IDENTIFICATION OF GENES CONTROLLING BIOLOGICAL PROCESSES AND PATHWAYS THROUGH STATISTICAL ANALYSIS AND NETWORK RECONSTRUCTION

The developmental processes and functions of an organism are controlled by the genes and the proteins that are derived from these genes. The identification of key genes and the reconstruction of gene networks can provide a model to help us understand the regulatory mechanisms for the initiation and progression of biological processes or functional abnormalities (e.g. diseases) in living organisms. In this dissertation, I have developed statistical methods to identify the genes and transcription factors (TFs) involved in biological processes, constructed their regulatory networks, and also evaluated some existing association methods to find robust methods for coexpression analyses. Two kinds of data sets were used for this work: genotype data and gene expression microarray data. On the basis of these data sets, this dissertation has two major parts, together forming six chapters. The first part deals with developing association methods for rare variants using genotype data (chapter 4 and 5). The second part deals with developing and/or evaluating statistical methods to identify genes and TFs involved in biological processes, and construction of their regulatory networks using gene expression data (chapter 2, 3, and 6). For the first part, I have developed two methods to find the groupwise association of rare variants with given diseases or traits. The first method is based on kernel machine learning and can be applied to both quantitative as well as qualitative traits. Simulation results showed that the proposed method has improved power over the existing weighted sum method (WS) in most settings. The second method uses multiple phenotypes to select a few top significant genes. It then finds the association of each gene with each phenotype while controlling the population stratification by adjusting the data for ancestry using principal components. This method was applied to GAW 17 data and was able to find several disease risk genes. For the second part, I have worked on three problems. First problem involved evaluation of eight gene association methods. A very comprehensive comparison of these methods with further analysis clearly demonstrates the distinct and common performance of these eight gene association methods. For the second problem, an algorithm named the bottom-up graphical Gaussian model was developed to identify the TFs that regulate pathway genes and reconstruct their hierarchical regulatory networks. This algorithm has produced very significant results and it is the first report to produce such hierarchical networks for these pathways. The third problem dealt with developing another algorithm called the top-down graphical Gaussian model that identifies the network governed by a specific TF. The network produced by the algorithm is proven to be of very high accuracy.

DESIGN AND SYNTHESIS OF MULTIFUNCTIONAL POLYMERIC MICELLES FOR GENE-DIRECTED ENZYME PRODRUG THERAPY

Gene-directed enzyme prodrug therapy is a form of cancer therapy in which delivery of a gene that encodes an enzyme is able to convert a prodrug, a pharmacologically inactive molecule, into a potent cytotoxin. Currently delivery of gene and prodrug is a two-step process. Here, we propose a one-step method using polymer nanocarriers to deliver prodrug, gene and cytotoxic drug simultaneously to malignant cells. Prodrugs acyclovir, ganciclovir and 5-doxifluridine were used to directly to initiate ring-opening polymerization of epsilon-caprolactone, forming a hydrophobic prodrug-tagged poly(epsilon-caprolactone) which was further grafted with hydrophilic polymers (methoxy poly(ethylene glycol), chitosan or polyethylenemine) to form amphiphilic copolymers for micelle formation. Successful synthesis of copolymers and micelle formation was confirmed by standard analytical means. Conversion of prodrugs to their cytotoxic forms was analyzed by both two-step and one-step means i.e. by first delivering gene plasmid into cell line HT29 and then challenging the cells with the prodrug-tagged micelle carriers and secondly by complexing gene plasmid onto micelle nanocarriers and delivery gene and prodrug simultaneously to parental HT29 cells. Anticancer effectiveness of prodrug-tagged micelles was further enhanced by encapsulating chemotherapy drugs doxorubicin or SN-38. Viability of colon cancer cell line HT29 was significantly reduced. Furthermore, in an effort to develop a stealth and targeted carrier, CD47-streptavidin fusion protein was attached onto the micelle surface utilizing biotin-streptavidin affinity. CD47, a marker of self on the red blood cell surface, was used for its antiphagocytic efficacy, results showed that micelles bound with CD47 showed antiphagocytic efficacy when exposed to J774A.1 macrophages. Since CD47 is not only an antiphagocytic ligand but also an integrin associated protein, it was used to target integrin alpha(v)beta(3), which is overexpressed on tumor-activated neovascular endothelial cells. Results showed that CD47-tagged micelles had enhanced uptake when treated to PC3 cells which have high expression of alpha(v)beta(3). The synthesized multifunctional polymeric micelle carriers developed could offer a new platform for an innovative cancer therapy regime.