Rac1 GTPase and the Rac1 exchange factor Tiam1 associate with Wnt-responsive promoters to enhance beta-catenin/TCF-dependent transcription in colorectal cancer cells

<p>Abstract</p> <p>Background</p> <p>β-catenin is a key mediator of the canonical Wnt pathway as it associates with members of the T-cell factor (TCF) family at Wnt-responsive promoters to drive the transcription of Wnt target genes. Recently, we showed that Rac1 GTPase synergizes with β-catenin to increase the activity of a TCF-responsive reporter. This synergy was dependent on the nuclear presence of Rac1, since inhibition of its nuclear localization effectively abolished the stimulatory effect of Rac1 on TCF-responsive reporter activity. We hypothesised that Rac1 plays a direct role in enhancing the transcription of endogenous Wnt target genes by modulating the β-catenin/TCF transcription factor complex.</p> <p>Results</p> <p>We employed chromatin immunoprecipitation studies to demonstrate that Rac1 associates with the β-catenin/TCF complex at Wnt-responsive promoters of target genes. This association served to facilitate transcription, since overexpression of active Rac1 augmented Wnt target gene activation, whereas depletion of endogenous Rac1 by RNA interference abrogated this effect. In addition, the Rac1-specific exchange factor, Tiam1, potentiated the stimulatory effects of Rac1 on the canonical Wnt pathway. Tiam1 promoted the formation of a complex containing Rac1 and β-catenin. Furthermore, endogenous Tiam1 associated with endogenous β-catenin, and this interaction was enhanced in response to Wnt3a stimulation. Intriguingly, Tiam1 was recruited to Wnt-responsive promoters upon Wnt3a stimulation, whereas Rac1 was tethered to TCF binding elements in a Wnt-independent manner.</p> <p>Conclusion</p> <p>Taken together, our results suggest that Rac1 and the Rac1-specific activator Tiam1 are components of transcriptionally active β-catenin/TCF complexes at Wnt-responsive promoters, and the presence of Rac1 and Tiam1 within these complexes serves to enhance target gene transcription. Our results demonstrate a novel functional mechanism underlying the cross-talk between Rac1 and the canonical Wnt signalling pathway.</p

Discovery of Novel Hypermethylated Genes in Prostate Cancer Using Genomic CpG Island Microarrays

BACKGROUND: Promoter and 5' end methylation regulation of tumour suppressor genes is a common feature of many cancers. Such occurrences often lead to the silencing of these key genes and thus they may contribute to the development of cancer, including prostate cancer. METHODOLOGY/PRINCIPAL FINDINGS: In order to identify methylation changes in prostate cancer, we performed a genome-wide analysis of DNA methylation using Agilent human CpG island arrays. Using computational and gene-specific validation approaches we have identified a large number of potential epigenetic biomarkers of prostate cancer. Further validation of candidate genes on a separate cohort of low and high grade prostate cancers by quantitative MethyLight analysis has allowed us to confirm DNA hypermethylation of HOXD3 and BMP7, two genes that may play a role in the development of high grade tumours. We also show that promoter hypermethylation is responsible for downregulated expression of these genes in the DU-145 PCa cell line. CONCLUSIONS/SIGNIFICANCE: This study identifies novel epigenetic biomarkers of prostate cancer and prostate cancer progression, and provides a global assessment of DNA methylation in prostate cancer

Epigenome-wide DNA methylation profiling identifies differential methylation biomarkers in high-grade bladder cancer

Epigenetic changes, including CpG island hypermethylation, occur frequently in bladder cancer (BC) and may be exploited for BC detection and distinction between high-grade (HG) and low-grade (LG) disease. Genome-wide methylation analysis was performed using Agilent Human CpG Island Microarrays to determine epigenetic differences between LG and HG cases. Pathway enrichment analysis and functional annotation determined that the most frequently methylated pathways in HG BC were enriched for anterior/posterior pattern specification, embryonic skeletal system development, neuron fate commitment, DNA binding, and transcription factor activity. We identified 990 probes comprising a 32-gene panel that completely distinguished LG from HG based on methylation. Selected genes from this panel, EOMES, GP5, PAX6, TCF4, and ZSCAN12, were selected for quantitative polymerase chain reaction-based validation by MethyLight in an independent series (n=84) of normal bladder samples and LG and HG cases. GP5 and ZSCAN12, two novel methylated genes in BC, were significantly hypermethylated in HG versus LG BC (P≤.03). We validated our data in a second independent cohort of LG and HG BC cases (n=42) from The Cancer Genome Atlas (TCGA). Probes representing our 32-gene panel were significantly differentially methylated in LG versus HG tumors (P≤.04). These results indicate the ability to distinguish normal tissue from cancer, as well as LG from HG, based on methylation and reveal important pathways dysregulated in HG BC. Our findings were corroborated using publicly available data sets from TCGA. Ultimately, the creation of a methylation panel, including GP5 and ZSCAN12, able to distinguish between disease phenotypes will improve disease management and patient outcomes

Specific Variants in the MLH1 Gene Region May Drive DNA Methylation, Loss of Protein Expression, and MSI-H Colorectal Cancer

Background: We previously identified an association between a mismatch repair gene, MLH1, promoter SNP (rs1800734) and microsatellite unstable (MSI-H) colorectal cancers (CRCs) in two samples. The current study expanded on this finding as we explored the genetic basis of DNA methylation in this region of chromosome 3. We hypothesized that specific polymorphisms in the MLH1 gene region predispose it to DNA methylation, resulting in the loss of MLH1 gene expression, mismatch-repair function, and consequently to genome-wide microsatellite instability. Methodology/Principal Findings: We first tested our hypothesis in one sample from Ontario (901 cases, 1,097 controls) and replicated major findings in two additional samples from Newfoundland and Labrador (479 cases, 336 controls) and from Seattle (591 cases, 629 controls). Logistic regression was used to test for association between SNPs in the region of MLH1 and CRC, MSI-H CRC, MLH1 gene expression in CRC, and DNA methylation in CRC. The association between rs1800734 and MSI-H CRCs, previously reported in Ontario and Newfoundland, was replicated in the Seattle sample. Two additional SNPs, in strong linkage disequilibrium with rs1800734, showed strong associations with MLH1 promoter methylation, loss of MLH1 protein, and MSI-H CRC in all three samples. The logistic regression model of MSI-H CRC that included MLH1-promotermethylation status and MLH1 immunohisotchemistry status fit most parsimoniously in all three samples combined. When rs1800734 was added to this model, its effect was not statistically significant (P-value = 0.72 vs. 2.361024 when the SNP was examined alone). Conclusions/Significance: The observed association of rs1800734 with MSI-H CRC occurs through its effect on the MLH1 promoter methylation, MLH1 IHC deficiency, or both

Proposed model for genetic susceptibility to DNA methylation in sporadic MSI-H CRCs.

<p>Specific SNPs predispose the region, including the <i>MLH1</i> gene promoter, to methylation, which results in promoter silencing and loss of <i>MLH1</i> gene expression that is measured by immunohistochemical staining. Loss of the <i>MLH1</i> gene expression leads to genome-wide microsatellite instability and MSI-H colorectal cancer.</p

Region of chromosome 3 examined with genes and 3 SNPs.

<p>A total of 99 polymorphisms were examined in the Ontario samples across a 500kb region of chromosome 3 surrounding the <i>MLH1</i> gene. Genes in this region are outlined (top panel) along with their transcriptional directionality (bottom panel). The three polymorphisms of interest are indicated. Modified from Ensembl (<a href="http://www.ensembl.org" target="_blank">www.ensembl.org</a>).</p

Logistic regression model results for MSI status with various predictor combinations in the combined data.

<p>Age at diagnosis, sex, and location are covariates common to all the models described above. IHC refers to the MLH1 immunohistochemical staining variable, CH3 refers to the <i>MLH1</i> promoter methylation variable, AIC  =  Akaike's information criterion. Logistic regression models for each SNP per study population and for the combined data are shown in <b>Supplementary <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0013314#pone.0013314.s003" target="_blank">File S3</a></b>.</p><p>The role of three SNPs of interest, rs1800734, rs749072, and rs13098279, is explored.</p

Single marker analysis in the combined data for 3 SNPs for CRC cases versus controls, <i>MLH1</i> promoter methylation, MLH1 IHC staining and MSI tumor status.

<p>Analyses of CRC cases versus controls are adjusted for age, sex, and site.</p><p>OR  =  odds ratio, CI  =  confidence interval.</p><p>Single marker results for the above SNPs for each study population are shown in <b>Supplementary <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0013314#pone.0013314.s002" target="_blank">File S2</a></b>.</p