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The goal of this research was to identify and characterize biologically active small molecule inhibitors for QSOX1. Chemical inhibition of QSOX1 enzymatic activity was hypothesized to reduce growth and invasion of tumor cells. Recombinant QSOX1 was screened against libraries of small molecules using an enzymatic activity assay to identify potential QSOX1 inhibitors. Two lead QSOX1 inhibitors were confirmed, 2-phenyl-1, 2-benzisoselenazol-3-one (ebselen), and 3-methoxy-n-[4-(1 pyrrolidinyl)phenyl]benzamide. The biological activity of these compounds is consistent with QSOX1 knockdown in tumor cell lines, reducing growth and invasion in vitro. Treatment of tumor cells with these compounds also resulted in specific ECM defects, a phenotype associated with QSOX1 knockdown. Additionally, these compounds were shown to be active in pancreatic and renal cancer xenografts, reducing tumor growth with daily treatment. For ebselen, the molecular mechanism of inhibition was determined using a combination of biochemical and mass spectrometric techniques. The results obtained in these studies provide proof-of-principle that targeting QSOX1 enzymatic activity with chemical compounds represents a novel potential therapeutic avenue worthy of further investigation in cancer. Additionally, the utility of these small molecules as chemical probes will yield future insight into the general biology of QSOX1, including the identification of novel substrates of QSOX1.
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I hypothesize that duplication events grant miRNA families with enhanced regulatory capabilities, specifically through distinct targeting preferences by family members. This has relevance for our understanding of vertebrate evolution, as well disease detection and personalized medicine. To test this hypothesis, I apply a conjunction of bioinformatic and experimental approaches, and design a novel high-throughput screening platform to identify human miRNA targets. Combined with conventional approaches, this tool allows systematic testing for functional targets of human miRNAs, and the identification of novel target genes on an unprecedented scale.
In this dissertation, I explore evolutionary signatures of 62 deeply conserved metazoan miRNA families, as well as the targeting preferences for several human miRNAs. I find that constraints on miRNA processing impact sequence evolution, creating evolutionary hotspots within families that guide distinct target preferences. I apply our novel screening platform to two cancer-relevant miRNAs, and identify hundreds of previously undescribed targets. I also analyze critical features of functional miRNA target sites, finding that each miRNA recognizes surprisingly distinct features of targets. To further explore the functional distinction between family members, I analyze miRNA expression patterns in multiple contexts, including mouse embryogenesis, RNA-seq data from human tissues, and cancer cell lines. Together, my results inform a model that describes the evolution of metazoan miRNAs, and suggests that highly similar miRNA family members possess distinct functions. These findings broaden our understanding of miRNA function in vertebrate evolution and development, and how their misexpression contributes to human disease.
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The conservation of the dystrophin gene across metazoans suggests that both vertebrate and invertebrate model systems can provide valuable contributions to the understanding of DMD initiation and progression. Specifically, the invertebrate C. elegans possesses a dystrophin protein ortholog, dys-1, and a mild inflammatory response that is inactive in the muscle, allowing for the characterization of transcriptome rearrangements affecting disease progression independently of inflammation. Furthermore, C. elegans do not possess a satellite cell equivalent, meaning muscle regeneration does not occur. This makes C. elegans unique in that they allow for the study of dystrophin deficiencies without muscle regeneration that may obscure detection of subtle but consequential changes in gene expression.
I hypothesize that gaining a comprehensive definition of both the structural and signaling roles of dystrophin in C. elegans will improve the community’s understanding of the progression of DMD as a whole. To address this hypothesis, I have performed a phylogenetic analysis on the conservation of each member of the dystrophin associated protein complex (DAPC) across 10 species, established an in vivo system to identify muscle-specific changes in gene expression in the dystrophin-deficient C. elegans, and performed a functional analysis to test the biological significance of changes in gene expression identified in my sequencing results. The results from this study indicate that in C. elegans, dystrophin may have a signaling role early in development, and its absence may activate compensatory mechanisms that counteract disease progression. Furthermore, these findings allow for the identification of transcriptome changes that potentially serve as both independent drivers of disease and potential therapeutic targets for the treatment of DMD.
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Human protein diversity arises as a result of alternative splicing, single nucleotide polymorphisms (SNPs) and posttranslational modifications. Because of these processes, each protein can exists as multiple variants in vivo. Tailored strategies are needed to study these protein variants and understand their role in health and disease. In this work we utilized quantitative mass spectrometric immunoassays to determine the protein variants concentration of beta-2-microglobulin, cystatin C, retinol binding protein, and transthyretin, in a population of 500 healthy individuals. Additionally, we determined the longitudinal concentration changes for the protein variants from four individuals over a 6 month period. Along with the native forms of the four proteins, 13 posttranslationally modified variants and 7 SNP-derived variants were detected and their concentration determined. Correlations of the variants concentration with geographical origin, gender, and age of the individuals were also examined. This work represents an important step toward building a catalog of protein variants concentrations and examining their longitudinal changes.
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MicroRNAs (miRNAs) are short non-coding RNAs that regulate gene output at the post-transcriptional level by targeting degenerate elements primarily in 3′untranslated regions (3′UTRs) of mRNAs. Individual miRNAs can regulate networks of hundreds of genes, yet for the majority of miRNAs few, if any, targets are known. Misexpression of miRNAs is also a major contributor to cancer progression, thus there is a critical need to validate miRNA targets in high-throughput to understand miRNAs' contribution to tumorigenesis. Here we introduce a novel high-throughput assay to detect miRNA targets in 3′UTRs, called Luminescent Identification of Functional Elements in 3′UTRs (3′LIFE). We demonstrate the feasibility of 3′LIFE using a data set of 275 human 3′UTRs and two cancer-relevant miRNAs, let-7c and miR-10b, and compare our results to alternative methods to detect miRNA targets throughout the genome. We identify a large number of novel gene targets for these miRNAs, with only 32% of hits being bioinformatically predicted and 27% directed by non-canonical interactions. Functional analysis of target genes reveals consistent roles for each miRNA as either a tumor suppressor (let-7c) or oncogenic miRNA (miR-10b), and preferentially target multiple genes within regulatory networks, suggesting 3′LIFE is a rapid and sensitive method to detect miRNA targets in high-throughput.
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Background: Healthy individuals on the lower end of the insulin sensitivity spectrum also have a reduced gene expression response to exercise for specific genes. The goal of this study was to determine the relationship between insulin sensitivity and exercise-induced gene expression in an unbiased, global manner.
Methods and Findings: Euglycemic clamps were used to measure insulin sensitivity and muscle biopsies were done at rest and 30 minutes after a single acute exercise bout in 14 healthy participants. Changes in mRNA expression were assessed using microarrays, and miRNA analysis was performed in a subset of 6 of the participants using sequencing techniques. Following exercise, 215 mRNAs were changed at the probe level (Bonferroni-corrected P<0.00000115). Pathway and Gene Ontology analysis showed enrichment in MAP kinase signaling, transcriptional regulation and DNA binding. Changes in several transcription factor mRNAs were correlated with insulin sensitivity, including MYC, r=0.71; SNF1LK, r=0.69; and ATF3, r= 0.61 (5 corrected for false discovery rate). Enrichment in the 5’-UTRs of exercise-responsive genes suggested regulation by common transcription factors, especially EGR1. miRNA species of interest that changed after exercise included miR-378, which is located in an intron of the PPARGC1B gene.
Conclusions: These results indicate that transcription factor gene expression responses to exercise depend highly on insulin sensitivity in healthy people. The overall pattern suggests a coordinated cycle by which exercise and insulin sensitivity regulate gene expression in muscle.