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Georgia Tech
1.
Clayton, Evan.
Global dysregulation of gene expression and tumorigenesis: Data science for cancer.
Degree: PhD, Biology, 2019, Georgia Tech
URL: http://hdl.handle.net/1853/62290 
► Dysregulation of gene expression is a hallmark of cancer. Broadly speaking, my research is focused on the changes in gene expression that characterize the transition…
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▼ Dysregulation of gene expression is a hallmark of cancer. Broadly speaking, my research is focused on the changes in gene expression that characterize the transition from normal to cancerous states, i.e. tumorigenesis. To study such changes, I performed integrated analysis of next generation sequencing data for matched normal and primary tumor samples from hundreds of patients across numerous different cancer types. By analyzing this sequencing data, I have been able to explore the global landscape of transcriptional reprogramming in cancer and discover how changes in the regulation of gene expression may be implicated in tumorigenesis. My thesis is focused on four specific areas of transcriptional reprogramming in cancer: (1) changes in the expression and activity of transposable elements (TEs), (2) changes in alternative splicing induced by TEs, (3) allele-specific expression of tumor suppressor genes (TSGs), and (4) gene expression changes that are implicated in cancer drug response. TEs are known to be uniformly overexpressed in cancer, suggesting a possible role for their activity in tumorigenesis. I discovered a class of long interspersed nuclear elements (the LINE-1 family) with elevated levels of expression and activity in three different cancer types, and I showed examples where cancer-specific LINE-1 insertions disrupt enhancers, leading to the down-regulation of TSGs. TEs are also implicated in the creation of novel splicing isoforms, and aberrant alternative splicing has been associated with tumorigenesis for a number of different cancers. Integrated analysis of genome sequence and transcriptome data revealed thousands of TE-generated alternative splice events genome-wide, including close to 5,000 events distributed among cancer associated genes. I explored the functional implications of specific cases of isoform switching, whereby TE-induced isoforms of cancer associated genes show elevated levels of relative expression in tumor samples. A closer look at TSG expression in matched normal and tumor samples indicated that functionally important changes in patterns of allele-specific expression in individuals heterozygous for loss-of-function TSG alleles is a significant factor in cancer onset/progression. These results identified a variety of molecular mechanisms that contribute to the observed changes in allele-specific expression patterns in cancer with allele-specific alternative splicing mediated by anti-sense RNA emerging as a predominant factor. Furthermore, analysis of the genomic variation for world-wide human populations demonstrates that loss-of-function TSG alleles are segregating at remarkedly high frequencies implying that a significant fraction of otherwise healthy individuals may be pre-disposed to developing cancer. For the final study of my thesis research, I applied the gene expression data from primary tumor samples to build predictive models of cancer drug response for two common chemotherapeutics: 5-Fluorouracil and Gemcitabine. My gene expression based models predict whether patients…
Advisors/Committee Members: Jordan, Irving K. (advisor), McDonald, John F. (advisor), Yi, Soojin (committee member), Choi, Jung (committee member), Qiu, Peng (committee member).
Subjects/Keywords: Bioinformatics; Tumorigenesis; Cancer; Transposable elements; Alternative splicing; Gene expression; Gene regulation; Tumor suppressor genes; Allele-specific expression; Machine learning; Drug response; Precision oncology; Predictive models
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APA (6th Edition):
Clayton, E. (2019). Global dysregulation of gene expression and tumorigenesis: Data science for cancer. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62290
Chicago Manual of Style (16th Edition):
Clayton, Evan. “Global dysregulation of gene expression and tumorigenesis: Data science for cancer.” 2019. Doctoral Dissertation, Georgia Tech. Accessed January 19, 2021.
http://hdl.handle.net/1853/62290.
MLA Handbook (7th Edition):
Clayton, Evan. “Global dysregulation of gene expression and tumorigenesis: Data science for cancer.” 2019. Web. 19 Jan 2021.
Vancouver:
Clayton E. Global dysregulation of gene expression and tumorigenesis: Data science for cancer. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Jan 19].
Available from: http://hdl.handle.net/1853/62290.
Council of Science Editors:
Clayton E. Global dysregulation of gene expression and tumorigenesis: Data science for cancer. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62290
Georgia Tech
2.
Zhang, Mengnan.
Analysis of the role of miRNAs in ovarian cancer metastasis.
Degree: PhD, Biology, 2019, Georgia Tech
URL: http://hdl.handle.net/1853/62647
► Cancer mortality is primarily due to metastasis. Metastasis is a complex multi-step process involving, on the molecular level, regulatory control of two key development pathways:…
(more)
▼ Cancer mortality is primarily due to metastasis. Metastasis is a complex multi-step process involving, on the molecular level, regulatory control of two key development pathways: epithelial-to-mesenchymal transition (EMT) and it reciprocal, mesenchymal-to-epithelial transition (MET) . MiRNAs are small regulatory RNA molecules that play key roles in the regulation of EMT/MET. In this thesis, I examine the role of miRNAs in regulating EMT/MET in ovarian cancer. In the first study, I show that sequentially divergent miRNAs converge to regulate the EMT/MET process through both direct and indirect regulatory changes. In the second study, I explore the impact of genetic difference between different cancer cell lines on the function of miRNAs to regulate the EMT/MET process. In the third study, I evaluate the importance of post-transcriptional/translational changes in the metastasis of a stage III ovarian cancer patient and the role played by miRNAs in regulating the process.
Advisors/Committee Members: McDonald, John F. (advisor), Jordan, King I. (committee member), Vannberg, Fredrik O. (committee member), Choi, Jung H. (committee member), Wu, Ronghu (committee member).
Subjects/Keywords: miRNA; Gene expression; Ovarian cancer; Epithelial-to-mesenchymal mesenchymal-to-epithelial transition
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APA (6th Edition):
Zhang, M. (2019). Analysis of the role of miRNAs in ovarian cancer metastasis. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62647
Chicago Manual of Style (16th Edition):
Zhang, Mengnan. “Analysis of the role of miRNAs in ovarian cancer metastasis.” 2019. Doctoral Dissertation, Georgia Tech. Accessed January 19, 2021.
http://hdl.handle.net/1853/62647.
MLA Handbook (7th Edition):
Zhang, Mengnan. “Analysis of the role of miRNAs in ovarian cancer metastasis.” 2019. Web. 19 Jan 2021.
Vancouver:
Zhang M. Analysis of the role of miRNAs in ovarian cancer metastasis. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Jan 19].
Available from: http://hdl.handle.net/1853/62647.
Council of Science Editors:
Zhang M. Analysis of the role of miRNAs in ovarian cancer metastasis. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62647
Georgia Tech
3.
Srinivasan, Swetha.
Understanding the systemic roles of exosomes in innate immunity.
Degree: PhD, Biology, 2016, Georgia Tech
URL: http://hdl.handle.net/1853/58595
► Cell-cell communication is critical for rapidly spreading the message of infection and enabling the innate immune system to mount a broad response against the pathogen.…
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▼ Cell-cell communication is critical for rapidly spreading the message of infection and enabling the innate immune system to mount a broad response against the pathogen. Exosomes are nanovesicles (~50nm in diameter) that are released extracellularly by all cell types. Their ability to transmit messages between cells at a distance and their rapid transport through the body makes them ideal messengers for establishing innate immune responses. However, their utilization of transport pathways in vivo was uncharacterized. The central role of lymphatic transport in trafficking exosomes in vivo was established for the first time in this thesis. Furthermore, differential distribution of exosomes in the draining lymph nodes that is dependent on the lymphatic flow has been established and macrophages and B-cells were identified as key players in exosome uptake.
The distal recapitulation of the local toll-like receptor response via exosomes definitively established their ability to disseminate innate immune information in vitro. This is the first delineation of the kinetics of the response accompanied with abrogation of the action-at-a-distance signaling of exosomes by UV irradiation, demonstrating that RNA is crucial for their effector function. The impact of exosome uptake in whole lymph node and macrophages uptake is elucidated to show reprogramming of the node to a pro-inflammatory state and M1 macrophage polarization. Therefore, this work characterized the role of exosomes in initiating an innate immune response comprehensively in the context of a viral infection both in vitro and in vivo.
Advisors/Committee Members: Vannberg, Fredrik O. (advisor), Dixon, J. Brandon (advisor), Gibson, Gregory (committee member), McDonald, John F. (committee member), Jordan, I. King (committee member).
Subjects/Keywords: Exosomes; Lymphatic transport; TLR; LPS; Poly (I:C) macrophages; Innate immunity
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APA (6th Edition):
Srinivasan, S. (2016). Understanding the systemic roles of exosomes in innate immunity. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/58595
Chicago Manual of Style (16th Edition):
Srinivasan, Swetha. “Understanding the systemic roles of exosomes in innate immunity.” 2016. Doctoral Dissertation, Georgia Tech. Accessed January 19, 2021.
http://hdl.handle.net/1853/58595.
MLA Handbook (7th Edition):
Srinivasan, Swetha. “Understanding the systemic roles of exosomes in innate immunity.” 2016. Web. 19 Jan 2021.
Vancouver:
Srinivasan S. Understanding the systemic roles of exosomes in innate immunity. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2021 Jan 19].
Available from: http://hdl.handle.net/1853/58595.
Council of Science Editors:
Srinivasan S. Understanding the systemic roles of exosomes in innate immunity. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/58595
Georgia Tech
4.
Bongiorno, Thomas.
Cellular stiffness as a sorting-compatible indicator of stem cell potency.
Degree: PhD, Mechanical Engineering, 2016, Georgia Tech
URL: http://hdl.handle.net/1853/59150
► Due to their characteristic properties of self-renewal and differentiation, stem cells hold the capacity to serve as phenotype-specific cell factories for various regenerative medicine and…
(more)
▼ Due to their characteristic properties of self-renewal and differentiation, stem cells hold the capacity to serve as phenotype-specific cell factories for various regenerative medicine and tissue engineering applications. However, current phenotyping techniques, which typically employ multiple surface protein-specific antibodies, are often insufficient to identify or enrich cells of a target phenotype. An improved technique that could select target cells could be used to purify starting cell populations for directed differentiation protocols or to enrich specific terminally differentiated phenotypes for tissue engineering. The goal of this project is to investigate cellular mechanical parameters as stem cell phenotype markers to complement the currently available biomolecular markers. This objective was accomplished through 1) the establishment of cell stiffness as a single-cell marker of potency in both mesenchymal stem cells, which give rise to cells of the connective tissue, and limbal stem cells, which replenish the cornea, 2) the development of a method to compare cell mechanics and gene expression at the single-cell level, which will enable more detailed studies of the relationships between cell phenotype, mechanics, and structure, and 3) the determination that pluripotent embryonic stem cells, which are softer than their differentiated progeny, can be enriched using a cell stiffness-based microfluidic sorting device, as assessed by potency-related morphological and genetic factors. Ultimately, this project established cell stiffness as a marker of stem cell differentiation in various cell systems, with applications to label-free selection of target cell phenotypes.
Advisors/Committee Members: Sulchek, Todd (advisor), Lam, Wilbur A. (committee member), McDevitt, Todd C. (committee member), McDonald, John F. (committee member), Vertino, Paula M. (committee member).
Subjects/Keywords: Cell mechanics; Stem cell; Atomic force microscopy; Microfluidics
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APA (6th Edition):
Bongiorno, T. (2016). Cellular stiffness as a sorting-compatible indicator of stem cell potency. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59150
Chicago Manual of Style (16th Edition):
Bongiorno, Thomas. “Cellular stiffness as a sorting-compatible indicator of stem cell potency.” 2016. Doctoral Dissertation, Georgia Tech. Accessed January 19, 2021.
http://hdl.handle.net/1853/59150.
MLA Handbook (7th Edition):
Bongiorno, Thomas. “Cellular stiffness as a sorting-compatible indicator of stem cell potency.” 2016. Web. 19 Jan 2021.
Vancouver:
Bongiorno T. Cellular stiffness as a sorting-compatible indicator of stem cell potency. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2021 Jan 19].
Available from: http://hdl.handle.net/1853/59150.
Council of Science Editors:
Bongiorno T. Cellular stiffness as a sorting-compatible indicator of stem cell potency. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/59150
Georgia Tech
5.
Mittal, Vinay K.
Detection and characterization of gene-fusions in breast and ovarian cancer using high-throughput sequencing.
Degree: PhD, Biology, 2014, Georgia Tech
URL: http://hdl.handle.net/1853/54014
► Gene-fusions are a prevalent class of genetic variants that are often employed as cancer biomarkers and therapeutic targets. In recent years, high-throughput sequencing of the…
(more)
▼ Gene-fusions are a prevalent class of genetic variants that are often employed as cancer biomarkers and therapeutic targets. In recent years, high-throughput sequencing of the cellular genome and transcriptome have emerged as a promising approach for the investigation of gene-fusions at the DNA and RNA level. Although, large volumes of sequencing data and complexity of gene-fusion structures presents unique computational challenges. This dissertation describes research that first addresses the bioinformatics challenges associated with the analysis of the massive volumes of sequencing data by developing bioinformatics pipeline and more applied integrated computational workflows. Application of high-throughput sequencing and the proposed bioinformatics approaches for the breast and ovarian cancer study reveals unexpected complex structures of gene-fusions and their functional significance in the onset and progression of cancer. Integrative analysis of gene-fusions at DNA and RNA level shows the key importance of the regulation of gene-fusion at the transcription level in cancer.
Advisors/Committee Members: McDonald, John F. (advisor), Jordan, King (committee member), Choi, Jung H. (committee member), Gibson, Gregory C. (committee member), Bowen, Nathan J. (committee member).
Subjects/Keywords: Cancer; RNA-Seq; Whole-genome sequencing; Gene-fusion; Bioinformatics; Chimeric transcript; Pipeline; Transcriptomics; Genomics; Next-generation sequencing; High-throughput sequencing
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APA (6th Edition):
Mittal, V. K. (2014). Detection and characterization of gene-fusions in breast and ovarian cancer using high-throughput sequencing. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54014
Chicago Manual of Style (16th Edition):
Mittal, Vinay K. “Detection and characterization of gene-fusions in breast and ovarian cancer using high-throughput sequencing.” 2014. Doctoral Dissertation, Georgia Tech. Accessed January 19, 2021.
http://hdl.handle.net/1853/54014.
MLA Handbook (7th Edition):
Mittal, Vinay K. “Detection and characterization of gene-fusions in breast and ovarian cancer using high-throughput sequencing.” 2014. Web. 19 Jan 2021.
Vancouver:
Mittal VK. Detection and characterization of gene-fusions in breast and ovarian cancer using high-throughput sequencing. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2021 Jan 19].
Available from: http://hdl.handle.net/1853/54014.
Council of Science Editors:
Mittal VK. Detection and characterization of gene-fusions in breast and ovarian cancer using high-throughput sequencing. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/54014
Georgia Tech
6.
Huang, Andrew Douglas.
Computational analysis of gene expression in complex disease.
Degree: PhD, Biology, 2014, Georgia Tech
URL: http://hdl.handle.net/1853/54257
► Cardiovascular disease (CVD) causes 45% of on-duty firefighter fatalities, a high fraction even when compared to the risk of CVD found in other first-responder professions…
(more)
▼ Cardiovascular disease (CVD) causes 45% of on-duty firefighter fatalities, a high fraction even when compared to the risk of CVD found in other first-responder professions like police work and emergency medical services. Monitoring and managing firefighter cardiac health is important for both individual health and public safety. In our study, we are interested in assessing the utility of the most commonly used risk assessment scoring, known as the Framingham Risk Score, in evaluating the atherosclerotic risk in asymptomatic firefighters. To this end we determined FRS for 159 male firefighters from Gwinnett County,
Georgia, and compared their risk categorization against their known atherosclerotic burden as determined by CIMT and CAC. While the 20% FRS threshold, corresponding to medium risk, had a high specificity for both CAC and CIMT, it also had a low sensitivity (17% and 40%, respectively), indicating that a large percentage of individuals with clinically significant atherosclerosis are being misclassified. By adjusting the FRS threshold downward, we were able to raise the sensitivity greatly with only a modest loss of specificity.
Following percutaneous transluminal coronary angioplasty for the treatment of coronary artery disease, stents are commonly implanted at the treatment site to prevent recoil and negative remodeling. To combat in-stent restenosis, an arterial healing response that results in luminal loss in stented arteries, anti-restenotic drugs like sirolimus (SES) and zotarolimus (ZES) are commonly eluted by stents to suppress cell proliferation at the treatment site. While comparative studies have revealed significant difference between bare metal stents (BMS), SES, and ZES in both clinical and histological arterial response, the molecular basis of these differences remains poorly understood. We conducted a comparative gene expression profiling study using microarrays to examine differences in gene expression and pathway function in coronary arteries exposed to ZES, SES, and BMS in a porcine animal model. These molecular profiles suggest a model of delayed restenosis, resulting from a drug-induced suppression of inflammatory responses and proliferative processes, rather than an elimination of restenosis.
microRNAs play a regulatory role in metastasis-related epithelial to mesenchymal transitions and mesenchymal to epithelial transitions in ovarian cancer cells. We previously showed that over-expression of miR-429 in ovarian cancer cells drove a transition from mesenchymal phenotypes to epithelial phenotypes both in morphology and expression of markers like ZEB1, ZEB2, and E-cadherin. Our study represents the first time course analysis of miR-429-induced MET in ovarian cancer cells. We transfected Hey cells with miR-429 and assayed gene expression over the course of 144 hours at regular intervals. The cell morphology and gene expression of our transfected cells changed to become more epithelial-like at 24 and 48 hours and then became more mesenchymal-like by 144 hours. By 144 hours the average…
Advisors/Committee Members: McDonald, John F. (advisor), Bowen, Nathan (committee member), Daneker, George W. (committee member), Momary, Kathyrn M. (committee member), Choi, Jung H. (committee member).
Subjects/Keywords: Gene expression; Microarrays; Coronary artery disease; Ovarian cancer; Bioinformatics
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APA (6th Edition):
Huang, A. D. (2014). Computational analysis of gene expression in complex disease. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54257
Chicago Manual of Style (16th Edition):
Huang, Andrew Douglas. “Computational analysis of gene expression in complex disease.” 2014. Doctoral Dissertation, Georgia Tech. Accessed January 19, 2021.
http://hdl.handle.net/1853/54257.
MLA Handbook (7th Edition):
Huang, Andrew Douglas. “Computational analysis of gene expression in complex disease.” 2014. Web. 19 Jan 2021.
Vancouver:
Huang AD. Computational analysis of gene expression in complex disease. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2021 Jan 19].
Available from: http://hdl.handle.net/1853/54257.
Council of Science Editors:
Huang AD. Computational analysis of gene expression in complex disease. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/54257
Georgia Tech
7.
Vermeersch, Kathleen A.
Systems-level characterization of ovarian cancer metabolism.
Degree: PhD, Chemical and Biomolecular Engineering, 2014, Georgia Tech
URL: http://hdl.handle.net/1853/54258
► The purpose of this thesis was to characterize cancer metabolism in vitro using epithelial ovarian cancer as a model on an untargeted, systems-level, basis with…
(more)
▼ The purpose of this thesis was to characterize cancer metabolism in vitro using epithelial ovarian cancer as a model on an untargeted, systems-level, basis with particular attention paid to the difference between cancer stem cell metabolism and cancer cell metabolism. Two-dimensional gas chromatography coupled to mass spectrometry was used to measure the metabolite profiles of the ovarian cancer and cancer stem cell lines under normal baseline conditions and also under chemotherapeutic and environmental perturbations. These two cell lines exhibited significant metabolic differences under normal baseline conditions and results demonstrated that metabolism in the ovarian cancer stem cell line was distinct from that of more differentiated isogenic cancer cells, showing similarities to stem cell metabolism that suggest the potential importance of metabolism for the cancer stem cell phenotype. Glucose deprivation, hypoxia, and ischemia all perturbed ovarian cancer and cancer stem cell metabolism, but not in the same ways between the cell types. Chemotherapeutic treatment with docetaxel caused metabolic changes mostly in amino acid and carbohydrate metabolism in ovarian cancer cells, while ovarian cancer stem cell metabolism was not affected by docetaxel. Overall, these metabolic differences between the two cell types will deepen our understanding of the metabolic changes occurring within the in vivo tumor and will help drive development of cancer stem cell targeted therapeutics.
Advisors/Committee Members: Styczynski, Mark P. (advisor), Chen, Rachel (committee member), Bommarius, Andreas S. (committee member), Dawson, Michelle R. (committee member), McDonald, John F. (committee member).
Subjects/Keywords: Cancer stem cells; Cancer metabolism; Ovarian cancer; Metabolomics
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APA (6th Edition):
Vermeersch, K. A. (2014). Systems-level characterization of ovarian cancer metabolism. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54258
Chicago Manual of Style (16th Edition):
Vermeersch, Kathleen A. “Systems-level characterization of ovarian cancer metabolism.” 2014. Doctoral Dissertation, Georgia Tech. Accessed January 19, 2021.
http://hdl.handle.net/1853/54258.
MLA Handbook (7th Edition):
Vermeersch, Kathleen A. “Systems-level characterization of ovarian cancer metabolism.” 2014. Web. 19 Jan 2021.
Vancouver:
Vermeersch KA. Systems-level characterization of ovarian cancer metabolism. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2021 Jan 19].
Available from: http://hdl.handle.net/1853/54258.
Council of Science Editors:
Vermeersch KA. Systems-level characterization of ovarian cancer metabolism. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/54258
Georgia Tech
8.
Jones, Christina Michele.
Applications and challenges in mass spectrometry-based untargeted metabolomics.
Degree: PhD, Chemistry and Biochemistry, 2015, Georgia Tech
URL: http://hdl.handle.net/1853/54830
► Metabolomics is the methodical scientific study of biochemical processes associated with the metabolome—which comprises the entire collection of metabolites in any biological entity. Metabolome changes…
(more)
▼ Metabolomics is the methodical scientific study of biochemical processes associated with the metabolome—which comprises the entire collection of metabolites in any biological entity. Metabolome changes occur as a result of modifications in the genome and proteome, and are, therefore, directly related to cellular phenotype. Thus, metabolomic analysis is capable of providing a snapshot of cellular physiology. Untargeted metabolomics is an impartial, all-inclusive approach for detecting as many metabolites as possible without a priori knowledge of their identity. Hence, it is a valuable exploratory tool capable of providing extensive chemical information for discovery and hypothesis-generation regarding biochemical processes. A history of metabolomics and advances in the field corresponding to improved analytical technologies are described in Chapter 1 of this dissertation. Additionally, Chapter 1 introduces the analytical workflows involved in untargeted metabolomics research to provide a foundation for Chapters 2 – 5.
Part I of this dissertation which encompasses Chapters 2 – 3 describes the utilization of mass spectrometry (MS)-based untargeted metabolomic analysis to acquire new insight into cancer detection. There is a knowledge deficit regarding the biochemical processes of the origin and proliferative molecular mechanisms of many types of cancer which has also led to a shortage of sensitive and specific biomarkers. Chapter 2 describes the development of an in vitro diagnostic multivariate index assay (IVDMIA) for prostate cancer (PCa) prediction based on ultra performance liquid chromatography-mass spectrometry (UPLC-MS) metabolic profiling of blood serum samples from 64 PCa patients and 50 healthy individuals. A panel of 40 metabolic spectral features was found to be differential with 92.1% sensitivity, 94.3% specificity, and 93.0% accuracy. The performance of the IVDMIA was higher than the prevalent prostate-specific antigen blood test, thus, highlighting that a combination of multiple discriminant features yields higher predictive power for PCa detection than the univariate analysis of a single marker. Chapter 3 describes two approaches that were taken to investigate metabolic patterns for early detection of ovarian cancer (OC). First, Dicer-Pten double knockout (DKO) mice that phenocopy many of the features of metastatic high-grade serous carcinoma (HGSC) observed in women were studied. Using UPLC-MS, serum samples from 14 early-stage tumor DKO mice and 11 controls were analyzed. Iterative multivariate classification selected 18 metabolites that, when considered as a panel, yielded 100% accuracy, sensitivity, and specificity for early-stage HGSC detection. In the second approach, serum metabolic phenotypes of an early-stage OC pilot patient cohort were characterized. Serum samples were collected from 24 early-stage OC patients and 40 healthy women, and subsequently analyzed using UPLC-MS. Multivariate statistical analysis employing support vector machine learning methods and recursive feature elimination…
Advisors/Committee Members: Fernández, Facundo M. (advisor), Bottomley, Lawrence A. (committee member), Kubanek, Julia (committee member), McDonald, John F. (committee member), Styczynski, Mark P. (committee member).
Subjects/Keywords: Metabolomics; Untargeted metabolomics; Metabolite profiling; Metabolite fingerprinting; Mass spectrometry; Oncometabolomics; Ecometabolomics; Serum metabolomics; Systems biology; Proteomics; Cancer detection; Early detection; Biomarkers; Prostate cancer; Prostate cancer detection; Machine learning methods; Support vector machines; In vitro diagnostic multivariate index assay; IVDMIA; Ovarian cancer; Ovarian cancer detection; Mouse models; DKO mouse model; Early stage cancer detection; Chemically mediated interactions; Chemical ecology; Karenia brevis; Allelopathy; Red tide; Ambient mass spectrometry; Ultra performance liquid chromatography; Direct analysis in real time; DART; Transmission mode DART; Probe mode DART; Traveling wave ion mobility-mass spectrometry; TWIMS; Exhaled breath condensate; Cystic fibrosis
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APA ·
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MLA ·
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APA (6th Edition):
Jones, C. M. (2015). Applications and challenges in mass spectrometry-based untargeted metabolomics. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54830
Chicago Manual of Style (16th Edition):
Jones, Christina Michele. “Applications and challenges in mass spectrometry-based untargeted metabolomics.” 2015. Doctoral Dissertation, Georgia Tech. Accessed January 19, 2021.
http://hdl.handle.net/1853/54830.
MLA Handbook (7th Edition):
Jones, Christina Michele. “Applications and challenges in mass spectrometry-based untargeted metabolomics.” 2015. Web. 19 Jan 2021.
Vancouver:
Jones CM. Applications and challenges in mass spectrometry-based untargeted metabolomics. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2021 Jan 19].
Available from: http://hdl.handle.net/1853/54830.
Council of Science Editors:
Jones CM. Applications and challenges in mass spectrometry-based untargeted metabolomics. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/54830
Georgia Tech
9.
Jabbari, Neda.
Functional significance of sequence variation among miR-200/205 families of miRNAs in ovarian cancer.
Degree: PhD, Biology, 2015, Georgia Tech
URL: http://hdl.handle.net/1853/55522
► MicroRNAs are short non-coding RNAs that regulate large suites of target genes. A family of miRNAs known as the miR-200 is implicated in the epithelial-mesenchymal/…
(more)
▼ MicroRNAs are short non-coding RNAs that regulate large suites of target genes.
A family of miRNAs known as the miR-200 is implicated in the epithelial-mesenchymal/
mesenchymal-epithelial transition (EMT/MET), a process associated with cancer
metastasis. Overexpression of miR-200 family miRNAs results in the induction of MET
and increased sensitivity to chemotherapeutic drugs. We demonstrated here that the
molecular changes and drug sensitivities induced by overexpression of miR-200 family
members in mesenchymal-like ovarian cancer cells are highly variable and correlated
with sequence variation within the seed and non-seed regions of individual family
members. Analysis of the functional and evolutionary significance of sequence variation
within the human miRNA seed regions indicates that as little as a single nucleotide
change within miRNA seed regions dramatically changes the spectrum of mRNAs
regulated by the overexpressed miRNA and that additional seed nucleotide changes have
no significant added effect. These findings help explain the highly conserved nature of
miRNA seed regions within and across species and develop a better understanding of the
evolution of miRNA mediated regulation of target mRNAs. Finally, we provide evidence
for seed region/non-seed interactions in the regulation of miRNA induced changes in
response to cisplatin in ovarian cancer cells. Our results provide a better understanding
of miRNA mediated regulation and their potential as new therapeutic agents.
Advisors/Committee Members: McDonald, John F (advisor), Merrill, Alfred H (advisor), Vannberg, Fredrik (advisor), Fan, Yuhong (advisor), Thomas, Susan N (advisor).
Subjects/Keywords: Ovarian cancer; miRNA
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APA (6th Edition):
Jabbari, N. (2015). Functional significance of sequence variation among miR-200/205 families of miRNAs in ovarian cancer. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55522
Chicago Manual of Style (16th Edition):
Jabbari, Neda. “Functional significance of sequence variation among miR-200/205 families of miRNAs in ovarian cancer.” 2015. Doctoral Dissertation, Georgia Tech. Accessed January 19, 2021.
http://hdl.handle.net/1853/55522.
MLA Handbook (7th Edition):
Jabbari, Neda. “Functional significance of sequence variation among miR-200/205 families of miRNAs in ovarian cancer.” 2015. Web. 19 Jan 2021.
Vancouver:
Jabbari N. Functional significance of sequence variation among miR-200/205 families of miRNAs in ovarian cancer. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2021 Jan 19].
Available from: http://hdl.handle.net/1853/55522.
Council of Science Editors:
Jabbari N. Functional significance of sequence variation among miR-200/205 families of miRNAs in ovarian cancer. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/55522
Georgia Tech
10.
McAndrews, Kathleen M.
Molecular and mechanical regulators of mesenchymal stem cell microenvironments.
Degree: PhD, Chemical and Biomolecular Engineering, 2015, Georgia Tech
URL: http://hdl.handle.net/1853/55535
► Mesenchymal stem cells (MSCs) are multipotent cells that are recruited to sites of inflammation, where they interact with the microenvironment to induce tissue regeneration. As…
(more)
▼ Mesenchymal stem cells (MSCs) are multipotent cells that are recruited to sites of inflammation, where they interact with the microenvironment to induce tissue regeneration. As a result, MSCs have shown promise clinically as candidates for tissue engineering and therapeutic targets; however, implementation in the clinic has been limited by an incomplete understanding of how mechanical and chemical cues provided by the microenvironment influence MSC behavior. We first show how molecular cues change the intracellular mechanical properties of differentiating MSCs. We then developed 3D gelatin scaffolds for the expansion and differentiation of MSCs. We found that the composition of the scaffold dictated whether the mechanical or architectural properties directed MSC differentiation. In addition to aiding in tissue regeneration, MSCs are also recruited to tumors, where they interact with the tumor microenvironment to promote metastasis. We sought to elucidate if MSCs are differentially adherent, and potentially recruited more frequently, to metastatic versus nonmetastatic tumors. We found that MSCs are more adherent to metastatic cancer cells and this response can be reversed by blocking the adhesion molecule cadherin 11. Finally, we utilized a 3D coculture model to determine how interactions between metastatic cancer cells and MSCs influence cancer cell invasion. Coculture with MSCs induced directional migration in cancer cells that was dependent on transforming growth factor β (TGF-β) and downstream mechanosensitive pathways. These studies elucidate how MSCs interact with their environment and may have important implications in biomaterial design and the development of cancer therapeutics.
Advisors/Committee Members: Dawson, Michelle R. (advisor), Meredith, Carson (committee member), McDonald, John F. (committee member), Prausnitz, Mark (committee member), Thomas, Susan N. (committee member).
Subjects/Keywords: Mesenchymal stem cells; Tissue engineering; Mechanotransduction; Biomaterials; Cancer; Cell adhesion; Cell migration
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APA (6th Edition):
McAndrews, K. M. (2015). Molecular and mechanical regulators of mesenchymal stem cell microenvironments. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/55535
Chicago Manual of Style (16th Edition):
McAndrews, Kathleen M. “Molecular and mechanical regulators of mesenchymal stem cell microenvironments.” 2015. Doctoral Dissertation, Georgia Tech. Accessed January 19, 2021.
http://hdl.handle.net/1853/55535.
MLA Handbook (7th Edition):
McAndrews, Kathleen M. “Molecular and mechanical regulators of mesenchymal stem cell microenvironments.” 2015. Web. 19 Jan 2021.
Vancouver:
McAndrews KM. Molecular and mechanical regulators of mesenchymal stem cell microenvironments. [Internet] [Doctoral dissertation]. Georgia Tech; 2015. [cited 2021 Jan 19].
Available from: http://hdl.handle.net/1853/55535.
Council of Science Editors:
McAndrews KM. Molecular and mechanical regulators of mesenchymal stem cell microenvironments. [Doctoral Dissertation]. Georgia Tech; 2015. Available from: http://hdl.handle.net/1853/55535
Georgia Tech
11.
Rishishwar, Lavanya.
Population genomics of human polymorphic transposable elements.
Degree: PhD, Biology, 2016, Georgia Tech
URL: http://hdl.handle.net/1853/56323
► Transposable element (TE) activity has had a major impact on the human genome; more than two-thirds of the sequence is derived from TE insertions. Several…
(more)
▼ Transposable element (TE) activity has had a major impact on the human genome; more than two-thirds of the sequence is derived from TE insertions. Several families of human TEs – primarily Alu, L1 and SVA – continue to actively transpose, thereby generating insertion polymorphisms between individuals. Until very recently, it has not been possible to characterize the genetic variation generated by the activity of these TE families at the scale of whole genomes for multiple individuals within and between human populations. For this reason, the impact of recent TE activity on human evolution has yet to be fully appreciated. My dissertation research leverages novel technologies in data science to investigate the role that recent TE activity has played in shaping human population genetic variation. Specifically, my dissertation addresses three problems: 1) evaluation of the computational techniques used to characterize human polymorphic TE insertion sites from whole genome, next-generation sequence data, 2) characterization of the population genomic variation of human polymorphic TEs and evaluation of their effectiveness as markers of human genetic ancestry and admixture, and 3) analysis of the effects that natural selection (negative and positive) has exerted on human polymorphic TE insertions. I close by presenting a broad prospectus on the implications of genome-scale analyses of human polymorphic TE insertions for population and clinical genetic studies. The results reported in this dissertation represent the dawn of the population genomics era for human TEs.
Advisors/Committee Members: Jordan, I. King (advisor), McDonald, John F. (committee member), Gibson, Greg (committee member), Yi, Soojin (committee member), Mariño-Ramírez, Leonardo (committee member).
Subjects/Keywords: Bioinformatics; Evolution; Natural selection; Human ancestry and admixture
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APA (6th Edition):
Rishishwar, L. (2016). Population genomics of human polymorphic transposable elements. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/56323
Chicago Manual of Style (16th Edition):
Rishishwar, Lavanya. “Population genomics of human polymorphic transposable elements.” 2016. Doctoral Dissertation, Georgia Tech. Accessed January 19, 2021.
http://hdl.handle.net/1853/56323.
MLA Handbook (7th Edition):
Rishishwar, Lavanya. “Population genomics of human polymorphic transposable elements.” 2016. Web. 19 Jan 2021.
Vancouver:
Rishishwar L. Population genomics of human polymorphic transposable elements. [Internet] [Doctoral dissertation]. Georgia Tech; 2016. [cited 2021 Jan 19].
Available from: http://hdl.handle.net/1853/56323.
Council of Science Editors:
Rishishwar L. Population genomics of human polymorphic transposable elements. [Doctoral Dissertation]. Georgia Tech; 2016. Available from: http://hdl.handle.net/1853/56323
Georgia Tech
12.
Wade, James Donald.
Computational modeling and analysis of single-cell signaling dynamics in heterogeneous cell populations.
Degree: PhD, Biomedical Engineering (Joint GT/Emory Department), 2019, Georgia Tech
URL: http://hdl.handle.net/1853/62648
► Cell signaling pathways are complex biochemical systems at the core of cellular information processing. The dynamics of these signaling systems in response to internal and…
(more)
▼ Cell signaling pathways are complex biochemical systems at the core of cellular information processing. The dynamics of these signaling systems in response to internal and extracellular cues plays a critical role for proper cell functioning. While we have learned much about signaling at the cell population level, no two cells are the same, and cell-to-cell variability can have complex and important consequences for signaling in both individual cells and the cell population as a whole. In many contexts, cells perform essentially identical functions despite their differences, whereas in other contexts, especially in cancer, cell-cell differences in state propagate to differences in function. The overall goal of this dissertation was the creation of mathematical and computational tools for the study of cell-to-cell variation in signaling and to use these tools to increase our understanding of when single cell differences do, or do not, make a meaningful difference. To address this goal we designed new methods of single-cell analysis, including a computational framework termed single-cell ordinary differential equation modeling (SCODEM) that overcomes the prior experimental trade-off between continuous and multiplexed single-cell measurements of signaling. We tested SCODEM against increasingly demanding datasets, which were all represented in a satisfactory fashion. After the initial analysis of cell-to-cell variability, we analyzed targeted inhibition, protein overexpression and an epithelial-mesenchymal transition. Throughout this process, we provided illustrative examples of how our modeling framework may be used to identify operating principles and limits of signaling systems, which is a first step toward proposing novel therapeutic targets. The work presented here provides new tools for analyzing cellular heterogeneity and increases our understanding of how differences in cell state effect function by showing intracellular signaling is primarily deterministic at the single cell level. The application of these tools to the dramatic phenotype shift during an epithelial-mesenchymal transition in murine breast cancer cells confirmed that stochasticity plays a much smaller role than had been assumed and that cells modulate signaling without the need of rewiring their signaling network.
Advisors/Committee Members: Voit, Eberhard O. (advisor), Bodenmiller, Bernd (committee member), Boyan, Barbara D. (committee member), Kemp, Melissa L. (committee member), McDonald, John F. (committee member), Qiu, Peng (committee member).
Subjects/Keywords: Computational biology; Computational modeling; Systems biology; Single cell; Mass cytometry; Signaling; Dynamics; Inference; Multiplexed; Multivariate; Snapshot; Trajectory
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APA (6th Edition):
Wade, J. D. (2019). Computational modeling and analysis of single-cell signaling dynamics in heterogeneous cell populations. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/62648
Chicago Manual of Style (16th Edition):
Wade, James Donald. “Computational modeling and analysis of single-cell signaling dynamics in heterogeneous cell populations.” 2019. Doctoral Dissertation, Georgia Tech. Accessed January 19, 2021.
http://hdl.handle.net/1853/62648.
MLA Handbook (7th Edition):
Wade, James Donald. “Computational modeling and analysis of single-cell signaling dynamics in heterogeneous cell populations.” 2019. Web. 19 Jan 2021.
Vancouver:
Wade JD. Computational modeling and analysis of single-cell signaling dynamics in heterogeneous cell populations. [Internet] [Doctoral dissertation]. Georgia Tech; 2019. [cited 2021 Jan 19].
Available from: http://hdl.handle.net/1853/62648.
Council of Science Editors:
Wade JD. Computational modeling and analysis of single-cell signaling dynamics in heterogeneous cell populations. [Doctoral Dissertation]. Georgia Tech; 2019. Available from: http://hdl.handle.net/1853/62648
Georgia Tech
13.
Lili, Loukia.
Computational analyses of gene expression profiles of ovarian and pancreatic cancer.
Degree: PhD, Biology, 2013, Georgia Tech
URL: http://hdl.handle.net/1853/52911
► Cancer is a devastating disease for human society with thousands of deaths and estimated new cases every year around the globe. Intensive research efforts on…
(more)
▼ Cancer is a devastating disease for human society with thousands of deaths and estimated new cases every year around the globe. Intensive research efforts on understanding the disease progression and determining effective diagnostics and therapeutics have been employed for over one hundred years. Throughout this time, and in particular during the last two decades, computational-based methods have gained increasing importance in cancer biology research by providing significant advantages in the analysis and interpretation of high-throughput data at the molecular and genomic levels.
More specifically, after completion of the Human Genome Project in 2003, and with the Cancer Human Genome Project underway, high-throughput biological assays (e.g., microarray chips, next generation sequencing machines) have supplied researchers thousands of measurements per experimental sample. The massive amount of related data has oftentimes been challenging to interpret and translate, particularly in cancer biology and therapeutics. This thesis reports the results of three independent studies in which high-throughput gene expression is computationally analyzed to address longstanding issues in cancer biology. Two of the studies utilize data from ovarian cancer patients while the third involves data collected from pancreatic cancer patients.
In Chapter 1, I address the importance of personalized profiling in pancreatic cancer ; in Chapter 2 the role of cancer stroma in the progression of ovarian cancer and in Chapter 3 evidence for the role of epithelial-to-mesenchymal transition (EMT) in ovarian cancer metastasis.
More specifically, Chapter 1 emphasizes the power of personalized molecular profiling in unmasking unique gene expression signatures that correspond to each individual patient. These individual expression patterns (individual profiling), which may be overlooked by the traditional methods of gene signatures enriched in groups of afflicted individuals (group profiling), can provide valuable information for more successful targeted therapies. In order to address this issue in pancreatic cancer, comparisons of the most significantly differentially expressed genes and functional pathways were performed between cancer and control patient samples as determined by group vs. personalized analyses. There was little to no overlap between genes/pathways identified by group analyses relative to those identified by personalized analyses. These results indicated that personalized and not group molecular profiling is the most appropriate approach for the identification of putative candidates for targeted gene therapy of pancreatic and perhaps other cancers with heterogeneous molecular etiology.
Chapter 2, also with strong implications on personalized molecular profiling, unveils the functional variability of the tumor microenvironment among ovarian cancer patients. The purpose of this study was to investigate the process of microenvironmental stroma activation in human ovarian cancer by molecular analysis of matched sets of…
Advisors/Committee Members: McDonald, John F. (advisor), Jordan, Kin I. (committee member), Daneker, George W. (committee member), Khan, Shafiq A. (committee member), Bowen, Nathan J. (committee member).
Subjects/Keywords: Cancer; Microarray; Gene expression
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APA ·
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APA (6th Edition):
Lili, L. (2013). Computational analyses of gene expression profiles of ovarian and pancreatic cancer. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/52911
Chicago Manual of Style (16th Edition):
Lili, Loukia. “Computational analyses of gene expression profiles of ovarian and pancreatic cancer.” 2013. Doctoral Dissertation, Georgia Tech. Accessed January 19, 2021.
http://hdl.handle.net/1853/52911.
MLA Handbook (7th Edition):
Lili, Loukia. “Computational analyses of gene expression profiles of ovarian and pancreatic cancer.” 2013. Web. 19 Jan 2021.
Vancouver:
Lili L. Computational analyses of gene expression profiles of ovarian and pancreatic cancer. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2021 Jan 19].
Available from: http://hdl.handle.net/1853/52911.
Council of Science Editors:
Lili L. Computational analyses of gene expression profiles of ovarian and pancreatic cancer. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/52911
Georgia Tech
14.
Wang, Lu.
Transposable element polymorphisms and human genome regulation.
Degree: PhD, Biology, 2017, Georgia Tech
URL: http://hdl.handle.net/1853/59266
► Transposable elements (TEs) are DNA sequences that are capable of moving from one genomic location to another. A large proportion of the human genome is…
(more)
▼ Transposable elements (TEs) are DNA sequences that are capable of moving from one genomic location to another. A large proportion of the human genome is derived from TEs, and TE-derived sequences have been shown to contribute to genome regulation in a variety of ways. There are several active families of human TEs, primarily the Alu, LINE-1 (L1), and SVA retrotransposons, which generate structural variations that segregate as polymorphisms within and between human populations. Given the known regulatory properties of human TEs, considered together with the fact that TE insertion activity is a source of population genetic variation, I hypothesized that TE polymorphisms can lead to gene regulatory differences among human individuals with health related phenotypic consequences. I evaluated this hypothesis via a series of genome-wide association screens aimed at assessing: (1) how the human genome regulates TE activity, and (2) how TE activity impacts human genome regulation and health related phenotypes. Expression quantitative trait loci (eQTL) analysis was used to discover a number of novel genetic modifiers of L1 element expression, including genes encoding for transcription factors and chromatin associated proteins. Human TE polymorphisms were shown to participate in population-specific gene regulation, with the potential to coordinately modify transcriptional networks. The regulatory effects of human TE polymorphisms were linked to immune system function, and related diseases, via insertions into cell type-specific enhancers. Results from my novel genome-wide approach to the study of human TE activity underscore the ability of TEs to effect health related phenotypes by virtue of changes to the regulatory landscape of the genome.
Advisors/Committee Members: Jordan, I. King (advisor), McDonald, John F. (committee member), Vannberg, Fredrik O. (committee member), Lunyak, Victoria V. (committee member), Gibson, Greg G. (committee member).
Subjects/Keywords: Transposable elements; Bioinformatics; Alu; L1; SVA; Gene expression; Gene regulation; GWAS; Expression quantitative trait loci; Polymorphism; Genetic variation
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APA ·
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MLA ·
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Export
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APA (6th Edition):
Wang, L. (2017). Transposable element polymorphisms and human genome regulation. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59266
Chicago Manual of Style (16th Edition):
Wang, Lu. “Transposable element polymorphisms and human genome regulation.” 2017. Doctoral Dissertation, Georgia Tech. Accessed January 19, 2021.
http://hdl.handle.net/1853/59266.
MLA Handbook (7th Edition):
Wang, Lu. “Transposable element polymorphisms and human genome regulation.” 2017. Web. 19 Jan 2021.
Vancouver:
Wang L. Transposable element polymorphisms and human genome regulation. [Internet] [Doctoral dissertation]. Georgia Tech; 2017. [cited 2021 Jan 19].
Available from: http://hdl.handle.net/1853/59266.
Council of Science Editors:
Wang L. Transposable element polymorphisms and human genome regulation. [Doctoral Dissertation]. Georgia Tech; 2017. Available from: http://hdl.handle.net/1853/59266
15.
Medrzycki, Magdalena.
The role of H1 linker histone variants in ovarian cancer.
Degree: PhD, Biology, 2013, Georgia Tech
URL: http://hdl.handle.net/1853/53980
► Linker histone H1 associates with nucleosomes, facilitating folding and packaging of DNA into higher order chromatin structure. With 11 variants in mammals, histone H1 is…
(more)
▼ Linker histone H1 associates with nucleosomes, facilitating folding and packaging of DNA into higher order chromatin structure. With 11 variants in mammals, histone H1 is the most divergent histone class. Histone H1 variants are differentially expressed during development and cellular differentiation, and regulate specific gene expression in vivo. Ample studies have established the role of linker histone H1 in chromatin compaction and gene expression regulation; however, its role in diseases, such as cancer, remain understudied.
In this study, we explore the role of H1 in ovarian cancer, one of the most devastating gynecological cancers due to its poor prognosis and difficulty in early diagnosis. Although mutations of genes responsible for cell proliferation, differentiation and survival have been found in ovarian cancers, ample evidence also suggests an important role of epigenetic changes in the disease occurrence and progression. Because epigenetic changes do not alter DNA sequence and can be reversed or reprogrammed, they offer an attractive avenue for therapeutic intervention in cancer treatment.
Using quantitative RT-PCR assays, we systematically examined the expression of 7 H1 genes in 33 human epithelial ovarian tumors. By clustering analysis, we found that ovarian malignant adenocarcinomas and benign adenomas exhibited characteristic expression patterns. We demonstrate that expression profiling of 7 H1 genes in tumor samples discriminates adenocarcinomas vs. adenomas with high accuracy. These findings indicate that the expression of H1 variants is exquisitely regulated and may serve as potential epigenetic biomarkers for ovarian cancer.
To further investigate the role of H1 subtypes in ovarian cancer cells, we employ an over-expression approach to test the function of H1 subtypes in an ovarian cancer cell line OVCAR-3. We found that histone H1.3 over-expression significantly suppresses the growth and colony formation of OVCAR-3 cells. Gene expression arrays identified many genes affected by H1.3 over-expression, and oncogene H19 is among the genes most dramatically repressed by H1.3 over-expression. Over-expression of several other H1 subtypes does not lead to significant reduction of H19 expression, suggesting a specific effect by H1.3. Consistently, knockdown of H1.3 increases H19 expression. Furthermore, increased expression of H1.3 leads to accumulation of H1.3 as well as increased DNA methylation at the regulatory regions of H19. Finally we identified a synergistic effect of H1.3 over-expression and H19 knockdown on inhibition of ovarian cancer cell growth. These results establish oncogene H19 as a direct target of histone H1.3, identify a novel role of H1 variants in ovarian cancer mediated through regulating oncogene H19 expression, and may offer new approaches for ovarian cancer therapeutics.
Advisors/Committee Members: Fan, Yuhong (advisor), Storici, Francesca (committee member), McDonald, John F. (committee member), Sewer, Marion B. (committee member), Kemp, Melissa L. (committee member).
Subjects/Keywords: Histone linker H1; Ovarian cancer
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APA ·
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MLA ·
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Export
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APA (6th Edition):
Medrzycki, M. (2013). The role of H1 linker histone variants in ovarian cancer. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/53980
Chicago Manual of Style (16th Edition):
Medrzycki, Magdalena. “The role of H1 linker histone variants in ovarian cancer.” 2013. Doctoral Dissertation, Georgia Tech. Accessed January 19, 2021.
http://hdl.handle.net/1853/53980.
MLA Handbook (7th Edition):
Medrzycki, Magdalena. “The role of H1 linker histone variants in ovarian cancer.” 2013. Web. 19 Jan 2021.
Vancouver:
Medrzycki M. The role of H1 linker histone variants in ovarian cancer. [Internet] [Doctoral dissertation]. Georgia Tech; 2013. [cited 2021 Jan 19].
Available from: http://hdl.handle.net/1853/53980.
Council of Science Editors:
Medrzycki M. The role of H1 linker histone variants in ovarian cancer. [Doctoral Dissertation]. Georgia Tech; 2013. Available from: http://hdl.handle.net/1853/53980
16.
Ghosh, Deepraj.
Soluble factor mediated manipulation of mesenchymal stem cell mechanics for improved function of cell-based therapeutics.
Degree: PhD, Chemical and Biomolecular Engineering, 2014, Georgia Tech
URL: http://hdl.handle.net/1853/54032
► Mesenchymal stem cells (MSCs) are bone marrow derived multipotent cells with the ability to self-renew and differentiate into multiple connective cell lineages. In vivo, MSCs…
(more)
▼ Mesenchymal stem cells (MSCs) are bone marrow derived multipotent cells with the ability to self-renew and differentiate into multiple connective cell lineages. In vivo, MSCs travel from the bone-marrow to the inflammatory sites and actively participate in remodeling and regeneration process under the influence of soluble growth factors. Due to these inherent properties, MSCs have emerged as an ideal candidate for diverse regenerative therapeutic applications. The development of MSC-based therapies requires in vitro expansion of MSCs; however, MSC expansion results in phenotypical changes that have limited its efficacy upon reintroduction in vivo. In order to increase the efficacy of MSC-based therapeutics, it is critical for us to improve the current understanding of MSC interactions with its niche specific factors and explore new methods to enhance MSC function in vivo.
We used tumor conditioned media, which contains soluble factors secreted by tumor cells in culture (TCM), and inflammatory niche-specific soluble factors, such as platelet derived growth factor (PDGF) and transforming growth factor-β1 (TGF-β1), to characterize the mechanical response of MSCs. The intracellular mechanical properties of MSCs were dramatically altered in response to soluble factors and MSCs displayed cytosolic stiffening in response to TCM and TGF-β1. Although PDGF treated cells did not elicit any mechanical response, blocking PDGF signaling with a small molecule inhibitor reversed the stiffening response in TGF-β1 treated cells, indicating crosstalk between these two pathways is essential in TGF-β1 mediated cell stiffening. Furthermore, a genome-wide microarray analysis revealed TGF-β1 dependent regulation of cytoskeletal actin-binding protein (ABP) genes. Actin crosslinking and bundling protein genes, which regulate cytosolic rheology through changes in semiflexible actin polymer meshworks, were upregulated with TGF-β1 treatment.
Since TGF-β1 treatment profoundly altered the MSC phenotype after relatively short exposure times, we sought to understand if pretreated cells could sustain these enhanced characteristics leading to higher efficacy in vivo. We found that MSCs pretreated with TGF-β1 displayed enhanced adhesive properties while maintaining the expression profile of surface adhesion molecules even after removal of stimulus. Additionally, pretreated MSCs exposed to lineage specific induction media, demonstrated superior differentiation potential along multiple lineages. Based on the large number of sustained changes, TGF-β1 pretreated cells were used to treat full thickness skin wounds for in vivo wound healing model to determine their therapeutic efficacy. TGF-β1 pretreated MSCs increased wound closure rate and displayed enhanced migration of MSCs towards the center of the wound compared to the control cells.
In conclusion, soluble factor pretreated MSCs with altered mechanical properties displayed significantly improved cell functions leading to highly efficient tissue regeneration in vivo. Mechanical priming of MSCs with…
Advisors/Committee Members: Dawson, Michelle (advisor), Lu, Hang (committee member), Taite, Lakeshia (committee member), McDonald, John F. (committee member), Botchwey, Edward A. (committee member).
Subjects/Keywords: Cell mechanics; Wound healing; Mesenchymal stem cells; Transforming growth factor-β1 (TGF-β1); Platelet derived growth factor (PDGF)
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APA ·
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APA (6th Edition):
Ghosh, D. (2014). Soluble factor mediated manipulation of mesenchymal stem cell mechanics for improved function of cell-based therapeutics. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/54032
Chicago Manual of Style (16th Edition):
Ghosh, Deepraj. “Soluble factor mediated manipulation of mesenchymal stem cell mechanics for improved function of cell-based therapeutics.” 2014. Doctoral Dissertation, Georgia Tech. Accessed January 19, 2021.
http://hdl.handle.net/1853/54032.
MLA Handbook (7th Edition):
Ghosh, Deepraj. “Soluble factor mediated manipulation of mesenchymal stem cell mechanics for improved function of cell-based therapeutics.” 2014. Web. 19 Jan 2021.
Vancouver:
Ghosh D. Soluble factor mediated manipulation of mesenchymal stem cell mechanics for improved function of cell-based therapeutics. [Internet] [Doctoral dissertation]. Georgia Tech; 2014. [cited 2021 Jan 19].
Available from: http://hdl.handle.net/1853/54032.
Council of Science Editors:
Ghosh D. Soluble factor mediated manipulation of mesenchymal stem cell mechanics for improved function of cell-based therapeutics. [Doctoral Dissertation]. Georgia Tech; 2014. Available from: http://hdl.handle.net/1853/54032
. 
Open Access Theses and Dissertations
