A NEW TUMOR SUPPRESSOR GENE CANDIDATE REGULATED BY THE NON-CODING RNA PCA3 IN HUMAN PROSTATE CANCER

Prostate cancer is the second leading cause of cancer-related death and the most common non-skin cancer in men in the USA. Considerable advancements in the practice of medicine have allowed a significant improvement in the diagnosis and treatment of this disease and, in recent years, both incidence and mortality rates have been slightly declining. However, it is still estimated that 1 man in 6 will be diagnosed with prostate cancer during his lifetime, and 1 man in 35 will die of the disease. In order to identify novel strategies and effective therapeutic approaches in the fight against prostate cancer, it is imperative to improve our understanding of its complex biology since many aspects of prostate cancer initiation and progression still remain elusive. The study of tumor biomarkers, due to their specific altered expression in tumor versus normal tissue, is a valid tool for elucidating key aspects of cancer biology, and may provide important insights into the molecular mechanisms underlining the tumorigenesis process of prostate cancer. PCA3, is considered the most specific prostate cancer biomarker, however its biological role, until now, remained unknown. PCA3 is a long non-coding RNA (ncRNA) expressed from chromosome 9q21 and its study led us to the discovery of a novel human gene, PC-TSGC, transcribed from the opposite strand and in an antisense orientation to PCA3. With the work presented in this thesis, we demonstrate that PCA3 exerts a negative regulatory role over PC-TSGC, and we propose PC-TSGC to be a new tumor suppressor gene that contrasts the transformation of prostate cells by inhibiting Rho-GTPases signaling pathways. Our findings provide a biological role for PCA3 in prostate cancer and suggest a new mechanism of tumor suppressor gene inactivation mediated by non-coding RNA. Also, the characterization of PCA3 and PC-TSGC led us to propose a new molecular pathway involving both genes in the transformation process of the prostate, thus providing a new piece of the jigsaw puzzle representing the complex biology of prostate cancer.

Gene Discovery in Nonsyndromic Cleft Lip with or without Cleft Palate

Nonsyndromic cleft lip with or without cleft palate (NSCLP), a common, complex orofacial birth defect that affects approximately 4,000 newborns each year in the United States, is caused by both genetic and environmental factors. Orofacial clefts affect the mouth and nose, causing severe deformity of the face, which require medical, dental and speech therapies. Despite having substantial genetic liability, less than 25% of the genetic contribute to NSCLP has been identified. The studies described in this thesis were performed to identify genes that contribute to NSCLP and to demonstrate the role of these genes in normal craniofacial development. Using genome scan and candidate gene approaches, novel associations with NSCLP were identified. These include MYH9 (7 SNPs, 0.009≤p<0.05), Wnt3A (4 SNPs, 0.001≤p≤0.005), Wnt11 (2 SNPs, 0.001≤p≤0.01) and CRISPLD2 (4 SNPs, 0.001≤p<0.05). The most interesting findings were for CRISPLD2. This gene is expressed in the fused mouse palate at E17.5. In zebrafish, crispld2 localized to the craniofacial region by one day post fertilization. Morpholino knockdown of crispld2 resulted in a lower survival rates and altered neural crest cell (NCC) clustering. Because NCCs form the tissues that populate the craniofacies, this NCC abnormality resulted in cartilage abnormalities of the jaw including fewer ceratobranchial cartilages forming the lower jaw (three pairs compared to five) and broader craniofacies compared to wild-type zebrafish. These findings suggest that the CRISPLD2 gene plays an important role in normal craniofacial development and perturbation of this gene in humans contributes to orofacial clefting. Overall, these results are important because they contribute to our understanding of normal craniofacial development and orofacial clefting etiology, information that can be used to develop better methods to diagnose, counsel and potentially treat NSCLP patients.

Serum IL-6: a candidate biomarker for intracranial pressure elevation following isolated traumatic brain injury.

BACKGROUND: Increased intracranial pressure (ICP) is a serious, life-threatening, secondary event following traumatic brain injury (TBI). In many cases, ICP rises in a delayed fashion, reaching a maximal level 48-96 hours after the initial insult. While pressure catheters can be implanted to monitor ICP, there is no clinically proven method for determining a patient's risk for developing this pathology. METHODS: In the present study, we employed antibody array and Luminex-based screening methods to interrogate the levels of inflammatory cytokines in the serum of healthy volunteers and in severe TBI patients (GCS RESULTS: Consistent with previous reports, we observed sustained increases in IL-6 levels in TBI patients irrespective of their ICP status. However, the group of patients who subsequently experienced ICP >or= 25 mm Hg had significantly higher IL-6 levels within the first 17 hours of injury as compared to the patients whose ICP remained 128 pg/ml correctly identified 85% of isolated TBI patients who subsequently developed elevated ICP, and values between these cut-off values correctly identified 75% of all patients whose ICP remained CONCLUSIONS: Our results suggest that serum IL-6 can be used for the differential diagnosis of elevated ICP in isolated TBI.

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.

TP53 as a Biomarker in Head and Neck Squamous Cell Carcinoma

Currently, there are no molecular biomarkers that guide treatment decisions for patients with head and neck squamous cell carcinoma (HNSCC). Several retrospective studies have evaluated TP53 in HNSCC, and results have suggested that specific mutations are associated with poor outcome. However, there exists heterogeneity among these studies in the site and stage of disease of the patients reviewed, the treatments rendered, and methods of evaluating TP53 mutation. Thus, it remains unclear as to which patients and in which clinical settings TP53 mutation is most useful in predicting treatment failure. In the current study, we reviewed the records of a cohort of patients with advanced, resectable HNSCC who received surgery and post-operative radiation (PORT) and had DNA isolated from fresh tumor tissue obtained at the time of surgery. TP53 mutations were identified using Sanger sequencing of exons 2-11 and the associated splice regions of the TP53 gene. We have found that the group of patients with either non-disruptive or disruptive TP53 mutations had decreased overall survival, disease-free survival, and an increased rate of distant metastasis. When examined as an independent factor, disruptive mutation was strongly associated with the development of distant metastasis. As a second aim of this project, we performed a pilot study examining the utility of the AmpliChip® p53 test as a practical method for TP53 sequencing in the clinical setting. AmpliChip® testing and Sanger sequencing was performed on a separate cohort of patients with HNSCC. Our study demonstrated the ablity of the AmpliChip® to call TP53 mutation from a single formalin-fixed paraffin-embedded slide. The results from AmpliChip® testing were identical with the Sanger method in 11 of 19 cases, with a higher rate of mutation calls using the AmpliChip® test. TP53 mutation is a potential prognostic biomarker among patients with advanced, resectable HNSCC treated with surgery and PORT. Whether this subgroup of patients could benefit from the addition of concurrent or induction chemotherapy remains to be evaluated in prospective clinical trials. Our pilot study of the p53 AmpliChip® suggests this could be a practical and reliable method of TP53 analysis in the clinical setting.

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. ^

Assessing the improved discriminatory power of a new biomarker in prognostic models

Although the area under the receiver operating characteristic (AUC) is the most popular measure of the performance of prediction models, it has limitations, especially when it is used to evaluate the added discrimination of a new biomarker in the model. Pencina et al. (2008) proposed two indices, the net reclassification improvement (NRI) and integrated discrimination improvement (IDI), to supplement the improvement in the AUC (IAUC). Their NRI and IDI are based on binary outcomes in case-control settings, which do not involve time-to-event outcome. However, many disease outcomes are time-dependent and the onset time can be censored. Measuring discrimination potential of a prognostic marker without considering time to event can lead to biased estimates. In this dissertation, we have extended the NRI and IDI to survival analysis settings and derived the corresponding sample estimators and asymptotic tests. Simulation studies were conducted to compare the performance of the time-dependent NRI and IDI with Pencina’s NRI and IDI. For illustration, we have applied the proposed method to a breast cancer study.^ Key words: Prognostic model, Discrimination, Time-dependent NRI and IDI ^

Biomarker circadian rhythm profiles in critically ill mechanically ventilated patients

Objective: To explore the natural trajectory of core body temperature (CBT) and cortisol (CORT) circadian rhythms in mechanically ventilated intensive care unit (MV ICU) patients. ^ Design: Prospective, observational, time-series pilot study. ^ Setting: Medical-surgical and pulmonary ICUs in a tertiary care hospital. ^ Sample: Nine (F = 3, M = 6) adults who were mechanically ventilated within 12 hrs of ICU admission with mean ± SD age of 65.2 ± 14 years old. ^ Measurements: Core body temperature and environmental measures of light, sound, temperature, and relative humidity were logged in 1-min intervals. Hourly urine specimens and 2-hr interval blood specimens were collected for up to 7 consecutive days for CORT assay. Mechanical ventilation days, ICU length of stay, and ICU mortality were documented. Acute Physiology and Chronic Health Evaluation (APACHE) II scores were computed for each study day. The data of each biologic and environmental variable were analyzed using single cosinor analysis of 24-hr serial segments. One patient did not complete the study because mortality occurred within 8 hrs of enrollment. Nine ICU patients completed the study in 1.6 to 7.0 days. ^ Results: No normal circadian rhythm pattern was found when the cosinor-derived parameters of amplitude (one-half the peak-trough variability) and acrophase (peak time) were compared with cosinor-derived parameter reference ranges of healthy, diurnally active humans, although 83% of patient-day CBT segments showed statistically significant (p ≤ .05) and biologically meaningful (R2≥ 0.30) 24-hr rhythms with abnormal cosinor parameters. Cosinor parameters of the environmental temporal profiles showed 27% of light, 76% of ambient temperature, and 78% of relative humidity serial segments had a significant and meaningful 24-hr diurnal pattern. Average daily light intensity varied from 34 to 187 lx with a maximum light exposure of 1877 lx. No sound measurement segment had a statistically significant cosine pattern, and numerous 1-minute interval peaks ≥ 60 dB occurred around the clock. Average daily ambient temperature and relative humidity varied from 19 to 24°C and from 25% to 61%, respectively. There was no statistically significant association between CBT or clinical outcomes and cosinor-derived parameters of the environmental variables. Circadian rhythms of urine and plasma CORT were deferred for later analysis. ^ Conclusions: The natural trajectory of the CBT circadian rhythm in MV ICU patients demonstrated persistent cosinor parameter alteration, even when a significant and meaningful 24-hr rhythm was present. The ICU environmental measures showed erratic light and sound exposures. Room temperature and relative humidity data produced the highest rate of significant and meaningful diurnal 24-hr patterns. Additional research is needed to clarify relations among the CBT biomarker of the circadian clock and environmental variables of MV ICU patients. ^

INTEGRATIVE BIOMARKER IDENTIFICATION AND CLASSIFICATION USING HIGH THROUGHPUT ASSAYS

It is well accepted that tumorigenesis is a multi-step procedure involving aberrant functioning of genes regulating cell proliferation, differentiation, apoptosis, genome stability, angiogenesis and motility. To obtain a full understanding of tumorigenesis, it is necessary to collect information on all aspects of cell activity. Recent advances in high throughput technologies allow biologists to generate massive amounts of data, more than might have been imagined decades ago. These advances have made it possible to launch comprehensive projects such as (TCGA) and (ICGC) which systematically characterize the molecular fingerprints of cancer cells using gene expression, methylation, copy number, microRNA and SNP microarrays as well as next generation sequencing assays interrogating somatic mutation, insertion, deletion, translocation and structural rearrangements. Given the massive amount of data, a major challenge is to integrate information from multiple sources and formulate testable hypotheses. This thesis focuses on developing methodologies for integrative analyses of genomic assays profiled on the same set of samples. We have developed several novel methods for integrative biomarker identification and cancer classification. We introduce a regression-based approach to identify biomarkers predictive to therapy response or survival by integrating multiple assays including gene expression, methylation and copy number data through penalized regression. To identify key cancer-specific genes accounting for multiple mechanisms of regulation, we have developed the integIRTy software that provides robust and reliable inferences about gene alteration by automatically adjusting for sample heterogeneity as well as technical artifacts using Item Response Theory. To cope with the increasing need for accurate cancer diagnosis and individualized therapy, we have developed a robust and powerful algorithm called SIBER to systematically identify bimodally expressed genes using next generation RNAseq data. We have shown that prediction models built from these bimodal genes have the same accuracy as models built from all genes. Further, prediction models with dichotomized gene expression measurements based on their bimodal shapes still perform well. The effectiveness of outcome prediction using discretized signals paves the road for more accurate and interpretable cancer classification by integrating signals from multiple sources.

Advanced Protein Modeling Method: Benchmarking and Applications in Computer-Aided Drug Discovery

Development of homology modeling methods will remain an area of active research. These methods aim to develop and model increasingly accurate three-dimensional structures of yet uncrystallized therapeutically relevant proteins e.g. Class A G-Protein Coupled Receptors. Incorporating protein flexibility is one way to achieve this goal. Here, I will discuss the enhancement and validation of the ligand-steered modeling, originally developed by Dr. Claudio Cavasotto, via cross modeling of the newly crystallized GPCR structures. This method uses known ligands and known experimental information to optimize relevant protein binding sites by incorporating protein flexibility. The ligand-steered models were able to model, reasonably reproduce binding sites and the co-crystallized native ligand poses of the β2 adrenergic and Adenosine 2A receptors using a single template structure. They also performed better than the choice of template, and crude models in a small scale high-throughput docking experiments and compound selectivity studies. Next, the application of this method to develop high-quality homology models of Cannabinoid Receptor 2, an emerging non-psychotic pain management target, is discussed. These models were validated by their ability to rationalize structure activity relationship data of two, inverse agonist and agonist, series of compounds. The method was also applied to improve the virtual screening performance of the β2 adrenergic crystal structure by optimizing the binding site using β2 specific compounds. These results show the feasibility of optimizing only the pharmacologically relevant protein binding sites and applicability to structure-based drug design projects.