S100A4 is a molecular mediator of endometrial carcinoma invasion

The molecular mechanisms of endometrail cancer invasion are poorly understood. S100A4, a member of the S100 Ca2+-binding protein family, was identified by oligonucleotide microarray qRT-PCR, and IHC, to be highly overexpressed in invasive endometrial carcinomas compared to non-invasive tumors. HEC-1A endometrial cancer cells transfected with S100A4 siRNA had undetectable S100A4 protein, decreased migration and invasion. The mechanism of S100A4 upregulation in endometrial cancer remains unclear. Methylation of the S100A4 gene was detected in benign endometrial glands and grade 1 tumors with no S100A4 expression. In contrast, grade 3 endometrioid tumors with high S100A4 expression showed no methylation of the gene. 5-Aza-2'-deoxycytidine, an inhibitor of DNA methyltransferase, induced the expression of S100A4 in the less invasive EC cell line, KLE, in which the S100A4 gene is hypermethylated and minimally expressed. S100A4 was induced during TGF-β1-triggered cell scattering in HEC-1A cells, in which S100A4 was demethylated. Transfection of HEC-1A cells with S100A4 siRNA significantly reduced the effect of TGF-β1 on basal migration and invasion. Our preliminary data suggested that this upregulation was mediated by the transcription factor Snail. One Snail binding consensus site was found in the region where DNA methylation was closely correlated with S100A4 gene expression. Chromatin immunoprecipitation assay confirmed the binding of Snail to this consensus site in HEC-1A cells. In SPEC2 endometrial cancer cells, loss of Snail leads to repressed S100A4 gene expression. Similar to S100A4, Snail was overexpressed in aggressive endometrial tumors. Our study suggested that the S100A4 gene was demethylated and further upregulated by the TGF-β1 and Snail pathway in invasive endometrial cancer. S100A4 could potentially serve as a good molecular marker for invasiveness and a target for therapeutic intervention for advanced endometrial cancer. ^

Is there an association between choline/betaine dietary intake and lung cancer?

Choline and betaine are important methyl donors that contribute to protein and phospholipid synthesis and DNA methylation. They can either be obtained through diet or synthesized de novo. Evidence from human and animal research indicates that choline metabolic pathways may be activated during a variety of diseases, including cancer. Studies have been conducted to investigate the role of dietary intake of choline and betaine on cancers, but results vary among studies by cancer types, and no such study had been conducted for lung cancer. We conducted a case-control study to explore the association between choline and betaine dietary intake and lung cancer. A total of 2807 cases and 2919 controls were included in the study. After adjusting for total calorie intake, age, sex, race and smoking status, multivariable logistic regression analysis revealed a significant negative association between choline/betaine intake and lung cancer. Specifically, we observed that higher choline intake was associated with reduced lung cancer odds, and the association did not differ significantly by smoking status. A similar negative trend was observed in the association between betaine intake and lung cancer after adjusting for total calorie intake, age, sex, smoking status, race, and pack-years of smoking. However, this association was strongly affected by smoking. No significant association was observed with increased betaine intake and lung cancer among never smokers, but higher betaine intake was strongly associated with reduced lung cancer odds among smokers, and lower odds ratios were observed among current smokers than among former smokers. Our results suggest that high intake of choline may be protective for lung cancer independent of smoking status, while high betaine intake may mitigate the adverse effect of smoking on lung cancer, and help prevent lung cancer among smokers.^

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.

Regulation of Set1-mediated methylation of Dam1

Eukaryotic genomes exist within a dynamic structure named chromatin in which DNA is wrapped around an octamer of histones forming the nucleosome. Histones are modified by a range of posttranslational modifications including methylation, phosphorylation, and ubiquitination, which are integral to a range of DNA-templated processes including transcriptional regulation. A hallmark for transcriptional activity is methylation of histone H3 on lysine (K) 4 within active gene promoters. In S. cerevisiae, H3K4 methylation is mediated by Set1 within the COMPASS complex. Methylation requires prior ubiquitination of histone H2BK123 by the E2-E3 ligases Rad6 and Bre1, as well as the Paf1 transcriptional elongation complex. This regulatory pathway exemplifies cross-talk in trans between posttranslational modifications on distinct histone molecules. Set1 has an additional substrate in the kinetochore protein Dam1, which is methylated on K233. This methylation antagonizes phosphorylation of adjacent serines by the Ipl1 Aurora kinase. The discovery of a second Set1 substrate raised the question of how Set1 function is regulated at the kinetochore. I hypothesized that transcriptional regulatory factors essential for H3K4 methylation at gene promoters might also regulate Set1-mediated methylation of Dam1K233. Here I show that the regulatory factors essential for COMPASS activity at gene promoters is also indispensable for the methylation of Dam1K233. Deletion of members of the COMPASS complex leads to loss of Dam1K233 methylation. In addition, deletion of Rad6, Bre1, or members of the Paf1 complex abolishes Dam1 methylation. The role of Rad6 and Bre1 in Dam1 methylation is dependent on H2BK123 ubiquitination, as mutation of K123 within H2B results in complete loss of Dam1 methylation. Importantly, methylation of Dam1K233 is independent of transcription and occurs at the kinetochore. My results demonstrate that Set1-mediated methylation is regulated by a general pathway regardless of substrate that is composed of transcriptional regulatory factors functioning independently of transcription at the kinetochore. My data provide the first example of cross-talk in trans between modifications on a histone and a non-histone protein. Additionally, my results indicate that several factors previously thought to be required for Set1 function at gene promoters are more generally required for the catalytic activity of the COMPASS complex regardless of substrate or cellular process.

Involvement of histone H3 methylation in Tup1-Ssn6 repression

The Tup1-Ssn6 complex regulates the expression of diverse classes of genes in Saccharomyces cerevisiae including those regulated by mating type, DNA damage, glucose, and anaerobic stress. The complex is recruited to target genes by sequence-specific repressor proteins. Once recruited to particular promoters, it is not completely clear how it functions to block transcription. Repression probably occurs through interactions with both the basal transcriptional machinery and components of chromatin. Tup1 interactions with chromatin are strongly influenced by acetylation of histories H3 and H4. Tup1 binds to underacetylated histone tails and requires multiple histone deacetylases (HDACs) for its repressive functions. Like acetylation, histone methylation is involved in regulation of gene expression. The possible role of histone methylation in Tup1 repression is not known. Here we examined possible roles of histone methyltransferases in Tup1-Ssn6 functions. We found that like other genes, Tup1-Ssn6 target genes exhibit increases in the levels of histone H3 lysine 4 methylation upon activation. However, deletion of individual or multiple histone methyltransferases (HMTs) and other SET-domain containing genes has no apparent effect on Tup1-Ssn6 mediated repression of a number of well-defined targets. Interestingly, we discovered that Ssn6 interacts with Set2. Since deletion of SET2 does not affect Tup1-Ssn6 repression, Ssn6 may utilize Set2 in other contexts to regulate gene repression. In order examine if the two components of the Tup1-Ssn6 complex have independent functions in the cell, we identified genes differentially expressed in tup1Δ and ssn6Δ mutants using DNA microarrays. Our data indicate that ∼4% of genes in the cell are regulated by Ssn6 independently of Tup1. In addition, expression of genes regulated by Tup1-Ssn6 seems to be differently affected by deletion of Ssn6 and deletion of Tup1, which indicates that these components might have separate functions. Our data shed new light on the classical view of Tup1-Ssn6 functions, and indicate that Ssn6 might have repressive functions as well. ^