Organizational Unit:
School of Biological Sciences

Permanent Link
https://hdl.handle.net/1853/70750
Research Organization Registry ID
Description
Previous Names
Parent Organization
Parent Organization
Organizational Unit
Includes Organization(s)
ArchiveSpace Name Record
https://finding-aids.library.gatech.edu/agents/corporate_entities/1131

Filters

10 1
8 1 1
10
Reset filters

Settings
search.filters.applied.f.advisor: McDonald, John F. × Item Type: Publication × search.filters.applied.f.isOrgUnitOfPublicationTitle: College of Sciences ×

Publication Search Results

Now showing 1 - 10 of 10
Thumbnail Image
Item

A holistic approach to improving ovarian cancer care

2023-07-17 , Ban, Dongjo

Ovarian cancer (OC), often referred to as the "silent killer" due to its elusive early-stage symptoms and frequent late diagnoses, remains a significant public health challenge. The primary objective of this research is to navigate the intricate landscape of OC at the genomic and metabolomic levels using high-throughput technologies. This exploration strives to uncover potential strategies for early detection and treatment improvement, thereby addressing this persistent health concern. In the initial phase of the study, the genomic complexity of OC is unraveled through an analysis of the tumor mutation burden (TMB) and patterns of copy-number alterations (CNAs). The investigation reveals a higher TMB in localized tumors and cancer-related genes compared to non-cancer genes. We observed that impaired DNA-repair mechanisms play a pivotal role in elevating TMB levels. A notable finding is the differential selective pressure patterns, represented by dN/dS ratio estimates, between early- and late-stage OC. Further, the impact of CNAs on OC patients was analyzed, showing a prevalence of amplification events over deletion ones and a higher number of affected genes in the early-stage group. Although CNAs were not found to be higher in cancer-associated genes, the study identifies a preference for amplification in oncogenes and deletion in tumor suppressor genes upon investigating driver regions. The latter phase of the research emphasizes the role of metabolomics in detecting early-stage OC. Machine learning (ML) approaches were employed to examine high-throughput serum metabolomic profiles from OC patients and non-cancerous individuals from various geographical locations. The resulting classifiers exhibited promising predictive potential, thus emphasizing the utility of metabolomics for early OC detection. Particularly, the emergence of lipid or lipid-like molecules as potential markers underscores their significance in OC detection. Collectively, these findings accentuate the potential of an integrated approach in developing personalized cancer management strategies, taking into account the unique variations observed in patients. This paves the way for clinically identifying high-risk individuals for more frequent monitoring and tailoring appropriate treatment options for optimal patient outcomes. Given the growing volume of data and the continuous advancements in technology, such comprehensive approaches can augment survival rates and ameliorate the quality of life for OC patients.

View
Thumbnail Image
Item

Global dysregulation of gene expression and tumorigenesis: Data science for cancer

2019-09-03 , Clayton, Evan

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 will respond to individual therapies with up to 86% accuracy. The genes that I found to be most informative for predicting drug response were enriched in well-known cancer signaling pathways highlighting their potential significance in prognosis of chemotherapy.

View
Thumbnail Image
Item

Computational analyses of gene expression profiles of ovarian and pancreatic cancer

2013-07-16 , Lili, Loukia

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 cancer and surrounding stroma tissues from individual patients. Expression patterns of genes encoding signaling molecules and compatible receptors in the cancer stroma and cancer epithelia samples indicated the existence of two sub-groups of cancer stroma with different propensities to support tumor growth. These results demonstrated that functionally significant variability exists among ovarian cancer patients in the ability of the microenvironment to modulate cancer development. Chapter 3 aims to uncover the molecular mechanisms that underlie the metastatic process with the hope that such knowledge may lead to more effective therapeutic treatments. For this purpose, pathological and molecular analyses were conducted in 14 matched sets of primary and metastatic samples from late staged ovarian cancer patients. Pathological examination revealed no morphological differences between any of the primary and metastatic samples. In contrast, gene expression analyses identified two distinct groups of patient samples. One group displayed essentially identical expression patterns to primary samples isolated from the same patients. The second group displayed expression patterns significantly different from primary samples isolated from the same patients. Predominant among the differentially expressed genes characterizing this second class of metastatic samples were genes previously associated with epithelial-to-mesenchymal transtion (EMT). These results supported a role of EMT in at least some ovarian cancer metastases and demonstrated that indistinguishable morphologies between primary and metastatic cancer samples is not sufficient evidence to negate the role of EMT in the metastatic process.

View
Thumbnail Image
Item

Comparative and functional genomic analysis of human and chimpanzee retrotransposon sequences

2007-06-25 , Polavarapu, Nalini

Transposable elements (TEs) are mobile DNA sequences that can move from one location to another in the genome. These elements encode regulatory features including transcriptional promotion and termination signals facilitating the production of new transcripts (or elements). The elements thus produced are inserted back into the genome. Due to their insertional capacity and encoded regulatory features, TEs have, in recent years, been recognized as significant contributors to regulatory variation both within and between species. In comparing the human and chimpanzee genomes it has been hypothesized that the genetic basis of the phenotypic differences that distinguish them may be the result of regulatory differences existing between the two species. Since TEs inserted in proximity to genes can significantly alter gene expression patterns, this research aims at exploring the influence of TE sequences and retrotransposons in particular in the evolution of gene regulation between humans and chimpanzees. A first systematic search of one particular class of retrotransposons - endogenous retroviruses (ERVs) was carried out in the chimpanzee genome. Forty two families of ERVs were identified in the chimpanzee genome including the discovery of 9 previously unknown families in humans. The vast majority of these families were found to have orthologs in the human genome except for two (CERV 1/PTERV1 and CERV 2) families. The two CERV families without orthologs in the human genome display a patchy distribution among primates. Nine families of chimpanzee ERVs have been transpositionally active since the human-chimpanzee divergence, while only two families have been active in the human lineage. The genomic differences [INDEL variation (80-12,000 bp in length)] between humans and chimpanzees are laid out. The INDEL variation located in or near genes is categorized in detail and is correlated with differences in gene expression patterns in a variety of organs and tissues. Results indicate that the majority of the INDEL variation between the two species is associated with retrotransposon sequences and that this variation is significantly correlated with differences in gene expression most notably in brain and testes. These findings are consistent with the hypothesis that retrotransposon mediated regulatory variation may have been a significant factor in human/chimpanzee evolution.

View
Thumbnail Image
Item

Differential Gene Co-Expression Network Characteristics Of Cancer

2022-12-13 , Arshad, Zainab

The transformation from a healthy state to a disease state in cancer is dictated in large part by structural and regulatory abnormalities in genes. While the molecular features underlying this transition have been investigated for some time, allowing groundbreaking advancements in cancer research, a majority of these efforts are focused on mutational and expression changes of individual genes. The recent advancement of network-based analytic methods affords an additional route through which disease pathophysiology and biologic regulation can be investigated. Furthermore, with the development of high-throughput technologies and the availability of large biobanks, gene interaction changes, and their functional consequences can be reliably interpreted from a systemic perspective, in a context specific manner. Towards this end, my research investigates gene co-expression changes, derived from transcriptomic case-control data, that underlie cancer onset and progression relative to healthy tissue. For the first study, global network changes associated with cancers of nine different tissues of origin were investigated. Network complexity generally dropped in the transition from normal precursor tissues to corresponding primary tumors, whereas cross-tissue cancer network similarity overall increased in early-stage cancers followed by a subsequent loss in similarity as tumors reacquire cancer-specific network complexity in late-stage cancers. In addition, gene-gene connections remaining stable through cancer development were found enriched for ‘‘housekeeping’’ gene functions, whereas newly acquired interactions were associated with established cancer-promoting functions. For the second study, gene-network characteristics of the molecular subtypes (Luminal A, Luminal B and Basal) of Breast Cancer (BC) were outlined based on a comparative analysis relative to precursor normal breast tissue. Basal was identified as the most highly connected yet dissimilar subtype to normal control. We discovered eight extensively connected network modules acquired in Basal BCs that harbored 19 genes found significantly associated with survival and encoding cancer hallmark functions including regulation of cell proliferation and motility, as well as neural pathways that have not been previously associated with basal BCs. Finally, the consensus approach of network construction for an unbiased differential analysis of gene co-expression networks used in these studies was published as a step-by-step protocol. Altogether, this thesis highlights gene-network changes characteristic of individual cancer types, molecular subtypes and disease stages that informs their diverse progression patterns and clinical outcomes. Furthermore, it underscores the importance and demonstrates the utility of gene co-expression networks in identifying key genes, gene interactions and functional characteristics of cancers that maybe undiscovered by standard molecular analysis approaches.

View
Thumbnail Image
Item

Analysis of metastatic-repressing microRNAs and determining ZEB1 as a gene candidate for siRNA knockout in mesenchymal-like ovarian and prostate cancer cell lines

2018-05 , Akbar, Amber A.

MicroRNAs (miRNAs) have been shown to play a significant role in cancer progression and metastasis through their regulation of gene expression to activate epithelial-mesenchymal transition (EMT). Understanding the genetic and molecular basis for how microRNAs induce EMT’s reciprocal mechanism, mesenchymal-epithelial transition (MET), is vital as metastatic disease is highly lethal. This study aims to identify genes involved in MET across two cancer types based on microRNA overexpressions that have previously been shown to induce MET in mesenchymal-like ovarian or prostate cancer cell lines. It also aims to understand how the same microRNAs behave in similar mesenchymal cell-lines. To elucidate the ability of different microRNAs to induce the same process of MET in two reproductive cancer cell lines, transfections to overexpress miR-429, miR-203a, and miR-205 in both ovarian cancer and prostate cancer cell lines, HEY and PC3, respectively, were performed. Using microarray analysis, differentially expressed genes were identified and comparisons of these genes to known EMT/MET genes was done to narrow down a set of genes important in both ovarian and prostate cancer MET processes. We show that miR-429 induces MET in both HEY and PC3 cells, but not through similar pathways, and that overexpression of miR-203a and miR-205 induced MET in either HEY or PC3, but not both. ZEB1 was identified as a gene candidate for siRNA knockout to recapitulate MET and further elucidate mechanisms of the three microRNAs inducing MET.

View
Thumbnail Image
Item

Comparative analysis of apoptotic function between humans, chimpanzees and macaques

2011-07-07 , Arora, Gaurav S.

Humans and chimpanzees differ in a number of phenotypic traits chief among them being a larger sized human brain and an increased propensity for cancer in humans. Apoptosis or programmed cell death plays a role during brain development and disease progression to cancer. Results from my study, based on gene expression analysis, suggest that the apoptotic function may be generally reduced in humans relative to chimpanzees. In this thesis, I test the hypothesis that the apoptotic function is generally reduced in humans relative to chimpanzees by gene expression and experimental data. The experimental data are consistent with the hypothesis and also suggest that the apoptotic function may be reduced in humans relative to chimpanzees and macaques, suggesting that the reduced apoptotic function may be an evolutionary derived condition within the human lineage. I also evaluate the role of this reduced function in humans during brain development and disease progression to cancer. In addition, I also correlate Insertion/Deletion sequence variation between humans and chimpanzees with differences in gene expression between the two species.

View
Thumbnail Image
Item

Analysis of the impact of a p53 mutation in a homogeneous genetic background

2020-04-21 , Karunakaran, Kirti A.

In more than 50% of cancers, p53, a tumor suppressor gene involved cell cycle arrest and apoptosis, has been seen to be heavily mutated making it an important gene to study. There are several studies on p53 and its role in cancer, but they ignore the impact of genetic background. Past studies have shown that genetic background can have a significant effect on the phenotypic consequences of cancer driver mutations, however, all these studies are carried out in a heterogeneous environment. The goal of my study was to utilize the CRISPR Cas 9 system to create a loss of function mutation in the p53 gene in a well characterized human cell line (HEYA8F8) and to evaluate the impact of this mutation on cell growth and apoptotic function in identical genetic backgrounds. The resulting mutation was a deletion in codons 33-36 of exon 4 which decreased the length of the protein from 393 to 389 amino acids. Using the cell lines with the specified deletion, growth rates over 96 hours were compared, which resulted in higher cell counts for the mutant in comparison to the wildtype. Assay for drug sensitivity using cisplatin, the standard of care for many cancers, showed that mutant cell lines had decreased apoptotic function (higher cell viability) in comparison to the wild type. The overall results demonstrated that mutations in p53 increase cell viability when treated with chemotherapy and an increase in cell proliferation. We believe that the cell lines with the loss of function mutations in p53 generated will provide an ideal experimental set up to study how the genetic background can evolve to enhance cancer in future studies.

View
Thumbnail Image
Item

Studies in microrna function and gene dysregulation in ovarian cancer

2014-11-18 , Hill, Christopher G.

Ovarian cancer results from the dysregulation, in normal ovarian epithelial cells, of genes responsible for the control of critical biological processes. Since their discovery 20 years ago, microRNAs have increasingly been implicated in that dysregulation due to their role mediating gene expression; changes in microRNA expression levels in cancer have been linked with tumor growth, proliferation and metastasis. Their imputed involvement in cancer has led to the possibility of their use as biomarkers and to their potential clinical use. Using mRNA and microRNA microarray analysis to compare human gene expression in normal ovarian surface epithelial (OSE) cells and epithelial ovarian cancer (EOC) cells, we explored the interactions between microRNAs and genes. First, we validated in silico predictions of microRNA targets by comparing them with in vitro evidence after exogenous microRNA transfection. We found that pairs of microRNAs with identical 7-nt (nucleotide) seed regions shared 88% of their predicted targets and 55% of their in vitro targets, confirming the importance of the seed as a targeting mechanism. But more importantly, we found that even a single nucleotide change in the seed region can result in a significant shift in the set of targeted genes, implying strong functional conservation of the seeds and their corresponding binding sites. Next, we discovered a 3-element network motif which explains the upregulation of nearly 800 genes in ovarian cancer which, as predicted microRNA targets, might be expected to be down- regulated. This model shows that, under certain circumstances, repressor genes which are down- regulated in cancer can apparently override the repressive effects of microRNAs, resulting in the upregulation of predicted microRNA targets. Finally, we developed a phenomenological network model, based on the Pearson correlation of microarray gene expression data, to identify subnetworks dysregulated in cell cycle and apoptosis. While our methodology reported many genes previously associated with ovarian cancer, it significantly suggested potentially oncogenic genes for further investigation. This network model can easily be extended to identify dysregulated genes in other cancers.

View
Thumbnail Image
Item

Microrna and messenger rna interactions in ovarian cancer

2011-05-19 , Shahab, Shubin

Regulation of gene expression is a complex process in mammalian cells with many levels of control. In recent years non-coding RNAs in the form of microRNAs (miRNA) have surfaced as important regulators of protein coding genes, with biologically important roles in development, differentiation and cell growth. In this dissertation the complex interactions between miRNAs and mRNAs in ovarian cancer are investigated using a combination of computational and experimental techniques. In vitro studies and current models predict that increases in levels of miRNA should result in corresponding decreases in the levels of targeted mRNAs due to miRNA induced degradation. Profiling the global miRNA and mRNA expression patterns in epithelial ovarian cancer cells from patients and surface epithelial cells from normal ovaries reveal only ~11% of predicted targets of miRNAs are inversely correlated in vivo. In an effort to dissect the mechanisms behind these unexpected observations single miRNA transfection experiments are carried out followed by gene expression profiling. Analysis of genes altered following these transfections reveal majority of the altered genes are not direct targets of the miRNAs. Network analysis however suggests that miRNAs may target "hub genes" to cause altered expression in downstream transcripts. Pathway enrichment analysis of altered genes demonstrates miRNAs may regulate specific pathways rather than causing random off-target effects. Finally investigation of miRNA regulation reveals miRNAs may also affect the levels of other miRNAs, which may indirectly affect more genes downstream. Together these results provide a detailed view of the mechanisms employed by miRNAs to regulate the expression of hundreds of genes in ovarian cancer cells.

View