Promoter methylation in APC, RUNX3, and GSTP1 and mortality in prostate cancer patients

Wnt/β-catenin signaling pathway in carcinogenesis and cancer therapy

The Wnt/β-catenin signaling pathway plays a crucial role in various physiological processes, encompassing development, tissue homeostasis, and cell proliferation. Under normal physiological conditions, the Wnt/β-catenin signaling pathway is meticulously regulated. However, aberrant activation of this pathway and downstream target genes can occur due to mutations in key components of the Wnt/β-catenin pathway, epigenetic modifications, and crosstalk with other signaling pathways. Consequently, these dysregulations contribute significantly to tumor initiation and progression. Therapies targeting the Wnt/β-catenin signaling transduction have exhibited promising prospects and potential for tumor treatment. An increasing number of medications targeting this pathway are continuously being developed and validated. This comprehensive review aims to summarize the latest advances in our understanding of the role played by the Wnt/β-catenin signaling pathway in carcinogenesis and targeted therapy, providing valuable insights into acknowledging current opportunities and challenges associated with targeting this signaling pathway in cancer research and treatment.

CT-Based Radiogenomics of P4HA3 Expression in Clear Cell Renal Cell Carcinoma

RATIONALE AND OBJECTIVES

The sequencing of the renal cell carcinoma (RCC) genome identified several mutations with prognostic significance. Genomic analysis, collected in The Cancer Genome Atlas Research Network, revealed several clear cell renal cell carcinoma (ccRCC) gene mutations and gene expressions. Radiogenomics is a new branch of diagnostic imaging based on the association between imaging phenotypes and genomics of diseases. P4HA3 expression has recently been shown to correlate with increased aggressiveness of ccRCC, with poor prognosis, proliferation, migration, invasion, and metastases, suggesting P4HA3 as a prognostic marker and therapeutic target in ccRCC. The aim of this study is to investigate the computed tomography (CT) imaging phenotype of P4HA3 expression in ccRCC patients.

MATERIALS AND METHODS

In this retrospective study we enrolled 196 ccRCC patients divided into two groups: ccRCC patients with P4HA3 expression (n = 13) and ccRCC patients without P4HA3 expression (n = 183). Several imaging features were evaluated on preoperative CT scan. The statistical significance threshold was set at P < .05.

RESULTS

A statistically significant association was found with larger primary tumor size (P = .033), tumor infiltration (P = .023), ill-defined tumor margins (P = .025), and advanced tumor stage American Joint Committee of Cancer (P = .014).

CONCLUSION

This study demonstrates CT imaging features associated with P4HA3 expression in ccRCC. These results could contribute to better understand P4HA3 expression with a noninvasive approach and could be applied to the development of targeted therapies.

Cohort profile: the Turin prostate cancer prognostication (TPCP) cohort

Introduction

Prostate cancer (PCa) is the most frequent tumor among men in Europe and has both indolent and aggressive forms. There are several treatment options, the choice of which depends on multiple factors. To further improve current prognostication models, we established the Turin Prostate Cancer Prognostication (TPCP) cohort, an Italian retrospective biopsy cohort of patients with PCa and long-term follow-up. This work presents this new cohort with its main characteristics and the distributions of some of its core variables, along with its potential contributions to PCa research.

Methods

The TPCP cohort includes consecutive non-metastatic patients with first positive biopsy for PCa performed between 2008 and 2013 at the main hospital in Turin, Italy. The follow-up ended on December 31st 2021. The primary outcome is the occurrence of metastasis; death from PCa and overall mortality are the secondary outcomes. In addition to numerous clinical variables, the study's prognostic variables include histopathologic information assigned by a centralized uropathology review using a digital pathology software system specialized for the study of PCa, tumor DNA methylation in candidate genes, and features extracted from digitized slide images via Deep Neural Networks.

Results

The cohort includes 891 patients followed-up for a median time of 10 years. During this period, 97 patients had progression to metastatic disease and 301 died; of these, 56 died from PCa. In total, 65.3% of the cohort has a Gleason score less than or equal to 3 + 4, and 44.5% has a clinical stage cT1. Consistent with previous studies, age and clinical stage at diagnosis are important prognostic factors: the crude cumulative incidence of metastatic disease during the 14-years of follow-up increases from 9.1% among patients younger than 64 to 16.2% for patients in the age group of 75-84, and from 6.1% for cT1 stage to 27.9% in cT3 stage.

Discussion

This study stands to be an important resource for updating existing prognostic models for PCa on an Italian cohort. In addition, the integrated collection of multi-modal data will allow development and/or validation of new models including new histopathological, digital, and molecular markers, with the goal of better directing clinical decisions to manage patients with PCa.

Accurate prediction of pan-cancer types using machine learning with minimal number of DNA methylation sites

DNA methylation analysis has been applied to determine the primary site of cancer; however, robust and accurate prediction of cancer types with a minimum number of sites is still a significant scientific challenge. To build an accurate and robust cancer type prediction tool with a minimum number of DNA methylation sites, we internally benchmarked different DNA methylation site selection and ranking procedures, as well as different classification models. We used The Cancer Genome Atlas dataset (26 cancer types with 8296 samples) to train and test models and used an independent dataset (17 cancer types with 2738 samples) for model validation. A deep neural network model using a combined feature selection procedure (named MethyDeep) can predict 26 cancer types using 30 methylation sites with superior performance compared with the known methods for both primary and metastatic cancers in independent validation datasets. In conclusion, MethyDeep is an accurate and robust cancer type predictor with the minimum number of DNA methylation sites; it could help the cost-effective clarification of cancer of unknown primary patients and the liquid biopsy-based early screening of cancers.

The role of next-generation sequencing in the examination of signaling genes in Brca1/2-negative breast cancer cases

INTRODUCTION

Breast cancer is the most prevalent malignancy in women worldwide. Although pathogenic variants in the BRCA1/2 genes are responsible for the majority of hereditary breast cancer cases, a substantial proportion of patients are negative for pathogenic variations in these genes. In cancers, the signal transduction pathways of the cell are usually affected first. Therefore, this study aimed to detect and classified genetic variations in non-BRCA signaling genes and investigate the underlying genetic causes of susceptibility to breast cancer.

METHODS

Ninety-six patients without pathogenic variants in the BRCA1/2 genes who met the inclusion criteria were enrolled in the study, and 34 genes were analyzed using next-generation sequencing (NGS) for genetic analysis.

RESULTS

Based on the ClinVar database or American College of Medical Genetics criteria, a total of 55 variants of 16 genes were detected in 43 (44.8%) of the 96 patients included in the study. The pathogenic variants were found in the TP53, CHEK2, and RET genes, whereas the likely pathogenic variants were found in the FGFR1, FGFR3, EGFR, and NOTCH1 genes.

CONCLUSION

The examination of signaling genes in patients who met the established criteria for hereditary breast cancer but were negative for BRCA1/2 pathogenic variants provided additional information for approximately 8% of the families. The results of the present study suggest that NGS is a powerful tool for investigating the underlying genetic causes of occurrence and progression of breast cancer.

Genomic, epigenomic, and transcriptomic signatures of prostate cancer between African American and European American patients

Prostate cancer is the second most common cancer in men in the United States, and racial disparities are greatly observed in the disease. Specifically, African American (AA) patients have 60% higher incidence and mortality rates, in addition to higher grade and stage prostate tumors, than European American (EA) patients. In order to narrow the gap between clinical outcomes for these two populations, genetic and molecular signatures contributing to this disparity have been characterized. Over the past decade, profiles of prostate tumor samples from different ethnic groups have been developed using molecular and functional assays coupled with next generation sequencing or microarrays. Comparative genome-wide analyses of genomic, epigenomic, and transcriptomic profiles from prostate tumor samples have uncovered potential race-specific mutations, copy number alterations, DNA methylation, and gene expression patterns. In this study, we reviewed over 20 published studies that examined the aforementioned molecular contributions to racial disparities in AA and EA prostate cancer patients. The reviewed genomic studies revealed mutations, deletions, amplifications, duplications, or fusion genes differentially enriched in AA patients relative to EA patients. Commonly reported genomic alterations included mutations or copy number alterations of FOXA1, KMT2D, SPOP, MYC, PTEN, TP53, ZFHX3, and the TMPRSS2-ERG fusion. The reviewed epigenomic studies identified that CpG sites near the promoters of PMEPA1, RARB, SNRPN, and TIMP3 genes were differentially methylated between AA and EA patients. Lastly, the reviewed transcriptomic studies identified genes (e.g. CCL4, CHRM3, CRYBB2, CXCR4, GALR1, GSTM3, SPINK1) and signaling pathways dysregulated between AA and EA patients. The most frequently found dysregulated pathways were involved in immune and inflammatory responses and neuroactive ligand signaling. Overall, we observed that the genomic, epigenomic, and transcriptomic alterations evaluated between AA and EA prostate cancer patients varied between studies, highlighting the impact of using different methods and sample sizes. The reported genomic, epigenomic, and transcriptomic alterations do not only uncover molecular mechanisms of tumorigenesis but also provide researchers and clinicians valuable resources to identify novel biomarkers and treatment modalities to improve the disparity of clinical outcomes between AA and EA patients.

Epigenetic (De)regulation in Prostate Cancer

Prostate cancer (PCa) is a heterogeneous disease exhibiting both genetic and epigenetic deregulations. Epigenetic alterations are defined as changes not based on DNA sequence, which include those of DNA methylation, histone modification, and chromatin remodeling. Androgen receptor (AR) is the main driver for PCa and androgen deprivation therapy (ADT) remains a backbone treatment for patients with PCa; however, ADT resistance almost inevitably occurs and advanced diseases develop termed castration-resistant PCa (CRPC), due to both genetic and epigenetic changes. Due to the reversible nature of epigenetic modifications, inhibitors targeting epigenetic factors have become promising anti-cancer agents. In this chapter, we focus on recent studies about the dysregulation of epigenetic regulators crucially involved in the initiation, development, and progression of PCa and discuss the potential use of inhibitors targeting epigenetic modifiers for treatment of advanced PCa.

Biomarkers for the Detection and Risk Stratification of Aggressive Prostate Cancer

Current strategies for the clinical management of prostate cancer are inadequate for a precise risk stratification between indolent and aggressive tumors. Recently developed tissue-based molecular biomarkers have refined the risk assessment of the disease. The characterization of tissue biopsy components and subsequent identification of relevant tissue-based molecular alterations have the potential to improve the clinical decision making and patient outcomes. However, tissue biopsies are invasive and spatially restricted due to tumor heterogeneity. Therefore, there is an urgent need for complementary diagnostic and prognostic options. Liquid biopsy approaches are minimally invasive with potential utility for the early detection, risk stratification, and monitoring of tumors. In this review, we focus on tissue and liquid biopsy biomarkers for early diagnosis and risk stratification of prostate cancer, including modifications on the genomic, epigenomic, transcriptomic, and proteomic levels. High-risk molecular alterations combined with orthogonal clinical parameters can improve the identification of aggressive tumors and increase patient survival.

RUNX Proteins as Epigenetic Modulators in Cancer

RUNX proteins are highly conserved in metazoans and perform critical functions during development. Dysregulation of RUNX proteins through various molecular mechanisms facilitates the development and progression of various cancers, where different RUNX proteins show tumor type-specific functions and regulate different aspects of tumorigenesis by cross-talking with different signaling pathways such as Wnt, TGF-β, and Hippo. Molecularly, they could serve as transcription factors (TFs) to activate their direct target genes or interact with many other TFs to modulate chromatin architecture globally. Here, we review the current knowledge on the functions and regulations of RUNX proteins in different cancer types and highlight their potential role as epigenetic modulators in cancer.

The Next Paradigm Shift in the Management of Clear Cell Renal Cancer: Radiogenomics—Definition, Current Advances, and Future Directions

With improved molecular characterization of clear cell renal cancer and advances in texture analysis as well as machine learning, diagnostic radiology is primed to enter personalized medicine with radiogenomics: the identification of relationships between tumor image features and underlying genomic expression. By developing surrogate image biomarkers, clinicians can augment their ability to non-invasively characterize a tumor and predict clinically relevant outcomes (i.e., overall survival; metastasis-free survival; or complete/partial response to treatment). It is thus important for clinicians to have a basic understanding of this nascent field, which can be difficult due to the technical complexity of many of the studies. We conducted a review of the existing literature for radiogenomics in clear cell kidney cancer, including original full-text articles until September 2021. We provide a basic description of radiogenomics in diagnostic radiology; summarize existing literature on relationships between image features and gene expression patterns, either computationally or by radiologists; and propose future directions to facilitate integration of this field into the clinical setting.

Expression patterns and prognostic value of RUNX genes in kidney cancer

Kidney cancer is the third most common malignancy of the urinary system, of which, kidney renal clear cell carcinoma (KIRC) accounts for the vast majority. Runt-related transcription factors (RUNX) are involved in multiple cellular functions. However, the diverse expression patterns and prognostic values of RUNX genes in kidney cancer remained to be elucidated. In our study, we mined the DNA methylation, transcriptional and survival data of RUNX genes in patients with different kinds of kidney cancer through Oncomine, Gene Expression Profiling Interactive Analysis, UALCAN, Kaplan–Meier Plotter, cBioPortal and LinkedOmics. We found that RUNX1 and RUNX3 were upregulated in KIRC tissues compared with those in normal tissues. The survival analysis results indicated a high transcription level of RUNX1 was associated with poor overall survival (OS) in KIRC patients. Furthermore, KIRC tumor tissues had significantly lower levels of RUNX1 promoter methylation than that in paracancerous tissues, with decreased DNA methylation of RUNX1 notably associated with poor OS in KIRC. In conclusion, our results revealed that RUNX1 may be a potential therapeutic target for treating KIRC, and RUNX1 promoter methylation level shows promise as a novel diagnostic and prognostic biomarker, which laid a foundation for further study.

Association of variably methylated tumour DNA regions with overall survival for invasive lobular breast cancer

Background

Tumour DNA methylation profiling has shown potential to refine disease subtyping and improve the diagnosis and prognosis prediction of breast cancer. However, limited data exist regarding invasive lobular breast cancer (ILBC). Here, we investigated the genome-wide variability of DNA methylation levels across ILBC tumours and assessed the association between methylation levels at the variably methylated regions and overall survival in women with ILBC.

Methods

Tumour-enriched DNA was prepared by macrodissecting formalin-fixed paraffin embedded (FFPE) tumour tissue from 130 ILBCs diagnosed in the participants of the Melbourne Collaborative Cohort Study (MCCS). Genome-wide tumour DNA methylation was measured using the HumanMethylation 450K (HM450K) BeadChip array. Variably methylated regions (VMRs) were identified using the DMRcate package in R. Cox proportional hazards regression models were used to assess the association between methylation levels at the ten most significant VMRs and overall survival. Gene set enrichment analyses were undertaken using the web-based tool Metaspace. Replication of the VMR and survival analysis findings was examined using data retrieved from The Cancer Genome Atlas (TCGA) for 168 ILBC cases. We also examined the correlation between methylation and gene expression for the ten VMRs of interest using TCGA data.

Results

We identified 2771 VMRs (P < 10⁻⁸) in ILBC tumours. The ten most variably methylated clusters were predominantly located in the promoter region of the genes: ISM1, APC, TMEM101, ASCL2, NKX6, HIST3H2A/HIST3H2BB, HCG4P3, HES5, CELF2 and EFCAB4B. Higher methylation level at several of these VMRs showed an association with reduced overall survival in the MCCS. In TCGA, all associations were in the same direction, however stronger than in the MCCS. The pooled analysis of the MCCS and TCGA data showed that methylation at four of the ten genes was associated with reduced overall survival, independently of age and tumour stage; APC: Hazard Ratio (95% Confidence interval) per one-unit M-value increase: 1.18 (1.02–1.36), TMEM101: 1.23 (1.02–1.48), HCG4P3: 1.37 (1.05–1.79) and CELF2: 1.21 (1.02–1.43). A negative correlation was observed between methylation and gene expression for CELF2 (R = − 0.25, P = 0.001), but not for TMEM101 and APC.

Conclusions

Our study identified regions showing greatest variability across the ILBC tumour genome and found methylation at several genes to potentially serve as a biomarker of survival for women with ILBC.

Hypermethylation of Cyclin D2 Predicts Poor Prognosis of Hepatitis B Virus-Associated Hepatocellular Carcinoma after Hepatectomy

Prognosis of patients with hepatocellular carcinoma remains poor because of progression of hepatocellular carcinoma and high recurrence rates. Cyclin D2 (CCND2) plays a vital role in regulating the cell cycle; indeed, aberrant methylation of CCND2 is involved in the development of hepatocellular carcinoma. Therefore, we aimed to investigate levels of CCND2 methylation in patients with hepatitis B virus (HBV)-associated hepatocellular carcinoma and to evaluate its prognostic significance after hepatectomy. In total, 257 subjects were enrolled (166 hepatocellular carcinoma patients undergoing surgical resection, 61 chronic hepatitis B (CHB) patients, and 30 healthy controls). CCND2 methylation in peripheral blood mononuclear cells was measured quantitatively using MethyLight. We found that CCND2 methylation levels in patients with HBV-associated hepatocellular carcinoma were significantly higher than in CHB patients (P < 0.001) or healthy controls (P < 0.001). Within the hepatocellular carcinoma group, CCND2 methylation levels were higher in patients with portal vein invasion, early tumor recurrence, TNM III/IV stage, and tumor size ≥ 5 cm (P < 0.05). Furthermore, higher levels of CCND2 methylation were associated with worse overall survival and disease-free survival (P = 0.005 and P < 0.001, respectively). Multivariate analysis identified CCND2 methylation as an independent prognostic factor for early tumor recurrence (P = 0.021), overall survival (P = 0.022), and disease-free survival (P < 0.001) in hepatocellular carcinoma patients after resection. In conclusion, hypermethylation of CCND2 may have clinical utility for predicting a high risk of poor prognosis and early tumor recurrence in patients with HBV-associated hepatocellular carcinoma after hepatectomy.

APC Promoter Hypermethylation as a Prognostic Marker in Breast Cancer Patients

Background:

Adenomatous polyposis coli (APC) promoter hypermethylation implicated in breast cancer development through Wnt signaling pathway, hypermethylation may result in inactivation of APC expression. This study aimed to investigated whether hypermethylation of APC promoter, the aggressive behavior of breast cancer cells, and correlated them with clinicopathological parameters and survival.

Methods:

Sixty-one fresh tissues of breast tumor were evaluated for APC promoter hypermethylation with methylation-specific PCR techniques (MS-PCR) and APC mRNA expression level analysis by quantitative real-time reverse transcription-PCR.

Results:

Our results show aberrant APC hypermethylation status was founded in 27 of 61 cases (44%), and significantly associated with chemotherapy treatment (OR= 6.9, 95%CI=1.5-31.01, P = 0.01), distant metastasis (OR = 5.52, 95%CI = 1.27-24.08, P = 0.04) as well as APC methylated status also associated with shorter overall survival than those without (8.4 and 11.0 years respectively, P = 0.02).

Conclusion:

The findings indicated hypermethylation of APC promoter may be used as a useful prognostic biomarker in breast cancer patients.

Advances in Prognostic Methylation Biomarkers for Prostate Cancer

There is a major clinical need for accurate biomarkers for prostate cancer prognosis, to better inform treatment strategies and disease monitoring. Current clinically recognised prognostic factors, including prostate-specific antigen (PSA) levels, lack sensitivity and specificity in distinguishing aggressive from indolent disease, particularly in patients with localised intermediate grade prostate cancer. There has therefore been a major focus on identifying molecular biomarkers that can add prognostic value to existing markers, including investigation of DNA methylation, which has a known role in tumorigenesis. In this review, we will provide a comprehensive overview of the current state of DNA methylation biomarker studies in prostate cancer prognosis, and highlight the advances that have been made in this field. We cover the numerous studies into well-established candidate genes, and explore the technological transition that has enabled hypothesis-free genome-wide studies and the subsequent discovery of novel prognostic genes.

SurvivalMeth: a web server to investigate the effect of DNA methylation-related functional elements on prognosis

Aberrant DNA methylation is a fundamental characterization of epigenetics for carcinogenesis. Abnormality of DNA methylation-related functional elements (DMFEs) may lead to dysfunction of regulatory genes in the progression of cancers, contributing to prognosis of many cancers. There is an urgent need to construct a tool to comprehensively assess the impact of DMFEs on prognosis. Therefore, we developed SurvivalMeth (http://bio-bigdata.hrbmu.edu.cn/survivalmeth) to explore the prognosis-related DMFEs, which documented many kinds of DMFEs, including 309,465 CpG island-related elements, 104,748 transcript-related elements, 77,634 repeat elements, as well as cell-type specific 1,689,653 super enhancers (SE) and 1,304,902 CTCF binding regions for analysis. SurvivalMeth is a convenient tool which collected DNA methylation profiles of 36 cancers and allowed users to query their genes of interest in different datasets for prognosis. Furthermore, SurvivalMeth not only integrated different combinations, including single DMFE, multiple DMFEs, SEs and clinical data, to perform survival analysis on preupload data but also allowed for uploading customized DNA methylation profile of DMFEs from various diseases to analyze. SurvivalMeth provided a comprehensive resource and automated analysis for prognostic DMFEs, including DMFE methylation level, correlation analysis, clinical analysis, differential analysis, DMFE annotation, survival-related detailed result and visualization of survival analysis. In summary, we believe that SurvivalMeth will facilitate prognostic research of DMFEs in diverse cancers.

Downregulation of RUNX3 has a poor prognosis and promotes tumor progress in kidney cancer

BACKGROUND

Kidney cancer usually shows no symptoms until the tumor is relatively large, and current drugs fail to stop the tumor recurrence. The transcriptional factor Runt-related transcription factor 3 (RUNX3) has been reported to function as a tumor suppressor in many types of cancers.

METHODS

Kidney cancer and adjacent normal tissues were collected from 12 patients to test the expression of RUNX3 by real-time quantitative PCR, immunoblotting, and immunohistochemistry. Promoter methylation status of RUNX3 was determined using methylation analysis from 103 patient samples. Kidney cancer cell lines and xenograft mouse model were used to investigate the promoter methylation and cancer progression through inhibitor treatment and loss/gain-of-function experiments.

RESULTS

RUNX3 was significantly downregulated in kidney cancer tissues and cells, which could be elevated by higher methylation status at its promoter region. RUNX3 promoter methylation was positively correlated with poor prognosis of kidney cancer. RUNX3 loss-of-function promoted the cell proliferation, migration, and invasion of kidney cancer cells, in contrast, RUNX3 overexpression inhibited the cancer cell progression. This study provides the first instance of the effect of RUNX3 expression and its promoter methylation status on kidney cancer.

CONCLUSION

Targeting RUNX3 pathway and its promoter methylation are potential therapeutic strategies to treat kidney cancer.

Combining molecular and imaging metrics in cancer: radiogenomics

Background

Radiogenomics is the extension of radiomics through the combination of genetic and radiomic data. Because genetic testing remains expensive, invasive, and time-consuming, and thus unavailable for all patients, radiogenomics may play an important role in providing accurate imaging surrogates which are correlated with genetic expression, thereby serving as a substitute for genetic testing.

Main body

In this article, we define the meaning of radiogenomics and the difference between radiomics and radiogenomics. We provide an up-to-date review of the radiomics and radiogenomics literature in oncology, focusing on breast, brain, gynecological, liver, kidney, prostate and lung malignancies. We also discuss the current challenges to radiogenomics analysis.

Conclusion

Radiomics and radiogenomics are promising to increase precision in diagnosis, assessment of prognosis, and prediction of treatment response, providing valuable information for patient care throughout the course of the disease, given that this information is easily obtainable with imaging. Larger prospective studies and standardization will be needed to define relevant imaging biomarkers before they can be implemented into the clinical workflow.

The Relationship between the Methylation of Promoter Regions of Tumor Suppressor Genes PTEN and APC with Endometrial Cancer

Background:

Endometrial neoplasms is one of the most typical gynecologic diseases with harmful effects. Promoter hypermethylation is an important mechanism of the inactivation of tumor suppressor genes in endometrial neoplasms. Epigenetic changes of the PTEN and APC genes have shown to be present in various cancers. Therefore, in this study, we have investigated the association between the promoter hypermethylation of PTEN and APC genes with endometrial neoplasms.

Methods:

For this study, 28 patients with endometrial neoplasms as well as 22 controls were studied. Analysis of the promoter methylation regions of PTEN and APC genes were performed by Methylation-Specific PCR.

Results:

The frequency of PTEN and APC genes promoter methylation was 28.57% and 17.86% in tumor tissues, and 11.54% and 3.85% in blood samples, respectively. We found a significant relationship between blood and tissue in PTEN methylation (p = 0.0353). Additionally, we determined a closely significant difference between normal tissue and tumor tissue of the PTEN gene (p = 0.0787) and blood and tissue samples of the APC gene in methylated promoter regions (p=0.0623). Furthermore, these results suggest that there is no significant relationship between the promoter methylation of PTEN and APC with clinical characteristics.

Conclusion:

DNA methylation deficiency is a well known highlighted factor in tumorigenesis, therefore the promoter hypermethylation of PTEN and APC can be indicated as a risk factor in endometrial neoplasms.

Differential gene methylation patterns in cancerous and non‑cancerous cells

Large-scale projects, such as The Cancer Genome Atlas (TCGA), Human Epigenome Project (HEP) and Human Epigenome Atlas (HEA), provide an insight into DNA methylation and histone modification markers. Changes in the epigenome significantly contribute to the initiation and progression of cancer. The goal of the present study was to characterize the prostate cancer malignant transformation model using the CpG island methylation pattern. The Human Prostate Cancer EpiTect Methyl II Signature PCR Array was used to evaluate the methylation status of 22 genes in prostate cancer cell lines: PC3, PC3M, PC3MPro4 and PC3MLN4, each representing different metastatic potential in vivo. Subsequently, it was ascertained whether DNA methylation plays a role in the expression of these genes in prostate cancer cells. Hypermethylation of APC, DKK3, GPX3, GSTP1, MGMT, PTGS2, RASSF1, TIMP2 and TNFRSF10D resulted in downregulation of their expression in prostate cancer cell lines as compared to WT fibroblasts. Mining of the TCGA data deposited in the MetHC database found increases in the methylation status of these 9 genes in prostate cancer patients, further supporting the role of methylation in altering the expression of these genes in prostate cancer. Future studies are warranted to investigate the role of these proteins in prostate cancer development.

Single-nucleotide polymorphisms in DNMT3B gene and DNMT3B mRNA expression in association with prostate cancer mortality

BACKGROUND

Germline variants in DNA methyltransferase 3B (DNMT3B) may influence DNMT3B enzymatic activity, which, in turn, may affect cancer aggressiveness by altering DNA methylation.

METHODS

The study involves two Italian cohorts (NTAT cohort, n = 157, and 1980s biopsy cohort, n = 182) and two U.S. cohorts (Health Professionals Follow-Up Study, n = 214, and Physicians' Health Study, n = 298) of prostate cancer (PCa) patients, and a case-control study of lethal (n = 113) vs indolent (n = 290) PCa with DNMT3B mRNA expression data nested in the U.S. cohorts. We evaluated the association between: three selected DNMT3B variants and global DNA methylation using linear regression in the NTAT cohort, the three DNMT3B variants and PCa mortality using Cox proportional hazards regression in all cohorts, and DNMT3B expression and lethal PCa using logistic regression, with replication in publicly available databases (TCGA, n = 492 and MSKCC, n = 140).

RESULTS

The TT genotype of rs1569686 was associated with LINE-1 hypomethylation in tumor tissue (β = -2.71, 95% CI: -5.41, -0.05). There was no evidence of association between DNMT3B variants and PCa mortality. DNMT3B expression was consistently associated with lethal PCa in the two U.S. cohorts (3rd vs 1st tertile, combined cohorts: OR = 2.04, 95% CI: 1.13, 3.76); the association was replicated in TCGA and MSKCC data (3rd vs 1st tertile, TCGA: HR = 3.00, 95% CI: 1.78, 5.06; MSKCC: HR = 2.22, 95% CI: 1.01, 4.86).

CONCLUSIONS

Although there was no consistent evidence of an association between DNMT3B variants and PCa mortality, the TT genotype of rs1569686 was associated with LINE-1 hypomethylation in tumor tissue and DNMT3B mRNA expression was associated with an increased risk of lethal PCa.

Marginal Time-Dependent Causal Effects in Mediation Analysis With Survival Data

The main aim of mediation analysis is to study the direct and indirect effects of an exposure on an outcome. To date, the literature on mediation analysis with multiple mediators has mainly focused on continuous and dichotomous outcomes. However, the development of methods for multiple mediation analysis of survival outcomes is still limited. Here we extend to survival outcomes a method for multiple mediation analysis based on the computation of appropriate weights. The approach considered has the advantages of not requiring specific models for mediators, allowing nonindependent mediators of any nature, and not relying on the assumption of rare outcomes. Simulation studies show good performance of the proposed estimator in terms of bias and coverage probability. The method is further applied to an example from a published study on prostate cancer mortality aimed at understanding the extent to which the effect of DNA methyltransferase 3b (DNMT3b) genotype on mortality was explained by DNA methylation and tumor aggressiveness. This approach can be used to quantify the marginal time-dependent direct and indirect effects carried by multiple indirect pathways, and software code is provided to facilitate its application.

GSTP1 methylation in cancer: a liquid biopsy biomarker?

The coding region of GSTP1 gene is preceded by a large CpG-rich region that is frequently affected by methylation. In many cancer types, GSTP1 is affected by hypermethylation and, as a consequence, it has a low expression. The aim of this review is to give an overview on GSTP1 methylation studies with a special focus on liquid biopsy, thus to summarize methods, results, sample types, different diseases, to have a complete information regarding this promising epigenetic biomarker. We used all the most valuable scientific search engines (PubMed, Medline, Scopus and Web of Science) searching the following keywords: GSTP1, methylation, cancer, urine, serum, plasma and blood. GSTP1 is a largely investigated tissue biomarker in several malignancies such as prostate, breast, lung and hepatocellular carcinoma with good performances especially for diagnostic purposes. As a liquid biopsy biomarker, it has been mainly investigated in prostate cancer (PCa) where it showed a high specificity but a low sensitivity; thus, it is recommended in combination with other biomarkers. Despite the large number of published papers and the promising results, GSTP1 has not yet entered the clinical practice even for PCa diagnosis. For this reason, further large and prospective studies are needed to validate this assay.

Renal cell carcinoma: predicting RUNX3 methylation level and its consequences on survival with CT features

PURPOSE

To investigate associations between CT imaging features, RUNX3 methylation level, and survival in clear cell renal cell carcinoma (ccRCC).

MATERIALS AND METHODS

Patients were divided into high RUNX3 methylation and low RUNX3 methylation groups according to RUNX3 methylation levels (the threshold was identified by using X-tile). The CT scanning data from 106 ccRCC patients were retrospectively analyzed. The relationship between RUNX3 methylation level and overall survivals was evaluated using the Kaplan-Meyer analysis and Cox regression analysis (univariate and multivariate). The relationship between RUNX3 methylation level and CT features was evaluated using chi-square test and logistic regression analysis (univariate and multivariate).

RESULTS

β value cutoff of 0.53 to distinguish high methylation (N = 44) from low methylation tumors (N = 62). Patients with lower levels of methylation had longer median overall survival (49.3 vs. 28.4) months (low vs. high, adjusted hazard ratio [HR] 4.933, 95% CI 2.054-11.852, p < 0.001). On univariate logistic regression analysis, four risk factors (margin, side, long diameter, and intratumoral vascularity) were associated with RUNX3 methylation level (all p < 0.05). Multivariate logistic regression analysis found that three risk factors (side: left vs. right, odds ratio [OR] 2.696; p = 0.024; 95% CI 1.138-6.386; margin: ill-defined vs. well-defined, OR 2.685; p = 0.038; 95% CI 1.057-6.820; and intratumoral vascularity: yes vs. no, OR 3.286; p = 0.008; 95% CI 1.367-7.898) were significant independent predictors of high methylation tumors. This model had an area under the receiver operating characteristic curve (AUC) of 0.725 (95% CI 0.623-0.827).

CONCLUSIONS

Higher levels of RUNX3 methylation are associated with shorter survival in ccRCC patients. And presence of intratumoral vascularity, ill-defined margin, and left side tumor were significant independent predictors of high methylation level of RUNX3 gene.

KEY POINTS

• RUNX3 methylation level is negatively associated with overall survival in ccRCC patients. • Presence of intratumoral vascularity, ill-defined margin, and left side tumor were significant independent predictors of high methylation level of RUNX3 gene.

epiCaPture: A Urine DNA Methylation Test for Early Detection of Aggressive Prostate Cancer

Purpose

Liquid biopsies that noninvasively detect molecular correlates of aggressive prostate cancer (PCa) could be used to triage patients, reducing the burdens of unnecessary invasive prostate biopsy and enabling early detection of high-risk disease. DNA hypermethylation is among the earliest and most frequent aberrations in PCa. We investigated the accuracy of a six-gene DNA methylation panel (Epigenetic Cancer of the Prostate Test in Urine [epiCaPture]) at detecting PCa, high-grade (Gleason score greater than or equal to 8) and high-risk (D’Amico and Cancer of the Prostate Risk Assessment] PCa from urine.

Patients and Methods

Prognostic utility of epiCaPture genes was first validated in two independent prostate tissue cohorts. epiCaPture was assessed in a multicenter prospective study of 463 men undergoing prostate biopsy. epiCaPture was performed by quantitative methylation-specific polymerase chain reaction in DNA isolated from prebiopsy urine sediments and evaluated by receiver operating characteristic and decision curves (clinical benefit). The epiCaPture score was developed and validated on a two thirds training set to one third test set.

Results

Higher methylation of epiCaPture genes was significantly associated with increasing aggressiveness in PCa tissues. In urine, area under the receiver operating characteristic curve was 0.64, 0.86, and 0.83 for detecting PCa, high-grade PCa, and high-risk PCa, respectively. Decision curves revealed a net benefit across relevant threshold probabilities. Independent analysis of two epiCaPture genes in the same clinical cohort provided analytical validation. Parallel epiCaPture analysis in urine and matched biopsy cores showed added value of a liquid biopsy.

Conclusion

epiCaPture is a urine DNA methylation test for high-risk PCa. Its tumor specificity out-performs that of prostate-specific antigen (greater than 3 ng/mL). Used as an adjunct to prostate-specific antigen, epiCaPture could aid patient stratification to determine need for biopsy.

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.

Molecular biomarkers to guide precision medicine in localized prostate cancer

INTRODUCTION

Major advances through tumor profiling technologies, that include next-generation sequencing, epigenetic, proteomic and transcriptomic methods, have been made in primary prostate cancer, providing novel biomarkers that may guide precision medicine in the near future. Areas covered: The authors provided an overview of novel molecular biomarkers in tissue, blood and urine that may be used as clinical tools to assess prognosis, improve selection criteria for active surveillance programs, and detect disease relapse early in localized prostate cancer. Expert commentary: Active surveillance (AS) in localized prostate cancer is an accepted strategy in patients with very low-risk prostate cancer. Many more patients may benefit from watchful waiting, and include patients of higher clinical stage and grade, however selection criteria have to be optimized and early recognition of transformation from localized to lethal disease has to be improved by addition of molecular biomarkers. The role of non-invasive biomarkers is challenging the need for repeat biopsies, commonly performed at 1 and 4 years in men under AS programs.

Biomarker potential of ST6GALNAC3 and ZNF660 promoter hypermethylation in prostate cancer tissue and liquid biopsies

Current diagnostic and prognostic tools for prostate cancer (PC) are suboptimal, leading to overdiagnosis and overtreatment. Aberrant promoter hypermethylation of specific genes has been suggested as novel candidate biomarkers for PC that may improve diagnosis and prognosis. We here analyzed ST6GALNAC3 and ZNF660 promoter methylation in prostate tissues, and ST6GALNAC3,ZNF660,CCDC181, and HAPLN3 promoter methylation in liquid biopsies. First, using four independent patient sample sets, including a total of 110 nonmalignant (NM) and 705 PC tissue samples, analyzed by methylation‐specific qPCR or methylation array, we found that hypermethylation of ST6GALNAC3 and ZNF660 was highly cancer‐specific with areas under the curve (AUC) of receiver operating characteristic (ROC) curve analysis of 0.917–0.995 and 0.846–0.903, respectively. Furthermore, ZNF660 hypermethylation was significantly associated with biochemical recurrence in two radical prostatectomy (RP) cohorts of 158 and 392 patients and remained significant also in the subsets of patients with Gleason score ≤7 (univariate Cox regression and log‐rank tests, P < 0.05), suggesting that ZNF660 methylation analysis can potentially help to stratify low‐/intermediate‐grade PCs into indolent vs. more aggressive subtypes. Notably, ZNF660 hypermethylation was also significantly associated with poor overall and PC‐specific survival in the RP cohort (n = 158) with long clinical follow‐up available. Moreover, as proof of principle, we successfully detected highly PC‐specific hypermethylated circulating tumor DNA (ctDNA) for ST6GALNAC3,ZNF660,HAPLN3, and CCDC181 in liquid biopsies (serum) from 27 patients with PC vs. 10 patients with BPH, using droplet digital methylation‐specific PCR analysis. Finally, we generated a three‐gene (ST6GALNAC3/CCDC181/HAPLN3) ctDNA hypermethylation model, which detected PC with 100% specificity and 67% sensitivity. In conclusion, we here for the first time demonstrate diagnostic biomarker potential of ST6GALNAC3 and ZNF660 methylation, as well as prognostic biomarker potential of ZNF660. Furthermore, we show that hypermethylation of four genes can be detected in ctDNA in liquid biopsies (serum) from patients with PC.

Deregulation of E-cadherin, β-catenin, APC and Caveolin-1 expression occurs in canine prostate cancer and metastatic processes

Prostate cancer is a heterogeneous disease with high levels of clinical and gene heterogeneity, consequently offering several targets for therapy. Dogs with naturally occurring prostate cancer are useful models for molecular investigations and studying new treatment efficacy. Three genes and proteins associated with the WNT pathway (β-catenin, APC and E-cadherin) and Caveolin-1 (CAV-1) were evaluated in canine pre-neoplastic proliferative inflammatory atrophy (PIA), prostate cancer and metastatic disease. The APC gene methylation status was also investigated. As in human prostate cancer, cytoplasmic and nuclear β-catenin, which are fundamental for activating the canonical WNT pathway, were found in canine prostate cancer and metastasis. Membranous E-cadherin was also lost in these lesions, allowing cellular migration to the stroma and nuclear localization of β-catenin. In contrast to human prostate tumours, no APC downregulation or hypermethylation was found in canine prostate cancer. The CAV-1 gene and protein overexpression were found in canine prostate cancer, and as in humans, the highest levels were found in Gleason scores ≥8. In conclusion, as with human prostate cancer, β-catenin and E-cadherin in the WNT pathway, as well as Caveolin-1, are molecular drivers in canine prostate cancer. These findings provide additional evidence that dogs are useful models for studying new therapeutic targets in prostate cancer.

Promoter hypermethylation of SOX11 correlates with adverse clinicopathological features of human prostate cancer

Currently available tools for early diagnosis and prognosis of prostate cancer lack sufficient accuracy. There is a need to identify novel biomarkers for this common malignancy. SOX family genes play an important role in embryogenesis and are also implicated in various cancers. SOX11 has been recently recognized as a potential tumour suppressor that is downregulated in prostate cancer. We hypothesized that hypermethylation may be responsible for SOX11 silencing in human prostate cancer. The aim of the study was to investigate SOX11 promoter methylation in prostate adenocarcinoma by comparing it with benign prostatic hyperplasia (BPH). A total of 143 human prostate tissue samples, 62 from patients with prostate cancer and 81 from patients with BPH were examined by methylation-specific PCR. Associations between SOX11 promoter methylation and clinicopathological parameters were assessed by univariate statistics. Detection rates of SOX11 promoter methylation were 80.6% and 35.8% in prostate cancer and BPH respectively (P < 0.001). SOX11 hypermethylation was associated with adverse clinicopathological characteristics of prostate cancer, including higher PSA level (P < 0.01), Gleason score ≥ 7 (P = 0.03) and perineural invasion (P = 0.03). SOX11 methylation was positively correlated with the PSA level (P = 0.001). Our data indicated that SOX11 can be a promising methylation marker candidate for differential diagnosis and risk stratification for prostate cancer.

Translating cancer epigenomics into the clinic: focus on lung cancer

Epigenetic deregulation is increasingly being recognized as a hallmark of cancer. Recent studies have identified many new epigenetic biomarkers, some of which are being introduced into clinical practice for diagnosis, molecular classification, prognosis or prediction of response to therapies. O-6-methylguanine-DNA methyltransferase gene is the most clinically advanced epigenetic biomarker as it predicts the response to temozolomide and carmustine in gliomas. Therefore, epigenomics may represent a novel and promising tool for precision medicine, and in particular, the detection of epigenomic biomarkers in liquid biopsies will be of great interest for monitoring diseases in patients. Of particular relevance is the identification of epigenetic biomarkers in lung cancer, one of the most prevalent and deadly types of cancer. DNA methylation of SHOX2 and RASSF1A could be used as diagnostic markers to differentiate between normal and tumor samples. MicroRNA and long noncoding RNA signatures associated with lung cancer development or tobacco smoke have also been identified. In addition to the field of biomarkers, therapeutic approaches using DNA methylation and histone deacetylation inhibitors are being tested in clinical trials for several cancer types. Moreover, new DNA editing techniques based on zinc finger and CRISPR/Cas9 technologies allow specific modification of aberrant methylation found in oncogenes or tumor suppressor genes. We envision that epigenomics will translate into the clinical field and will have an impact on lung cancer diagnosis/prognosis and treatment.

Epigenetic risk score improves prostate cancer risk assessment

BACKGROUND

Early detection of aggressive prostate cancer (PCa) remains crucial for effective treatment of patients. However, PCa screening remains controversial due to a high rate of overdiagnosis and overtreatment. To better reconcile both objectives, more effective methods for assessing disease severity at the time of diagnosis are needed.

METHODS

The relationship between DNA-methylation and high-grade PCa was examined in a cohort of 102 prospectively enrolled men who received standard 12-core prostate biopsies. EpiScore, an algorithm that quantifies the relative DNA methylation intensities of GSTP1, RASSF1, and APC in prostate biopsy tissue, was evaluated as a method to compensate for biopsy under-sampling and improve risk stratification at the time of diagnosis.

RESULTS

DNA-methylation intensities of GSTP1, RASSF1, and APC were higher in biopsy cores from men diagnosed with GS ≥ 7 cancer compared to men with diagnosed GS 6 disease. This was confirmed by EpiScore, which was significantly higher for subjects with high-grade biopsies and higher NCCN risk categories (both P < 0.001). In patients diagnosed with GS ≥ 7, increased levels of DNA-methylation were present, not only in the high-grade biopsy cores, but also in other cores with no or low-grade disease (P < 0.001). By combining EpiScore with traditional clinical risk factors into a logistic regression model, the prediction of high GS reached an AUC of 0.82 (95%CI: 0.73-0.91) with EpiScore, DRE, and atypical histological findings as most important contributors.

CONCLUSIONS

In men diagnosed with PCa, DNA-methylation profiling can detect under-sampled high-risk PCa in prostate biopsy specimens through a field effect. Predictive accuracy increased when EpiScore was combined with other clinical risk factors. These results suggest that EpiScore could aid in the detection of occult high-grade disease at the time of diagnosis, thereby improving the selection of candidates for Active Surveillance.

Epigenetic regulation of APC in the molecular pathogenesis of gallbladder cancer

Background & objectives:

Loss of function of adenomatous polyposis coli (APC) has been reported in cancer. The two promoters of APC, 1A and 1B also have roles in cancer. But, the epigenetic role of APC promoters is not yet clear in gallbladder cancer (GBC) and gallstone diseases (GSD). We undertook this study to determine the epigenetic role of APC in GBC and GSD.

Methods:

Methylation-specific (MS)-PCR was used to analyze the methylation of APC gene. The expression of APC gene was studied by semi-quantitative PCR, real-time PCR and immunohistochemistry (IHC) in GBC, GSD and adjacent normal tissues.

Results:

Of the two promoters, APC 1A promoter was found methylated in 96 per cent GBC (P=0.0155) and 80 per cent GSD (P=0.015). Exon 1 was downregulated in grade II (P=0.002) and grade III (P=0.0001) of GBC, while exon 2 was normally expressed. Scoring analysis of IHC revealed 0 or negativity in 34.48 per cent (P=0.057) and 1+ in 24.14 per cent (P=0.005) GBC cases suggesting loss of APC expression.

Interpretation & conclusions:

The present findings indicate epigenetic silencing of APC in advanced GBC. The methylation pattern, followed by expression analysis of APC may be suggested for diagnostic, prognostic and therapeutic purposes in GBC in future.

A Heterogeneous Network Based Method for Identifying GBM-Related Genes by Integrating Multi-Dimensional Data

The emergence of multi-dimensional data offers opportunities for more comprehensive analysis of the molecular characteristics of human diseases and therefore improving diagnosis, treatment, and prevention. In this study, we proposed a heterogeneous network based method by integrating multi-dimensional data (HNMD) to identify GBM-related genes. The novelty of the method lies in that the multi-dimensional data of GBM from TCGA dataset that provide comprehensive information of genes, are combined with protein-protein interactions to construct a weighted heterogeneous network, which reflects both the general and disease-specific relationships between genes. In addition, a propagation algorithm with resistance is introduced to precisely score and rank GBM-related genes. The results of comprehensive performance evaluation show that the proposed method significantly outperforms the network based methods with single-dimensional data and other existing approaches. Subsequent analysis of the top ranked genes suggests they may be functionally implicated in GBM, which further corroborates the superiority of the proposed method. The source code and the results of HNMD can be downloaded from the following URL: http://bioinformatics.ustc.edu.cn/hnmd/ .

Prospective Study of CRMP4 Promoter Methylation in Prostate Biopsies as a Predictor For Lymph Node Metastases

Background

For patients with prostate cancer (PCa), the presence of pelvic lymph node metastasis (LNM) is a strong predictor of poor outcome. However, the approaches with promising sensitivity and specificity to detect LNM are still lacking. We investigated the value of collapsin response mediator protein 4 (CRMP4) promoter methylation in biopsies as a predictor for LNM.

Methods

CRMP4 promoter methylation at two previously identified CpG sites was determined in 80 case-matched biopsy samples (the training set) using bisulfite pyrosequencing. The predictive cutoff value was independently validated using cohort I of 339 PCa patients (Southern China) and cohort II of 328 case patients (Germany, across China). Mann-Whitney U test, the receiver operating characteristic curve, McNemar's test, and logistic regression were used to assess data. All statistical tests were two-sided.

Results

In the training set, CRMP4 promoter methylation (≥15.0% methylated) was statistically significantly associated with LNM (P < 001). Successful validations were achieved in both cohorts I and II (sensitivity = 92.3%, 95% confidence interval [CI] = 79.3 to 97.9, and sensitivity = 92.2%, 95% CI = 81.1 to 97.8, respectively; specificity = 92.7%, 95% CI = 80.2 to 99.1, and specificity = 91.3%, 95% CI = 87.4 to 94.4, respectively). The sensitivity of CRMP4 promoter methylation is superior to conventional MRI (cohort I: 92.3% vs 26.2%, P < 001; cohort II: 92.2% vs 33.3%, P < 001). CRMP4 promoter methylation is an independent predictor of LNM (cohort I: hazard ratio [HR] = 8.35, 95% CI = 5.64 to 12.35, P < 001; cohort II: HR = 12.46, 95% CI = 5.82 to 26.70, P < 001) in a multivariable analysis model.

Conclusion

CRMP4 promoter methylation in diagnostic biopsies could be a robust biomarker for LNM in PCa.

Epigenome-Wide Tumor DNA Methylation Profiling Identifies Novel Prognostic Biomarkers of Metastatic-Lethal Progression in Men Diagnosed with Clinically Localized Prostate Cancer

PURPOSE

Aside from Gleason sum, few factors accurately identify the subset of prostate cancer patients at high risk for metastatic progression. We hypothesized that epigenetic alterations could distinguish prostate tumors with life-threatening potential.

EXPERIMENTAL DESIGN

Epigenome-wide DNA methylation profiling was performed in surgically resected primary tumor tissues from a population-based (n = 430) and a replication (n = 80) cohort of prostate cancer patients followed prospectively for at least 5 years. Metastasis was confirmed by positive bone scan, MRI, CT, or biopsy, and death certificates confirmed cause of death. AUC, partial AUC (pAUC, 95% specificity), and P value criteria were used to select differentially methylated CpG sites that robustly stratify patients with metastatic-lethal from nonrecurrent tumors, and which were complementary to Gleason sum.

RESULTS

Forty-two CpG biomarkers stratified patients with metastatic-lethal versus nonrecurrent prostate cancer in the discovery cohort, and eight of these CpGs replicated in the validation cohort based on a significant (P < 0.05) AUC (range, 0.66-0.75) or pAUC (range, 0.007-0.009). The biomarkers that improved discrimination of patients with metastatic-lethal prostate cancer include CpGs in five genes (ALKBH5, ATP11A, FHAD1, KLHL8, and PI15) and three intergenic regions. In the validation dataset, the AUC for Gleason sum alone (0.82) significantly increased with the addition of four individual CpGs (range, 0.86-0.89; all P <0.05).

CONCLUSIONS

Eight differentially methylated CpGs that distinguish patients with metastatic-lethal from nonrecurrent tumors were validated. These novel epigenetic biomarkers warrant further investigation as they may improve prognostic classification of patients with clinically localized prostate cancer and provide new insights on tumor aggressiveness. Clin Cancer Res; 23(1); 311-9. ©2016 AACR.

LINE-1 methylation status in prostate cancer and non-neoplastic tissue adjacent to tumor in association with mortality

Aberrant DNA methylation seems to be associated with prostate cancer behavior. We investigated LINE-1 methylation in prostate cancer and non-neoplastic tissue adjacent to tumor (NTAT) in association with mortality from prostate cancer. We selected 157 prostate cancer patients with available NTAT from 2 cohorts of patients diagnosed between 1982-1988 and 1993-1996, followed up until 2010. An association between LINE-1 hypomethylation and prostate cancer mortality in tumor was suggested [hazard ratio per 5% decrease in LINE-1 methylation levels: 1.40, 95% confidence interval (CI): 0.95-2.01]. After stratification of the patients for Gleason score, the association was present only for those with a Gleason score of at least 8. Among these, low (<75%) vs. high (>80%) LINE-1 methylation was associated with a hazard ratio of 4.68 (95% CI: 1.03-21.34). LINE-1 methylation in the NTAT was not associated with prostate cancer mortality. Our results are consistent with the hypothesis that tumor tissue global hypomethylation may be a late event in prostate cancerogenesis and is associated with tumor progression.

DNA Methylation-Mediated Downregulation of DEFB1 in Prostate Cancer Cells

Epigenetic aberrations play crucial roles in prostate cancer (PCa) development and progression. The DEFB1 gene, which encodes human ß-defensin-1 (HBD-1), contributes to innate immune responses and functions as a potential tumor suppressor in urological cancers. We investigated whether differential DNA methylation at the low CpG-content promoter (LCP) of DEFB1 was associated with transcriptional regulation of DEFB1 in PCa cells. To identify distinct CpG loci within the DEFB1 LCP related to the epigenetic regulation of DEFB1, we performed an in vitro methylated reporter assay followed by bisulfite sequencing of the DEFB1 promoter fragment. The methylation status of two adjacent CpG loci in the DEFB1 LCP was found to be important for DEFB1 expression in PCa cells. Paired epithelial specimens of PCa patients (n = 60), which were distinguished as non-tumor and tumor tissues by microdissection, were analyzed by bisulfite pyrosequencing of site-specific CpG dinucleotide units in the DEFB1 LCP. CpG methylation frequencies in the DEFB1 LCP were significantly higher in malignant tissues than in adjacent benign tissues across almost all PCa patients. These results suggested that methylation status of each CpG site in the DEFB1 promoter could mediate downregulation of DEFB1 in PCa cells.

Methylation pattern analysis in prostate cancer tissue: identification of biomarkers using an MS-MLPA approach

Background

Epigenetic silencing mediated by CpG island methylation is a common feature of many cancers. Characterizing aberrant DNA methylation changes associated with prostate carcinogenesis could potentially identify a tumour-specific methylation pattern, facilitating the early diagnosis of prostate cancer. The objective of the study was to assess the methylation status of 40 tumour suppressor genes in prostate cancer and healthy prostatic tissues.

Methods

We used methylation specific-multiplex ligation probe amplification (MS-MLPA) assay in two independent case series (training and validation set). The training set comprised samples of prostate cancer tissue (n = 40), healthy prostatic tissue adjacent to the tumor (n = 26), and healthy non prostatic tissue (n = 23), for a total of 89 DNA samples; the validation set was composed of 40 prostate cancer tissue samples and their adjacent healthy prostatic tissue, for a total of 80 DNA samples. Methylation specific-polymerase chain reaction (MSP) was used to confirm the results obtained in the validation set.

Results

We identified five highly methylated genes in prostate cancer: GSTP1, RARB, RASSF1, SCGB3A1, CCND2 (P < 0.0001), with an area under the ROC curve varying between 0.89 (95 % CI 0.82–0.97) and 0.95 (95 % CI 0.90–1.00). Diagnostic accuracy ranged from 80 % (95 % CI 70–88) to 90 % (95 % CI 81–96). Moreover, a concordance rate ranging from 83 % (95 % CI 72–90) to 89 % (95 % CI 80–95) was observed between MS-MLPA and MSP.

Conclusions

Our preliminary results highlighted that hypermethylation of GSTP1, RARB, RASSF1, SCGB3A1 and CCND2 was highly tumour-specific in prostate cancer tissue.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-016-1014-6) contains supplementary material, which is available to authorized users.

Performance of Different Analytical Software Packages in Quantification of DNA Methylation by Pyrosequencing

BACKGROUND

Pyrosequencing has emerged as an alternative method of nucleic acid sequencing, well suited for many applications which aim to characterize single nucleotide polymorphisms, mutations, microbial types and CpG methylation in the target DNA. The commercially available pyrosequencing systems can harbor two different types of software which allow analysis in AQ or CpG mode, respectively, both widely employed for DNA methylation analysis.

OBJECTIVE

Aim of the study was to assess the performance for DNA methylation analysis at CpG sites of the two pyrosequencing software which allow analysis in AQ or CpG mode, respectively. Despite CpG mode having been specifically generated for CpG methylation quantification, many investigations on this topic have been carried out with AQ mode. As proof of equivalent performance of the two software for this type of analysis is not available, the focus of this paper was to evaluate if the two modes currently used for CpG methylation assessment by pyrosequencing may give overlapping results.

METHODS

We compared the performance of the two software in quantifying DNA methylation in the promoter of selected genes (GSTP1, MGMT, LINE-1) by testing two case series which include DNA from paraffin embedded prostate cancer tissues (PC study, N = 36) and DNA from blood fractions of healthy people (DD study, N = 28), respectively.

RESULTS

We found discrepancy in the two pyrosequencing software-based quality assignment of DNA methylation assays. Compared to the software for analysis in the AQ mode, less permissive criteria are supported by the Pyro Q-CpG software, which enables analysis in CpG mode. CpG mode warns the operators about potential unsatisfactory performance of the assay and ensures a more accurate quantitative evaluation of DNA methylation at CpG sites.

CONCLUSION

The implementation of CpG mode is strongly advisable in order to improve the reliability of the methylation analysis results achievable by pyrosequencing.

Methylation in benign prostate and risk of disease progression in men subsequently diagnosed with prostate cancer

In DNA from prostate tumors, methylation patterns in gene promoter regions can be a biomarker for disease progression. It remains unclear whether methylation patterns in benign prostate tissue--prior to malignant transformation--may provide similar prognostic information. To determine whether early methylation events predict prostate cancer outcomes, we evaluated histologically benign prostate specimens from 353 men who eventually developed prostate cancer and received "definitive" treatment [radical prostatectomy (58%) or radiation therapy (42%)]. Cases were drawn from a large hospital-based cohort of men with benign prostate biopsy specimens collected between 1990 and 2002. Risk of disease progression associated with methylation was estimated using time-to-event analyses. Average follow-up was over 5 years; biochemical recurrence (BCR) occurred in 91 cases (26%). In White men, methylation of the APC gene was associated with increased risk of BCR, even after adjusting for standard clinical risk factors for prostate cancer progression (adjusted hazard ratio (aHR) = 2.26; 95%CI 1.23-4.16). APC methylation was most strongly associated with a significant increased risk of BCR in White men with low prostate specific antigen at cohort entry (HR = 3.66; 95%CI 1.51-8.85). In additional stratified analyses, we found that methylation of the RARB gene significantly increased risk of BCR in African American cases who demonstrated methylation of at least one of the other four genes under study (HR = 3.80; 95%CI 1.07-13.53). These findings may have implications in the early identification of aggressive prostate cancer as well as reducing unnecessary medical procedures and emotional distress for men who present with markers of indolent disease.

Ability of PITX2 methylation to predict survival in patients with prostate cancer

Background

The aim of this study was to explore whether candidate gene methylation can effectively predict death from prostate cancer.

Methods

After reviewing the literature to identify likely candidate genes, we assembled a case-control cohort (in a 1:2 ratio) to explore the distribution of PITX2, WNT5a, SPARC, EPB41L3, and TPM4 methylation levels. The case group comprised 45 patients with a Gleason score ≤7 who had died as a result of prostate cancer, and the control group comprised 90 current prostate cancer patients or those who died of other causes. The methylation possibility of each of the candidate genes were maximized. Univariate conditional logistic was applied for data analysis and to evaluate prediction efficiency of gene methylation on prostate cancer.

Results

The results indicated that a raised level of PITX2 methylation increased the likelihood of death due to prostate cancer by 10% (odds ratio 1.56, 95% confidence interval 1.17–2.08; P=0.005). Methylation of SPARC was found to be able to distinguish between benign prostate hyperplasia and prostate cancer.

Conclusion

Methylation of PITX2 is an effective biomarker to predict death from prostate cancer, particularly in patients with a low Gleason score.

Concurrent Hepsin overexpression and adenomatous polyposis coli deletion causes invasive prostate carcinoma in mice

BACKGROUND

A clinical need to better categorize patients with prostate cancer exists. The Wnt/β-catenin signaling pathway plays important roles in human prostate cancer progression. Deletion of the endogenous Wnt antagonist adenomatous polyposis coli (Apc) in mice causes high grade prostate intraepithelial neoplasia, widely thought to be the precursor to prostate cancer. However, no metastasis occurrs in this model. New mouse models are needed to determine molecular causes of tumorigenesis, progression, and metastasis.

METHODS

To determine whether the overexpression of the prostate oncogene Hepsin could cause prostate cancer progression, we crossed a prostate-specific Hepsin overexpression model to a prostate-specific Apc-deletion model and classified the observed phenotype.

RESULTS

When Apc was deleted and Hepsin overexpressed concurrently, mice displayed invasive carcinoma, with loss of membrane characteristics and increase of fibrosis. These tumors had both luminal and basaloid characteristics. Though no metastasis was observed, there was evidence of adenomas and lung necrosis, inflammation, and chronic hemorrhage.

CONCLUSIONS

This work indicates that the Wnt/β-catenin pathway and the Hepsin pathway act in concert to promote prostate cancer progression. Both of these pathways are up-regulated in human prostate cancer and could represent chemotherapeutic targets.

Integrated analysis of epigenomic and genomic changes by DNA methylation dependent mechanisms provides potential novel biomarkers for prostate cancer

Epigenetic silencing mediated by CpG methylation is a common feature of many cancers. Characterizing aberrant DNA methylation changes associated with tumor progression may identify potential prognostic markers for prostate cancer (PCa). We treated two PCa cell lines, 22Rv1 and DU-145 with the demethylating agent 5-Aza 2’–deoxycitidine (DAC) and global methylation status was analyzed by performing methylation-sensitive restriction enzyme based differential methylation hybridization strategy followed by genome-wide CpG methylation array profiling. In addition, we examined gene expression changes using a custom microarray. Gene Set Enrichment Analysis (GSEA) identified the most significantly dysregulated pathways. In addition, we assessed methylation status of candidate genes that showed reduced CpG methylation and increased gene expression after DAC treatment, in Gleason score (GS) 8 vs. GS6 patients using three independent cohorts of patients; the publically available The Cancer Genome Atlas (TCGA) dataset, and two separate patient cohorts. Our analysis, by integrating methylation and gene expression in PCa cell lines, combined with patient tumor data, identified novel potential biomarkers for PCa patients. These markers may help elucidate the pathogenesis of PCa and represent potential prognostic markers for PCa patients.

The epigenetics of prostate cancer diagnosis and prognosis: update on clinical applications

PURPOSE OF REVIEW

There is a major deficit in our ability to detect and predict the clinical behavior of prostate cancer (PCa). Epigenetic changes are associated with PCa development and progression. This review will focus on recent results in the clinical application of diagnostic and prognostic epigenetic markers.

RECENT FINDINGS

The development of high throughput technology has seen an enormous increase in the discovery of new markers that encompass epigenetic changes including those in DNA methylation and histone modifications. Application of these findings to urine and other biofluids, but also cancer and noncancerous prostate tissue, has resulted in new biomarkers. There has been a recent commercial development of a DNA methylation-based assay for identifying PCa risk from normal biopsy tissue. Other biomarkers are currently in the validation phase and encompass combinations of multiple genes.

SUMMARY

Epigenetic changes improve the specificity and sensitivity of PCa diagnosis and have the potential to help determine clinical prognosis. Additional studies will not only provide new and better biomarker candidates, but also have the potential to inform new therapeutic strategies given the reversibility of these processes.

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.

Correlation between the expression of DNMT1, and GSTP1 and APC, and the methylation status of GSTP1 and APC in association with their clinical significance in prostate cancer

The aim of the present study was to investigate the correlation between the expression of DNA (cytosine-5)-methyltransferase 1 (DNMT1), glutathione S-transferase-P1 (GSTP1) and adenomatous polyposis coli (APC), and the methylation status of GSTP1 and APC in prostate cancer (PCa) and benign prostatic hyperplasia (BPH), and to examine its clinical significance. Immunohistochemistry and reverse transcription-polymerase chain reaction (RT-PCR) was used to detect the expression of DNMT1, GSTP1 and APC in 56 samples of PCa tissue and 10 samples of BPH tissue. Methylation-specific-PCR was used to detect the methylation status of the CpG island promoters of GSTP1 and APC. The positive rate of expression of DNMT1 in poorly-differentiated PCa, moderately-differentiated PCa, well-differentiated PCa and BPH was 86.7%, 70.6%, 55.6% and 30.0%, respectively (P<0.05); for GSTP1, the positive rate was 13.3%, 29.4%, 44.4% and 90.0%, respectively (P<0.05); and for APC, the positive rate was 23.3%, 47.6%, 55.6% and 70.0%, respectively (P<0.05). The correlation coefficient for the association between the expression of DNMT1 and GSTP1 was −0.891 (P<0.05). Between the expression of DNMT1 and APC, the correlation coefficient was −0.721 (P<0.05). GSTP1 and APC were hypermethylated in the majority of PCa tissue samples. The positive rate of methylation of these genes in poorly-differentiated PCa was 83.3% and 73.3%, respectively. By contrast, hypomethylation (or demethylation) was observed in BPH samples, in which the positive rate of methylation was 10.0% and 20.0%, respectively (P<0.05). The increased expression of DNMT1, and the reduced expression of GSTP1 and APC have an important role in the development of PCa. Due to the high expression of DNMT1 mRNA, it is likely that the hypermethylation of CpG islands contributed to the silencing of GSTP1 and APC in PCa tissues.

Prostate cancer: The main risk and protective factors-Epigenetic modifications

With 13 million new cases worldwide every year, prostate cancer is as a very real public health concern. Prostate cancer is common in over-50s men and the sixth-leading cause of cancer-related death in men worldwide. Like all cancers, prostate cancer is multifactorial - there are non-modifiable risk factors like heredity, ethnicity and geographic location, but also modifiable risk factors such as diet. Diet-cancer linkages have risen to prominence in the last few years, with accruing epidemiological data pointing to between-population incidence differentials in numerous cancers. Indeed, there are correlations between fat-rich diet and risk of hormone-dependent cancers like prostate cancer and breast cancer. Diet is a risk factor for prostate cancer, but certain micronutrients in specific diets are considered protective factors against prostate cancer. Examples include tomato lycopene, green tea epigallocatechin gallate, and soy phytoestrogens. These micronutrients are thought to exert cancer-protective effects via anti-oxidant pathways and inhibition of cell proliferation. Here, we focus in on the effects of phytoestrogens, and chiefly genistein and daidzein, which are the best-researched to date. Soy phytoestrogens are nonsteroid molecules whose structural similarity lends them the ability to mimic the effects of 17ß-estradiol. On top of anti-oxidant effects, there is evidence that soy phytoestrogens can modulate the epigenetic modifications found in prostate cancer. We also studied the impact of phytoestrogens on epigenetic modifications in prostate cancer, with special focus on DNA methylation, miRNA-mediated regulation and histone modifications.