Statistical characterization and development of summary measures of non-normal distributions of nuclear morphometry data from prostate cancer cells for use as prognostic indicators

Nuclear morphometry (NM) uses image analysis to measure features of the cell nucleus which are classified as: bulk properties, shape or form, and DNA distribution. Studies have used these measurements as diagnostic and prognostic indicators of disease with inconclusive results. The distributional properties of these variables have not been systematically investigated although much of the medical data exhibit nonnormal distributions. Measurements are done on several hundred cells per patient so summary measurements reflecting the underlying distribution are needed.^ Distributional characteristics of 34 NM variables from prostate cancer cells were investigated using graphical and analytical techniques. Cells per sample ranged from 52 to 458. A small sample of patients with benign prostatic hyperplasia (BPH), representing non-cancer cells, was used for general comparison with the cancer cells.^ Data transformations such as log, square root and 1/x did not yield normality as measured by the Shapiro-Wilks test for normality. A modulus transformation, used for distributions having abnormal kurtosis values, also did not produce normality.^ Kernel density histograms of the 34 variables exhibited non-normality and 18 variables also exhibited bimodality. A bimodality coefficient was calculated and 3 variables: DNA concentration, shape and elongation, showed the strongest evidence of bimodality and were studied further.^ Two analytical approaches were used to obtain a summary measure for each variable for each patient: cluster analysis to determine significant clusters and a mixture model analysis using a two component model having a Gaussian distribution with equal variances. The mixture component parameters were used to bootstrap the log likelihood ratio to determine the significant number of components, 1 or 2. These summary measures were used as predictors of disease severity in several proportional odds logistic regression models. The disease severity scale had 5 levels and was constructed of 3 components: extracapsulary penetration (ECP), lymph node involvement (LN+) and seminal vesicle involvement (SV+) which represent surrogate measures of prognosis. The summary measures were not strong predictors of disease severity. There was some indication from the mixture model results that there were changes in mean levels and proportions of the components in the lower severity levels. ^

Effect of nonnormal random components on level and power in group-randomized trials

The use of group-randomized trials is particularly widespread in the evaluation of health care, educational, and screening strategies. Group-randomized trials represent a subset of a larger class of designs often labeled nested, hierarchical, or multilevel and are characterized by the randomization of intact social units or groups, rather than individuals. The application of random effects models to group-randomized trials requires the specification of fixed and random components of the model. The underlying assumption is usually that these random components are normally distributed. This research is intended to determine if the Type I error rate and power are affected when the assumption of normality for the random component representing the group effect is violated. ^ In this study, simulated data are used to examine the Type I error rate, power, bias and mean squared error of the estimates of the fixed effect and the observed intraclass correlation coefficient (ICC) when the random component representing the group effect possess distributions with non-normal characteristics, such as heavy tails or severe skewness. The simulated data are generated with various characteristics (e.g. number of schools per condition, number of students per school, and several within school ICCs) observed in most small, school-based, group-randomized trials. The analysis is carried out using SAS PROC MIXED, Version 6.12, with random effects specified in a random statement and restricted maximum likelihood (REML) estimation specified. The results from the non-normally distributed data are compared to the results obtained from the analysis of data with similar design characteristics but normally distributed random effects. ^ The results suggest that the violation of the normality assumption for the group component by a skewed or heavy-tailed distribution does not appear to influence the estimation of the fixed effect, Type I error, and power. Negative biases were detected when estimating the sample ICC and dramatically increased in magnitude as the true ICC increased. These biases were not as pronounced when the true ICC was within the range observed in most group-randomized trials (i.e. 0.00 to 0.05). The normally distributed group effect also resulted in bias ICC estimates when the true ICC was greater than 0.05. However, this may be a result of higher correlation within the data. ^

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.

Role of the cyclin dependent kinase-4 in normal and neoplastic proliferation

In the last few years, our laboratory has studied the regulatory mechanisms of proliferation and differentiation in epidermal tissues. Our results showed differences in the roles of cyclin dependent-kinases 4 and 6, and the three D-type cyclins, during normal epidermal proliferation and neoplastic development. Thus, to elucidate the role of the different cell cycle regulators, we developed transgenic mice that overexpress CDK4 (K5-CDK4), or their cognate D-type cyclins, in epithelial tissues. The most severe phenotype was observed in K5-CDK4 animals that developed dermal fibrosis, epidermal hyperplasia and hypertrophy. Forced expression of CDK4 in the epidermal basal cell layer increased the malignant conversion of skin papillomas to squamous cell carcinomas (SCC). Contrastingly, lack of CDK4 completely inhibited tumor development, suggesting that CDK4 is required in this process. Biochemical studies demonstrated that p21 Cip1 and p27Kip1 inhibitors are sequestered by CDK4 resulting in indirect activation of Cyclin E/CDK2, implicating the non-catalytic activity of CDK4 in deregulation of the cell cycle progression. ^ It has been proposed that the proliferative and oncogenic role of Myc is linked to its ability to induce the transcription of CDK4, cyclin D1, and cyclin D2 in vitro. Deregulation of Myc oncogene has been found in several human cancers. Also it has been demonstrated that CDK4 has the ability to functionally inactivate the product of the tumor suppressor gene Rb, providing a link between Myc and the CDK4/cyclin D1/pRb/p16 pathway in some malignant tumors. Here, we sought to determine the role of CDK4 as a mediator of Myc activities by developing a Myc overexpressing mouse nullizygous for CDK4. We demonstrated that lack of CDK4 results in reduced keratinocyte proliferation and epidermal thickness in K5-Myc/CDK4-null mice. In addition, complete reversion of tumor development was observed. All together, this work demonstrates that CDK4 acts as an oncogene independent of the D-type cyclin levels and it is an important mediator of the tumorigenesis induced by Myc. In addition, we showed that the sequestering activity of CDK4 is critical for the development of epidermal hyperplasia during normal proliferation, malignant progression from papillomas to squamous cell carcinomas, and tumorigenesis induced by Myc. ^

BLyS/BAFF-R signaling pathway in human aggressive non Hodgkin's lymphoma B cell and normal peripheral blood B lymphocytes

B-lymphocyte stimulator (BLyS also called BAFF), is a potent cell survival factor expressed in many hematopoietic cells. BLyS levels are elevated in the serum of non-Hodgkin lymphoma (NHL) patients, and have been reported to be associated with disease progression, and prognosis. To understand the mechanisms involved in BLyS gene expression and regulation, we examined expression, function, and regulation of the BLyS gene in B cell non-Hodgkin's lymphoma (NHL-B) cells. BLyS is constitutively expressed in aggressive NHL-B cells including large B cell lymphoma (LBCL) and mantle cell lymphoma (MCL) contributing to survival and proliferation of malignant B cells. Two important transcription factors, NF-κB and NFAT, were found to be involved in regulating BLyS expression through at least one NF-κB and two NFAT binding sites in the BLyS promoter. Further study indicates that the constitutive activation of NF-κB and BLyS in NHL-B cells forms a positive feedback loop contributing to cell survival and proliferation. In order to further investigate BLyS signaling pathway, we studied the function of BAFF-R, a major BLyS receptor, on B cells survival and proliferation. Initial study revealed that BAFF-R was also found in the nucleus, in addition to its presence on plasma membrane of B cells. Nuclear presentation of BAFF-R can be increased by anti-IgM and soluble BLyS treatment in normal peripheral B lymphocytes. Inhibition of BLyS expression decreases nuclear BAFF-R level in LBCL cells. Furthermore, we showed that BAFF-R translocated to nucleus through the classic karyopherin pathway. A candidate nuclear localization sequence (NLS) was identified in the BAFF-R protein sequence and mutation of this putative NLS can block BAFF-R entering nucleus and LBCL cell proliferation. Further study showed that BAFF-R co-localized with NF-κB family member, c-rel in the nucleus. We also found BAFF-R mediated transcriptional activity, which could be increased by c-rel. We also found that nuclear BAFF-R could bind to the NF-κB binding site on the promoters of NF-κB target genes such as BLyS, CD154, Bcl-xL, Bfl-1/A1 and IL-8. These findings indicate that BAFF-R may also promote survival and proliferation of normal B cells and NHL-B cells by directly functioning as a transcriptional co-factor with NF-κB family member. ^

Identification and characterization of cellular genes differentially expressed in a subset of tumors with non -functional WT1

Wilms tumor (WT) or nephroblastoma is a genetically heterogeneous pediatric renal tumor that accounts for 6–7% of all childhood cancers in the U.S. WT1, located at 11p13, is the sole WT gene cloned to date. Additional genomic regions containing genes that play a role in the development of Wilms tumor include 11p15, 7p, 16q, 1p, 17q and 19q. This heterogeneity has made it extremely difficult to develop an understanding of the pathways involved in the development of WT, even in the 5–20% of tumors that show mutations at the WT1 locus. My research addresses this gap in our current comprehension of the development of WT. ^ I have used two complementary approaches to extend the current understanding of molecular changes involved in the development of WT. In order to minimize complexities due to genetic heterogeneity, I confined my analysis to the WT1 pathway by assessing those genetically defined tumors that carry WT1 mutations. WT1 encodes a zinc finger transcription factor, and in vitro studies have identified many genes that are potentially regulated in vivo by WT1. However, there is very little in vivo data that suggests that they are transcriptionally regulated endogenously by WT1. In one approach I assessed the role of WT1 in the in vivo regulation of PDGFA and IGF2, two genes that are strong contenders for endogenous regulation by WT1. Using primary tissue samples, I found no correlation between the level of RNA expression of WT1 with either PDGFA or IGF2, suggesting that WT1 does not play a critical role in their expression in either normal kidney or WT. ^ In a parallel strategy, using differential display analysis I compared global gene expression in a subset of tumors with known homozygous inactivating WT1 mutations (WT1-tumors) to the gene expression in a panel of appropriate control tissues (fetal kidney, normal kidney, rhabdoid tumor and pediatric renal cell carcinoma). Transcripts that are aberrantly expressed in this subset of Wilms tumors are candidates for endogenous transcriptional regulation by WT1 as well as for potentially functioning in the development of WT. By this approach I identified several differentially expressed transcripts. I further characterized two of these transcripts, identifying a candidate WT gene in the process. I then performed a detailed analysis of this WT candidate gene, which maps to 7p. Future studies will shed more light on the role of these differentially expressed genes in WT. ^