Mechanism of methylation gene reactivation in human cancer cells

Epigenetic silencing of tumor suppressor genes by DNA hypermethylation at promoter regions is a common event in carcinogenesis and tumor progression. Abrogation of methylation and reversal of epigenetic silencing is a very potent way in cancer treatment. However, the reactivation mechanisms are poorly understood. In this study, we first developed a cell line model system named YB5, derived from SW48 cancer cell line, which bears one copy of stably integrated EGFP gene on Chromosome 1p31.1 region. The GFP gene expression is transcriptionally silenced due to the hypermethylated promoter CMV. However, the GFP expression can be restored using demethylating agent 5-aza-2' deoxycytidine (DAC), and detected by FACS and fluorescent microscopy. Using this system, we observed the heterogeneous reactivation induced by DAC treatment. After flow sorting, GFP negative cells exhibited similar level of incomplete demethylation compared to GFP positive cells on repetitive LINE1 element, tumor suppressor genes such as P16, CDH13, and RASSF1a, and CMV promoter as well. However, the local chromatin of CMV-GFP locus altered to an open structure marked by high H3 lysine 9 acetylation and low H3 lysine 27 tri-methylation in GFP positive cells, while the GFP negative cells retained mostly the original repressive marks. Thus, we concluded that DAC induced DNA hypomethylation alone does not directly determine the level of re-expression, and the resetting of the local chromatin structure under hypomethylation environment is required for gene reactivation. Besides, a lentivirus vector-based shRNA screening was performed using the YB5 system. Although it is the rare chance that vector lands in the neighboring region of GFP, we found that the exogenous vector DNA inserted into the upstream region of GFP gene locus led to the promoter demethylation and reactivated the silenced GFP gene. Thus, epigenetic state can be affected by changing of the adjacent nucleic acid sequences. Further, this hypermethylation silenced system was utilized for epigenetic drug screening. We have found that DAC combined with carboplatin would enhance the GFP% yield and increase expression of other tumor suppressor genes than DAC alone, and this synergistic effect may be related to DNA repair process. In summary, these studies reveal that reversing of methylation silencing requires coordinated alterations of DNA methylation, chromatin structure, and local microenvironment. ^

Characterization of cytochrome P450 4F subfamily: Response in traumatic brain injury and gene regulation

CYP4F enzymes metabolize endogenous molecules including arachidonic acid, leukotrienes and prostaglandins. The involvement of these eisosanoids in inflammation has led to the hypothesis that CYP4Fs may modulate inflammatory conditions after traumatic brain injury (TBI). In rat, TBI elicited changes in mRNA expression of CYP4Fs as a function of time in the cerebrum region. These changes in CYP4F mRNA levels inversely correlated with the cerebral leukotriene B4 (LTB4) level following injury at the same time points. TBI also resulted in changes in CYP4F protein expression and localization around the injury site, where CYP4F1 and CYP4F6 immunoreactivity increased in surrounding astrocytes and CYP4F4 immunoreactivity shifted from endothelia of cerebral vessels to astrocytes. The study with rat primary astrocytes indicated that pro-inflammatory cytokines TNFα and IL-1β could affect the transcription of CYP4Fs to a certain degree, whereas the changing pattern in the primary astrocytes appeared to be different from that in the in vivo TBI model.^ In addition, the regulation of CYP4F genes has been an unsolved issue although factors including cytokines and fatty acids appear to affect CYP4Fs expression in multiple models. In this project, HaCaT cells were used as an in vitro cellular model to define signaling pathways involved in the regulation of human CYP4F genes. Retinoic acids inhibited CYP4F11 expression, whereas cytokines TNFα and IL-1β induced transcription of CYP4F11 in HaCaT cells. The induction of CYP4F11 by both cytokines could be blocked by a JNK specific inhibitor, indicating the involvement of the JNK pathway in the up-regulation of CYP4F11. Retinoic acids are known to function in gene regulation through nuclear receptors RARs and RXRs. The RXR agonist LG268 greatly induced transcription of CYP4F11, whereas RAR agonist TTNPB obviously inhibited CYP4F11 transcription, indicating that the down-regulation of CYP4F11 by retinoic acid was mediated by RARs, and that inhibition of CYP4F11 by retinoic acid may also be related to the competition for RXR receptors. Thus, the CYP4F11 gene is regulated by signaling pathways including the RXR pathway and the JNK pathway. In contrast, the regulation mechanism of other CYP4Fs by retinoic acids appears to be different from that of CYP4F11.^

Studies of the expression of DNA repair related genes

This dissertation examines the biological functions and the regulation of expression of DNA ligase I by studying its expression under different conditions.^ The gene expression of DNA ligase I was induced two- to four-fold in S-phase lymphoblastoid cells but was decreased to 15% of control after administration of a DNA damaging agent, 4-nitroquinoline-1-oxide. When cells were induced into differentiation, the expression level of DNA ligase I was decreased to less than 15% of that of the control cells. When the gene of DNA ligase I was examined for tissue specific expression in adult rats, high levels of DNA ligase I mRNA were observed in testis (8-fold), intermediate levels in ovary and brain (4-fold), and low levels were found in intestine, spleen, and liver (1- to 2-fold).^ In confluent cells of normal skin fibroblasts, UV irradiation induced the gene expression of DNA ligase I at 24 and 48 h. The induction of DNA ligase I gene expression requires active p53 protein. Introducing a vector containing the wild type p53 protein in the cells caused an induction of the DNA ligase I protein 24 h after the treatment.^ Our results indicate that, in addition to the regulation by phosphorylation/dephosphorylation, cellular DNA ligase I activity can be regulated at the gene transcription level, and the p53 tumor suppresser is one of the transcription factors for the DNA ligase I gene. Also, our results suggest that DNA ligase I is involved in DNA repair as well as in DNA replication.^ Also, as an early attempt to clone the human homolog of the yeast CDC9 gene which has been shown to be involved in DNA replication, DNA repair, and DNA recombination, we have identified a human gene with mRNA of 1.7 kb. This dissertation studies the gene regulation and the possible biological functions of this new human gene by examining its expression at different stages of the cell cycle, during cell differentiation, and in cellular response to DNA damage.^ The new gene that we recently identified from human cells is highly expressed in brain and reproductive organs (BRE). This BRE gene encodes an mRNA of 1.7-1.9 kb, with an open reading frame of 1,149 bp, and gives rise to a deduced polypeptide of 383 amino acid residues. No extensive homology was found between BRE and sequences from the EMBL-Gene Banks. BRE showed tissue-specific expression in adult rats. The steady state mRNA levels were high in testis (5-6 fold), ovary and brain (3-4 fold) compared to the spleen level, but low in intestine and liver (1-2 fold). The expression of this gene is responsive to DNA damage and/or retinoic acid (RA) treatment. Treatment of fibroblast cells with UV irradiation and 4-nitroquinoline-1-oxide caused more than 90% and 50% decreases in BRE mRNA, respectively. Similar decreases in BRE expression were observed after treatment of the brain glioma cell line U-251 and the promyelocytic cell line HL-60 with retinoic acid. (Abstract shortened by UMI). ^

Longitudinal and logistic analysis of endocrine hormone profiles, physical maturation, and candidate genes related to pubertal events in children

Children who experience early pubertal development have an increased risk of developing cancer (breast, ovarian, and testicular), osteoporosis, insulin resistance, and obesity as adults. Early pubertal development has been associated with depression, aggressiveness, and increased sexual prowess. Possible explanations for the decline in age of pubertal onset include genetics, exposure to environmental toxins, better nutrition, and a reduction in childhood infections. In this study we (1) evaluated the association between 415 single nucleotide polymorphisms (SNPs) from hormonal pathways and early puberty, defined as menarche prior to age 12 in females and Tanner Stage 2 development prior to age 11 in males, and (2) measured endocrine hormone trajectories (estradiol, testosterone, and DHEAS) in relation to age, race, and Tanner Stage in a cohort of children from Project HeartBeat! At the end of the 4-year study, 193 females had onset of menarche and 121 males had pubertal staging at age 11. African American females had a younger mean age at menarche than Non-Hispanic White females. African American females and males had a lower mean age at each pubertal stage (1-5) than Non-Hispanic White females and males. African American females had higher mean BMI measures at each pubertal stage than Non-Hispanic White females. Of the 415 SNPs evaluated in females, 22 SNPs were associated with early menarche, when adjusted for race ( p<0.05), but none remained significant after adjusting for multiple testing by False Discovery Rate (p<0.00017). In males, 17 SNPs were associated with early pubertal development when adjusted for race (p<0.05), but none remained significant when adjusted for multiple testing (p<0.00017). ^ There were 4955 hormone measurements taken during the 4-year study period from 632 African American and Non-Hispanic White males and females. On average, African American females started and ended the pubertal process at a younger age than Non-Hispanic White females. The mean age of Tanner Stage 2 breast development in African American and Non-Hispanic White females was 9.7 (S.D.=0.8) and 10.2 (S.D.=1.1) years, respectively. There was a significant difference by race in mean age for each pubertal stage, except Tanner Stage 1 for pubic hair development. Both Estradiol and DHEAS levels in females varied significantly with age, but not by race. Estradiol and DHEAS levels increased from Tanner Stage 1 to Tanner Stage 5.^ African American males had a lower mean age at each Tanner Stage of development than Non-Hispanic White males. The mean age of Tanner Stage 2 genital development in African American and Non-Hispanic White males was 10.5 (S.D.=1.1) and 10.8 (S.D.=1.1) years, respectively, but this difference was not significant (p=0.11). Testosterone levels varied significantly with age and race. Non-Hispanic White males had higher levels of testosterone than African American males from Tanner Stage 1-4. Testosterone levels increased for both races from Tanner Stage 1 to Tanner Stage 5. Testosterone levels had the steepest increase from ages 11-15 for both races. DHEAS levels in males varied significantly with age, but not by race. DHEAS levels had the steepest increase from ages 14-17. ^ In conclusion, African American males and females experience pubertal onset at a younger age than Non-Hispanic White males and females, but in this study, we could not find a specific gene that explained the observed variation in age of pubertal onset. Future studies with larger study populations may provide a better understanding of the contribution of genes in early pubertal onset.^

Systems Biology Approaches to Probe Gene Regulation in Bacteria

Mechanisms that allow pathogens to colonize the host are not the product of isolated genes, but instead emerge from the concerted operation of regulatory networks. Therefore, identifying components and the systemic behavior of networks is necessary to a better understanding of gene regulation and pathogenesis. To this end, I have developed systems biology approaches to study transcriptional and post-transcriptional gene regulation in bacteria, with an emphasis in the human pathogen Mycobacterium tuberculosis (Mtb). First, I developed a network response method to identify parts of the Mtb global transcriptional regulatory network utilized by the pathogen to counteract phagosomal stresses and survive within resting macrophages. As a result, the method unveiled transcriptional regulators and associated regulons utilized by Mtb to establish a successful infection of macrophages throughout the first 14 days of infection. Additionally, this network-based analysis identified the production of Fe-S proteins coupled to lipid metabolism through the alkane hydroxylase complex as a possible strategy employed by Mtb to survive in the host. Second, I developed a network inference method to infer the small non-coding RNA (sRNA) regulatory network in Mtb. The method identifies sRNA-mRNA interactions by integrating a priori knowledge of possible binding sites with structure-driven identification of binding sites. The reconstructed network was useful to predict functional roles for the multitude of sRNAs recently discovered in the pathogen, being that several sRNAs were postulated to be involved in virulence-related processes. Finally, I applied a combined experimental and computational approach to study post-transcriptional repression mediated by small non-coding RNAs in bacteria. Specifically, a probabilistic ranking methodology termed rank-conciliation was developed to infer sRNA-mRNA interactions based on multiple types of data. The method was shown to improve target prediction in Escherichia coli, and therefore is useful to prioritize candidate targets for experimental validation.

Detecting genetic and nutritional lung cancer risk factors related to folate metabolism using Bayesian generalized linear models

Complex diseases, such as cancer, are caused by various genetic and environmental factors, and their interactions. Joint analysis of these factors and their interactions would increase the power to detect risk factors but is statistically. Bayesian generalized linear models using student-t prior distributions on coefficients, is a novel method to simultaneously analyze genetic factors, environmental factors, and interactions. I performed simulation studies using three different disease models and demonstrated that the variable selection performance of Bayesian generalized linear models is comparable to that of Bayesian stochastic search variable selection, an improved method for variable selection when compared to standard methods. I further evaluated the variable selection performance of Bayesian generalized linear models using different numbers of candidate covariates and different sample sizes, and provided a guideline for required sample size to achieve a high power of variable selection using Bayesian generalize linear models, considering different scales of number of candidate covariates. ^ Polymorphisms in folate metabolism genes and nutritional factors have been previously associated with lung cancer risk. In this study, I simultaneously analyzed 115 tag SNPs in folate metabolism genes, 14 nutritional factors, and all possible genetic-nutritional interactions from 1239 lung cancer cases and 1692 controls using Bayesian generalized linear models stratified by never, former, and current smoking status. SNPs in MTRR were significantly associated with lung cancer risk across never, former, and current smokers. In never smokers, three SNPs in TYMS and three gene-nutrient interactions, including an interaction between SHMT1 and vitamin B12, an interaction between MTRR and total fat intake, and an interaction between MTR and alcohol use, were also identified as associated with lung cancer risk. These lung cancer risk factors are worthy of further investigation.^

RNA-SEQUENCING APPLICATIONS: GENE EXPRESSION QUANTIFICATION AND METHYLATOR PHENOTYPE IDENTIFICATION

My dissertation focuses on two aspects of RNA sequencing technology. The first is the methodology for modeling the overdispersion inherent in RNA-seq data for differential expression analysis. This aspect is addressed in three sections. The second aspect is the application of RNA-seq data to identify the CpG island methylator phenotype (CIMP) by integrating datasets of mRNA expression level and DNA methylation status. Section 1: The cost of DNA sequencing has reduced dramatically in the past decade. Consequently, genomic research increasingly depends on sequencing technology. However it remains elusive how the sequencing capacity influences the accuracy of mRNA expression measurement. We observe that accuracy improves along with the increasing sequencing depth. To model the overdispersion, we use the beta-binomial distribution with a new parameter indicating the dependency between overdispersion and sequencing depth. Our modified beta-binomial model performs better than the binomial or the pure beta-binomial model with a lower false discovery rate. Section 2: Although a number of methods have been proposed in order to accurately analyze differential RNA expression on the gene level, modeling on the base pair level is required. Here, we find that the overdispersion rate decreases as the sequencing depth increases on the base pair level. Also, we propose four models and compare them with each other. As expected, our beta binomial model with a dynamic overdispersion rate is shown to be superior. Section 3: We investigate biases in RNA-seq by exploring the measurement of the external control, spike-in RNA. This study is based on two datasets with spike-in controls obtained from a recent study. We observe an undiscovered bias in the measurement of the spike-in transcripts that arises from the influence of the sample transcripts in RNA-seq. Also, we find that this influence is related to the local sequence of the random hexamer that is used in priming. We suggest a model of the inequality between samples and to correct this type of bias. Section 4: The expression of a gene can be turned off when its promoter is highly methylated. Several studies have reported that a clear threshold effect exists in gene silencing that is mediated by DNA methylation. It is reasonable to assume the thresholds are specific for each gene. It is also intriguing to investigate genes that are largely controlled by DNA methylation. These genes are called “L-shaped” genes. We develop a method to determine the DNA methylation threshold and identify a new CIMP of BRCA. In conclusion, we provide a detailed understanding of the relationship between the overdispersion rate and sequencing depth. And we reveal a new bias in RNA-seq and provide a detailed understanding of the relationship between this new bias and the local sequence. Also we develop a powerful method to dichotomize methylation status and consequently we identify a new CIMP of breast cancer with a distinct classification of molecular characteristics and clinical features.

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.

Patenting genes and gene sequences: Analysis of public health implications and the law

At issue is whether or not isolated DNA is patent eligible under the U.S. Patent Law and the implications of that determination on public health. The U.S. Patent and Trademark Office has issued patents on DNA since the 1980s, and scientists and researchers have proceeded under that milieu since that time. Today, genetic research and testing related to the human breast cancer genes BRCA1 and BRCA2 is conducted within the framework of seven patents that were issued to Myriad Genetics and the University of Utah Research Foundation between 1997 and 2000. In 2009, suit was filed on behalf of multiple researchers, professional associations and others to invalidate fifteen of the claims underlying those patents. The Court of Appeals for the Federal Circuit, which hears patent cases, has invalidated claims for analyzing and comparing isolated DNA but has upheld claims to isolated DNA. The specific issue of whether isolated DNA is patent eligible is now before the Supreme Court, which is expected to decide the case by year's end. In this work, a systematic review was performed to determine the effects of DNA patents on various stakeholders and, ultimately, on public health; and to provide a legal analysis of the patent eligibility of isolated DNA and the likely outcome of the Supreme Court's decision. ^ A literature review was conducted to: first, identify principle stakeholders with an interest in patent eligibility of the isolated DNA sequences BRCA1 and BRCA2; and second, determine the effect of the case on those stakeholders. Published reports that addressed gene patents, the Myriad litigation, and implications of gene patents on stakeholders were included. Next, an in-depth legal analysis of the patent eligibility of isolated DNA and methods for analyzing it was performed pursuant to accepted methods of legal research and analysis based on legal briefs, federal law and jurisprudence, scholarly works and standard practice legal analysis. ^ Biotechnology, biomedical and clinical research, access to health care, and personalized medicine were identified as the principle stakeholders and interests herein. Many experts believe that the patent eligibility of isolated DNA will not greatly affect the biotechnology industry insofar as genetic testing is concerned; unlike for therapeutics, genetic testing does not require tremendous resources or lead time. The actual impact on biomedical researchers is uncertain, with greater impact expected for researchers whose work is intended for commercial purposes (versus basic science). The impact on access to health care has been surprisingly difficult to assess; while invalidating gene patents might be expected to decrease the cost of genetic testing and improve access to more laboratories and physicians' offices that provide the test, a 2010 study on the actual impact was inconclusive. As for personalized medicine, many experts believe that the availability of personalized medicine is ultimately a public policy issue for Congress, not the courts. ^ Based on the legal analysis performed in this work, this writer believes the Supreme Court is likely to invalidate patents on isolated DNA whose sequences are found in nature, because these gene sequences are a basic tool of scientific and technologic work and patents on isolated DNA would unduly inhibit their future use. Patents on complementary DNA (cDNA) are expected to stand, however, based on the human intervention required to craft cDNA and the product's distinction from the DNA found in nature. ^ In the end, the solution as to how to address gene patents may lie not in jurisprudence but in a fundamental change in business practices to provide expanded licenses to better address the interests of the several stakeholders. ^

The transcriptional regulation of the {\it neu\/} gene: Examples of activation, repression, and cell-specific expression

The neu oncogene encodes a growth factor receptor-like protein, p185, with an intrinsic tyrosine kinase activity. A single point mutation, an A to T transversion resulting in an amino acid substitution from valine to glutamic acid, in the transmembrane domain of the rat neu gene was found to be responsible for the transforming and tumorigenic phenotype of the cells that carry it. In contrast, the human proto-neu oncogene is frequently amplified in tumors and cell lines derived from tumors and the human neu gene overexpression/amplification in breast and ovarian cancers is known to correlate with poor patient prognosis. Examples of the human neu gene overexpression in the absence of gene amplification have been observed, which may suggest the significant role of the transcriptional and/or post-transcriptional control of the neu gene in the oncogenic process. However, little is known about the transcriptional mechanisms which regulate the neu gene expression. In this study, three examples are presented to demonstrate the positive and negative control of the neu gene expression.^ First, by using band shift assays and methylation interference analyses, I have identified a specific protein-binding sequence, AAGATAAAACC ($-$466 to $-$456), that binds a specific trans-acting factor termed RVF (for EcoRV factor on the neu promoter). The RVF-binding site is required for maximum transcriptional activity of the rat neu promoter. This same sequence is also found in the corresponding regions of both human and mouse neu promoters. Furthermore, this sequence can enhance the CAT activity driven by a minimum promoter of the thymidine kinase gene in an orientation-independent manner, and thus it behaves as an enhancer. In addition, Southwestern (DNA-protein) blot analysis using the RVF-binding site as a probe points to a 60-kDa polypeptide as a potential candidate for RVF.^ Second, it has been reported that the E3 region of adenovirus 5 induces down-regulation of epidermal growth factor (EGF) receptor through endocytosis. I found that the human neu gene product, p185, (an EGF receptor-related protein) is also down-regulated by adenovirus 5, but via a different mechanism. I demonstrate that the adenovirus E1a gene is responsible for the repression of the human neu gene at the transcriptional level.^ Third, a differential expression of the neu gene has been found in two cell model systems: between the mouse fibroblast Swiss-Webster 3T3 (SW3T3) and its variant NR-6 cells; and between the mouse liver tumor cell line, Hep1-a, and the mouse pancreas tumor cell line, 266-6. Both NR-6 and 266-6 cell lines are not able to express the neu gene product, p185. I demonstrate that, in both cases, the transcriptional repression of the neu gene may account for the lack of the p185 expression in these two cell lines. ^

Alterations in the ras oncogene and the p53 tumor suppressor gene in ultraviolet radiation-induced skin carcinogenesis

A rapid increase of the ultraviolet radiation (UVR)-related skin cancer incidence has attracted more and more public attention during the last few decades. Prevention and treatment of UVR-related skin cancer has become an important public health issue in the United States. Recent studies indicate that mutations in ras and/or p53 genes may be involved in UVR-induced skin tumor development but the precise molecular mechanism remains unclear. In this study, alterations of H-ras and p53 genes were investigated in different stages of carcinogenesis in a chronic UVR (solar simulator) exposure-induced Sencar mouse skin carcinogenesis model in order to clarify the role of the alterations of these genes during the skin carcinogenesis process and to further understand the mechanisms by which UVR causes skin cancer.^ Positive ras-p21 staining in cell membranes and cytosol were detected in 18/33 (55%) of squamous cell carcinomas (SCCs), but were not detected in UV-exposed skin, papillomas, or spindle cell tumors (SCTs). Positive staining of the malignant progression marker K13 was found in 17/33 (52%) of SCCs only. A significant positive correlation was observed between the K13 and the ras-p21 expression. Polymerase chain reaction (PCR)-based single strand conformation polymorphism (SSCP) analysis and gene sequencing analysis revealed three point mutations, one (codon 56) in UV-exposed non-tumor bearing skin and the other two (codons 21 and 13) in SCCs. No UV-specific mutation patterns were found.^ Positive p53 nuclear staining was found in 10/37 (27%) of SCCs and 12/24 (50%) of SCTs, but was not detected in normal skin or papillomas. PCR-based SSCP and sequencing analysis revealed eight point mutations in exons 5 and 6 (four in SCTs, two in SCCs, and two in UV-exposed skin) including six C-T or C-A transitions. Four of the mutations occurred at a dipyrimidine (CC) sequence. The pattern of the mutations indicated that the mutagenic lesions were induced by UVR.^ These results indicate that overexpression of ras-p21 in conjunction with aberrant expression of K13 occurred frequently in UVR-induced SCCs in Sencar mouse skin. The point mutation in the H-ras gene appeared to be a rare event in UVR skin carcinogenesis and may not be responsible for overexpression of ras-p21. UVR-induced P53 gene alteration is a frequent event in UVR-induced SCCs and later stage SCT tumors in Sencar mice skin, suggesting the p53 gene mutation plays an important role in skin tumor malignant progression. ^

Functional analysis of SOX9 in chondrogenesis by targeted gene inactivation

Sox9 is a Sry-related HMG-domain containing transcription factor. Lines of evidence suggest that Sox9 has a potential role in skeletal development. During mouse development, Sox9 is predominantly expressed in all chondroprogenitors and differentiated chondrocytes, throughout the deposition of cartilage matrix. Mutations in one allele of SOX9 in humans result in campomelic dysplasia (CD), a skeletal dysplasia. syndrome characterized by the bowing of long bones. Moreover, Sox9 binds to and activates chondrocyte-specific enhancers in Col2a1 and Col11a2 genes. To further investigate the function of Sox9 in chondrogenesis, we analyzed chimeras derived from Sox9 heterozygous and homozygous null embryonic stem (ES) cells. In mouse chimeras, Sox9 −/− cells were excluded from all cartilages and did not express chondrocyte-specific genes. The segregation occurred during mesenchymal condensation. No cartilages developed in teratocarcinomas derived from Sox9 −/− ES cells. Mice heterozygous for the Sox9 mutation died neonatally and exhibited skeletal abnormalities resembling those of the CD patients. The Sox9 +/− mutants had a cleft palate and hypoplasia of scapula, pelvis and other skeletal structures derived by endochondral ossification. Bending of the radius, ulna and tibia cartilage was prominent at embryonic day 14.5 (E14.5). At E12.5 many pre-cartilaginous condensations were already defective. Advanced ossification was observed and the hypertrophic zone was enlarged in the growth plates, suggesting that Sox9 also regulates hypertrophic chondrocyte differentiation. Our results identify Sox9 as the first essential regulator of chondrocyte differentiation, which plays multiple roles in chondrogenesis. ^