Inducible caspase 9 suicide gene to improve the safety of allodepleted T cells after haploidentical stem cell transplantation.

Addback of donor T cells following T cell-depleted stem cell transplantation (SCT) can accelerate immune reconstitution and be effective against relapsed malignancy. After haploidentical SCT, a high risk of graft-versus-host disease (GVHD) essentially precludes this option, unless the T cells are first depleted of alloreactive precursor cells. Even then, the risks of severe GVHD remain significant. To increase the safety of the approach and thereby permit administration of larger T cell doses, we used a suicide gene, inducible caspase 9 (iCasp9), to transduce allodepleted T cells, permitting their destruction should administration have adverse effects. We made a retroviral vector encoding iCasp9 and a selectable marker (truncated CD19). Even after allodepletion (using anti-CD25 immunotoxin), donor T cells could be efficiently transduced, expanded, and subsequently enriched by CD19 immunomagnetic selection to >90% purity. These engineered cells retained antiviral specificity and functionality, and contained a subset with regulatory phenotype and function. Activating iCasp9 with a small-molecule dimerizer rapidly produced >90% apoptosis. Although transgene expression was downregulated in quiescent T cells, iCasp9 remained an efficient suicide gene, as expression was rapidly upregulated in activated (alloreactive) T cells. We have demonstrated the clinical feasibility of this approach after haploidentical transplantation by scaling up production using clinical grade materials.

Gene transfer by viral vectors

To initiate our clinical trial for chemotherapy protection, I established the retroviral vector system for human MDR1 cDNA gene transfer. The human MDR1 cDNA continued to be expressed in the transduced bone marrow cells after four cohorts of serial transplants, 17 months after the initial transduction and transplant. In addition, we used this retroviral vector pVMDR1 to transduce human bone marrow and peripheral blood CD34$\sp+$ cells on stromal monolayer in the presence of hematopoietic growth factors. These data suggest that the retroviral vector pVMDR1 could modify hematopoietic precursor cells with a capacity for long-term self renewal. Thus, it may be possible to use the MDR1 retroviruses to confer chemotherapeutic protection on human normal hematopoietic precursor cells of ovarian and breast cancer patients in whom high doses of MDR drugs may be required to control the diseases.^ Another promising vector system is recombinant adeno-associated virus (rAAV) vector. An impediment to use rAAV vectors is that production of rAAV vectors for clinical use is extremely cumbersome and labor intensive. First I set up the rAAV vector system in our laboratory and then, I focused on studies related to the production of rAAV vectors for clinical use. By using a self-inactivating retroviral vector carrying a selection marker under the control of the CMV immediate early promoter and an AAV genome with the deletion of both ITRs, I have developed either a transient or a stable method to produce rAAV vectors. These methods involve infection only and can generate high-titer rAAV vectors (up to 2 x 10$\sp5$ cfu/ml of CVL) with much less work.^ Although recombinant adenoviral vectors hardly infect early hematopoietic precursor cells lacking $\alpha\sb v\beta\sb5$ or $\alpha\sb v\beta\sb3$ integrin on their surface, but efficiently infect other cells, we can use these properties of adenoviral vectors for bone marrow purging as well as for development of new viral vectors such as pseudotyped retroviral vectors and rAAV vectors. Replacement of self-inactivating retroviral vectors by recombinant adenoviral vectors will facilitate the above strategies for production of new viral vectors. In order to accomplish these goals, I developed a new method which is much more efficient than the current methods to construct adenoviral vectors. This method involves a cosmid vector system which is utilized to construct the full-length recombinant adenoviral vectors in vitro.^ First, I developed an efficient and flexible method for in vitro construction of the full-length recombinant adenoviral vectors in the cosmid vector system by use of a three-DNA fragment ligation. Then, this system was improved by use of a two-DNA fragment ligation. The cloning capacity of recombinant adenoviral vectors constructed by this method to develop recombinant adenoviral vectors depends on the efficiency of transfection only. No homologous recombination is required for development of infectious adenoviral vectors. Thus, the efficiency of generating the recombinant adenoviral vectors by the cosmid method reported here was much higher than that by the in vitro direct ligation method or the in vivo homologous recombination method reported before. This method of the in vitro construction of recombinant adenoviral vectors in the cosmid vector system may facilitate the development of adenoviral vector for human gene therapy. (Abstract shortened by UMI.) ^

ARRANGEMENT OF GENE LOCI IN EUPLOID CHINESE HAMSTER CELLS AND GENETIC CONSEQUENCES OF REARRANGEMENT IN CHO CELLS

In both euploid Chinese hamster (Cricetulus griseus) cells and pseudodiploid Chinese hamster ovary (CHO) cells, gene assignments were accomplished by G band chromosome and isozyme analysis (32 isozymes) of interspecific somatic cell hybrids obtained after HAT selection of mouse CL 1D (TK('-)) cells which were PEG-fused with either euploid Chinese hamster cells or HPRT('-) CHO cells. Hybrids slowly segregated hamster chromosomes. Clone panels consisting of independent hybrid clones and subclones containing different combinations of Chinese hamster chromosomes and isozymes were established from each type of fusion.^ These clone panels enabled us to provisionally assign the loci for: nucleoside phosphorylase (NP), glyoxalase (GLO), glutathione reductase (GSR), adenosine kinase (ADK), esterase D (ESD), peptidases B and S (PEPB and -S) and phosphoglucomutase 2 (PGM2, human nomenclature) to chromosome 1; adenylate kinase 1 (AK1), adenosine deaminase (ADA) and inosine triosephosphatase (ITP) to chromosome 6; triosephosphate isomerase (TPI) to chromosome 8; and glucose phosphate isomerse (GPI) and peptidase D (PEPD) to chromosome 9.^ We also confirm the assignments of 6-phosphogluconate dehydrogenase (PGD), PGM1, enolase 1 (ENO1) and diptheria toxin sensitivity (DTS) to chromosome 2 as well as provisionally assign galactose-1-phosphate uridyl transferase (GALT) and AK2 to chromosome 2. Selection in either HAT or BrdU for hybrids that had retained or lost the chromosome carrying the locus for TK enabled us to assign the loci for TK, galactokinase (GALK) and acid phosphatase 1 (ACP1) to Chinese hamster chromosome 7.^ These results are discussed in relation to current theories on the basis for high frequency of drug resistant autosomal recessive mutants in CHO cells and conservation of mammalian autosomal linkage groups. ^

INCREASED EXPRESSION OF ONE OF TWO ADENOSINE DEAMINASE ALLELES IN A HUMAN CHORIOCARCINOMA CELL LINE FOLLOWING SELECTION WITH ADENINE NUCLEOSIDES

The human choriocarcinoma cell line JEG-3 is heterozygous at the adenosine deaminase (ADA) gene locus. Both allelic genes are under strong but incomplete repression causing a very low level expression of the gene locus. Because cytotoxic adenosine analogues such as 9-(beta)-D arabinofuranosyladenine (ara-A) and 9-(beta)-D xylofuranosyladenine (xyl-A) can be specifically detoxified by the action of ADA, these analogues were used to select for JEG-3 derived cells which had increased ADA expression. When JEG-3 cells were subjected to a multi-step, successively increasing dosage of either ara-A or xyl-A, resistant cells with increased ADA expression were generated. This increased ADA expression in the resistant cells was unstable, so that when the selective pressure was removed, cellular ADA expression would decrease. Subclone analysis of xyl-A resistant cells revealed that compared to parental JEG-3 cells, individual resistant cells had either elevated ADA levels or decreased adenosine kinase (ADK) levels or both. This altered ADA and ADK expression in the resistant cells were found to be independent events. Because of high endogenous tissue conversion factor (TCF) expression in the JEG-3 cells, the allelic nature of the increased ADA expression in most of the resistant cells could not be determined. However, several resistant subcloned cells were found to have lost TCF expression. These TCF('-) cells expressed only the ADA*2 allelic gene product. Cell fusion experiments demonstrated that the ADA*1 allelic gene was intact and functional in the A3-1A7 cell line. Chromosomal analysis of the A3-1A7 cells showed that they had no double-minutes or homogeneously staining chromosomal regions, although a pair of new chromosomes were found in these cells. Segregation analysis of the hybrid cells indicated that an ADA*2 allelic gene was probably located on this new chromosome. The analysis of the A3-1A7 cell line suggested that the expression of only ADA 2 in these cells was the result of possibly a cis-deregulation of the ADA gene locus or more probably an amplification of the ADA*2 allelic gene. Two effective positive selection systems for ADA('+) cells were also developed and tested. These selection systems should eventually lead to the isolation of the ADA gene.^

Single nucleotide polymorphism (SNP) selection for genotype-phenotype association studies

With hundreds of single nucleotide polymorphisms (SNPs) in a candidate gene and millions of SNPs across the genome, selecting an informative subset of SNPs to maximize the ability to detect genotype-phenotype association is of great interest and importance. In addition, with a large number of SNPs, analytic methods are needed that allow investigators to control the false positive rate resulting from large numbers of SNP genotype-phenotype analyses. This dissertation uses simulated data to explore methods for selecting SNPs for genotype-phenotype association studies. I examined the pattern of linkage disequilibrium (LD) across a candidate gene region and used this pattern to aid in localizing a disease-influencing mutation. The results indicate that the r2 measure of linkage disequilibrium is preferred over the common D′ measure for use in genotype-phenotype association studies. Using step-wise linear regression, the best predictor of the quantitative trait was not usually the single functional mutation. Rather it was a SNP that was in high linkage disequilibrium with the functional mutation. Next, I compared three strategies for selecting SNPs for application to phenotype association studies: based on measures of linkage disequilibrium, based on a measure of haplotype diversity, and random selection. The results demonstrate that SNPs selected based on maximum haplotype diversity are more informative and yield higher power than randomly selected SNPs or SNPs selected based on low pair-wise LD. The data also indicate that for genes with small contribution to the phenotype, it is more prudent for investigators to increase their sample size than to continuously increase the number of SNPs in order to improve statistical power. When typing large numbers of SNPs, researchers are faced with the challenge of utilizing an appropriate statistical method that controls the type I error rate while maintaining adequate power. We show that an empirical genotype based multi-locus global test that uses permutation testing to investigate the null distribution of the maximum test statistic maintains a desired overall type I error rate while not overly sacrificing statistical power. The results also show that when the penetrance model is simple the multi-locus global test does as well or better than the haplotype analysis. However, for more complex models, haplotype analyses offer advantages. The results of this dissertation will be of utility to human geneticists designing large-scale multi-locus genotype-phenotype association studies. ^

Conditional expression of Sry, and Wnt4 by gene-targeting: Studies in sexual and skeletal development

Sry and Wnt4 cDNAs were individually introduced into the ubiquitously-expressed Rosa26 ( R26) locus by gene targeting in embryonic stem (ES) cells to create a conditional gene expression system in mice. In the targeted alleles, expression of these cDNAs should be blocked by a neomycin resistance selection cassette that is flanked by loxP sites. Transgene expression should be activated after the blocking cassette is deleted by Cre recombinase. ^ To test this conditional expression system, I have bred R26-stop- Sry and R26-stop-Wnt4 heterozygotes with a MisRII-Cre mouse line that expresses Cre in the gonads of both sexes. Analysis of these two types of bigenic heterozygotes indicated that their gonads developed normally like those of wild types. However, one XX R26-Sry/R26-Sry; MisR2-Cre/+ showed epididymis-like structures resembling those of males. In contrast, only normal phenotypes were observed in XY R26-Wnt4/R26-Wnt4; MisR2-Cre /+ mice. To interpret these results, I have tested for Cre recombinase activity by Southern blot and transcription of the Sry and Wnt4 transgenes by RT-PCR. Results showed that bigenic mutants had insufficient activation of the transgenes in their gonads at E12.5 and E13.5. Therefore, the failure to observe mutant phenotypes may have resulted from low activity of MisR2-Cre recombination at the appropriate time. ^ Col2a1-Cre transgenic mice express Cre in differentiating chondrocytes. R26-Wnt4; Col2a1-Cre bigenic heterozygous mice were found to exhibit a dramatic alteration in growth presumably caused by Wnt4 overexpression during chondrogenesis. R26-Wnt4; Col2a1-Cre mice exhibited dwarfism beginning approximately 10 days after birth. In addition, they also had craniofacial abnormalities, and had delayed ossification of the lumbar vertebrate and pelvic bones. Histological analysis of the growth plates of R26-Wnt4; Col2a1-Cre mice revealed less structural organization and a delay in onset of the primary and secondary ossification centers. Molecular studies confirmed that overexpression of Wnt4 causes decreased proliferation and early maturation of chondrocytes. In addition, R26-Wnt4; Col2a1-Cre mice had decreased expression of vascular endothelial growth factor (VEGF), suggesting that defects in vascularization may contribute to the dwarf phenotype. Finally, 9-month-old R26-Wnt4; Col2a1-Cre mice had significantly more fat cells in the marrow cavities of their metaphysis long bones, implying that long-term overexpression of Wnt4may cause bone marrow pathologies. In conclusion, Wnt4 was activated by Col2a1-Cre recombinase and was overexpressed in the growth plate, resulting in aberrant proliferation and differentiation of chondrocytes, and ultimately leads to dwarfism in mice. ^

Network-based analysis of genome-wide scans of natural selection

The genomic era brought by recent advances in the next-generation sequencing technology makes the genome-wide scans of natural selection a reality. Currently, almost all the statistical tests and analytical methods for identifying genes under selection was performed on the individual gene basis. Although these methods have the power of identifying gene subject to strong selection, they have limited power in discovering genes targeted by moderate or weak selection forces, which are crucial for understanding the molecular mechanisms of complex phenotypes and diseases. Recent availability and rapid completeness of many gene network and protein-protein interaction databases accompanying the genomic era open the avenues of exploring the possibility of enhancing the power of discovering genes under natural selection. The aim of the thesis is to explore and develop normal mixture model based methods for leveraging gene network information to enhance the power of natural selection target gene discovery. The results show that the developed statistical method, which combines the posterior log odds of the standard normal mixture model and the Guilt-By-Association score of the gene network in a naïve Bayes framework, has the power to discover moderate/weak selection gene which bridges the genes under strong selection and it helps our understanding the biology under complex diseases and related natural selection phenotypes.^

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.

Evolution of cis-regulatory elements in a repetitive sequence adjacent to a sea urchin aboral ectoderm -specific gene

The creation, preservation, and degeneration of cis-regulatory elements controlling developmental gene expression are fundamental genome-level evolutionary processes about which little is known. In this study, critical differences in cis-regulatory elements controlling the expression of the sea urchin aboral ectoderm-specific spec genes were identified and explored. In genomes of species within the Strongylocentrotidae family, multiple copies of a repetitive sequence element termed RSR were present, but RSRs were not detected in genomes of species outside Strongylocentrotidae. RSRs are invariably associated with spec genes, and in Strongylocentrotus purpuratus, the spec2a RSR functioned as a transcriptional enhancer displaying greater activity than RSRs from the spec1 or spec2c paralogs. Single base-pair differences at two cis-regulatory elements within the spec2a RSR greatly increased the binding affinities of four transcription factors: SpCCAAT-binding factor at one element and SpOtx, SpGoosecoid, and SpGATA-E at another. The cis-regulatory elements to which SpCCAAT-binding factor, SpOtx, SpGoosecoid, and SpGATA-E bound were recent evolutionary acquisitions that could act either to activate or repress transcription, depending on the cell type. These elements were found in the spec2a RSR ortholog in Strongylocentrotus pallidus but not in the RSR orthologs of Strongylocentrotus droebachiensis or Hemicentrotus pulcherrimus. These results indicate that spec genes exhibit a dynamic pattern of cis-regulatory element evolution while stabilizing selection preserves their aboral ectoderm expression domain. ^