that evolution research attempts to address. Here, we explore the best methods to present scientific research using interactive educational models to facilitate the learning experience of the audience most effectively. By creating artistic and game-play oriented models, it becomes possible to simplify the multifaceted aspects of evolution research such that it enables a larger, more inclusive, audience to better comprehend these complexities. In allowing the public to engage with highly interactive education materials, the full spectrum of the scientific process, from hypothesis construction to experimental testing, can be experienced and understood. Providing information about current cancer evolution research in a way that is easy to access and understand and accompanying it with an interactive model that reflects this information and reinforces learning shows that research platforms can be translated into interactive teaching tools that make understanding evolutionary theory more accessible.
ContributorsSilva, Yasmin (Author) / Maley, Carlo (Thesis director) / Compton, Zachary (Committee member) / Baciu, Cristina (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / School of Life Sciences (Contributor)
Created2022-05
Description
This paper will serve as a review of relevant scleractinian coral biology and genetics, discuss the ecological and biological impacts of growth anomalies in scleractinians, discuss the importance of studying this phenomena in terms of conservation, outline and discuss the processes undertaken to elucidate possible genetic markers of the growth anomalies, as well as discuss growth anomalies within the context of other coral disease and the anthropocene to add clarity no the subject to the oncological discussion taking place around such anomalies.
ContributorsLittle, Patrick (Author) / Maley, Carlo (Thesis director) / Metzger, Michael (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2022-05
Description
Life history theory offers a powerful framework to understand evolutionary selection pressures and explain how adaptive strategies use the life history trade-off and differences in cancer defenses across the tree of life. There is often some cost to the phenotype of therapeutic resistance and so sensitive cells can usually outcompete resistant cells in the absence of therapy. Adaptive therapy, as an evolutionary and ecologically inspired paradigm in cancer treatment, uses the competitive interactions between drug-sensitive, and drug-resistant subclones to help suppress the drug-resistant subclones. However, there remain several open challenges in designing adaptive therapies, particularly in extending this approach to multiple drugs. Furthermore, the immune system also plays a role in preventing and controlling cancers. Life history theory may help to explain the variation in immune cell levels across the tree of life that likely contributes to variance in cancer prevalence across vertebrates. However, this has not been previously explored. This work 1) describes resistance management for cancer, lessons cancer researchers learned from farmers since adaptive evolutionary strategies were inspired by the management of resistance in agricultural pests, 2) demonstrates how adaptive therapy protocols work with gemcitabine and capecitabine in a hormone-refractory breast cancer mouse model, 3) tests for a relationship between life history strategy and the immune system, and tests for an effect of immune cells levels on cancer prevalence across vertebrates, and 4) provides a novel approach to improve the teaching of life history theory. This work applies lessons that cancer researchers learned from pest managers, who face similar issues of pesticide resistance, to control cancers. It represents the first time that multiple drugs have been used in adaptive therapy for cancer, and the first time that adaptive therapy has been used on hormone-refractory breast cancer. I found that this evolutionary approach to cancer treatment prolongs survival in mice and also selects for the slow life history strategy. I also discovered that species with slower life histories have higher concentrations of white blood cells and a higher percentage of heterophils, monocytes and segmented neutrophils. Moreover, larger platelet size is associated with higher cancer prevalence in mammals.
ContributorsSeyedi, Seyedehsareh (Author) / Maley, Carlo (Thesis advisor) / Blattman, Joseph (Committee member) / Anderson, Karen (Committee member) / Wilson, Melissa (Committee member) / Huijben, Silvie (Committee member) / Gatenby, Robert (Committee member) / Arizona State University (Publisher)
Created2023
Description
Cancer is a major health problem in the world today and is expected to become an even larger one in the future. Although cancer therapy has improved for many cancers in the last several decades, there is much room for further improvement. Mathematical modeling has the advantage of being able to test many theoretical therapies without having to perform clinical trials and experiments. Mathematical oncology will continue to be an important tool in the future regarding cancer therapies and management.
This dissertation is structured as a growing tumor. Chapters 2 and 3 consider spheroid models. These models are adept at describing 'early-time' tumors, before the tumor needs to co-opt blood vessels to continue sustained growth. I consider two partial differential equation (PDE) models for spheroid growth of glioblastoma. I compare these models to in vitro experimental data for glioblastoma tumor cell lines and other proposed models. Further, I investigate the conditions under which traveling wave solutions exist and confirm numerically.
As a tumor grows, it can no longer be approximated by a spheroid, and it becomes necessary to use in vivo data and more sophisticated modeling to model the growth and diffusion. In Chapter 4, I explore experimental data and computational models for describing growth and diffusion of glioblastoma in murine brains. I discuss not only how the data was obtained, but how the 3D brain geometry is created from Magnetic Resonance (MR) images. A 3D finite-difference code is used to model tumor growth using a basic reaction-diffusion equation. I formulate and test hypotheses as to why there are large differences between the final tumor sizes between the mice.
Once a tumor has reached a detectable size, it is diagnosed, and treatment begins. Chapter 5 considers modeling the treatment of prostate cancer. I consider a joint model with hormonal therapy as well as immunotherapy. I consider a timing study to determine whether changing the vaccine timing has any effect on the outcome of the patient. In addition, I perform basic analysis on the six-dimensional ordinary differential equation (ODE). I also consider the limiting case, and perform a full global analysis.
This dissertation is structured as a growing tumor. Chapters 2 and 3 consider spheroid models. These models are adept at describing 'early-time' tumors, before the tumor needs to co-opt blood vessels to continue sustained growth. I consider two partial differential equation (PDE) models for spheroid growth of glioblastoma. I compare these models to in vitro experimental data for glioblastoma tumor cell lines and other proposed models. Further, I investigate the conditions under which traveling wave solutions exist and confirm numerically.
As a tumor grows, it can no longer be approximated by a spheroid, and it becomes necessary to use in vivo data and more sophisticated modeling to model the growth and diffusion. In Chapter 4, I explore experimental data and computational models for describing growth and diffusion of glioblastoma in murine brains. I discuss not only how the data was obtained, but how the 3D brain geometry is created from Magnetic Resonance (MR) images. A 3D finite-difference code is used to model tumor growth using a basic reaction-diffusion equation. I formulate and test hypotheses as to why there are large differences between the final tumor sizes between the mice.
Once a tumor has reached a detectable size, it is diagnosed, and treatment begins. Chapter 5 considers modeling the treatment of prostate cancer. I consider a joint model with hormonal therapy as well as immunotherapy. I consider a timing study to determine whether changing the vaccine timing has any effect on the outcome of the patient. In addition, I perform basic analysis on the six-dimensional ordinary differential equation (ODE). I also consider the limiting case, and perform a full global analysis.
ContributorsRutter, Erica Marie (Author) / Kuang, Yang (Thesis advisor) / Kostelich, Eric J (Thesis advisor) / Frakes, David (Committee member) / Gardner, Carl (Committee member) / Jackiewicz, Zdzislaw (Committee member) / Arizona State University (Publisher)
Created2016
Description
Cancer is a worldwide burden in every aspect: physically, emotionally, and financially. A need for innovation in cancer research has led to a vast interdisciplinary effort to search for the next breakthrough. Mathematical modeling allows for a unique look into the underlying cellular dynamics and allows for testing treatment strategies without the need for clinical trials. This dissertation explores several iterations of a dendritic cell (DC) therapy model and correspondingly investigates what each iteration teaches about response to treatment.
In Chapter 2, motivated by the work of de Pillis et al. (2013), a mathematical model employing six ordinary differential (ODEs) and delay differential equations (DDEs) is formulated to understand the effectiveness of DC vaccines, accounting for cell trafficking with a blood and tumor compartment. A preliminary analysis is performed, with numerical simulations used to show the existence of oscillatory behavior. The model is then reduced to a system of four ODEs. Both models are validated using experimental data from melanoma-induced mice. Conditions under which the model admits rich dynamics observed in a clinical setting, such as periodic solutions and bistability, are established. Mathematical analysis proves the existence of a backward bifurcation and establishes thresholds for R0 that ensure tumor elimination or existence. A sensitivity analysis determines which parameters most significantly impact the reproduction number R0. Identifiability analysis reveals parameters of interest for estimation. Results are framed in terms of treatment implications, including effective combination and monotherapy strategies.
In Chapter 3, a study of whether the observed complexity can be represented with a simplified model is conducted. The DC model of Chapter 2 is reduced to a non-dimensional system of two DDEs. Mathematical and numerical analysis explore the impact of immune response time on the stability and eradication of the tumor, including an analytical proof of conditions necessary for the existence of a Hopf bifurcation. In a limiting case, conditions for global stability of the tumor-free equilibrium are outlined.
Lastly, Chapter 4 discusses future directions to explore. There still remain open questions to investigate and much work to be done, particularly involving uncertainty analysis. An outline of these steps is provided for future undertakings.
In Chapter 2, motivated by the work of de Pillis et al. (2013), a mathematical model employing six ordinary differential (ODEs) and delay differential equations (DDEs) is formulated to understand the effectiveness of DC vaccines, accounting for cell trafficking with a blood and tumor compartment. A preliminary analysis is performed, with numerical simulations used to show the existence of oscillatory behavior. The model is then reduced to a system of four ODEs. Both models are validated using experimental data from melanoma-induced mice. Conditions under which the model admits rich dynamics observed in a clinical setting, such as periodic solutions and bistability, are established. Mathematical analysis proves the existence of a backward bifurcation and establishes thresholds for R0 that ensure tumor elimination or existence. A sensitivity analysis determines which parameters most significantly impact the reproduction number R0. Identifiability analysis reveals parameters of interest for estimation. Results are framed in terms of treatment implications, including effective combination and monotherapy strategies.
In Chapter 3, a study of whether the observed complexity can be represented with a simplified model is conducted. The DC model of Chapter 2 is reduced to a non-dimensional system of two DDEs. Mathematical and numerical analysis explore the impact of immune response time on the stability and eradication of the tumor, including an analytical proof of conditions necessary for the existence of a Hopf bifurcation. In a limiting case, conditions for global stability of the tumor-free equilibrium are outlined.
Lastly, Chapter 4 discusses future directions to explore. There still remain open questions to investigate and much work to be done, particularly involving uncertainty analysis. An outline of these steps is provided for future undertakings.
ContributorsDickman, Lauren (Author) / Kuang, Yang (Thesis advisor) / Baer, Steven M. (Committee member) / Gardner, Carl (Committee member) / Gumel, Abba B. (Committee member) / Kostelich, Eric J. (Committee member) / Arizona State University (Publisher)
Created2020
Description
Background: Esophageal adenocarcinoma (EAC) is one of the only malignancies whose incidence is rising in the United States. Current multidrug treatment for EAC has considerable toxic side effects that necessitate the development of less toxic, more specific target drugs. Recent large scale genomic analysis reveals that TP53 is the most frequently inactivated gene in EAC. One of the primary functions of TP53 and its gene product, the tumor suppressor p53, is in regulation of DNA repair in response to DNA damage. Inactivation of TP53 results in loss of the G1/S cell cycle checkpoint, and dependence on the G2/M checkpoint for DNA repair. Activity of cyclin-dependent kinase 1 (CDK1) is necessary for cells to exit the G2/M checkpoint and enter mitosis. Phosphorylation of CDK1 by the wee1 kinase inhibits CDK1 in response to DNA damage, allowing cells to maintain G2 arrest and repair the damaged DNA. Active in normal cells, wee1 kinase is critical in cancer cells to promote DNA repair and cell survival in response to DNA damage, particularly from commonly used DNA damaging therapies. AZD1775 is a small molecule inhibitor of wee1 kinase, currently under investigation in clinical trials. AZD1775 differentially targets cancer cells by blocking wee1 mediated inhibition of CDK1 and consequently preventing G2/M arrest in response to DNA damage. Combination of AZD1775 with DNA damaging agents is thought to push cancer cells with damaged DNA through to mitosis and initiate apoptosis instead of G2/M arrest and DNA repair. Based upon the incidence of TP53 mutation in EAC, we hypothesize that treatment with a DNA damaging agent in combination with AZD1775 will be as effective at eliciting DNA damage and cell death as the more toxic current standard of care, which is comprised of treatment with cisplatin, docetaxel, and radiation. Methods: p53 mutant EAC cell lines were dosed with cisplatin, AZD1775, and the combination of cisplatin and AZD1775, and then assayed for viability. Nude mice were implanted with p53 mutant patient derived xenograft esophageal adenocarcinoma tumors and randomized for treatment with AZD1775 alone, cisplatin and AZD1775, radiation and AZD1775, cisplatin, docetaxel, and radiation or vehicle (control). Tumor volume was measured over the five week treatment course. Results: In vitro and in vivo assays reveal a potent synergistic effect between AZD1775 and DNA damaging agents that is as efficacious as the standard of care therapy. The difference in AZD1775 sensitivity among TP53 mutant EAC cell lines indicates that TP53 alone may not be an adequate biomarker to assess for AZD1775- mediated toxicity.
ContributorsBlomquist, Mylan (Author) / Maley, Carlo (Thesis director) / Inge, Landon (Committee member) / Oberle, Eric (Committee member) / College of Letters and Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05