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.^

Detection and sequence analysis of a nickel-induced mutation in a retroviral model system

We have developed a novel way to assess the mutagenicity of environmentally important metal carcinogens, such as nickel, by creating a positive selection system based upon the conditional expression of a retroviral transforming gene. The target gene is the v-mos gene in MuSVts110, a murine retrovirus possessing a growth temperature dependent defect in expression of the transforming gene due to viral RNA splicing. In normal rat kidney cells infected with MuSVts110 (6m2 cells), splicing of the MuSVts110 RNA to form the mRNA from which the transforming protein, p85$\sp{\rm gag-mos}$, is translated is growth-temperature dependent, occurring at 33 C and below but not at 39 C and above. This splicing "defect" is mediated by cis-acting viral sequences. Nickel chloride treatment of 6m2 cells followed by growth at 39 C, allowed the selection of "revertant" cells which constitutively express p85$\sp{\rm gag-mos}$ due to stable changes in the viral RNA splicing phenotype, suggesting that nickel, a carcinogen whose mutagenicity has not been well established, could induce mutations in mammalian genes. We also show by direct sequencing of PCR-amplified integrated MuSVts110 DNA from a 6m2 nickel-revertant cell line that the nickel-induced mutation affecting the splicing phenotype is a cis-acting 70-base duplication of a region of the viral DNA surrounding the 3$\sp\prime$ splice site. These findings provide the first example of the molecular basis for a nickel-induced DNA lesion and establish the mutagenicity of this potent carcinogen. ^

Identification of cadmium-induced mutations in a mammalian cell line

Epidemiological studies have shown cadmium to induce cancer in humans, while experimental studies have proven this metal to be a potent tumor inducer in animals. However, cadmium appears nonmutagenic in most prokaryotic and eukaryotic mutagenesis assays. In this study, we present the identification of mutations in normal rat kidney cells infected with the mutant MuSVts110 retrovirus (6m2 cells) as a result of treatment with cadmium chloride. The detection of these mutations was facilitated by the use of a novel mutagenesis assay established in this laboratory. The 6m2 reversion assay is a positive selection system based on the conditional expression of the MuSVts110 v-mos gene. In MuSVts110 the gag and mos genes are fused out of frame, thus the translation of the v-mos sequence requires a frameshift in the genomic RNA. In 6m2 cells this frameshift is accomplished by the temperature-dependent splicing of the primary MuSVts110 transcript. Splicing of MuSVts110, which is mediated by cis-acting sequences, occurs when 6m2 cells are grown at 33$\sp\circ$C and below, but not at 39$\sp\circ$C. Therefore, 6m2 cells appear transformed at low growth temperatures, but take on a morphologically normal appearance when grown at high temperatures. The treatment of 6m2 cells with cadmium chloride resulted in the outgrowth of a number of cells that reverted to the transformed state at high growth temperatures. Analysis of the viral proteins expressed in these cadmium-induced 6m2 revertants suggested that they contained mutations in their MuSVts110 DNA. Sequencing of the viral DNA from three revertants that constitutively expressed the P85$\sp{gag{-}mos}$ transforming protein revealed five different mutations. The Cd-B2 revertant contained three of those mutations: an A-to-G transition 48 bases downstream of the MuSVts110 3$\sp\prime$ splice site, plus a G-to-T and an A-to-T transversion 84 and 100 bases downstream of the 5$\sp\prime$ splice site, respectively. The Cd-15-5 revertant also contained a point mutation, a T-to-C transition 46 bases downstream of the 5$\sp\prime$ splice site, while Cd-10-5 contained a three base deletion of MuSVts110 11 bases upstream of the 3$\sp\prime$ splice site. A fourth revertant, Cd-10, expressed a P100$\sp{gag{-}mos}$ transforming protein, and was found to have a two base deletion. This deletion accomplished the frameshift necessary for v-mos expression, but did not alter MuSVts110 RNA splicing and the expression of p85$\sp{gag{-}mos}.$ Lastly, sequencing of the MuSVts110 DNA from three spontaneous revertants revealed the same G to T transversion in each one. This was the same mutation that was found in the Cd-B2 revertant. These findings provide the first example of mutations resulting from exposure to cadmium and suggest, by the difference in each mutation, the complexity of the mechanism utilized by cadmium to induce DNA damage. ^

Characterization of anti -sulfatide autoantibodies in demyelinating diseases

Multiple sclerosis (MS) is the most common autoimmune disease of the central nerve system and Guillain Barré Syndrome (GBS) is an inflammatory neuropathy involving the peripheral nerves. Anti-myelin immunoglobins may play a role in the demyelination processes of the both diseases. Sulfatide is an abundant glycolipid on myelin and is a candidate target antigen for disease related autoantibodies. The objective of this study was to characterize anti-sulfatide antibodies and compare antibodies from GBS and MS patients with fetal antibodies. Our hypothesis is that some B cells producing disease-associated autoantibodies are derived from or related to B cells of the fetal repertoire. Here we report that reactivity of plasma IgM against sulfatide was elevated in twelve MS patients compared with twelve normal subjects. This result implies that anti-sulfatide antibodies are disease-related. A total of sixteen human B lymphocyte clones producing anti-sulfatide autoantibodies were isolated from MS patients, GBS patients and a human fetus. Seven of the clones were from three MS patients, four of the clones were from three GBS patients and five were from the spleen of a twenty-week human fetus. Sequences have been obtained for the heavy and light chain variable regions (VDJ and VJ regions) of all of the anti-sulfatide immunoglobulins. Seven of the sixteen antibodies used VH3 for the variable region gene of the heavy chain consistent with the rate of VH3 usage in randomly selected B cells. Somatic mutations were significantly more frequent in the patient antibodies than in the fetus and somatic mutations in CDR's (Complementarity Determining Region) were significantly more frequent than in framework regions. No significant difference was found between patients and fetus in length of VH CDRIII. However, it is reported that antibodies from randomly selected normal adult B cells have longer CDRIII lengths than those of the fetus (Sanz I, 1991 Journal of Immunology Sep 1;147(5):1720-9). Our results are consistent with derivation of the precursors of B cells producing these autoantibodies from B cells related to those of the fetal repertoire. These findings are consistent with a model in which quiescent B cells from clones produced early in development undergo proliferation in dysregulated disease states, accumulating somatic mutations and increasing in reactivity toward self-antigens. ^ Epitope mapping and molecular modeling were done to elucidate the relationships between antibody structure and binding characteristics. The autoantibodies were tested for binding activity to three different antigens: sulfatide, galactoceramide and ceramide. Molecular modeling suggests that antibodies with positive charge surrounded by or adjacent to hydrophobic groups in the binding pocket bind to the head of sulfatide via the sulfate group through electrostatic interactions. However, the antibodies with hydrophobic groups separated from positive charges appear to bind to the hydrophobic tail of sulfatide. This observation was supported by a study of the effect of NaCl concentration on antigen binding. The result suggested that electrostatic interactions played a major role in sulfate group binding and that hydrophobic interactions were of greater importance for binding to the ceramide group. Our three-dimensional structure data indicated that epitope specificity of these antibodies is more predictable at the level of tertiary than primary structure and suggested positive selection based on structure occurred in the. formation of those autoantibodies. ^

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. ^

An empirical evaluation of the Random Forests classifier models for variable selection in a large-scale lung cancer case-control study

Random Forests™ is reported to be one of the most accurate classification algorithms in complex data analysis. It shows excellent performance even when most predictors are noisy and the number of variables is much larger than the number of observations. In this thesis Random Forests was applied to a large-scale lung cancer case-control study. A novel way of automatically selecting prognostic factors was proposed. Also, synthetic positive control was used to validate Random Forests method. Throughout this study we showed that Random Forests can deal with large number of weak input variables without overfitting. It can account for non-additive interactions between these input variables. Random Forests can also be used for variable selection without being adversely affected by collinearities. ^ Random Forests can deal with the large-scale data sets without rigorous data preprocessing. It has robust variable importance ranking measure. Proposed is a novel variable selection method in context of Random Forests that uses the data noise level as the cut-off value to determine the subset of the important predictors. This new approach enhanced the ability of the Random Forests algorithm to automatically identify important predictors for complex data. The cut-off value can also be adjusted based on the results of the synthetic positive control experiments. ^ When the data set had high variables to observations ratio, Random Forests complemented the established logistic regression. This study suggested that Random Forests is recommended for such high dimensionality data. One can use Random Forests to select the important variables and then use logistic regression or Random Forests itself to estimate the effect size of the predictors and to classify new observations. ^ We also found that the mean decrease of accuracy is a more reliable variable ranking measurement than mean decrease of Gini. ^