Matching Items (12)

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Improving the Realism and Magnetic Resonance Imaging of Multicellular Tumor Spheroids

Description

Magnetic resonance imaging (MRI) of changes in metabolic activity in tumors and metabolic abnormalities can provide a window to understanding the complex behavior of malignant tumors. Both diagnostics and treatment

Magnetic resonance imaging (MRI) of changes in metabolic activity in tumors and metabolic abnormalities can provide a window to understanding the complex behavior of malignant tumors. Both diagnostics and treatment options can be improved through the further comprehension of the processes that contribute to tumor malignancy and growth. By detecting and disturbing this activity through personalized treatments, it is the hope to provide better diagnostics and care to patients. Experimenting with multicellular tumor spheroids (MCTS) allows for a rapid, inexpensive and convenient solution to studying multiple in vitro tumors. High quality magnetic resonance images of small samples, such as spheroid, however, are difficult to achieve with current radio frequency coils. In addition, in order for the information provided by these scans to accurately represent the interactions and metabolic activity in vivo, there is a need for a perfused vascular network. A perfused vascular network has the potential to improve metabolic realism and particle transport within a tumor spheroid. By creating a more life-like cancer model and allowing the progressive imaging of metabolic functions of such small samples, a better, more efficient mode of studying metabolic activity in cancer can be created and research efforts can expand. The progress described in this paper attempts to address both of these current shortcomings of metabolic cancer research and offers potential solutions, while acknowledging the potential of future work to improve cancer research with MCTS.

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Created

Date Created
  • 2016-12

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Can Akt3 Decrease Tumorigenicity in Glioblastoma Multiforme Through a Cell Cycle Mechanism?

Description

Glioblastoma multiforme is associated with a very low survival rate and is recognized as the most vicious form of intracranial cancer. The Akt gene pathway has three different isoforms, each

Glioblastoma multiforme is associated with a very low survival rate and is recognized as the most vicious form of intracranial cancer. The Akt gene pathway has three different isoforms, each of which has a different role in the tumors of GBM. Preliminary data suggests that Akt3 may work to decrease tumorigenicity. A produced image that visualizes the subcellular localization of Akt3 led the author to believe that Akt3 may reduce tumorigenicity by decreasing genomic instability caused by the cancer. To explore this, flow cytometry was performed on GBM cell lines with Akt3v1 over-expression, Akt3v2 over-expression, and a control glioma cell line.

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Created

Date Created
  • 2012-12

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Clonal Analysis of a Human Breast Cancer

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

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.

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Created

Date Created
  • 2015-05

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Investigate and characterize the means to reduce the toxicity of genetically engineered cancer therapeutic recombinant attenuated Salmonella

Description

Cancer is one of the leading causes of death in the world and represents a tremendous burden on patients, families and societies. S. Typhimurium strains are specifically attracted to compounds

Cancer is one of the leading causes of death in the world and represents a tremendous burden on patients, families and societies. S. Typhimurium strains are specifically attracted to compounds produced by cancer cells and could overcome the traditional therapeutic barrier. However, a major problem with using live attenuated Salmonella as anti-cancer agents is their toxicity at the dose required for therapeutic efficacy, but reducing the dose results in diminished efficacy. In this project, we explored novel means to reduce the toxicity of the recombinant attenuated Salmonella by genetically engineering those virulence factors to facilitate maximal colonization of tumor tissues and reduced fitness in normal tissues. We have constructed two sets of Salmonella strains. In the first set, each targeted gene was knocked out by deletion of the gene. In the second set, the predicted promoter region of each gene was replaced with a rhamnose-regulated promoter, which will cease the synthesis of these genes in vivo, a rhamnose-free environment.

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Agent

Created

Date Created
  • 2013-05

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Identification of Tumor Associated Antigens using Nucleic Acid Programmable Protein Arrays

Description

Identifying disease biomarkers may aid in the early detection of breast cancer and improve patient outcomes. Recent evidence suggests that tumors are immunogenic and therefore patients may launch an autoantibody

Identifying disease biomarkers may aid in the early detection of breast cancer and improve patient outcomes. Recent evidence suggests that tumors are immunogenic and therefore patients may launch an autoantibody response to tumor associated antigens. Single-chain variable fragments of autoantibodies derived from regional lymph node B cells of breast cancer patients were used to discover these tumor associated biomarkers on protein microarrays. Six candidate biomarkers were discovered from 22 heavy chain-only variable region antibody fragments screened. Validation tests are necessary to confirm the tumorgenicity of these antigens. However, the use of single-chain variable autoantibody fragments presents a novel platform for diagnostics and cancer therapeutics.

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Created

Date Created
  • 2012-12

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Molecular Engineering of Novel Polymeric Agents for Targeted Cancer Gene Therapy

Description

Abstract Molecular Engineering of Novel Polymeric Agents for Targeted Cancer Gene Therapy Dana Matthews Cancer gene cell therapy is a strategy that involves the administration of genes for correcting the

Abstract Molecular Engineering of Novel Polymeric Agents for Targeted Cancer Gene Therapy Dana Matthews Cancer gene cell therapy is a strategy that involves the administration of genes for correcting the effect of mutated cancer cells in order to induce tumor cell death. In particular, genes that encode for pro-apoptotic proteins can result in death of tumor cells. Prostate cancer is a very common cancer among males in America, and as highly destructive chemotherapy and radiation are generally the only treatments available once the cancer has metastasized, there is a need for the development of treatments that can specifically target and kill prostate cancer cells, while demonstrating low toxicity to other tissue. This experiment will attempt to create such a treatment through gene therapy techniques. The parallel synthesis and DNA binding affinity assay utilized in these experiments have produced a polymer that surpasses pEI-25, a gene delivery polymer standard, in both transfection efficacy and low cytotoxicity and trafficking of polyplexes in the cell, and finding methods to increase the transfection efficacy and specificity of polyplexes for PC3-PSMA cells.

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Created

Date Created
  • 2008-12

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Cell quota based population models and their applications

Description

In 1968, phycologist M.R. Droop published his famous discovery on the functional relationship between growth rate and internal nutrient status of algae in chemostat culture. The simple notion that growth

In 1968, phycologist M.R. Droop published his famous discovery on the functional relationship between growth rate and internal nutrient status of algae in chemostat culture. The simple notion that growth is directly dependent on intracellular nutrient concentration is useful for understanding the dynamics in many ecological systems. The cell quota in particular lends itself to ecological stoichiometry, which is a powerful framework for mathematical ecology. Three models are developed based on the cell quota principal in order to demonstrate its applications beyond chemostat culture.

First, a data-driven model is derived for neutral lipid synthesis in green microalgae with respect to nitrogen limitation. This model synthesizes several established frameworks in phycology and ecological stoichiometry. The model demonstrates how the cell quota is a useful abstraction for understanding the metabolic shift to neutral lipid production that is observed in certain oleaginous species.

Next a producer-grazer model is developed based on the cell quota model and nutrient recycling. The model incorporates a novel feedback loop to account for animal toxicity due to accumulation of nitrogen waste. The model exhibits rich, complex dynamics which leave several open mathematical questions.

Lastly, disease dynamics in vivo are in many ways analogous to those of an ecosystem, giving natural extensions of the cell quota concept to disease modeling. Prostate cancer can be modeled within this framework, with androgen the limiting nutrient and the prostate and cancer cells as competing species. Here the cell quota model provides a useful abstraction for the dependence of cellular proliferation and apoptosis on androgen and the androgen receptor. Androgen ablation therapy is often used for patients in biochemical recurrence or late-stage disease progression and is in general initially effective. However, for many patients the cancer eventually develops resistance months to years after treatment begins. Understanding how and predicting when hormone therapy facilitates evolution of resistant phenotypes has immediate implications for treatment. Cell quota models for prostate cancer can be useful tools for this purpose and motivate applications to other diseases.

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Agent

Created

Date Created
  • 2014

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Discovering subclones and their driver genes in tumors sequenced at standard depths

Description

Understanding intratumor heterogeneity and their driver genes is critical to

designing personalized treatments and improving clinical outcomes of cancers. Such

investigations require accurate delineation of the subclonal composition of a tumor, which

to

Understanding intratumor heterogeneity and their driver genes is critical to

designing personalized treatments and improving clinical outcomes of cancers. Such

investigations require accurate delineation of the subclonal composition of a tumor, which

to date can only be reliably inferred from deep-sequencing data (>300x depth). The

resulting algorithm from the work presented here, incorporates an adaptive error model

into statistical decomposition of mixed populations, which corrects the mean-variance

dependency of sequencing data at the subclonal level and enables accurate subclonal

discovery in tumors sequenced at standard depths (30-50x). Tested on extensive computer

simulations and real-world data, this new method, named model-based adaptive grouping

of subclones (MAGOS), consistently outperforms existing methods on minimum

sequencing depth, decomposition accuracy and computation efficiency. MAGOS supports

subclone analysis using single nucleotide variants and copy number variants from one or

more samples of an individual tumor. GUST algorithm, on the other hand is a novel method

in detecting the cancer type specific driver genes. Combination of MAGOS and GUST

results can provide insights into cancer progression. Applications of MAGOS and GUST

to whole-exome sequencing data of 33 different cancer types’ samples discovered a

significant association between subclonal diversity and their drivers and patient overall

survival.

Contributors

Agent

Created

Date Created
  • 2019

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Mathematical and computational models of cancer and the immune system

Description

The immune system plays a dual role during neoplastic progression. It can suppress tumor growth by eliminating cancer cells, and also promote neoplastic expansion by either selecting for tumor cells

The immune system plays a dual role during neoplastic progression. It can suppress tumor growth by eliminating cancer cells, and also promote neoplastic expansion by either selecting for tumor cells that are fitter to survive in an immunocompetent host or by establishing the right conditions within the tumor microenvironment. First, I present a model to study the dynamics of subclonal evolution of cancer. I model selection through time as an epistatic process. That is, the fitness change in a given cell is not simply additive, but depends on previous mutations. Simulation studies indicate that tumors are composed of myriads of small subclones at the time of diagnosis. Because some of these rare subclones harbor pre-existing treatment-resistant mutations, they present a major challenge to precision medicine. Second, I study the question of self and non-self discrimination by the immune system, which is fundamental in the field in cancer immunology. By performing a quantitative analysis of the biochemical properties of thousands of MHC class I peptides, I find that hydrophobicity of T cell receptors contact residues is a hallmark of immunogenic epitopes. Based on these findings, I further develop a computational model to predict immunogenic epitopes which facilitate the development of T cell vaccines against pathogen and tumor antigens. Lastly, I study the effect of early detection in the context of Ebola. I develope a simple mathematical model calibrated to the transmission dynamics of Ebola virus in West Africa. My findings suggest that a strategy that focuses on early diagnosis of high-risk individuals, caregivers, and health-care workers at the pre-symptomatic stage, when combined with public health measures to improve the speed and efficacy of isolation of infectious individuals, can lead to rapid reductions in Ebola transmission.

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Agent

Created

Date Created
  • 2016

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A two strain spatiotemporal mathematical model of cancer with free boundary condition

Description

In a 2004 paper, John Nagy raised the possibility of the existence of a hypertumor \emph{i.e.}, a focus of aggressively reproducing parenchyma cells that invade part or all of a

In a 2004 paper, John Nagy raised the possibility of the existence of a hypertumor \emph{i.e.}, a focus of aggressively reproducing parenchyma cells that invade part or all of a tumor. His model used a system of nonlinear ordinary differential equations to find a suitable set of conditions for which these hypertumors exist. Here that model is expanded by transforming it into a system of nonlinear partial differential equations with diffusion, advection, and a free boundary condition to represent a radially symmetric tumor growth. Two strains of parenchymal cells are incorporated; one forming almost the entirety of the tumor while the much more aggressive strain

appears in a smaller region inside of the tumor. Simulations show that if the aggressive strain focuses its efforts on proliferating and does not contribute to angiogenesis signaling when in a hypoxic state, a hypertumor will form. More importantly, this resultant aggressive tumor is paradoxically prone to extinction and hypothesize is the cause of necrosis in many vascularized tumors.

Contributors

Agent

Created

Date Created
  • 2014