From protein microarray to biology: The discovery of epigenetic regulatory molecules

Chromatin, composed of repeating nucleosome units, is the genetic polymer of life. To aid in DNA compaction and organized storage, the double helix wraps around a core complex of histone proteins to form the nucleosome, and is therefore no longer freely accessible to cellular proteins for the processes of transcription, replication and DNA repair. Over the course of evolution, DNA-based applications have developed routes to access DNA bound up in chromatin, and further, have actually utilized the chromatin structure to create another level of complexity and information storage. The histone molecules that DNA surrounds have free-floating tails that extend out of the nucleosome. These tails are post-translationally modified to create docking sites for the proteins involved in transcription, replication and repair, thus providing one prominent way that specific genomic sequences are accessed and manipulated. Adding another degree of information storage, histone tail-modifications paint the genome in precise manners to influence a state of transcriptional activity or repression, to generate euchromatin, containing gene-dense regions, or heterochromatin, containing repeat sequences and low-density gene regions. The work presented here is the study of histone tail modifications, how they are written and how they are read, divided into two projects. Both begin with protein microarray experiments where we discover the protein domains that can bind modified histone tails, and how multiple tail modifications can influence this binding. Project one then looks deeper into the enzymes that lay down the tail modifications. Specifically, we studied histone-tail arginine methylation by PRMT6. We found that methylation of a specific histone residue by PRMT6, arginine 2 of H3, can antagonize the binding of protein domains to the H3 tail and therefore affect transcription of genes regulated by the H3-tail binding proteins. Project two focuses on a protein we identified to bind modified histone tails, PHF20, and was an endeavor to discover the biological role of this protein. Thus, in total, we are looking at a complete process: (1) histone tail modification by an enzyme (here, PRMT6), (2) how this and other modifications are bound by conserved protein domains, and (3) by using PHF20 as an example, the functional outcome of binding through investigating the biological role of a chromatin reader. ^

Collagen I modulates growth and gene expression in prostate cancer cells

Prostate cancer is the second leading cause of male cancer-related deaths in the United States. Interestingly, prostate cancer preferentially metastasizes to skeletal tissue. Once in the bone microenvironment, advanced prostate cancer becomes highly resistant to therapeutic modalities. Several factors, such as extracellular matrix (ECM) components, have been implicated in the spread and propagation of prostatic carcinoma. In these studies, we have utilized the PC3 cell line, derived from a human bone metastasis, to investigate the influence of the predominant bone ECM protein, type I collagen, on prostate cancer cell proliferation and gene expression. We have also initiated the design and production of ribozymes to specific gene targets that may influence prostate cancer bone metastasis. ^ Our results demonstrate that PC3 cells rapidly adhere and spread on collagen I to a greater degree than on fibronectin (FN) or poly-L-lysine (PLL). Flow cytometry analysis reveals the presence of the α1, α2 and α3 collagen binding integrin subunits. The use of antibody function blocking studies reveals that PC3 cells can utilize α2β 1 and α3β1 integrins to adhere to collagen I. Once plated on collagen I, the cells exhibit increased rates of proliferation compared with cells plated on FN or tissue culture plastic. Additionally, cells plated on collagen I show increased expression of proteins associated with progression through G1 phase of the cell cycle. Inhibitor studies point to a role for phosphatidylinositol 3-kinase (PI3K), MAP kinase (MAPK), and p70 S6 kinase in collagen I-mediated PC3 cell proliferation and cyclin D1 expression. To further characterize the effect of type I collagen on prostate cancer bone metastasis, we utilized a cDNA microarray strategy to monitor type I collagen-mediated changes in gene expression. Results of this analysis revealed a gene expression profile reflecting the increased proliferation occurring on type I collagen. Microarray analysis also revealed differences in the expression of specific gene targets that may impact on prostate cancer metastasis to bone. ^ As a result of our studies on the interaction of prostate cancer cells and the skeletal ECM, we sought to develop novel molecular tools for future gene therapy of functional knockdown experiments. To this end, we developed a series of ribozymes directed against the α2 integrin and at osteopontin, a protein implicated in the metastasis of various cancers, including prostate. These ribozymes should facilitate the future study of the mechanism of prostate cancer cell proliferation, and disease progression occurring at sites of skeletal metastasis where a type I collagen-based environment predominates. ^ Together these studies demonstrate the involvement of bone ECM proteins on prostate cancer cell proliferation and suggest that they may play a significant role on the growth of prostate metastases once in the bone microenvironment. ^

Loss of activator protein-2alpha results in overexpression of the thrombin receptor and correlates with the malignant phenotype of human melanoma

Increasing evidence demonstrates that the thrombin receptor (protease activated receptor-1, PAR-1) plays a major role in tumor invasion and contributes to the metastatic phenotype of human melanoma. We demonstrate that the metastatic potential of human melanoma cells correlates with overexpression of PAR-1. The promoter of the PAR-1 gene contains multiple putative AP-2 and Sp1 consensus elements. We provide evidence that an inverse correlation exists between the expression of AP-2 and the expression of PAR-1 in human melanoma cells. Re-expression of AP-2 in WM266-4 melanoma cells (AP-2 negative) resulted in decreased mRNA and protein expression of PAR-1 and significantly reduced the tumor potential in nude mice. ChIP analysis of the PAR-1 promoter regions bp −365 to −329 (complex 1) and bp −206 to −180 (complex 2) demonstrates that in metastatic cells Sp1 is predominantly binding to the PAR-1 promoter, while in nonmetastatic cells AP-2 is bound. In vitro analysis of complex 1 demonstrates that AP-2 and Sp1 bind to this region in a mutually exclusive manner. Transfection experiments with full-length and progressive deletions of the PAR-1 promoter luciferase constructs demonstrated that metastatic cells had increased promoter activity compared to low and nonmetastatic melanoma cells. Our data shows that exogenous AP-2 expression decreased promoter activity, while transient expression of Sp1 further activated expression of the reporter gene. Mutational analysis of complex 1 within PAR-1 luciferase constructs further demonstrates that the regulation of PAR-1 is mediated through interactions with AP-2 and Sp1. Moreover, loss of AP-2 in metastatic cells alters the AP-2 to Sp1 ratio and DNA-binding activity resulting in overexpression of PAR-1. In addition, we evaluated the expression of AP-2 and PAR-1 utilizing a tissue microarray of 93 melanocytic lesions spanning from benign nevi to melanoma metastasis. We report loss of AP-2 expression in malignant tumors compared to benign tissue while PAR-1 was expressed more often in metastatic melanoma cells than in benign melanocytes. We propose that loss of AP-2 results in increased expression of PAR-1, which in turn results in upregulation of gene products that contribute to the metastatic phenotype of melanoma. ^

Application of stellar photometry to the analysis of microarray images

Improvements in the analysis of microarray images are critical for accurately quantifying gene expression levels. The acquisition of accurate spot intensities directly influences the results and interpretation of statistical analyses. This dissertation discusses the implementation of a novel approach to the analysis of cDNA microarray images. We use a stellar photometric model, the Moffat function, to quantify microarray spots from nylon microarray images. The inherent flexibility of the Moffat shape model makes it ideal for quantifying microarray spots. We apply our novel approach to a Wilms' tumor microarray study and compare our results with a fixed-circle segmentation approach for spot quantification. Our results suggest that different spot feature extraction methods can have an impact on the ability of statistical methods to identify differentially expressed genes. We also used the Moffat function to simulate a series of microarray images under various experimental conditions. These simulations were used to validate the performance of various statistical methods for identifying differentially expressed genes. Our simulation results indicate that tests taking into account the dependency between mean spot intensity and variance estimation, such as the smoothened t-test, can better identify differentially expressed genes, especially when the number of replicates and mean fold change are low. The analysis of the simulations also showed that overall, a rank sum test (Mann-Whitney) performed well at identifying differentially expressed genes. Previous work has suggested the strengths of nonparametric approaches for identifying differentially expressed genes. We also show that multivariate approaches, such as hierarchical and k-means cluster analysis along with principal components analysis, are only effective at classifying samples when replicate numbers and mean fold change are high. Finally, we show how our stellar shape model approach can be extended to the analysis of 2D-gel images by adapting the Moffat function to take into account the elliptical nature of spots in such images. Our results indicate that stellar shape models offer a previously unexplored approach for the quantification of 2D-gel spots. ^

The roles of UPF3a and UPF3b in nonsense mediated decay

Nonsense-mediated decay (NMD) degrades aberrant transcripts containing premature termination codons (PTCs). The T-cell receptor (TCR) locus undergoes error-prone rearrangements that frequently acquire PTCs. Transcripts harboring PTCs from this locus are downregulated much more than transcripts from non-rearranging genes. Efficient splicing is essential for this robust downregulation. ^ Here I show that TCR NMD is unique in another respect: it is not impaired by RNAi-mediated depletion of the NMD factor UPF3b. This differentiates TCR transcripts from classical NMD (assayed using β-globin or triose phosphate isomerase transcripts), which does depend on UPF3b. Depletion of UPF3a, which encodes a gene related to UPF3b, also had no effect on TCR NMD. Mapping experiments identified TCR sequences that when deleted or mutated caused a switch to UPF3b dependence. Since UPF3b dependence was invariably accompanied by less efficient RNA splicing, this suggests that UPF3b-dependent NMD occurs when transcripts are generated by inefficient splicing. Microarray analysis revealed the existence of many NMD-targeted mRNAs from wild-type genes whose downregulation is impervious to UPF3b depletion. This suggests the existence of an alternative NMD pathway independent of UPF3b that is widely used to downregulate the level of both normal and mutant transcripts. ^ During the course of my studies, I also found that the function of UPF3a is fundamentally distinct from that of UPF3b in several aspects. First, classical NMD failed to be impaired by UPF3a depletion, whereas it was reversed by UPF3b depletion. Second, UPF3a depletion had no effect on NMD elicited by tethered UPF2, whereas UPF3b depletion blocked this response. Thus, UPF3a does not function in classical NMD. Third, UPF3b depletion upregulated the expression of UPF3a, whereas UPF3a depletion had no effect on UPF3b expression. This suggests that a UPF3b-mediated feedback network exists that regulates the UPF3a expression. Lastly, UPF3a depletion but not UPF3b depletion significantly upregulated TCR precursor RNAs. This suggests that UPF3a, not UPF3b, functions in the surveillance of precursor RNAs, which typically contain many PTCs in the introns. Collectively, my data suggests that UPF3a and UPF3b are not functionally redundant, as previously thought, but instead have separable functions. ^

The role of coactivator associated arginine methyltransferase 1 (CARM1) in nuclear receptor mediated transcription

Arginine methylation has been implicated in the regulation of gene expression. The coactivator-associated arginine methyltransferase 1 (CARMI/PRMT4) binds the p160 family of steroid receptor coactivators (SRCs). This association enhances transcriptional activation by nuclear receptors. Here, we generated and characterized CARM1 knockout mice. Embryos with a targeted disruption of CARM1 are 35% smaller in size than the wild-type littermates and die perinatally. We also generated Carm1-/- and Carm1+/+ mouse embryonic fibroblasts and tested gene expression in response to estrogen. Estrogenresponsive gene expression was aberrant in Carm1-/- fibroblasts and embryos, thus emphasizing the role of arginine methylation as a transcription activation tag. We subsequently studied the role of CARM1 in estrogen signaling in viva in the mammary gland. Conditional knockout of CARM1 in mammary gland and Carml-1-embryonic mammary anlagen transplant experiments did not show any defects in growth and development of the glands. To further dissect the role of CARM1 in estrogen receptor mediated transactivation, we performed cDNA microarray and serial analysis of gene expression on Carm1-/- and Carm1+/+ embryos treated with the estrogen analog, DES. Our results indicate global changes in estrogen regulated genes as well as genes involved in lipid homeostasis. Marker genes for Peroxisome Proliferator Activated Receptor γ (PPARγ) activity, adipsin and aP2, are downregulated in the Carm1-/- embryos. Furthermore, OCT frozen sections of 18.5dpc embryos, processed simultaneously for oil red O staining to look for neutral fat, reveals greatly reduced brown fat accumulation in the Carm1-/- embryos in contrast to wild-type and gain-of-function Carm1 transgenic (ubiquitous) embryo. We used a well-established 3T3-L1 preadipocyte cell line to knockdown CARM1 by short hairpin RNA. 3T3-L1 cells with CARM1 knockdown showed greatly reduced potential to differentiate into mature lipid accumulating adipocytes upon administration of adipogenic stimuli. Ligand-dependent activation of reporter genes by the PPARγ receptor showed that PPRE-luciferase reporter activity was enhanced in the presence of CARM1, additionally, luciferase activity was reduced to background levels when enzyme dead CARM1 (CARM1-VLD) was used. Thus, in this study, we have identified novel pathways that use CARM1 as coactivator and showed that CARM1 functions as a key component of PPARγ receptor mediated gene expression. ^

High-resolution microarray analysis of chromosome 20q in human colon cancer metastasis model systems

Amplification of human chromosome 20q DNA is the most frequently occurring chromosomal abnormality detected in sporadic colorectal carcinomas and shows significant correlation with liver metastases. Through comprehensive high-resolution microarray comparative genomic hybridization and microarray gene expression profiling, we have characterized chromosome 20q amplicon genes associated with human colorectal cancer metastasis in two in vitro metastasis model systems. The results revealed increasing complexity of the 20q genomic profile from the primary tumor-derived cell lines to the lymph node and liver metastasis derived cell lines. Expression analysis of chromosome 20q revealed a subset of over expressed genes residing within the regions of genomic copy number gain in all the tumor cell lines, suggesting these are Chromosome 20q copy number responsive genes. Bases on their preferential expression levels in the model system cell lines and known biological function, four of the over expressed genes mapping to the common intervals of genomic copy gain were considered the most promising candidate colorectal metastasis-associated genes. Validation of genomic copy number and expression array data was carried out on these genes, with one gene, DNMT3B, standing out as expressed at a relatively higher levels in the metastasis-derived cell lines compared with their primary-derived counterparts in both the models systems analyzed. The data provide evidence for the role of chromosome 20q genes with low copy gain and elevated expression in the clonal evolution of metastatic cells and suggests that such genes may serve as early biomarkers of metastatic potential. The data also support the utility of the combined microarray comparative genomic hybridization and expression array analysis for identifying copy number responsive genes in areas of low DNA copy gain in cancer cells. ^

Integrating sequence information in microarray data analysis by free energy modeling

Microarray technology is a high-throughput method for genotyping and gene expression profiling. Limited sensitivity and specificity are one of the essential problems for this technology. Most of existing methods of microarray data analysis have an apparent limitation for they merely deal with the numerical part of microarray data and have made little use of gene sequence information. Because it's the gene sequences that precisely define the physical objects being measured by a microarray, it is natural to make the gene sequences an essential part of the data analysis. This dissertation focused on the development of free energy models to integrate sequence information in microarray data analysis. The models were used to characterize the mechanism of hybridization on microarrays and enhance sensitivity and specificity of microarray measurements. ^ Cross-hybridization is a major obstacle factor for the sensitivity and specificity of microarray measurements. In this dissertation, we evaluated the scope of cross-hybridization problem on short-oligo microarrays. The results showed that cross hybridization on arrays is mostly caused by oligo fragments with a run of 10 to 16 nucleotides complementary to the probes. Furthermore, a free-energy based model was proposed to quantify the amount of cross-hybridization signal on each probe. This model treats cross-hybridization as an integral effect of the interactions between a probe and various off-target oligo fragments. Using public spike-in datasets, the model showed high accuracy in predicting the cross-hybridization signals on those probes whose intended targets are absent in the sample. ^ Several prospective models were proposed to improve Positional Dependent Nearest-Neighbor (PDNN) model for better quantification of gene expression and cross-hybridization. ^ The problem addressed in this dissertation is fundamental to the microarray technology. We expect that this study will help us to understand the detailed mechanism that determines sensitivity and specificity on the microarrays. Consequently, this research will have a wide impact on how microarrays are designed and how the data are interpreted. ^

Comparison of multiple comparison methods for identifying differential gene expression in simulated and real papillary thyroid cancer microarray data

The difficulty of detecting differential gene expression in microarray data has existed for many years. Several correction procedures try to avoid the family-wise error rate in multiple comparison process, including the Bonferroni and Sidak single-step p-value adjustments, Holm's step-down correction method, and Benjamini and Hochberg's false discovery rate (FDR) correction procedure. Each multiple comparison technique has its advantages and weaknesses. We studied each multiple comparison method through numerical studies (simulations) and applied the methods to the real exploratory DNA microarray data, which detect of molecular signatures in papillary thyroid cancer (PTC) patients. According to our results of simulation studies, Benjamini and Hochberg step-up FDR controlling procedure is the best process among these multiple comparison methods and we discovered 1277 potential biomarkers among 54675 probe sets after applying the Benjamini and Hochberg's method to PTC microarray data.^

Statistical Methods for Differential Expressions of Genes Detected in Multiple-Condition Experiment of Microarray

Most studies of differential gene-expressions have been conducted between two given conditions. The two-condition experimental (TCE) approach is simple in that all genes detected display a common differential expression pattern responsive to a common two-condition difference. Therefore, the genes that are differentially expressed under the other conditions other than the given two conditions are undetectable with the TCE approach. In order to address the problem, we propose a new approach called multiple-condition experiment (MCE) without replication and develop corresponding statistical methods including inference of pairs of conditions for genes, new t-statistics, and a generalized multiple-testing method for any multiple-testing procedure via a control parameter C. We applied these statistical methods to analyze our real MCE data from breast cancer cell lines and found that 85 percent of gene-expression variations were caused by genotypic effects and genotype-ANAX1 overexpression interactions, which agrees well with our expected results. We also applied our methods to the adenoma dataset of Notterman et al. and identified 93 differentially expressed genes that could not be found in TCE. The MCE approach is a conceptual breakthrough in many aspects: (a) many conditions of interests can be conducted simultaneously; (b) study of association between differential expressions of genes and conditions becomes easy; (c) it can provide more precise information for molecular classification and diagnosis of tumors; (d) it can save lot of experimental resources and time for investigators.^