DNA methylation profiling reveals novel biomarkers and important roles for DNA methyltransferases in prostate cancer

Detection of differentially methylated CpGs between tumour and adjacent benign cells in diagnostic prostate cancer samples

Differentially methylated CpG sites (dmCpGs) that distinguish prostate tumour from adjacent benign tissue could aid in the diagnosis and prognosis of prostate cancer. Previously, the identification of such dmCpGs has only been undertaken in radical prostatectomy (RP) samples and not primary diagnostic tumour samples (needle biopsy or transurethral resection of the prostate). We interrogated an Australian dataset comprising 125 tumour and 43 adjacent histologically benign diagnostic tissue samples, including 41 paired samples, using the Infinium Human Methylation450 BeadChip. Regression analyses of paired tumour and adjacent benign samples identified 2,386 significant dmCpGs (Bonferroni p < 0.01; delta-β ≥ 40%), with LASSO regression selecting 16 dmCpGs that distinguished tumour samples in the full Australian diagnostic dataset (AUC = 0.99). Results were validated in independent North American (npaired = 19; AUC = 0.87) and The Cancer Genome Atlas (TCGA; npaired = 50; AUC = 0.94) RP datasets. Two of the 16 dmCpGs were in genes that were significantly down-regulated in Australian tumour samples (Bonferroni p < 0.01; GSTM2 and PRKCB). Ten additional dmCpGs distinguished low (n = 34) and high Gleason (n = 88) score tumours in the diagnostic Australian dataset (AUC = 0.95), but these performed poorly when applied to the RP datasets (North American: AUC = 0.66; TCGA: AUC = 0.62). The DNA methylation marks identified here could augment and improve current diagnostic tests and/or form the basis of future prognostic tests.

Research progress of human key DNA and RNA methylation-related enzymes assay

Gene methylation-related enzymes (GMREs) are disfunction and aberrantly expressed in a variety of cancers, such as lung, gastric, and pancreatic cancers and have important implications for human health. Therefore，it is critical for early diagnosis and therapy of tumor to develop strategies that allow rapid and sensitive quantitative and qualitative detection of GMREs. With the development of modern analytical techniques and the application of various biosensors, there are numerous methods have been developed for analysis of GMREs. Therefore, this paper provides a systematic review of the strategies for level and activity assay of various GMREs including methyltransferases and demethylase. The detection methods mainly involve immunohistochemistry, colorimetry, fluorescence, chemiluminescence, electrochemistry, etc. Then, this review also addresses the coordinated role of various detection probes, novel nanomaterials, and signal amplification methods. The aim is to highlight potential challenges in the present field, to expand the analytical application of GMREs detection strategies, and to meet the urgent need for future disease diagnosis and intervention.

TP63-TRIM29 axis regulates enhancer methylation and chromosomal instability in prostate cancer

BACKGROUND

Prostate adenocarcinoma (PRAD) is the second leading cause of cancer-related deaths in men. High variability in DNA methylation and a high rate of large genomic rearrangements are often observed in PRAD.

RESULTS

To investigate the reasons for such high variance, we integrated DNA methylation, RNA-seq, and copy number alterations datasets from The Cancer Genome Atlas (TCGA), focusing on PRAD, and employed weighted gene co-expression network analysis (WGCNA). Our results show that only single cluster of co-expressed genes is associated with genomic and epigenomic instability. Within this cluster, TP63 and TRIM29 are key transcription regulators and are downregulated in PRAD. We discovered that TP63 regulates the level of enhancer methylation in prostate basal epithelial cells. TRIM29 forms a complex with TP63 and together regulates the expression of genes specific to the prostate basal epithelium. In addition, TRIM29 binds DNA repair proteins and prevents the formation of the TMPRSS2:ERG gene fusion typically observed in PRAD.

CONCLUSION

Our study demonstrates that TRIM29 and TP63 are important regulators in maintaining the identity of the basal epithelium under physiological conditions. Furthermore, we uncover the role of TRIM29 in PRAD development.

Comparative and integrative analysis of transcriptomic and epigenomic-wide DNA methylation changes in African American prostate cancer

African American (AA) men have the highest incidence and mortality rate from Prostate cancer (PCa) than any other racial/ethnic group. To date, PCa genomic studies have largely under-represented tumour samples from AA men. We measured genome-wide DNA methylation in benign and tumor prostate tissues from AA men using the Illumina Infunium 850 K EPIC array. mRNA expression database from a subset of the AA biospecimen were used to assess correlation of transcriptome and methylation datasets. Genome-wide methylation analysis identified 11,460 probes that were significant (p < 0.01) and differentially methylated in AA PCa compared to normal prostate tissues and showed significant (p < 0.01) inverse-correlation with mRNA expression. Ingenuity pathway analysis and Gene Ontology analysis in our AA dataset compared with TCGA dataset showed similarities in methylation patterns: top candidate genes with significant hypermethylation and corresponding down-regulated gene expression were associated with biological pathways in hemidesmosome assembly, mammary gland development, epidermis development, hormone biosynthesis, and cell communication. In addition, top candidate genes with significant hypomethylation and corresponding up-regulated gene expression were associated with biological pathways in macrophage differentiation, cAMP-dependent protein kinase activity, protein destabilization, transcription co-repression, and fatty acid biosynthesis. In contrast, differences in genome-wide methylation in our AA dataset compared with TCGA dataset were enriched for genes in steroid signalling, immune signalling, chromatin structure remodelling and RNA processing. Overall, differential methylation of AMIGO3, IER3, UPB1, GRM7, TFAP2C, TOX2, PLSCR2, ZNF292, ESR2, MIXL1, BOLL, and FGF6 were significant and uniquely associated with PCa progression in our AA cohort.

Comprehensive Analysis of DNA Methyltransferases Expression in Primary and Relapsed Ovarian Carcinoma

BACKGROUND

Despite recent advances in epithelial ovarian carcinoma (EOC) treatment, its recurrence and mortality rates have not improved significantly. DNA hypermethylation has generally been associated with an ominous prognosis and chemotherapy resistance, but the role of DNA methyltransferases (DNMTs) in EOC remains to be investigated.

METHODS

In the current study, we systematically retrieved gene expression data from patients with EOC and studied the immunohistochemical expression of DNMTs in 108 primary and 26 relapsed tumors.

RESULTS

Our results showed that the DNMT1, DNMT3A, DNMT3B and DNMT3L RNA levels were higher and the DNMT2 level was lower in tumors compared to non-neoplastic tissue, and DNMT3A and DNMT2 expression decreased from Stage-II to Stage-IV carcinomas. The proteomic data also suggested that the DNMT1 and DNMT3A levels were increased in the tumors. Similarly, the DNMT1, DNMT3A and DNMT3L protein levels were overexpressed and DNMT2 expression was reduced in high-grade carcinomas compared to non-neoplastic tissue and low-grade tumors. Moreover, DNMT1 and DNMT3L were increased in relapsed tumors compared to their primaries. The DNMT3A, DNMT1 and DNMT3B mRNA levels were correlated with overall survival.

CONCLUSIONS

Our study demonstrates that DNMT1 and DNMT3L are upregulated in primary high-grade EOC and further increase in relapses, whereas DNMT3A is upregulated only in the earlier stages of cancer progression. DNMT2 downregulation highlights the presumed tumor-suppressor activity of this gene in ovarian carcinoma.

Global research hotspots and frontier trends of epigenetic modifications in autoimmune diseases: A bibliometric analysis from 2012 to 2022

BACKGROUND

Recent studies have shown substantial progress in understanding the association between epigenetics and autoimmune diseases. However, there is a lack of comprehensive bibliometric analysis in this research area. This article aims to present the current status and hot topics of epigenetic research in autoimmune diseases (ADs) from a bibliometric perspective, as well as explore the frontier hotspots and trends in epigenetic studies related to ADs.

METHODS

This study collected 1870 epigenetic records related to autoimmune diseases from the web of science core collection database, spanning from 2012 to 2022. Analysis of regions, institutions, journals, authors, and keywords was conducted using CiteSpace, VOSviewer, and the R package "bibliometrix" to predict the latest trends in epigenetic research relevant to autoimmune diseases.

RESULTS

The number of epigenetic publications related to autoimmune diseases has been increasing annually. The United States has played a major role in this field, contributing over 45.9% of publications and leading in terms of publication volume and citation counts. Central South University emerged as the most active institution, contributing the highest number of publications. Frontiers in Immunology is the most popular journal in this field, publishing the most articles, while the Journal of Autoimmunity is the most co-cited journal. Lu QJ is the most prolific author, and Zhao M is the most frequently co-cited author. "Immunology" serves as a broad representative of epigenetic research in ADs. Hot topics in the field of epigenetic modifications associated with autoimmune diseases include "regulatory T cells (Treg)," "rheumatoid arthritis," "epigenetic regulation," "cAMPresponsive element modulator alpha," "cell-specific enhancer," "genetic susceptibility," and "systemic lupus erythematosus." Furthermore, the study discusses the frontiers and existing issues of epigenetic modifications in the development of autoimmune diseases.

CONCLUSIONS

This study provides a comprehensive overview of the knowledge structure and developmental trends in epigenetic research related to autoimmune diseases over the past 11 years.

Zfp296 knockout enhances chromatin accessibility and induces a unique state of pluripotency in embryonic stem cells

The Zfp296 gene encodes a zinc finger-type protein. Its expression is high in mouse embryonic stem cells (ESCs) but rapidly decreases following differentiation. Zfp296-knockout (KO) ESCs grew as flat colonies, which were reverted to rounded colonies by exogenous expression of Zfp296. KO ESCs could not form teratomas when transplanted into mice but could efficiently contribute to germline-competent chimeric mice following blastocyst injection. Transcriptome analysis revealed that Zfp296 deficiency up- and down-regulates a distinct group of genes, among which Dppa3, Otx2, and Pou3f1 were markedly downregulated. Chromatin immunoprecipitation sequencing demonstrated that ZFP296 binding is predominantly seen in the vicinity of the transcription start sites (TSSs) of a number of genes, and ZFP296 was suggested to negatively regulate transcription. Consistently, chromatin accessibility assay clearly showed that ZFP296 binding reduces the accessibility of the TSS regions of target genes. Zfp296-KO ESCs showed increased histone H3K9 di- and trimethylation. Co-immunoprecipitation analyses revealed interaction of ZFP296 with G9a and GLP. These results show that ZFP296 plays essential roles in maintaining the global epigenetic state of ESCs through multiple mechanisms including activation of Dppa3, attenuation of chromatin accessibility, and repression of H3K9 methylation, but that Zfp296-KO ESCs retain a unique state of pluripotency while lacking the teratoma-forming ability.

Recent advances in understanding DNA methylation of prostate cancer

Epigenetic modifications, such as DNA methylation, is widely studied in cancer. DNA methylation patterns have been shown to distinguish between benign and malignant tumors in various cancers, including prostate cancer. It may also contribute to oncogenesis, as it is frequently associated with downregulation of tumor suppressor genes. Aberrant patterns of DNA methylation, in particular the CpG island hypermethylator phenotype (CIMP), have shown associative evidence with distinct clinical features and outcomes, such as aggressive subtypes, higher Gleason score, prostate-specific antigen (PSA), and overall tumor stage, overall worse prognosis, as well as reduced survival. In prostate cancer, hypermethylation of specific genes is significantly different between tumor and normal tissues. Methylation patterns could distinguish between aggressive subtypes of prostate cancer, including neuroendocrine prostate cancer (NEPC) and castration resistant prostate adenocarcinoma. Further, DNA methylation is detectable in cell-free DNA (cfDNA) and is reflective of clinical outcome, making it a potential biomarker for prostate cancer. This review summarizes recent advances in understanding DNA methylation alterations in cancers with the focus on prostate cancer. We discuss the advanced methodology used for evaluating DNA methylation changes and the molecular regulators behind these changes. We also explore the clinical potential of DNA methylation as prostate cancer biomarkers and its potential for developing targeted treatment of CIMP subtype of prostate cancer.

Ultrasensitive fluorescence detection of multiple DNA methyltransferases based on DNA walkers and hyperbranched rolling circle amplification

The accurate and ultrasensitive detection of multiple methyltransferases was in great request for clinical diagnosis and epigenetic therapy. Here, a novel fluorescence assay was proposed for ultrasensitive CpG methyltransferase (M.SssI) and DNA adenine methyltransferase (Dam) activity detection based on hyperbranched rolling circle amplification (HRCA) and DNA walkers. The biosensor showed an extremely high sensitivity due to the dual-amplification strategy of HRCA and DNA walker. The LOD of the biosensor for M.SssI and Dam methyltransferase was estimated at 0.0004 U/mL and 0.001 U/mL, respectively. Without the presence of M.SssI methyltransferase, the corresponding recognition site of hairpin H_M was cleaved by HpaII endonuclease, generating a DNA fragment (T-DNA) and inducing the DNA walker-HRCA reaction. Since the HRCA products contained numerous double-strand DNA (dsDNA), SYBR Green I could be embedded in the dsDNA, leading to a high fluorescent signal. In the presence of M.SssI methyltransferase, the corresponding recognition site of hairpin H_M was methylated and the HpaII endonuclease-catalyzed stem of hairpin H_M dissociation was hindered, leading to no DNA fragment (T-DNA) present. Hence, the DNA walker-HRCA reaction was not initiated and the fluorescent signal of SYBR Green I remained at a low level. Similarly, DNA adenine methyltransferase (Dam) and its inhibitors could also be detected by redesigning hairpin H_D with the Dam recognition sequences. Furthermore, the sensing system was applied to analyze the endogenic Dam methyltransferase in the real samples such as E. coli cell lysate.

Endocrine Disrupting Chemicals Influence Hub Genes Associated with Aggressive Prostate Cancer

Prostate cancer (PCa) is one of the most frequently diagnosed cancers among men in the world. Its prevention has been limited because of an incomplete understanding of how environmental exposures to chemicals contribute to the molecular pathogenesis of aggressive PCa. Environmental exposures to endocrine-disrupting chemicals (EDCs) may mimic hormones involved in PCa development. This research aims to identify EDCs associated with PCa hub genes and/or transcription factors (TF) of these hub genes in addition to their protein-protein interaction (PPI) network. We are expanding upon the scope of our previous work, using six PCa microarray datasets, namely, GSE46602, GSE38241, GSE69223, GSE32571, GSE55945, and GSE26126, from the NCBI/GEO, to select differentially expressed genes based on |log2FC| (fold change) ≥ 1 and an adjusted p-value < 0.05. An integrated bioinformatics analysis was used for enrichment analysis (using DAVID.6.8, GO, KEGG, STRING, MCODE, CytoHubba, and GeneMANIA). Next, we validated the association of these PCa hub genes in RNA-seq PCa cases and controls from TCGA. The influence of environmental chemical exposures, including EDCs, was extrapolated using the chemical toxicogenomic database (CTD). A total of 369 overlapping DEGs were identified associated with biological processes, such as cancer pathways, cell division, response to estradiol, peptide hormone processing, and the p53 signaling pathway. Enrichment analysis revealed five up-regulated (NCAPG, MKI67, TPX2, CCNA2, CCNB1) and seven down-regulated (CDK1, CCNB2, AURKA, UBE2C, BUB1B, CENPF, RRM2) hub gene expressions. Expression levels of these hub genes were significant in PCa tissues with high Gleason scores ≥ 7. These identified hub genes influenced disease-free survival and overall survival of patients 60-80 years of age. The CTD studies showed 17 recognized EDCs that affect TFs (NFY, CETS1P54, OLF1, SRF, COMP1) that are known to bind to our PCa hub genes, namely, NCAPG, MKI67, CCNA2, CDK1, UBE2C, and CENPF. These validated differentially expressed hub genes can be potentially developed as molecular biomarkers with a systems perspective for risk assessment of a wide-ranging list of EDCs that may play overlapping and important role(s) in the prognosis of aggressive PCa.

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.

Aberrations of DNA methylation in cancer

DNA methylation is a chromatin modification that plays an important role in the epigenetic regulation of gene expression. Changes in DNA methylation patterns are characteristic of many malignant neoplasms. DNA methylation is occurred by DNA methyltransferases (DNMTs), while demethylation is mediated by TET family proteins. Mutations and changes in the expression profile of these enzymes lead to DNA hypo- and hypermethylation and have a strong impact on carcinogenesis. In this review, we considered the key aspects of the mechanisms of regulation of DNA methylation and demethylation, and also analyzed the role of DNA methyltransferases and TET family proteins in the pathogenesis of various malignant neoplasms.During the preparation of the review, we used the following biomedical literature information bases: Scopus (504), PubMed (553), Web of Science (1568), eLibrary (190). To obtain full-text documents, the electronic resources of PubMed Central (PMC), Science Direct, Research Gate, CyberLeninka were used. To analyze the mutational profile of epigenetic regulatory enzymes, we used the cBioportal portal (https://www.cbioportal.org / ), data from The AACR Project GENIE Consortium (https://www.mycancergenome.org / ), COSMIC, Clinvar, and The Cancer Genome Atlas (TCGA).

Genomic targets and selective inhibition of DNA methyltransferase isoforms

Background

DNA methylation in the human genome is established and maintained by DNA methyltransferases (DNMTs). DNMT isoforms show differential expression by cell lineage and during development, but much remains to be elucidated about their shared and unique genomic targets.

Results

We examined changes in the epigenome following overexpression of 13 DNMT isoforms in HEK293T cells. We observed increased methylation (Δβ > 0.2) at 43,405 CpG sites, with expression of DNMT3A2, DNMTΔ3B4 and DNMTΔ3B2 associated with the greatest impact. De novo methylation occurred primarily within open sea regions and at loci with intermediate methylation levels (β: 0.2–0.6). 53% of differentially methylated loci showed specificity towards a single DNMT subfamily, primarily DNMTΔ3B and DNMT3A and 39% towards a single isoform. These loci were significantly enriched for pathways related to neuronal development (DNMTΔ3B4), calcium homeostasis (DNMTΔ3B3) and ion transport (DNMT3L). Repetitive elements did not display differential sensitivity to overexpressed DNMTs, but hypermethylation of Alu elements was associated with their evolutionary age following overexpression of DNMT3A2, DNMT3B1, DNMT3B2 and DNMT3L. Differential methylation (Δβ > 0.1) was observed at 121 of the 353 loci associated with the Horvath ‘epigenetic clock’ model of ageing, with 51 showing isoform specificity, and was associated with reduction of epigenetic age by 5–15 years following overexpression of seven isoforms. Finally, we demonstrate the potential for dietary constituents to modify epigenetic marks through isoform-specific inhibition of methylation activity.

Conclusions

Our results provide insight into regions of the genome methylated uniquely by specific DNMT isoforms and demonstrate the potential for dietary intervention to modify the epigenome.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01325-4.

Prostate cancer in omics era

Recent advances in omics technology have prompted extraordinary attempts to define the molecular changes underlying the onset and progression of a variety of complex human diseases, including cancer. Since the advent of sequencing technology, cancer biology has become increasingly reliant on the generation and integration of data generated at these levels. The availability of multi-omic data has transformed medicine and biology by enabling integrated systems-level approaches. Multivariate signatures are expected to play a role in cancer detection, screening, patient classification, assessment of treatment response, and biomarker identification. This review reports current findings and highlights a number of studies that are both novel and groundbreaking in their application of multi Omics to prostate cancer.

Protocadherin Gamma C3 (PCDHGC3) Is Strongly Expressed in Glioblastoma and Its High Expression Is Associated with Longer Progression-Free Survival of Patients

Protocadherins (PCDHs) belong to the cadherin superfamily and represent the largest subgroup of calcium-dependent adhesion molecules. In the genome, most PCDHs are arranged in three clusters, α, β, and γ on chromosome 5q31. PCDHs are highly expressed in the central nervous system (CNS). Several PCDHs have tumor suppressor functions, but their individual role in primary brain tumors has not yet been elucidated. Here, we examined the mRNA expression of PCDHGC3, a member of the PCDHγ cluster, in non-cancerous brain tissue and in gliomas of different World Health Organization (WHO) grades and correlated it with the clinical data of the patients. We generated a PCDHGC3 knockout U343 cell line and examined its growth rate and migration in a wound healing assay. We showed that PCDHGC3 mRNA and protein were significantly overexpressed in glioma tissue compared to a non-cancerous brain specimen. This could be confirmed in glioma cell lines. High PCDHGC3 mRNA expression correlated with longer progression-free survival (PFS) in glioma patients. PCDHGC3 knockout in U343 resulted in a slower growth rate but a significantly faster migration rate in the wound healing assay and decreased the expression of several genes involved in WNT signaling. PCDHGC3 expression should therefore be further investigated as a PFS-marker in gliomas. However, more studies are needed to elucidate the molecular mechanisms underlying the PCDHGC3 effects.

Global DNA methylation of WTC prostate cancer tissues show signature differences compared to non-exposed cases

There is increased incidence of prostate cancer (PC) among World Trade Center (WTC)-exposed responders and community members, with preliminary evidence suggestive of more aggressive disease. While previous research is supportive of differences in DNA methylation and gene expression as a consequence of WTC exposure, as measured in blood of healthy individuals, the epigenetics of WTC PC tissues has yet to be explored. Patients were recruited from the World Trade Center Health Program. Non-WTC PC samples were frequency matched on age, race/ethnicity and Gleason score. Bisulfite-treated DNA was extracted from tumor tissue blocks and used to assess global DNA methylation with the MethylationEPIC BeadChip. Differential and pathway enrichment analyses were conducted. RNA from the same tumor blocks was used for gene expression analysis to further support DNA methylation findings. Methylation data were generated for 28 samples (13 WTC and 15 non-WTC). Statistically significant differences in methylation were observed for 3,586 genes; on average WTC samples were statistically significantly more hypermethylated (P = 0.04131). Pathway enrichment analysis revealed hypermethylation in epithelial mesenchymal transition (EMT), hypoxia, mitotic spindle, TNFA signaling via NFKB, WNT signaling, and TGF beta signaling pathways in WTC compared to non-WTC samples. The androgen response, G2M and MYC target pathways were hypomethylated. These results correlated well with RNA gene expression. In conclusion, long-term epigenic changes associated with WTC dust exposure were observed in PC tissues. These occurred in genes of critical pathways, likely increasing prostate tumorigenesis potential. This warrants analysis of larger WTC groups and other cancer types.

Computational epigenetic landscape analysis reveals association of CACNA1G-AS1, F11-AS1, NNT-AS1, and MSC-AS1 lncRNAs in prostate cancer progression through aberrant methylation

Aberrant expression of long non-coding RNAs (lncRNAs), caused by alterations in DNA methylation, is a driving factor in several cancers. Interplay between lncRNAs’ aberrant methylation and expression in prostate cancer (PC) progression still remains largely elusive. Therefore, this study characterized the genome-wide epigenetic landscape and expression profiles of lncRNAs and their clinical impact by integrating multi-omics data implementing bioinformatics approaches. We identified 62 differentially methylated CpG-sites (DMCs) and 199 differentially expressed lncRNAs (DElncRNAs), where 32 DElncRNAs contain 32 corresponding DMCs within promoter regions. Significant negative correlation was observed between 8 DElncRNAs-DMCs pairs. 3 (cg23614229, cg23957912, and cg11052780) DMCs and 4 (CACNA1G-AS1, F11-AS1, NNT-AS1, and MSC-AS1) DElncRNAs were identified as high-risk factors for poor prognosis of PC patients. Overexpression of hypo-methylated CACNA1G-AS1, F11-AS1, and NNT-AS1 and down-regulation of hyper-methylated MSC-AS1 significantly lower the survival of PC patients and could be a potential prognostic and therapeutic biomarker. These DElncRNAs were found to be associated with several molecular functions whose deregulation can lead to cancer. Involvement of these epigenetically deregulated DElncRNAs in cancer-related biological processes was also noticed. These findings provide new insights into the understanding of lncRNA regulation by aberrant DNA methylation which will help to clarify the epigenetic mechanisms underlying PC.

G9a inhibition by CM-272: Developing a novel anti-tumoral strategy for castration-resistant prostate cancer using 2D and 3D in vitro models

Castration-resistant prostate cancer (CRPC) is an incurable form of prostate cancer (PCa), with DNMT1 and G9a being reported as overexpressed, rendering them highly attractive targets for precision medicine. CM-272 is a dual inhibitor of both methyltransferases' activity. Herein, we assessed the response of different PCa cell lines to CM-272, in both 2D and 3D models, and explored the molecular mechanisms underlying CM-272 inhibitory effects. CRPC tissues displayed significantly higher DNMT1, G9a and H3K9me2 expression than localized PCa. In vitro, CM-272 caused a significant decrease in PCa cell viability and proliferation alongside with increased apoptotic levels. We disclose that, under the evaluated dose, CM-272 led to G9a activity inhibition, while not significantly affecting DNMT1 activity. Upon G9a knockdown, DU145 and PC3 showed decreased cell viability. Remarkably, DU145 cells treated with CM-272 or with G9a knockdown displayed no differences in viability, suggesting a SET-dependent mechanism. Contrarily, PC3 cell viability impact was higher in G9a knockdown, compared with CM-272 treatment, suggesting an additional G9a function. Moreover, DU145 cells overexpressing catalytically functional G9a disclosed higher resistance to CM-272 treatment, reinforcing that the drug mechanism of action is dependent on G9a catalytic function. Importantly, we successfully assembled spheroids from several prostate cell lines. Our results showed that CM-272 retained its anti-tumoral effects in 3D PCa models, leading to a clear reduction in cancer cell survival. We concluded that inhibition of G9a methyltransferase activity by CM-272 has anti-tumor effect in PCa cells, holding therapeutic potential against CRPC.

SEEMLIS: a flexible semi-automated method for enrichment of methylated DNA from low-input samples

Background

DNA methylation alterations have emerged as hallmarks of cancer and have been proposed as screening, prognostic, and predictive biomarkers. Traditional approaches for methylation analysis have relied on bisulfite conversion of DNA, which can damage DNA and is not suitable for targeted gene analysis in low-input samples. Here, we have adapted methyl-CpG-binding domain protein 2 (MBD2)-based DNA enrichment for use on a semi-automated exclusion-based sample preparation (ESP) platform for robust and scalable enrichment of methylated DNA from low-input samples, called SEEMLIS.

Results

We show that combining methylation-sensitive enzyme digestion with ESP-based MBD2 enrichment allows for single gene analysis with high sensitivity for GSTP1 in highly impure, heterogenous samples. We also show that ESP-based MBD2 enrichment coupled with targeted pre-amplification allows for analysis of multiple genes with sensitivities approaching the single cell level in pure samples for GSTP1 and RASSF1 and sensitivity down to 14 cells for these genes in highly impure samples. Finally, we demonstrate the potential clinical utility of SEEMLIS by successful detection of methylated gene signatures in circulating tumor cells (CTCs) from patients with prostate cancer with varying CTC number and sample purity.

Conclusions

SEEMLIS is a robust assay for targeted DNA methylation analysis in low-input samples, with flexibility at multiple steps. We demonstrate the feasibility of this assay to analyze DNA methylation in prostate cancer cells using CTCs from patients with prostate cancer as a real-world example of a low-input analyte of clinical importance. In summary, this novel assay provides a platform for determining methylation signatures in rare cell populations with broad implications for research as well as clinical applications.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01252-4.

Ultrasensitive detection of DNA methyltransferase activity: a novel dual-amplification fluorescence technique

A dual amplification fluorescence strategy was developed for the ultrasensitive detection of Dam MTase activity based on strand displacement amplification coupled with rolling circle amplification.

Signature Panel of 11 Methylated mRNAs and 3 Methylated lncRNAs for Prediction of Recurrence-Free Survival in Prostate Cancer Patients

Background

Radical prostatectomy is the main treatment for prostate cancer (PCa), a common cancer type among men. Recurrence frequently occurs in a proportion of patients. Therefore, there is a great need to early screen those patients to specifically schedule adjuvant therapy to improve the recurrence-free survival (RFS) rate. This study aims to develop a biomarker to predict RFS for patients with PCa based on the data of methylation, an important heritable contributor to carcinogenesis.

Methods

Methylation expression data of PCa patients were downloaded from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus database (GSE26126), and the European Bioinformatics Institute (E-MTAB-6131). The stable co-methylation modules were identified by weighted gene co-expression network analysis. The genes in modules were overlapped with differentially methylated RNAs (DMRs) screened by MetaDE package in three datasets, which were used to screen the prognostic genes using least absolute shrinkage and selection operator analyses. The prognostic performance of the prognostic signature was assessed by survival curve analysis.

Results

Five co-methylation modules were considered preserved in three datasets. A total of 192 genes in these 5 modules were overlapped with 985 DMRs, from which a signature panel of 11 methylated messenger RNAs and 3 methylated long non-coding RNAs was identified. This signature panel could independently predict the 5-year RFS of PCa patients, with an area under the receiver operating characteristic curve (AUC) of 0.969 for the training TCGA dataset and 0.811 for the testing E-MTAB-6131 dataset, both of which were higher than the predictive accuracy of Gleason score (AUC = 0.689). Also, the patients with the same Gleason score (6–7 or 8–10) could be further divided into the high-risk group and the low-risk group.

Conclusion

These results suggest that our prognostic model may be a promising biomarker for clinical prediction of RFS in PCa patients.

5-aza-2'-deoxycitidine inhibits cell proliferation, extracellular matrix formation and Wnt/β-catenin pathway in human uterine leiomyomas

BACKGROUND

Uterine leiomyoma is a benign tumor with unclear pathogenesis and inaccurate treatment. This tumor exhibits altered DNA methylation related to disease progression. DNMT inhibitors as 5-aza-2'-deoxycytidine (5-aza-CdR), have been suggested to treat tumors in which DNA methylation is altered. We aimed to evaluate whether DNA methylation reversion with 5-aza-CdR reduces cell proliferation and extracellular matrix (ECM) formation in uterine leiomyoma cells to provide a potential treatment option.

METHODS

Prospective study using uterine leiomyoma and adjacent myometrium tissues and human uterine leiomyoma primary (HULP) cells (n = 16). In tissues, gene expression was analyzed by qRT-PCR and DNMT activity by ELISA. Effects of 5-aza-CdR treatment on HULP cells were assessed by CellTiter, western blot, and qRT-PCR.

RESULTS

DNMT1 gene expression was higher in uterine leiomyoma vs myometrium. Similarly, DNMT activity was greater in uterine leiomyoma and HULP cells (6.5 vs 3.8 OD/h/mg; 211.3 vs 63.7 OD/h/mg, respectively). After 5-aza-CdR treatment on HULP cells, cell viability was reduced, significantly so at 10 μM (85.3%). Treatment with 10 μM 5-aza-CdR on HULP cells significantly decreased expression of proliferation marker PCNA (FC = 0.695) and of ECM proteins (COLLAGEN I FC = 0.654; PAI-1, FC = 0.654; FIBRONECTIN FC = 0.733). 5-aza-CdR treatment also decreased expression of Wnt/β-catenin pathway final targets, including WISP1 protein expression (10 μM, FC = 0.699), c-MYC gene expression (2 μM, FC = 0.745 and 10 μM, FC = 0.728), and MMP7 gene expression (5 μM, FC = 0.520 and 10 μM, FC = 0.577).

CONCLUSIONS

5-aza-CdR treatment inhibits cell proliferation, ECM formation, and Wnt/β-catenin signaling pathway targets in HULP cells, suggesting that DNA methylation inhibition is a viable therapeutic target in uterine leiomyoma.

Promoter Methylation of PRKCB, ADAMTS12, and NAALAD2 Is Specific to Prostate Cancer and Predicts Biochemical Disease Recurrence

The molecular diversity of prostate cancer (PCa) has been demonstrated by recent genome-wide studies, proposing a significant number of different molecular markers. However, only a few of them have been transferred into clinical practice so far. The present study aimed to identify and validate novel DNA methylation biomarkers for PCa diagnosis and prognosis. Microarray-based methylome data of well-characterized cancerous and noncancerous prostate tissue (NPT) pairs was used for the initial screening. Ten protein-coding genes were selected for validation in a set of 151 PCa, 51 NPT, as well as 17 benign prostatic hyperplasia samples. The Prostate Cancer Dataset (PRAD) of The Cancer Genome Atlas (TCGA) was utilized for independent validation of our findings. Methylation frequencies of ADAMTS12, CCDC181, FILIP1L, NAALAD2, PRKCB, and ZMIZ1 were up to 91% in our study. PCa specific methylation of ADAMTS12, CCDC181, NAALAD2, and PRKCB was demonstrated by qualitative and quantitative means (all p < 0.05). In agreement with PRAD, promoter methylation of these four genes was associated with the transcript down-regulation in the Lithuanian cohort (all p < 0.05). Methylation of ADAMTS12, NAALAD2, and PRKCB was independently predictive for biochemical disease recurrence, while NAALAD2 and PRKCB increased the prognostic power of multivariate models (all p < 0.01). The present study identified methylation of ADAMTS12, NAALAD2, and PRKCB as novel diagnostic and prognostic PCa biomarkers that might guide treatment decisions in clinical practice.

MYC DNA Methylation in Prostate Tumor Tissue Is Associated with Gleason Score

Increasing evidence suggests a role of epigenetic mechanisms at chromosome 8q24, an important cancer genetic susceptibility region, in prostate cancer. We investigated whether MYC DNA methylation at 8q24 (six CpG sites from exon 3 to the 3′ UTR) in prostate tumor was associated with tumor aggressiveness (based on Gleason score, GS), and we incorporated RNA expression data to investigate the function. We accessed radical prostatectomy tissue for 50 Caucasian and 50 African American prostate cancer patients at the University of Maryland Medical Center, selecting an equal number of GS 6 and GS 7 cases per group. MYC DNA methylation was lower in tumor than paired normal prostate tissue for all six CpG sites (median difference: −14.74 to −0.20 percentage points), and we observed similar results for two nearby sites in The Cancer Genome Atlas (p < 0.0001). We observed significantly lower methylation for more aggressive (GS 7) than less aggressive (GS 6) tumors for three exon 3 sites (for CpG 212 (chr8:128753145), GS 6 median = 89.7%; GS 7 median = 85.8%; p-value = 9.4 × 10⁻⁴). MYC DNA methylation was not associated with MYC expression, but was inversely associated with PRNCR1 expression after multiple comparison adjustment (q-value = 0.04). Findings suggest that prostate tumor MYC exon 3 hypomethylation is associated with increased aggressiveness.

DNA methyltransferase 3B plays a protective role against hepatocarcinogenesis caused by chronic inflammation via maintaining mitochondrial homeostasis

Most hepatocellular carcinomas (HCCs) develop on the basis of chronic hepatitis, but the mechanism of epigenetic regulation in inflammatory hepatocarcinogenesis has yet to be elucidated. Among de novo DNA methyltransferases (DNMTs), DNMT3B has lately been reported to act specifically on actively transcribed genes, suggesting the possibility that it plays a role in the pathogenesis of cancer. We confirmed that DNMT3B isoforms lacking its catalytic domain were highly expressed in HCCs compared with non-tumorous liver tissue. To elucidate the role of DNMT3B in hepatocarcinogenesis, we generated a genetically engineered mouse model with hepatocyte-specific Dnmt3b deletion. The liver of the Dnmt3b-deficient mice exhibited an exacerbation of thioacetamide-induced hepatitis, progression of liver fibrosis and a higher incidence of HCC compared with the liver of the control mice. Whole-genome bisulfite sequencing verified a lower CG methylation level in the Dnmt3b-deficient liver, demonstrating differentially methylated regions throughout the genome. Transcriptome analysis revealed decreased expression of genes related to oxidative phosphorylation in the Dnmt3b-deficient liver. Moreover, primary hepatocytes isolated from the Dnmt3b-deficient mice showed reduced mitochondrial respiratory capacity, leading to the enhancement of oxidative stress in the liver tissue. Our findings suggest the protective role of DNMT3B against chronic inflammation and HCC development via maintaining mitochondrial homeostasis.

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.

Omics Derived Biomarkers and Novel Drug Targets for Improved Intervention in Advanced Prostate Cancer

Prostate cancer (PCa) is one of the most frequently diagnosed malignancies, and the fifth leading cause of cancer related mortality in men. For advanced PCa, radical prostatectomy, radiotherapy, and/or long-term androgen deprivation therapy are the recommended treatment options. However, subsequent progression to metastatic disease after initial therapy results in low 5-year survival rates (29%). Omics technologies enable the acquisition of high-resolution large datasets that can provide insights into molecular mechanisms underlying PCa pathology. For the purpose of this article, a systematic literature search was conducted through the Web of Science Database to critically evaluate recent omics-driven studies that were performed towards: (a) Biomarker development and (b) characterization of novel molecular-based therapeutic targets. The results indicate that multiple omics-based biomarkers with prognostic and predictive value have been validated in the context of PCa, with several of those being also available for commercial use. At the same time, omics-driven potential drug targets have been investigated in pre-clinical settings and even in clinical trials, holding the promise for improved clinical management of advanced PCa, as part of personalized medicine pipelines.

Regulation of RUNX3 Expression by DNA Methylation in Prostate Cancer

Purpose

To investigate the role of DNA methylation in the regulation of Runt-related transcription factor 3 (RUNX3) and the effect of such mechanism on the proliferation of prostate cancer (PCa) cells.

Materials and Methods

The methylation of the RUNX3 in the promoter region in PCa cells was detected by bisulfite-sequencing PCR (BSP). Following treatment of the PCa cells with DNA methylation transferase inhibitor 5-AZA-2'-deoxycytidine (AZA), the effect on methylation level and expression of RUNX3 were analyzed by qRT-PCR, Western blot, and BSP assays. Furthermore, we investigated the effect of the demethylated RUNX3 on proliferation, cell cycle and apoptosis of PCa cells using CCK-8 and flow cytometry assays. Using the DNA methylation transferase (DNMT3b) knockout or overexpression models, the relationship between DNMT3b and RUNX3 methylation was further assessed by qRT-PCR, Western blot and methylation-specific PCR (MSP).

Results

The results indicated that the methylation level of RUNX3 in PCa cell lines was significantly higher than that of normal prostate epithelial (RWPE-1) cells. Furthermore, treatment with AZA not only promoted the demethylation of RUNX3 but also restored the mRNA and protein expression of RUNX3, and the reactivation of expression of the later exhibited its anti-tumor effects through regulation of the cycle progression in PCa cells. Moreover, DNMT3b could regulate the expression level of RUNX3 by altering the DNA methylation of the RUNX3 in PCa cells.

Conclusion

RUNX3 is hypermethylated in a panel of PCa cell lines; inhibition of DNA methylation of RUNX3 could restore its gene expression, which could promote its anticancer effect. Thus, RUNX3 may serve as a novel putative molecular target gene for PCa therapy.

An integrative multi-omics analysis to identify candidate DNA methylation biomarkers related to prostate cancer risk

It remains elusive whether some of the associations identified in genome-wide association studies of prostate cancer (PrCa) may be due to regulatory effects of genetic variants on CpG sites, which may further influence expression of PrCa target genes. To search for CpG sites associated with PrCa risk, here we establish genetic models to predict methylation (N = 1,595) and conduct association analyses with PrCa risk (79,194 cases and 61,112 controls). We identify 759 CpG sites showing an association, including 15 located at novel loci. Among those 759 CpG sites, methylation of 42 is associated with expression of 28 adjacent genes. Among 22 genes, 18 show an association with PrCa risk. Overall, 25 CpG sites show consistent association directions for the methylation-gene expression-PrCa pathway. We identify DNA methylation biomarkers associated with PrCa, and our findings suggest that specific CpG sites may influence PrCa via regulating expression of candidate PrCa target genes.

Fluorescence biosensor for DNA methyltransferase activity and related inhibitor detection based on methylation-sensitive cleavage primer triggered hyperbranched rolling circle amplification

Highly sensitive and selective detection of DNA adenine methylation methyltransferase (Dam MTase) activity is essential for clinical diagnosis and treatment as Dam MTase can catalyze DNA methylation and has a profound effect on gene regulation. In this study, a fluorescence biosensor has been developed for label-free detection of Dam MTase activity via methylation-sensitive cleavage primers triggered hyperbranched rolling circle amplification (HRCA). A hairpin DNA probe (HP) with a Dam MTase specific recognition sequence on the stem acting as a substrate has been designed. This substrate probe can be methylated by the target in the system and subsequently cleaved by DpnI, which results in the release of the primer release probe (RP) and hence in turn triggers the subsequent HRCA reaction. As the HRCA products contain many double-strand DNA (dsDNA) with different lengths, and the SYBR Green I can be embedded in the dsDNA to produce a strong fluorescence signal. However, in the absence of the target, the presence of the probe HP in the form of a hairpin cannot induce the HRCA reaction, and only weak fluorescence intensity can be detected. Under the optimized conditions, the fluorescence of the system has a linear relationship with the logarithm of the concentration of Dam MTase in the range of 2.5-70 U/mL with a detection limit of 1.8 U/mL. The Dam MTase can be well distinguished from other MTase analogs. The developed sensor was applied to detect target in serum and E. coli cell lysate, and the standard recovery rates were in the range of 96%-105%. The results showed that this method has great potential for assessing Dam MTase activity in complex biological samples. In addition, the method has been applied to detect the related inhibitors with high efficiency.

The DNA methylation landscape of advanced prostate cancer

Although DNA methylation is a key regulator of gene expression, the comprehensive methylation landscape of metastatic cancer has never been defined. Through whole-genome bisulfite sequencing paired with deep whole-genome and transcriptome sequencing of 100 castration-resistant prostate metastases, we discovered alterations affecting driver genes only detectable with integrated whole-genome approaches. Notably, we observed that 22% of tumors exhibited a novel epigenomic subtype associated with hyper-methylation and somatic mutations in TET2, DNMT3B, IDH1, and BRAF. We also identified intergenic regions where methylation is associated with RNA expression of the oncogenic driver genes AR, MYC and ERG. Finally, we showed that differential methylation during progression preferentially occurs at somatic mutational hotspots and putative regulatory regions. This study is a large integrated study of whole-genome, whole-methylome and whole-transcriptome sequencing in metastatic cancer and provides a comprehensive overview of the important regulatory role of methylation in metastatic castration-resistant prostate cancer.

De novo methyltransferases: Potential players in diseases and new directions for targeted therapy

Epigenetic modifications govern gene expression by guiding the human genome on 'what to express and what not to'. DNA methyltransferases (DNMTs) establish methylation patterns on DNA, particularly in CpG islands, and such patterns play a major role in gene silencing. DNMTs are a family of proteins/enzymes (DNMT1, 2, 3A, 3B, and 3L), among which, DNMT1 (maintenance methyltransferase) and DNMT3 (de novo methyltransferases) that direct mammalian development and genome imprinting are highly investigated. In recent decades, many studies revealed a strong association of DNA methylation patterns with gene expression in various clinical conditions. Differential expression of DNMT3 family proteins and their splice variants result in changes in methylation patterns and such alterations have been associated with the initiation and progression of various diseases, especially cancer. This review will discuss the aberrant modifications generated by DNMT3 proteins under various clinical conditions, suggesting a potential signature for de novo methyltransferases in targeted disease therapy. Further, this review discusses the possibility of using 'CpG island methylation signatures' as promising biomarkers and emphasizes 'targeted hypomethylation' by disrupting the interaction of specific DNMT-protein complexes as the future of cancer therapeutics.

Improving the classification performance with group lasso-based ranking method in high dimensional correlated data

The high-throughput correlated DNA methylation (DNAmeth) dataset generated from Illumina Infinium Human Methylation 27 (IIHM 27K) BeadChip assay. In the DNAmeth data, there are several CpG sites for every gene, and these grouped CpG sites are highly correlated. Most of the current filtering-based ranking (FBR) methods do not consider the group correlation structures. Obtaining the significant features with the FBR methods and applying these features to the classifiers to attain the best classification accuracy in highly correlated DNAmeth data is a challenging task. In this research, we introduce a resampling of group least absolute shrinkage and selection operator (glasso) FBR method capable of ignoring the unrelated features in the data considering the group correlation among the features. The various classifiers, such as random forests (RF), Naive Bayes (NB), and support vector machines (SVM) with the significant CpGs obtained from the proposed resampling of group lasso-based ranking (RGLR) method helped to boost the classification accuracy. Through simulated and experimental prostate DNAmeth data, we showed that higher performance of accuracy, sensitivity, specificity, and geometric mean is achieved by ignoring the unimportant CpG sites through the RGLR method.

RETRACTED: lncRNA RMST Enhances DNMT3 Expression through Interaction with HuR

This article has been retracted: please see Elsevier Policy on Article Withdrawal (http://www.elsevier.com/locate/withdrawalpolicy). This article has been retracted at the request of the editors and the corresponding author (Yin-Yuan Mo). Concerns regarding potentially duplicated western blots in Figures 2I and 3I were raised by readers on PubPeer (https://pubpeer.com/publications/64075911BAD21941D78C27FD3B8DB3#16), and the authors contacted the editorial office with the original blots to issue a correction. Following the correction of the article, the authors provided additional raw data to address further concerns raised by a reader. Given multiple inconsistencies in file labeling and post-acquisition processing, the editors have lost faith in the findings presented in the article. The retraction notice email was undeliverable to the following authors: Chao Ni, Pratirodh Koirala, Wei Zhang, and Wan-Xin Peng.

DNA hypermethylation associated with upregulated gene expression in prostate cancer demonstrates the diversity of epigenetic regulation

Background

Prostate cancer (PCa) has the highest incidence rates of cancers in men in western countries. Unlike several other types of cancer, PCa has few genetic drivers, which has led researchers to look for additional epigenetic and transcriptomic contributors to PCa development and progression. Especially datasets on DNA methylation, the most commonly studied epigenetic marker, have recently been measured and analysed in several PCa patient cohorts. DNA methylation is most commonly associated with downregulation of gene expression. However, positive associations of DNA methylation to gene expression have also been reported, suggesting a more diverse mechanism of epigenetic regulation. Such additional complexity could have important implications for understanding prostate cancer development but has not been studied at a genome-wide scale.

Results

In this study, we have compared three sets of genome-wide single-site DNA methylation data from 870 PCa and normal tissue samples with multi-cohort gene expression data from 1117 samples, including 532 samples where DNA methylation and gene expression have been measured on the exact same samples. Genes were classified according to their corresponding methylation and expression profiles. A large group of hypermethylated genes was robustly associated with increased gene expression (UPUP group) in all three methylation datasets. These genes demonstrated distinct patterns of correlation between DNA methylation and gene expression compared to the genes showing the canonical negative association between methylation and expression (UPDOWN group). This indicates a more diversified role of DNA methylation in regulating gene expression than previously appreciated. Moreover, UPUP and UPDOWN genes were associated with different compartments — UPUP genes were related to the structures in nucleus, while UPDOWN genes were linked to extracellular features.

Conclusion

We identified a robust association between hypermethylation and upregulation of gene expression when comparing samples from prostate cancer and normal tissue. These results challenge the classical view where DNA methylation is always associated with suppression of gene expression, which underlines the importance of considering corresponding expression data when assessing the downstream regulatory effect of DNA methylation.

Immuno-DNA binding directed template-free DNA extension and enzyme catalysis for sensitive electrochemical DNA methyltransferase activity assay and inhibitor screening

A new electrochemical immuno-DNA sensing platform for DNA methyltransferase activity assay and inhibitor screening.

Analyzing high dimensional correlated data using feature ranking and classifiers

The Illumina Infinium HumanMethylation27 (Illumina 27K) BeadChip assay is a relatively recent high-throughput technology that allows over 27,000 CpGs to be assayed. The Illumina 27K methylation data is less commonly used in comparison to gene expression in bioinformatics. It provides a critical need to find the optimal feature ranking (FR) method for handling the high dimensional data. The optimal FR method on the classifier is not well known, and choosing the best performing FR method becomes more challenging in high dimensional data setting. Therefore, identifying the statistical methods which boost the inference is of crucial importance in this context. This paper describes the detailed performances of FR methods such as fisher score, information gain, chi-square, and minimum redundancy and maximum relevance on different classification methods such as Adaboost, Random Forest, Naive Bayes, and Support Vector Machines. Through simulation study and real data applications, we show that the fisher score as an FR method, when applied on all the classifiers, achieved best prediction accuracy with significantly small number of ranked features.

Epigenetic regulation of prostate cancer

Prostate cancer is (PCa) the second leading cause of cancer death in males in the United State, with 174,650 new cases and 31,620 deaths estimated in 2019. It has been documented that epigenetic deregulation such as histone modification and DNA methylation contributes to PCa initiation and progression. EZH2 (enhancer of zeste homolog 2), the catalytic subunit of the Polycomb Repressive Complex (PRC2) responsible for H3K27me3 and gene repression, has been identified as a promising target in PCa. In addition, overexpression of other epigenetic regulators such as DNA methyltransferases (DNMT) is also observed in PCa. These epigenetic regulators undergo extensive post-translational modifications, in particular, phosphorylation. AKT, CDKs, PLK1, PKA, ATR and DNA-PK are the established kinases responsible for phosphorylation of various epigenetic regulators.

A three-gene DNA methylation biomarker accurately classifies early stage prostate cancer

BACKGROUND

We identify and validate accurate diagnostic biomarkers for prostate cancer through a systematic evaluation of DNA methylation alterations.

MATERIALS AND METHODS

We assembled three early prostate cancer cohorts (total patients = 699) from which we collected and processed over 1300 prostatectomy tissue samples for DNA extraction. Using real-time methylation-specific PCR, we measured normalized methylation levels at 15 frequently methylated loci. After partitioning sample sets into independent training and validation cohorts, classifiers were developed using logistic regression, analyzed, and validated.

RESULTS

In the training dataset, DNA methylation levels at 7 of 15 genomic loci (glutathione S-transferase Pi 1 [GSTP1], CCDC181, hyaluronan, and proteoglycan link protein 3 [HAPLN3], GSTM2, growth arrest-specific 6 [GAS6], RASSF1, and APC) showed large differences between cancer and benign samples. The best binary classifier was the GAS6/GSTP1/HAPLN3 logistic regression model, with an area under these curves of 0.97, which showed a sensitivity of 94%, and a specificity of 93% after external validation.

CONCLUSION

We created and validated a multigene model for the classification of benign and malignant prostate tissue. With false positive and negative rates below 7%, this three-gene biomarker represents a promising basis for more accurate prostate cancer diagnosis.

Potential of epigenetic events in human thyroid cancer

Thyroid cancer remains the highest prevailing endocrine malignancy, and its incidence rate has progressively increased in the previous years. Above 95% of thyroid tumor are follicular cells types of carcinoma in which are considered invasive type of tumor. The pathogenesis and molecular mechanism of thyroid tumors are yet remains elucidated, in spite of activating RET, RAS and BRAF carcinogenesis have been well introduced. Nemours molecular alterations have been defined and have revealed promise for their diagnostic, prognostic and therapeutic capacity but still need further confirmation. Among different types of mechanisms, the current article reviews the importance of epigenetic modifications in thyroid cancer. Increasing data from previous reports demonstrate that acquired epigenetic abnormalities together with genetic changes plays an important role in alteration of gene expression patterns. Aberrant DNA methylation has been well known in the CpG regions and profile of microRNAs (mi-RNAs) expression also involved in cancer development. In addition, the gene expression through epigenetic control contribution to thyroid cancer is analyzed and it is semi considered in the clinic. However the epigenetic of the thyroid cancer is yet remains in its early stages, and it carries encouraging potential thyroid cancer detections in its early stages, assessment of prognosis and targeted cancer treatment.

SLCO4C1 promoter methylation is a potential biomarker for prognosis associated with biochemical recurrence-free survival after radical prostatectomy

BACKGROUND

Prostate cancer (PC) is a commonly diagnosed malignancy in males, especially in the western hemisphere. The extensive use of multiple biomarkers plays an important role in the diagnosis and prognosis of PC. However, the accuracy of biomarkers for PC prognosis needs to be urgently improved. This study aimed to identify a novel prognostic biomarker for PC.

MATERIALS AND METHODS

Differentially methylated CpG sites were identified from the GSE76938 dataset ( https://www.ncbi.nlm.nih.gov/geo/ ) using R software version 3.1.4. Four significant CpG sites on the SLCO4C1 gene were found to be closely associated with prognosis in PC. Data downloaded from The Cancer Genome Atlas (TCGA) were used for validation. Co-expression and functional enrichment analyses were used to explore the roles of SLCO4C1 in molecular functions, biological processes and cellular components. Total RNA extraction and qRT-PCR were used to reveal the difference in SLCO4C1 expression between tumour and normal tissues. Bisulfite amplicon sequencing (BSAS) was used to identify methylation levels at the CpG sites.

RESULTS

In the GSE76938 cohort, 10,206 CpG sites were identified to be differentially methylated in tumour versus normal prostate tissues. Among the CpG sites, four sites (cg06480736, cg19774478, cg19788741 and cg22149516) located in the promotor region (TSS200-1500) of SLCO4C1 were found to be significantly hypermethylated in tumour tissues. The results were validated in an independent dataset (TCGA PRAD cohort). In the cohort from TCGA, SLCO4C1 expression was negatively correlated with methylation levels at the four sites. The results of qRT-PCR validated that tumour tissues had a relatively lower expression of SLCO4C1. Bisulfite amplicon sequencing (BSAS) further confirmed a higher methylation level at the SLCO4C1 promoter in tumour tissues. SLCO4C1 (cg06480736, cg19774478, cg19788741 and cg22149516) was identified as a significant promising biomarker for biochemical recurrence-free survival in Kaplan-Meier analysis (P < 0.01) and univariate Cox proportional hazards analysis: cg06480736 (HR 15.914, P < 0.001), cg19774478 (HR 9.001, P < 0.001), cg19788741 (HR 10.759, P = 0.003) and cg22149516 (HR 17.144, P = 0.006). However, three sites, namely, cg06480736 (HR 1.809, P = 0.049), cg19774478 (HR 1.903, P = 0.041) and cg22149516 (HR 2.316, P = 0.008), were confirmed in multivariate analysis.

CONCLUSIONS

SLCO4C1 promoter methylation, including that at three CpG sites, namely, cg06480736, cg19774478 and cg22149516, is a potential biomarker for risk stratification and might offer significantly relevant prognostic information for PC patients after radical prostatectomy.

Identification of TAF1, HNF4A, and CALM2 as potential therapeutic target genes for liver fibrosis

The molecular mechanism of liver fibrosis caused by hepatitis C virus (HCV) is not clear. The aim of this study is to understand the molecular mechanism of liver fibrosis induced by HCV and to identify potential therapeutic targets for hepatic fibrosis. We analyzed gene expression patterns between high liver fibrosis and low liver fibrosis samples, and identified genes related to liver fibrosis. We identified TAF1, HNF4A, and CALM2 were related to the development of liver fibrosis. HNF4A is important for hepatic fibrogenesis, and upregulation of HNF4A is an ideal choice for treating liver fibrosis. The gene expression of CALM2 is significantly lower in liver fibrosis samples than nonfibrotic samples. TAF1 may serve as a biomarker for liver fibrosis. The results were further validated by an independent data set GSE84044. In summary, our study described changes in the gene expression during the occurrence and development of liver fibrosis. The TAF1, HNF4A, and CALM2 may serve as novel targets for the treatment of liver fibrosis.

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.

Dual-Amplification Strategy-Based SERS Chip for Sensitive and Reproducible Detection of DNA Methyltransferase Activity in Human Serum

Herein, we present a dual-amplification sensing strategy-based surface-enhanced Raman scattering (SERS) chip, which combines rolling circle amplification (RCA) and polyadenine (PolyA) assembly for sensitive and reproducible determination of the activity of M.SssI, a cytosine-guanine dinucleotide (CpG) methyltransferase (MTase). Typically, in the presence of M.SssI, RCA process is triggered, resulting in long, single-stranded DNA (ssDNA) fragments that are hybridized with thousands of Raman reporters of Cy3. Afterward, the resultant ssDNA fragments are conjugated to SERS-active substrates made of silver core-gold satellite nanocomposites-modified silicon wafer (Ag-Au NPs@Si), with the SERS enhancement factor of ∼5 × 10⁶. The core-satellite nanostructures are assembled relied on the strong affinity of PolyA toward gold/silver surface. Of particular significance, the developed SERS chip displays an ultrahigh sensitivity with a low limit of detection (LOD) of 2.8 × 10^-3 U/mL, which is around 2 orders of magnitude higher than most reported methods. In addition, the constructed chip features a broad detection range covering from 0.05 to 50 U/mL. Besides for the ultrahigh sensitivity and broad dynamic range, the chip also features good reproducibility (e.g., the relative standard deviation (RSD) is less than ∼12%). Taking advantages of these merits, the developed chip is feasible for accurate discrimination of M.SssI with various concentrations spiked in human serum samples with good recoveries ranging from 99.6% to 107%.

Epigenetic Suppression of SERPINB1 Promotes Inflammation-Mediated Prostate Cancer Progression

Granulocytic myeloid infiltration and resultant enhanced neutrophil elastase (NE) activity is associated with poor outcomes in numerous malignancies. We recently showed that NE expression and activity from infiltrating myeloid cells was high in human prostate cancer xenografts and mouse Pten-null prostate tumors. We further demonstrated that NE directly stimulated human prostate cancer cells to proliferate, migrate, and invade, and inhibition of NE in vivo attenuated xenograft growth. Interestingly, reduced expression of SERPINB1, an endogenous NE inhibitor, also correlates with diminished survival in some cancers. Therefore, we sought to characterize the role of SERPINB1 in prostate cancer. We find that SERPINB1 expression is reduced in human metastatic and locally advanced disease and predicts poor outcome. SERPINB1 is also reduced in Pten-null mouse prostate tumors compared with wild-type prostates, and treatment with sivelestat (SERPINB1 pharmacomimetic) attenuates tumor growth. Knockdown of highly expressed SERPINB1 in nonmalignant prostatic epithelial cells (RWPE-1) increases proliferation, decreases apoptosis, and stimulates expression of epithelial-to-mesenchymal transition markers. In contrast, stable SERPINB1 expression in normally low-expressing prostate cancer cells (C4-2) reduces xenograft growth in vivo. Finally, EZH2-mediated histone (H3K27me3) methylation and DNA methyltransferase-mediated DNA methylation suppress SERPINB1 expression in prostate cancer cells. Analysis of The Cancer Genome Atlas and pyrosequencing demonstrate hypermethylation of the SERPINB1 promoter in prostate cancer compared with normal tissue, and the extent of promoter methylation negatively correlates with SERPINB1 mRNA expression. IMPLICATIONS: Our findings suggest that the balance between SERPINB1 and NE is physiologically important within the prostate and may serve as a biomarker and therapeutic target in prostate cancer.