LDOC1, A NOVEL BIOMARKER OF PROGNOSIS IN CHRONIC LYMPHOCYTIC LEUKEMIA

In chronic lymphocytic leukemia (CLL), one of the best predictors of outcome is the somatic mutation status of the immunoglobulin heavy chain variable region (IGHV) genes. Patients whose CLL cells have unmutated IGHV genes have a median survival of 8 years; those with mutated IGHV genes have a median survival of 25 years. To identify new prognostic biomarkers and molecular targets for therapy in untreated CLL patients, we reanalyzed the raw data from four published gene expression profiling microarray studies. Of 88 candidate biomarkers associated with IGHV somatic mutation status, we identified LDOC1 (Leucine Zipper, Down-regulated in Cancer 1), as one of the most significantly differentially expressed genes that distinguished mutated from unmutated CLL cases. LDOC1 is a putative transcription factor of unknown function in B-cell development and CLL pathophysiology. Using a highly sensitive quantitative RT-PCR (QRT-PCR) assay, we confirmed that LDOC1 mRNA was dramatically down-regulated in mutated compared to unmutated CLL cases. Expression of LDOC1 mRNA was also vii strongly associated with other markers of poor prognosis, including ZAP70 protein and cytogenetic abnormalities of poor prognosis (deletions of chromosomes 6q21, 11q23, and 17p13.1, and trisomy 12). CLL cases positive for LDOC1 mRNA had significantly shorter overall survival than negative cases. Moreover, in a multivariate model, LDOC1 mRNA expression predicted overall survival better than IGHV mutation status or ZAP70 protein, among the best markers of prognosis in CLL. We also discovered LDOC1S, a new LDOC1 splice variant. Using isoform-specific QRT-PCR assays that we developed, we found that both isoforms were expressed in normal B cells (naïve > memory), unmutated CLL cells, and in B-cell non-Hodgkin lymphomas with unmutated IGHV genes. To investigate pathways in which LDOC1 is involved, we knocked down LDOC1 in HeLa cells and performed global gene expression profiling. GFI1 (Growth Factor-Independent 1) emerged as a significantly up-regulated gene in both HeLa cells and CLL cells that expressed high levels of LDOC1. GFI1 oncoprotein is implicated in hematopoietic stem cell maintenance, lymphocyte development, and lymphomagenesis. Our findings indicate that LDOC1 mRNA is an excellent biomarker of overall survival in CLL, and may contribute to B-cell differentiation and malignant transformation.

SURVIVAL PREDICTION FOR BRAIN TUMOR PATIENTS USING GENE EXPRESSION DATA

Brain tumor is one of the most aggressive types of cancer in humans, with an estimated median survival time of 12 months and only 4% of the patients surviving more than 5 years after disease diagnosis. Until recently, brain tumor prognosis has been based only on clinical information such as tumor grade and patient age, but there are reports indicating that molecular profiling of gliomas can reveal subgroups of patients with distinct survival rates. We hypothesize that coupling molecular profiling of brain tumors with clinical information might improve predictions of patient survival time and, consequently, better guide future treatment decisions. In order to evaluate this hypothesis, the general goal of this research is to build models for survival prediction of glioma patients using DNA molecular profiles (U133 Affymetrix gene expression microarrays) along with clinical information. First, a predictive Random Forest model is built for binary outcomes (i.e. short vs. long-term survival) and a small subset of genes whose expression values can be used to predict survival time is selected. Following, a new statistical methodology is developed for predicting time-to-death outcomes using Bayesian ensemble trees. Due to a large heterogeneity observed within prognostic classes obtained by the Random Forest model, prediction can be improved by relating time-to-death with gene expression profile directly. We propose a Bayesian ensemble model for survival prediction which is appropriate for high-dimensional data such as gene expression data. Our approach is based on the ensemble "sum-of-trees" model which is flexible to incorporate additive and interaction effects between genes. We specify a fully Bayesian hierarchical approach and illustrate our methodology for the CPH, Weibull, and AFT survival models. We overcome the lack of conjugacy using a latent variable formulation to model the covariate effects which decreases computation time for model fitting. Also, our proposed models provides a model-free way to select important predictive prognostic markers based on controlling false discovery rates. We compare the performance of our methods with baseline reference survival methods and apply our methodology to an unpublished data set of brain tumor survival times and gene expression data, selecting genes potentially related to the development of the disease under study. A closing discussion compares results obtained by Random Forest and Bayesian ensemble methods under the biological/clinical perspectives and highlights the statistical advantages and disadvantages of the new methodology in the context of DNA microarray data analysis.

The molecular basis for beta-lactamase gene expression in B. anthracis, B. cereus and B. thuringiensis

The susceptibility of most Bacillus anthracis strains to β-lactam antibiotics is intriguing considering that the B. anthracis genome harbors two β-lactamase genes, bla1 and bla2, and closely-related species, Bacillus cereus and Bacillus thuringiensis, typically produce β-lactamases. This work demonstrates that B. anthracis bla expression is affected by two genes, sigP and rsp, predicted to encode an extracytoplasmic function sigma factor and an antisigma factor, respectively. Deletion of the sigP/rsp locus abolished bla expression in a penicillin-resistant clinical isolate and had no effect on bla expression in a prototypical penicillin-susceptible strain. Complementation with sigP/rsp from the penicillin-resistant strain, but not the penicillin-susceptible strain, conferred β-lactamase activity upon both mutants. These results are attributed to a nucleotide deletion near the 5' end of rsp in the penicillin-resistant strain that is predicted to result in a nonfunctional protein. B. cereus and B. thuringiensis sigP and rsp homologues are required for inducible penicillin resistance in those species. Expression of the B. cereus or B. thuringiensis sigP and rsp genes in a B. anthracis sigP/rsp-null mutant confers resistance to β-lactam antibiotics, suggesting that while B. anthracis contains the genes necessary for sensing β-lactam antibiotics, the B. anthracis sigP/rsp gene products are insufficient for bla induction. ^ Because alternative sigma factors recognize unique promoter sequence, direct targets can be elucidated by comparing transcriptional profiling results with an in silico search using the sigma factor binding sequence. Potential σP -10 and -35 promoter elements were identified upstream from bla1 bla2 and sigP. Results obtained from searching the B. anthracis genome with the conserved sequences were evaluated against transcriptional profiling results comparing B. anthracis 32 and an isogenic sigP/rsp -null strain. Results from these analyses indicate that while the absence of the sigP gene significantly affects the transcript levels of 16 genes, only bla1, bla2 and sigP are directly regulated by σP. The genomes of B. cereus and B. thuringiensis strains were also analyzed for the potential σP binding elements. The sequence was located upstream from the sigP and bla genes, and previously unidentified genes predicted to encode a penicillin-binding protein (PBP) and a D-alanyl-D-alanine carboxypeptidase, indicating that the σ P regulon in these species responds to cell-wall stress caused by β-lactam antibiotics. ^ β-lactam antibiotics prevent attachment of new peptidoglycan to the cell wall by blocking the active site of PBPs. A B. cereus and B. thuringiensis pbp-encoding gene located near bla1 contains a potential σP recognition sequence upstream from the annotated translational start. Deletion of this gene abolished β-lactam resistance in both strains. Mutations in the active site of the PBP were detrimental to β-lactam resistance in B. cereus, but not B. thuringiensis, indicating that the transpeptidase activity is only important in B. cereus. I also found that transcript levels of the PBP-encoding gene are not significantly affected by the presence of β-lactam antibiotic. Based on these data I hypothesize that the gene product acts a sensor of β-lactam antibiotic. ^

Transcriptional and translational regulators of gene expression in germ cell development

Germ cell development is a highly coordinated process driven, in part, by regulatory mechanisms that control gene expression. Not only transcription, but also translation, is under regulatory control to direct proper germ cell development. In this dissertation, I have focused on two regulators of germ cell development. One is the homeobox protein RHOX10, which has the potential to be both a transcriptional and translational regulator in mouse male germ cell development. The other is the RNA-binding protein, Hermes, which functions as a translational regulator in Xenopus laevis female germ cell development. ^ Rhox10 is a member of reproductive homeobox gene X-(linked (Rhox) gene cluster, of which expression is developmentally regulated in developing mouse testes. To identify the cell types and developmental stages in which Rhox10 might function, I characterized its temporal and spatial expression pattern in mouse embryonic, neonatal, and adult tissues. Among other things, this analysis revealed that both the level and the subcellular localization of RHOX10 are regulated during germ cell development. To understand the role of Rhox10 in germ cell development, I generated transgenic mice expressing an artificial microRNA (miRNA) targeting Rhox10. While this artificial miRNA robustly downregulated RHOX10 protein expression in vitro, it did not significantly reduce RHOX10 expression in vivo. So I next elected to knockdown RHOX10 levels in spermatogonial stem cells (SSCs), which I found highly express both Rhox10 mRNA and RHOX10 protein. Using a recently developed in vitro culture system for SSCs combined with a short-hairpin RNA (shRNA) approach, I strongly depleted RHOX10 expression in SSCs. These RHOX10-depleted cells exhibited a defect in the ability to form stem cell clusters in vitro. Expression profiling analysis revealed many genes regulated by Rhox10, including many meiotic genes, which could be downstream of Rhox10 in a molecular pathway that controls SSC differentiation. ^ RNA recognition motif (RRM) containing protein, Hermes is localized in germ plasm, where dormant mRNAs are also located, of Xenopus oocytes, which implicates its role in translational regulator. To understand the function of Hermes in oocyte meiosis, I used a morpholino oligonucleotide (MO) based knockdown approach. Microinjection of Hermes MO into fully grown oocytes, which are arrested in meiotic prophase, caused acceleration of oocytes reentry into meiosis (i.e., maturation) upon progesterone induction. Using a candidate approach, I identified at least three targets of Hermes: Ringo/Spy, Xcat2, and Mos. Ringo/Spy and Mos are known to have functions in oocyte maturation, while Ringo/Spy, Xcat2 mRNA are localized in the germ plasm of oocytes, which drives germ cell specification after fertilization. This led me to propose that Hermes functions in both oocyte maturation and germ cell development through its ability to regulate 3 crucial target mRNAs. ^