Detection of RASSF1A and RAR? Hypermethylation in Serum DNA from Breast Cancer Patients

Breast cancer is fast emerging as the leading cancer amongst females, especially in young females in metropolitan cities in India. The epigenetic alterations involved in the onset and progression of breast cancer may serve as biomarkers for early detection and prognosis of the disease. Furthermore, using body fluids such as serum offers a non-invasive method to procure multiple samples for such analyses. In this study, we examined methylation status of two normally unmethylated but biologically significant cancer genes, RAS association domain family protein 1A (RASSF1A) and Retionic acid receptor ? (RAR?) by Methylation Specific PCR (MSP) in invasive ductal carcinomas of the breast and paired serum DNA. RASSF1A was found to be methylated in 17 of 20 (85%) breast tumors; while sera from 15 of 20 (75%) of the patients showed concordant methylated RASSF1A, with a sensitivity of 88%. RAR? was methylated in 2/20 (10%) breast tumors. A gene unmethylated in the tumor DNA was always found to be unmethylated in the matched serum DNA for both RASSF1A and RAR? genes; hence specificity was 100%. Immunohistochemical analysis of RAR? protein in 15 breast carcinoma patients harboring unmethylated RAR? in tumors and serum DNA showed the expression of RAR? protein in tumors and paired normal breast tissues, confirming the MSP findings, suggesting that RAR? promoter is functional in these cases. This study underscores the potential utility of DNA methylation based screening of serum, a readily accessible body fluid, as a surrogate marker for early detection of breast cancer.      

Relationship between tumor DNA methylation status and patient characteristics in African-American and European-American women with breast cancer

Aberrant DNA methylation is critical for development and progression of breast cancer. We investigated the association of CpG island methylation in candidate genes and clinicopathological features in 65 African-American (AA) and European-American (EA) breast cancer patients. Quantitative methylation analysis was carried out on bisulfite modified genomic DNA and sequencing (pyrosequencing) for promoter CpG islands of p16, ESR1, RASSF1A, RARβ2, CDH13, HIN1, SFRP1 genes and the LINE1 repetitive element using matched paired non-cancerous and breast tumor specimen (32 AA and 33 EA women). Five of the genes, all known tumor suppressor genes (RASSF1A, RARβ2, CDH13, HIN1 and SFRP1), were found to be frequently hypermethylated in breast tumor tissues but not in the adjacent non-cancerous tissues. Significant differences in the CDH13 methylation status were observed by comparing DNA methylation between AA and EA patients, with more obvious CDH13 methylation differences between the two patient groups in the ER- disease and among young patients (age<50). In addition, we observed associations between CDH13, SFRP1, and RASSF1A methylation and breast cancer subtypes and between SFRP1 methylation and patient's age. Furthermore, tumors that received neoadjuvant therapy tended to have reduced RASSF1A methylation when compared with chemotherapy na?ve tumors. Finally, Kaplan Meier survival analysis showed a significant association between methylation at 3 loci (RASSF1A, RARβ2 and CDH13) and reduced overall disease survival. In conclusion, the DNA methylation status of breast tumors was found to be significantly associated with clinicopathological features and race/ethnicity of the patients.     

TGF-β regulates DNA methyltransferase expression in prostate cancer, correlates with aggressive capabilities, and predicts disease recurrence

Background

DNA methyltransferase (DNMT) is one of the major factors mediating the methylation of cancer related genes such as TGF-β receptors (TβRs). This in turn may result in a loss of sensitivity to physiologic levels of TGF-β in aggressive prostate cancer (CaP). The specific mechanisms of DNMT''s role in CaP remain undetermined. In this study, we describe the mechanism of TGF-β-mediated DNMT in CaP and its association with clinical outcomes following radical prostatectomy.

Methodology/Principal Findings

We used human CaP cell lines with varying degrees of invasive capability to describe how TGF-β mediates the expression of DNMT in CaP, and its effects on methylation status of TGF-β receptors and the invasive capability of CaP in vitro and in vivo. Furthermore, we determined the association between DNMT expression and clinical outcome after radical prostatectomy. We found that more aggressive CaP cells had significantly higher TGF-β levels, increased expression of DNMT, but reduced TβRs when compared to benign prostate cells and less aggressive prostate cancer cells. Blockade of TGF-β signaling or ERK activation (p-ERK) was associated with a dramatic decrease in the expression of DNMT, which results in a coincident increase in the expression of TβRs. Blockade of either TGF-β signaling or DNMT dramatically decreased the invasive capabilities of CaP. Inhibition of TGF-β in an TRAMP-C2 CaP model in C57BL/6 mice using 1D11 was associated with downregulation of DNMTs and p-ERK and impairment in tumor growth. Finally, independent of Gleason grade, increased DNMT1 expression was associated with biochemical recurrence following surgical treatment for prostate cancer.

Conclusions and Significance

Our findings demonstrate that CaP derived TGF-β may induce the expression of DNMTs in CaP which is associated with methylation of its receptors and the aggressive potential of CaP. In addition, DNMTs is an independent predictor for disease recurrence after prostatectomy, and may have clinical implications for CaP prognostication and therapy.     

DNA methylation profiles in African American prostate cancer patients in relation to disease progression

This study examined whether differential DNA methylation is associated with clinical features of more aggressive disease at diagnosis and prostate cancer recurrence in African American men, who are more likely to die from prostate cancer than other populations. Tumor tissues from 76 African Americans diagnosed with prostate cancer who had radical prostatectomy as their primary treatment were profiled for epigenome-wide DNA methylation levels. Long-term follow-up identified 19 patients with prostate cancer recurrence. Twenty-three CpGs were differentially methylated (FDR q ≤ 0.25, mean methylation difference ≥ 0.10) in patients with vs. without recurrence, including CpGs in GCK, CDKL2, PRDM13, and ZFR2. Methylation differences were also observed between men with metastatic-lethal prostate cancer vs. no recurrence (five CpGs), regional vs. local pathological stage (two CpGs), and higher vs. lower tumor aggressiveness (one CpG). These results indicate that differentially methylated CpG sites identified in tumor tissues of African American men may contribute to prostate cancer aggressiveness.     

DNA Methylation-Guided Prediction of Clinical Failure in High-Risk Prostate Cancer

Background

Prostate cancer (PCa) is a very heterogeneous disease with respect to clinical outcome. This study explored differential DNA methylation in a priori selected genes to diagnose PCa and predict clinical failure (CF) in high-risk patients.

Methods

A quantitative multiplex, methylation-specific PCR assay was developed to assess promoter methylation of the APC, CCND2, GSTP1, PTGS2 and RARB genes in formalin-fixed, paraffin-embedded tissue samples from 42 patients with benign prostatic hyperplasia and radical prostatectomy specimens of patients with high-risk PCa, encompassing training and validation cohorts of 147 and 71 patients, respectively. Log-rank tests, univariate and multivariate Cox models were used to investigate the prognostic value of the DNA methylation.

Results

Hypermethylation of APC, CCND2, GSTP1, PTGS2 and RARB was highly cancer-specific. However, only GSTP1 methylation was significantly associated with CF in both independent high-risk PCa cohorts. Importantly, trichotomization into low, moderate and high GSTP1 methylation level subgroups was highly predictive for CF. Patients with either a low or high GSTP1 methylation level, as compared to the moderate methylation groups, were at a higher risk for CF in both the training (Hazard ratio [HR], 3.65; 95% CI, 1.65 to 8.07) and validation sets (HR, 4.27; 95% CI, 1.03 to 17.72) as well as in the combined cohort (HR, 2.74; 95% CI, 1.42 to 5.27) in multivariate analysis.

Conclusions

Classification of primary high-risk tumors into three subtypes based on DNA methylation can be combined with clinico-pathological parameters for a more informative risk-stratification of these PCa patients.     

Abberant methylation of p16, HIC1, N33 and GSTP1 genes in tumor epitelium and tumor-associated stromal cells of prostate cancer

The methylation status of four genes significant in prostate carcinogenesis p16, HIC1, N33 and GSTP1, were evaluated using quantitative methylationsensitive polymerase chain reaction. Tumor epithelia, tumor-associated stroma, normal epithelia, foci of PIN and benign prostate hyperplasia, and stroma adjacent to tumor tissues were isolated from whole-mount prostatectomy specimens of patients with localized prostate cancer by using laser capture microdissection. We found high levels of gene methylation in the tumor epithelium and tumor-associated stromal cells and some methylation in both hyperplastic epithelium and stromal cells in normal-appearing tissues located adjacent to tumors. Promoter methylation in the non-neoplastic cells of the prostate tumor microenvironment may play an important role in cancer development and progression. We examined the promoter methylation status of pl6, HIC1, N33 and GSTP1 in prostate biopsy fragments and prostate tissues after radical prostatectomy from patients with adenocarcinoma without laser capture microdissection. Methylation frequencies of all genes in tumor samples were considerably lower than frequencies in microdissected tumour samples (HIC1, 71 versus 89%; p16, 22 versus 78%; GSTP1, 32 versus 100%; N33, 20 versus 33%). The laser capture microdissection is required procedure in methylation studies taking into account multifocality and heterogenity of prostate cancer tissue.     

Bisulphite Differential Denaturation PCR for Analysis of DNA Methylation

Differential denaturation during PCR can be used to selectively amplify unmethylated DNA from a methylated DNA background. The use of differential denaturation in PCR is particularly suited to amplification of undermethylated sequences following treatment with bisulphite, since bisulphite selectively converts cytosines to uracil while methylated cytosines remain unreactive. Thus amplicons derived from unmethylated DNA retain less cytosines and their lower G + C content allows for their amplification at the lower melting temperatures, while limiting amplification of the corresponding methylated amplicons (Bisulphite Differential Denaturation PCR, BDD-PCR). Selective amplification of unmethylated DNA of four human genomic regions from three genes, GSTP1, BRCA1 and MAGE-A1, is demonstrated with selectivity observed at a ratio of down to one unmethylated molecule in 105 methylated molecules. BDD-PCR has the potential to be used to selectively amplify and detect aberrantly demethylated genes, such as oncogenes, in cancers. Additionally BDD-PCR can be effectively utilised in improving the specificity of methylation specific PCR (MSP) by limiting amplification of DNA that is not fully converted, thus preventing misinterpretation of the methylation versus non-conversion.      

Co-Occurring Gland Angularity in Localized Subgraphs: Predicting Biochemical Recurrence in Intermediate-Risk Prostate Cancer Patients

Quantitative histomorphometry (QH) refers to the application of advanced computational image analysis to reproducibly describe disease appearance on digitized histopathology images. QH thus could serve as an important complementary tool for pathologists in interrogating and interpreting cancer morphology and malignancy. In the US, annually, over 60,000 prostate cancer patients undergo radical prostatectomy treatment. Around 10,000 of these men experience biochemical recurrence within 5 years of surgery, a marker for local or distant disease recurrence. The ability to predict the risk of biochemical recurrence soon after surgery could allow for adjuvant therapies to be prescribed as necessary to improve long term treatment outcomes. The underlying hypothesis with our approach, co-occurring gland angularity (CGA), is that in benign or less aggressive prostate cancer, gland orientations within local neighborhoods are similar to each other but are more chaotically arranged in aggressive disease. By modeling the extent of the disorder, we can differentiate surgically removed prostate tissue sections from (a) benign and malignant regions and (b) more and less aggressive prostate cancer. For a cohort of 40 intermediate-risk (mostly Gleason sum 7) surgically cured prostate cancer patients where half suffered biochemical recurrence, the CGA features were able to predict biochemical recurrence with 73% accuracy. Additionally, for 80 regions of interest chosen from the 40 studies, corresponding to both normal and cancerous cases, the CGA features yielded a 99% accuracy. CGAs were shown to be statistically signicantly () better at predicting BCR compared to state-of-the-art QH methods and postoperative prostate cancer nomograms.     

Long-Range Allosteric Interactions between the Folate and Methionine Cycles Stabilize DNA Methylation Reaction Rate

Several metabolites in the folate and methionine cycles influence the activities of distant enzymes involved in one-carbon metabolism. Many hypotheses have been advanced about the functional impact of these long-range interactions. Using both steady-state and fluctuation analyses of a mathematical model of methionine metabolism, we investigate the biochemical basis for several of these hypotheses. We show that the long-range interactions provide remarkable stabilization of the DNA methylation rate in the face of large fluctuations in methionine input. In particular, they enable the system to maintain methylation in the face of low and extremely low protein input. These interactions may therefore have evolved primarily to stabilize DNA methylation under conditions of methionine starvation. In silico experimentation allows us to evaluate the independent effects of various combinations of the long-range interactions, and thereby propose a plausible evolutionary scenario.      

Up‐regulation of LIMK1 expression in prostate cancer is correlated with poor pathological features,lymph node metastases and biochemical recurrence

This study aimed to explore the association between LIM domain kinase 1 (LIMK1) expression in prostate cancer (PCa) tissues with advanced pathological features, lymph node metastases and biochemical recurrence. A total of 279 PCa specimens from patients who underwent radical prostatectomy and 50 benign prostatic hyperplasia (BPH) specimens were collected to construct tissue microarray, which were subjected to immunohistochemical staining for LIMK1 expression subsequently. Logistic and Cox regression analysis were used to evaluate the relationship between LIMK1 expression and clinicopathological features of patients with PCa. Immunohistochemical staining assay demonstrated that LIMK1 expression was significantly higher in PCa than BPH specimens (77.1% vs 26.0%; P < .001). LIMK1 expression was significantly higher in positive lymph node specimens than corresponding PCa specimens (P = .002; P < .001). Up‐regulation of LIMK1 was associated with prostate volume, prostate‐specific antigen, prostate‐specific antigen density, Gleason score, T stage, lymph node metastases, extracapsular extension and seminal vesicle invasion, and positive surgical margin. Multivariate logistic regression analysis demonstrated that LIMK1 was an independent risk factor for PCa lymph node metastasis (P < .05). Multivariate Cox regression analysis revealed that the up‐regulation of LIMK1 was an independent risk factor for biochemical recurrence. Kaplan‐Meier analysis indicated that up‐regulation LIMK1 was associated with shortened biochemical‐free survival (BFS) after radical prostatectomy (P < .001). In conclusion, LIMK1 was significantly up‐regulated in PCa and positive lymph node specimens and correlated with lymph node metastasis and shortened BFS of PCa. The underlying molecular mechanism of LIMK1 in PCa should be further evaluated.     

Using LUMA: a Luminometric-Based Assay for Global DNA-Methylation

Changes in genomic DNA methylation are important events in normal and pathological cellular processes, contributing both to normal development and differentiation as well as to cancer and other diseases. We describe here a method to analyze global genomic DNA methylation, using a luminometric technology to quantitate methylation sensitive restriction digestions. The method is called LUminometric Methylation Assay (LUMA), and is based on a polymerase extension assay using the the Pyrosequencing? platform. The method is quantitative, highly reproducible and uses an internal control for DNA input. No modification of genomic DNA is needed and the total running time is only six hours. The method is suitable for analyzing clinical material, as well as determining dynamic changes in global methylation/demethylation events. This report describes the method in detail and gives an example of its application in epigenetic research.      

Discovery and Validation of a Prostate Cancer Genomic Classifier that Predicts Early Metastasis Following Radical Prostatectomy

Purpose

Clinicopathologic features and biochemical recurrence are sensitive, but not specific, predictors of metastatic disease and lethal prostate cancer. We hypothesize that a genomic expression signature detected in the primary tumor represents true biological potential of aggressive disease and provides improved prediction of early prostate cancer metastasis.

Methods

A nested case-control design was used to select 639 patients from the Mayo Clinic tumor registry who underwent radical prostatectomy between 1987 and 2001. A genomic classifier (GC) was developed by modeling differential RNA expression using 1.4 million feature high-density expression arrays of men enriched for rising PSA after prostatectomy, including 213 who experienced early clinical metastasis after biochemical recurrence. A training set was used to develop a random forest classifier of 22 markers to predict for cases - men with early clinical metastasis after rising PSA. Performance of GC was compared to prognostic factors such as Gleason score and previous gene expression signatures in a withheld validation set.

Results

Expression profiles were generated from 545 unique patient samples, with median follow-up of 16.9 years. GC achieved an area under the receiver operating characteristic curve of 0.75 (0.67–0.83) in validation, outperforming clinical variables and gene signatures. GC was the only significant prognostic factor in multivariable analyses. Within Gleason score groups, cases with high GC scores experienced earlier death from prostate cancer and reduced overall survival. The markers in the classifier were found to be associated with a number of key biological processes in prostate cancer metastatic disease progression.

Conclusion

A genomic classifier was developed and validated in a large patient cohort enriched with prostate cancer metastasis patients and a rising PSA that went on to experience metastatic disease. This early metastasis prediction model based on genomic expression in the primary tumor may be useful for identification of aggressive prostate cancer.     

Reactivation of Epigenetically Silenced Genes by DNA Methyltransferase Inhibitors: Basic Concepts and Clinical Applications

Hypermethylation of tumor suppressor genes is one of the most consistent hallmarks of human cancers. This epigenetic alteration has been associated with gene silencing and thus represents an important pathway for generating loss-of-function mutations. In this review, we survey the available literature on systematic, genome-wide approaches aimed at the identification of epigenetically silenced loci. These studies uncovered a variety of diverse genes, but a common signature for epigenetic reactivation has not been identified. Nevertheless, DNA methyltransferase inhibitors have shown significant clinical benefits, mostly in the therapy of leukemias. Recent analyses revealed substantial drug-induced methylation changes that can now be used as endpoints for the further refinement of clinical treatment schedules. Further optimization of epigenetic cancer therapies should be feasible through the use of novel DNA methyltransferase inhibitors with improved specificity. Rational design of epigenetic inhibitors might provide the foundation for a broader use of these drugs in the treatment of cancer.      

DNA Methylation-Dependent Epigenetic Regulation of Gene Expression in MCF-7 Breast Cancer Cells

To identify epigenetically-regulated genes in breast cancer, MCF-7 cells were exposed to 250nM 5-aza or 5-aza + 50nM TSA for 3 weeks followed by a 5 week recovery period after treatment withdrawal and gene expression patterns were examined by microarray analysis. We identified 20 genes that are associated with a >2-fold increase in expression in response to the demethylating treatment but returned to control levels after treatment withdrawal. RT-PCR verified that the genes identified were expressed at low or undetectable levels in control MCF-7 cells, but increased expression in treated cells. Most of these putative epigentically-regulated genes in MCF-7 cells do not contain CpG islands. In fact, these genes could be classified based upon their promoter CpG features, including genes with: (i) typical CpG features (CpG islands), (ii) intermediate CpG features (weak CpG islands), and (iii) atypical CpG features (no CpG islands). Prototype genes from each class (including CpG-deficient genes) were shown to be methylation-sensitive (subject to CpG methylation and responsive to demethylating agents), suggesting that not all gene targets of DNA methylation in breast cancer will contain a CpG island. Based upon the results of the current study and observations from the literature, we propose expansion of the current model for methylation-dependent regulation of gene expression to include genes lacking typical CpG islands. The expanded model we propose recognizes that all promoter CpG dinucleotides represent legitimate targets for DNA methylation and that the methylation of specific CpG dinucleotides in critical domains of regulatory regions can result in gene silencing.      

DNA methylation in pre-diagnostic serum samples of breast cancer cases: Results of a nested case–control study

Background: Promoter methylation of tumor suppressor genes is a frequent and early event in breast carcinogenesis. Paired tumor tissue and serum samples from women with breast cancer show that promoter methylation is detectable in both sample types, with good concordance. This suggests the potential for these serum markers to be used for breast cancer detection. Methods: The current study was a case–control study nested within the prospective New York University Women's Health Study cohort aimed to assess the ability of promoter methylation in serum to detect pre-clinical disease. Cases were women with blood samples collected within the 6 months preceding breast cancer diagnosis (n = 50). Each case was matched to 2 healthy cancer-free controls and 1 cancer-free control with a history of benign breast disease (BBD). Results: Promoter methylation analysis of four cancer-related genes: — RASSF1A, GSTP1, APC and RARβ2, — was conducted using quantitative methylation-specific PCR. Results showed that the frequency of methylation was lower than expected among cases and higher than expected among controls. Methylation was detected in the promoter region of: RASSF1A in 22.0%, 22.9% and 17.2% of cases, BBD controls and healthy controls respectively; GSTP1 in 4%, 10.4% and 7.1% respectively; APC in 2.0%, 4.4% and 4.2% respectively and RARβ2 in 6.7%, 2.3% and 1.1% respectively. Conclusion: Methylation status of the four genes included in this study was unable to distinguish between cases and either control group. This study highlights some methodological issues to be addressed in planning prospective studies to evaluate methylation markers as diagnostic biomarkers.     

Serum methionine metabolites are risk factors for metastatic prostate cancer progression

Background

Clinical decision for primary treatment for prostate cancer is dictated by variables with insufficient specificity. Early detection of prostate cancer likely to develop rapid recurrence could support neo-adjuvant therapeutics and adjuvant options prior to frank biochemical recurrence. This study compared markers in serum and urine of patients with rapidly recurrent prostate cancer to recurrence-free patients after radical prostatectomy. Based on previous identification of urinary sarcosine as a metastatic marker, we tested whether methionine metabolites in urine and serum could serve as pre-surgical markers for aggressive disease.

Methodology/Principal Findings

Urine and serum samples (n = 54 and 58, respectively), collected at the time of prostatectomy were divided into subjects who developed biochemical recurrence within 2 years and those who remained recurrence-free after 5 years. Multiple methionine metabolites were measured in urine and serum by GC-MS. The role of serum metabolites and clinical variables (biopsy Gleason grade, clinical stage, serum prostate specific antigen [PSA]) on biochemical recurrence prediction were evaluated. Urinary sarcosine and cysteine levels were significantly higher (p = 0.03 and p = 0.007 respectively) in the recurrent group. However, in serum, concentrations of homocysteine (p = 0.003), cystathionine (p = 0.007) and cysteine (p<0.001) were more abundant in the recurrent population. The inclusion of serum cysteine to a model with PSA and biopsy Gleason grade improved prediction over the clinical variables alone (p<0.001).

Conclusions

Higher serum homocysteine, cystathionine, and cysteine concentrations independently predicted risk of early biochemical recurrence and aggressiveness of disease in a nested case control study. The methionine metabolites further supplemented known clinical variables to provide superior sensitivity and specificity in multivariable prediction models for rapid biochemical recurrence following prostatectomy.     

A Novel MiRNA-Based Predictive Model for Biochemical Failure Following Post-Prostatectomy Salvage Radiation Therapy

Purpose

To develop a microRNA (miRNA)-based predictive model for prostate cancer patients of 1) time to biochemical recurrence after radical prostatectomy and 2) biochemical recurrence after salvage radiation therapy following documented biochemical disease progression post-radical prostatectomy.

Methods

Forty three patients who had undergone salvage radiation therapy following biochemical failure after radical prostatectomy with greater than 4 years of follow-up data were identified. Formalin-fixed, paraffin-embedded tissue blocks were collected for all patients and total RNA was isolated from 1mm cores enriched for tumor (>70%). Eight hundred miRNAs were analyzed simultaneously using the nCounter human miRNA v2 assay (NanoString Technologies; Seattle, WA). Univariate and multivariate Cox proportion hazards regression models as well as receiver operating characteristics were used to identify statistically significant miRNAs that were predictive of biochemical recurrence.

Results

Eighty eight miRNAs were identified to be significantly (p<0.05) associated with biochemical failure post-prostatectomy by multivariate analysis and clustered into two groups that correlated with early (≤ 36 months) versus late recurrence (>36 months). Nine miRNAs were identified to be significantly (p<0.05) associated by multivariate analysis with biochemical failure after salvage radiation therapy. A new predictive model for biochemical recurrence after salvage radiation therapy was developed; this model consisted of miR-4516 and miR-601 together with, Gleason score, and lymph node status. The area under the ROC curve (AUC) was improved to 0.83 compared to that of 0.66 for Gleason score and lymph node status alone.

Conclusion

miRNA signatures can distinguish patients who fail soon after radical prostatectomy versus late failures, giving insight into which patients may need adjuvant therapy. Notably, two novel miRNAs (miR-4516 and miR-601) were identified that significantly improve prediction of biochemical failure post-salvage radiation therapy compared to clinico-histopathological factors, supporting the use of miRNAs within clinically used predictive models. Both findings warrant further validation studies.