Use of DNA methylation for cancer detection: Promises and challenges

Genomic Analysis of Abnormal DNAM Methylation in Parathyroid Tumors

BACKGROUND

Parathyroid tumors are common endocrine neoplasias associated with primary hyperparathyroidism. Although numerous studies have studied the subject, the predictive value of gene biomarkers nevertheless remains low.

METHODS

In this study, we performed genomic analysis of abnormal DNA methylation in parathyroid tumors. After data preprocessing, differentially methylated genes were extracted from patients with parathyroid tumors by using t-tests.

RESULTS

After refinement of the basic differential methylation, 28241 unique CpGs (634 genes) were identified to be methylated. The methylated genes were primarily involved in 7 GO terms, and the top 3 terms were associated with cyst morphogenesis, ion transport, and GTPase signal. Following pathway enrichment analyses, a total of 10 significant pathways were enriched; notably, the top 3 pathways were cholinergic synapses, glutamatergic synapses, and oxytocin signaling pathways. Based on PPIN and ego-net analysis, 67 ego genes were found which could completely separate the diseased group from the normal group. The 10 most prominent genes included POLA1, FAM155 B, AMMECR1, THOC2, CCND1, CLDN11, IDS, TST, RBPJ, and GNA11. SVM analysis confirmed that this grouping approach was precise.

CONCLUSIONS

This research provides useful data to further explore novel genes and pathways as therapeutic targets for parathyroid tumors.

Magnetic particle based liquid biopsy chip for isolation of extracellular vesicles and characterization by gene amplification

Extracellular vesicles (EVs) are the cell-derived vesicles which play a critical role in cell-to-cell communication, and disease progression. These vesicles contain a myriad of substances like RNA, DNA, proteins, and lipids from their origin cells, offering a good source of biomarkers. The existing methods for the isolation of EVs are time-consuming, lack yield and purity, and expensive. In this work, we present a magnetic particle based liquid biopsy chip for the isolation of EVs by using a synthetic peptide, Vn96. To ensure capture efficiency, a 3D mixer is integrated in the chip, along with a sedimentation unit, which allows EV-captured magnetic particles to settle in it based on gravity assisted sedimentation. The captured EVs are then isolated for their elution and validation. The EVs are characterized by the scanning electron microscopy (SEM) measurements and the ability of capture and isolation of EVs is validated by the nanoparticle tracking analysis (NTA) and atomic force microscopy (AFM). The DNA content of the EVs is further characterized by the absolute quantification of a housekeeping gene (RNase P) copies using droplet digital PCR (ddPCR). The results show that the chip can capture and isolate the EVs, without affecting their morphology. Thus, the liquid biopsy chip can be considered as a potential point of care device for diagnostics in a clinical setting.

Integrative Analysis of DNA Methylation and Transcriptome Identifies a Predictive Epigenetic Signature Associated With Immune Infiltration in Gliomas

Glioma is the most common primary brain tumor with poor prognosis and high mortality. The purpose of this study was to use the epigenetic signature to predict prognosis and evaluate the degree of immune infiltration in gliomas. We integrated gene expression profiles and DNA methylation data of lower-grade glioma and glioblastoma to explore epigenetic differences and associated differences in biological function. Cox regression and lasso analysis were used to develop an epigenetic signature based on eight DNA methylation sites to predict prognosis of glioma patients. Kaplan–Meier analysis showed that the overall survival time of high- and low-risk groups was significantly separated, and ROC analysis verified that the model had great predictive ability. In addition, we constructed a nomogram based on age, sex, 1p/19q status, glioma type, and risk score. The epigenetic signature was obviously associated with tumor purity, immune checkpoints, and tumor-immune infiltrating cells (CD8+ T cells, gamma delta T cells, M0 macrophages, M1 macrophages, M2 macrophages, activated NK cells, monocytes, and activated mast cells) and thus, it may find application as a guide for the evaluation of immune infiltration or in treatment decisions in immunotherapy.

PAX2 promoter methylation and AIB1 overexpression promote tamoxifen resistance in breast carcinoma patients

INTRODUCTION

Disease recurrence is an important obstacle in estrogen receptor positive (ER⁺) tamoxifen treated breast carcinoma patients. Tamoxifen resistance-related molecular mechanisms are not fully understood. Alteration in DNA methylation which contributes to transcriptional regulation of cancer-related genes plays a crucial role in tamoxifen response. In the present study, the contribution of promoter methylation and mRNA expression of PAX2 and AIB1 in the development of breast carcinoma and tamoxifen refractory was assessed.

METHODS

Methylation specific-high resolution melting (MS-HRM) analysis and Real-time quantitative PCR (RT-qPCR) experiment were performed to analyze the promoter methylation and mRNA expression levels of PAX2 and AIB1 genes in 102 breast tumors and adjacent normal breast specimens.

RESULTS

We indicated that PAX2 expression is decreased in breast tissues due to hypermethylation in its promoter region. Compared to the adjacent normal tissues, the tumors exhibited significantly lower relative mRNA levels of PAX2 and increased expression of AIB1. Aberrant promoter methylation of PAX2 and overexpression of AIB1 was observed in tamoxifen resistance patients compared to the sensitive ones. Cox regression analysis exhibited that the increased promoter methylation status of PAX2 and overexpression of AIB1 remained as unfavorable identifiers which influence patients' survival independently.

CONCLUSIONS

Our results revealed that the aberration in PAX2 promoter methylation and AIB1 overexpression are associated with the tamoxifen response in breast carcinoma patients. Further research is needed to demonstrate the potential of using PAX2 and AIB1 expression and their methylation-mediated regulation as predictive or prognostic biomarkers or as a new target therapy for better disease management.

Genome-wide identification of differentially methylated promoters and enhancers associated with response to anti-PD-1 therapy in non-small cell lung cancer

Although approved programmed cell death protein (PD)-1 inhibitors show durable responses, clinical benefits to these agents are only seen in one-third of patients in most cancer types. Therefore, strategies for improving the response to PD-1 inhibitor for treating various cancers including non-small cell lung cancer (NSCLC) are urgently needed. Compared with genome and transcriptome, tumor DNA methylome in anti-PD-1 response was relatively unexplored. We compared the pre-treatment methylation status of cis-regulatory elements between responders and non-responders to treatment with nivolumab or pembrolizumab using the Infinium Methylation EPIC Array, which can profile ~850,000 CpG sites, including ~350,000 CpG sites located in enhancer regions. Then, we analyzed differentially methylated regions overlapping promoters (pDMRs) or enhancers (eDMRs) between responders and non-responders to PD-1 inhibitors. We identified 1007 pDMRs and 607 eDMRs associated with the anti-PD-1 response. We also identified 1109 and 1173 target genes putatively regulated by these pDMRs and eDMRs, respectively. We found that eDMRs contribute to the epigenetic regulation of the anti-PD-1 response more than pDMRs. Hypomethylated pDMRs of Cytohesin 1 Interacting Protein (CYTIP) and TNF superfamily member 8 (TNFSF8) were more predictive than programmed cell death protein ligand 1 (PD-L1) expression for anti-PD-1 response and progression-free survival (PFS) and overall survival (OS) in a validation cohort, suggesting their potential as predictive biomarkers for anti-PD-1 immunotherapy. The catalog of promoters and enhancers differentially methylated between responders and non-responders to PD-1 inhibitors presented herein will guide the development of biomarkers and therapeutic strategies for improving anti-PD-1 immunotherapy in NSCLC.

Methylation‑driven genes PMPCAP1, SOWAHC and ZNF454 as potential prognostic biomarkers in lung squamous cell carcinoma

Of the different types of lung cancer, lung squamous cell cancer (LUSC) has the second highest rates of morbidity and mortality, which have been increasing in recent years. Epigenetic abnormalities may serve as potential biomarkers and diagnostic and/or therapeutic targets, which may help to monitor and improve the prognosis of patients with cancer. In the present study, data were obtained from The Cancer Genome Atlas database and survival and joint survival analyses were conducted using the R MethylMix package. Peptidase, mitochondrial processing a subunit pseudogene 1 (PMPCAP1), sosondowah ankyrin repeat domain family member C (SOWAHC) and zinc finger protein (ZNF) 454 were identified as independent prognosis‑related hub methylation‑driven genes (MDGs). Of these three genes, PMPCAP1 and SOWAHC, characterized by hypomethylation and high expression levels, were associated with poor prognosis in patients with LUSC, whilst ZNF454 was associated with an improved prognosis. In addition, pathway enrichment analysis suggested that PMPCAP1, SOWAHC and ZNF454 were primarily involved in gene expression or transcription pathways. Furthermore, 5, 1 and 10 key methylation sites of PMPCAP1, SOWAHC and ZNF454, respectively, were confirmed to be significantly relevant to gene expression, establishing a basis for further investigation into the mechanisms and more precise targets of these 3 genes. In conclusion, the MDGs PMPCAP1, SOWAHC and ZNF454 may be potential prognostic biomarkers of LUSC for guiding diagnosis and therapy options, as well as providing a theoretical basis for further investigation.

Recent Progress of Biomarker Detection Sensors

Early cancer diagnosis and treatment are crucial research fields of human health. One method that has proven efficient is biomarker detection which can provide real-time and accurate biological information for early diagnosis. This review presents several biomarker sensors based on electrochemistry, surface plasmon resonance (SPR), nanowires, other nanostructures, and, most recently, metamaterials which have also shown their mechanisms and prospects in application in recent years. Compared with previous reviews, electrochemistry-based biomarker sensors have been classified into three strategies according to their optimizing methods in this review. This makes it more convenient for researchers to find a specific fabrication method to improve the performance of their sensors. Besides that, as microfabrication technologies have improved and novel materials are explored, some novel biomarker sensors-such as nanowire-based and metamaterial-based biomarker sensors-have also been investigated and summarized in this review, which can exhibit ultrahigh resolution, sensitivity, and limit of detection (LoD) in a more complex detection environment. The purpose of this review is to understand the present by reviewing the past. Researchers can break through bottlenecks of existing biomarker sensors by reviewing previous works and finally meet the various complex detection needs for the early diagnosis of human cancer.

Epigenetic Profiles Reveal That ADCYAP1 Serves as Key Molecule in Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) refers to the condition which shows abnormal glucose metabolism that occurs during pregnancy, while normal glucose metabolism before pregnancy. In the present study, a novel analytical procedure was used to explore the key molecule of gestational diabetes mellitus. First, the weighted pathway model was carried out subsequently to eliminate the gene-overlapping effects among pathways. Second, we assessed the enriched pathways by a combination of Fisher's t-test and the Mann–Whitney U test. We carried out the functional principal component analysis by estimating F values of genes to identify the hub genes in the enriched pathways. Results showed that a total of 4 differential pathways were enriched. The key pathway was considered as the insulin secretion pathway. F values of each gene in the key pathway were calculated. Three hub molecules were identified as hub differentially methylated genes, namely, CAMK2B, ADCYAP1, and KCNN2. In addition, by further comparing the gene expression data in a validation cohort, one key molecule was obtained, ADCYAP1. Therefore, ADCYAP1 may serve as a potential target for the treatment of GDM.

Bioinformatics identification of potential genes and pathways in preeclampsia based on functional gene set enrichment analyses

Preeclampsia is a complication of pregnancy characterized by new-onset hypertension and proteinuria of gestation, with serious consequences for mother and infant. Although a vast amount of research has been performed on the pathogenesis of preeclampsia, the underlying mechanisms of this multisystemic disease have remained to be fully elucidated. Data were retrieved from Gene Expression Omnibus database GSE40182 dataset. After data preprocessing, differentially expressed genes of placental cells cultured in vitro from preeclampsia and normal pregnancy were determined and subjected to Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to identify the associated pathways. Furthermore, functional principal component analysis (FPCA) was used to calculate the corresponding F-value of each gene. In order to further study the key signaling pathways of preeclampsia, an elastic-net regression model and the Mann-Whitney U (MWU) test were used to estimate the weight of the signaling pathways. Finally, a co-expression network was generated and hub genes were identified based on the topological features. A total of 134 pathways with a role in preeclampsia were identified. The gene expression data of placenta cells cultured in vitro for different durations were determined and F-values of genes were estimated using the FPCA model. The top 1,000 genes were identified as the differentially expressed genes and subjected to further analysis by elastic-net regression and MWU test. Two key signaling pathways were different between the preeclampsia and control groups, namely hsa05142 Chagas disease and hsa05204 Chemical carcinogenesis. Among the genes involved in these two key pathways, 13 hub genes were identified from the co-expression network. Clustering analysis demonstrated that depending on these hub genes, it was possible to divide the sample into four distinct groups based on different incubation time. The top 3 candidates were Toll-like receptor 2 (TLR2), glutathione S-transferase omega 1 (GSTO1) and mitogen-activated protein kinase 13 (MAPK13). TLR2 and associated pathways are known to be closely associated with preeclampsia, indirectly demonstrating the applicability of the analytic process applied. However, the role of GSTO1 and MAPK13 in preeclampsia has remained poorly investigated, and elucidation thereof may be a worthwhile endeavor. The present study may provide a basis for exploring potential novel genes and pathways as therapeutic targets for preeclampsia.

Novel predictive epigenetic signature for temozolomide in non-G-CIMP glioblastomas

Objective

To identify novel epigenetic signatures that could provide predictive information that is complementary to promoter methylation status of the O-6-methylguanine-DNA methyltransferase (MGMT) gene for predicting temozolomide (TMZ) response, among glioblastomas (GBMs) without glioma-CpGs island methylator phenotype (G-CIMP)

Methods

Different cohorts of primary non-G-CIMP GBMs with genome-wide DNA methylation microarray data were included for discovery and validation of a multimarker signature, combined using a RISK score model. Different statistical analyses and functional experiments were performed for clinical and biological validation.

Results

By employing discovery cohorts with radiotherapy (RT) and TMZ versus RT alone and a strict multistep selection strategy, we identified seven CpGs, each of which was significantly correlated with overall survival (OS) of non-G-CIMP GBMs with RT/TMZ, independent of age, MGMT promoter methylation status, and other identified CpGs. A RISK score signature of the 7 CpGs was developed and validated to distinguish non-G-CIMP GBMs with differential survival outcomes to RT/TMZ, but not to RT alone. The interaction analyses also showed differential outcomes to RT/TMZ versus RT alone within the RISK score-based subgroups. The signature could also improve the risk classification by age and MGMT promoter methylation status. Functional experiments showed that HSBP2 appeared to be epigenetically regulated by one identified CpG and was associated with TMZ resistance, but it was not associated with cell proliferation or apoptosis in GBM cell lines. The predictive value of the single CpG methylation of HSBP2 by pyrosequencing was observed in a local cohort of isocitrate dehydrogenase 1 (IDH1) ^R132H wild-type GBMs.

Conclusions

This novel epigenetic signature might be a promising predictive (but not a general prognostic) biomarker and be helpful for refining the MGMT-based guiding approach to TMZ usage in non-G-CIMP GBMs.

Electronic supplementary material

The online version of this article (10.1186/s13148-019-0670-9) contains supplementary material, which is available to authorized users.

Potential Genes and Pathways of Neonatal Sepsis Based on Functional Gene Set Enrichment Analyses

BACKGROUND

Neonatal sepsis (NS) is considered as the most common cause of neonatal deaths that newborns suffer from. Although numerous studies focus on gene biomarkers of NS, the predictive value of the gene biomarkers is low. NS pathogenesis is still needed to be investigated.

METHODS

After data preprocessing, we used KEGG enrichment method to identify the differentially expressed pathways between NS and normal controls. Then, functional principal component analysis (FPCA) was adopted to calculate gene values in NS. In order to further study the key signaling pathway of the NS, elastic-net regression model, Mann-Whitney U test, and coexpression network were used to estimate the weights of signaling pathway and hub genes.

RESULTS

A total of 115 different pathways between NS and controls were first identified. FPCA made full use of time-series gene expression information and estimated F values of genes in the different pathways. The top 1000 genes were considered as the different genes and were further analyzed by elastic-net regression and MWU test. There were 7 key signaling pathways between the NS and controls, according to different sources. Among those genes involved in key pathways, 7 hub genes, PIK3CA, TGFBR2, CDKN1B, KRAS, E2F3, TRAF6, and CHUK, were determined based on the coexpression network. Most of them were cancer-related genes. PIK3CA was considered as the common marker, which is highly expressed in the lymphocyte group. Little was known about the correlation of PIK3CA with NS, which gives us a new enlightenment for NS study.

CONCLUSION

This research might provide the perspective information to explore the potential novel genes and pathways as NS therapy targets.

Quantitative assessment of gene promoter methylation in non-small cell lung cancer using methylation-sensitive high-resolution melting

DNA methylation is closely associated with aberrant epigenetic changes. Previous studies have identified various genes associated with non-small cell lung cancer (NSCLC), but the precise combination responsible for its etiology is still debated. The aim of the present study was to select a new set of NSCLC-related genes using methylation-sensitive high-resolution melting. The promoter methylation status of six selected genes, consisting of protocadherin γ subfamily B, 6 (PCDHGB6), homeobox A9 (HOXA9), O₆-methylguanine-DNA methyltransferase (MGMT), microRNA (miR)-126, suppressor of cytokine signaling 3 (SOCS3) and Ras association domain family member 5, also termed NORE1A, was evaluated in 54 NSCLC patients. From these samples, genome-wide DNA was extracted and bisulfite conversion was performed along with fluorogenic quantitative polymerase chain reaction to detect methylation values of the six selected promoters. The present results revealed frequent methylation on PCDHGB6, HOXA9 and miR-126, which contrasted with infrequent methylation on MGMT. The results indicated no methylation on either SOCS3 or NORE1A. The sensitivity and specificity of the methylation assessment were 85.2 and 81.5%, respectively, and the analysis results were validated by pyrosequencing. Furthermore, minute comparison of the association between DNA methylation and clinical features was performed. Overall, these results may provide potential information for the development of better clinical diagnostics and more targeted and effective therapies for NSCLC.

A novel prognostic six-CpG signature in glioblastomas

AIMS

We aimed to identify a clinically useful biomarker using DNA methylation-based information to optimize individual treatment of patients with glioblastoma (GBM).

METHODS

A six-CpG panel was identified by incorporating genome-wide DNA methylation data and clinical information of three distinct discovery sets and was combined using a risk-score model. Different validation sets of GBMs and lower-grade gliomas and different statistical methods were implemented for prognostic evaluation. An integrative analysis of multidimensional TCGA data was performed to molecularly characterize different risk tumors.

RESULTS

The six-CpG risk-score signature robustly predicted overall survival (OS) in all discovery and validation cohorts and in a treatment-independent manner. It also predicted progression-free survival (PFS) in available patients. The multimarker epigenetic signature was demonstrated as an independent prognosticator and had better performance than known molecular indicators such as glioma-CpG island methylator phenotype (G-CIMP) and proneural subtype. The defined risk subgroups were molecularly distinct; high-risk tumors were biologically more aggressive with concordant activation of proangiogenic signaling at multimolecular levels. Accordingly, we observed better OS benefits of bevacizumab-contained therapy to high-risk patients in independent sets, supporting its implication in guiding usage of antiangiogenic therapy. Finally, the six-CpG signature refined the risk classification based on G-CIMP and MGMT methylation status.

CONCLUSIONS

The novel six-CpG signature is a robust and independent prognostic indicator for GBMs and is of promising value to improve personalized management.

Abnormal DNA methylation may contribute to the progression of osteosarcoma

The identification of optimal methylation biomarkers to achieve maximum diagnostic ability remains a challenge. The present study aimed to elucidate the potential molecular mechanisms underlying osteosarcoma (OS) using DNA methylation analysis. Based on the GSE36002 dataset obtained from the Gene Expression Omnibus database, differentially methylated genes were extracted between patients with OS and controls using t-tests. Subsequently, hierarchical clustering was performed to segregate the samples into two distinct clusters, OS and normal. Gene Ontology (GO) and pathway enrichment analyses for differentially methylated genes were performed using the Database for Annotation, Visualization and Integrated Discovery tool. A protein-protein interaction (PPI) network was established, followed by hub gene identification. Using the cut-off threshold of ≥0.2 average β-value difference, 3,725 unique CpGs (2,862 genes) were identified to be differentially methylated between the OS and normal groups. Among these 2,862 genes, 510 genes were differentially hypermethylated and 2,352 were differentially hypomethylated. The differentially hypermethylated genes were primarily involved in 20 GO terms, and the top 3 terms were associated with potassium ion transport. For differentially hypomethylated genes, GO functions principally included passive transmembrane transporter activity, channel activity and metal ion transmembrane transporter activity. In addition, a total of 10 significant pathways were enriched by differentially hypomethylated genes; notably, neuroactive ligand-receptor interaction was the most significant pathway. Based on a connectivity degree >90, 7 hub genes were selected from the PPI network, including neuromedin U (NMU; degree=103) and NMU receptor 1 (NMUR1; degree=103). Functional terms (potassium ion transport, transmembrane transporter activity, and neuroactive ligand-receptor interaction) and hub genes (NMU and NMUR1) may serve as potential targets for the treatment and diagnosis of OS.

Combined detection of insulin-like growth factor-binding protein 7 promoter methylation improves the diagnostic efficacy of AFP in hepatitis B virus-associated hepatocellular carcinoma

This study quantitatively assessed serum insulin-like growth factor-binding protein 7 (IGFBP7) promoter methylation in hepatocellular carcinoma (HCC), and explored its clinical value. A total of 80 patients with hepatitis B virus-associated HCC, 35 patients with chronic hepatitis B (CHB), and 20 healthy controls (HC) were enrolled. MethyLight was used to quantitatively assess the methylation levels of serum IGFBP7 promoter. A logistic regression model was established for the combined evaluation of AFP and serum IGFBP7 promoter methylation. The results showed that mean methylation levels of serum IGFBP7 promoter were significantly higher in HCC (5.33%, interquartile range [IQR] 1.14-15.70%) patients than in individuals with CHB (1.54%, IQR 0.64-2.45%; P<0.01) and HC (0.63%, IQR 0.22-0.98%; P<0.01). In HCC subgroups, patients with vascular invasion, tumor size >3cm and advanced tumor node metastasis (TNM) showed higher methylation levels compared with the remaining groups (P<0.05). Compared with AFP alone, combined determination based on logistic regression analysis significantly improved the area under the receiver operating characteristic (ROC) curve (AUC) (0.759 vs 0.623, P<0.05). In addition, the Youden index was increased from 5.71%, 11.25% and 15.18%, when considering AFP alone at cut-off values of 20, 200, and 400ng/ml, respectively, to 45.71% with IGFBP7 promoter methylation taken into consideration (all P<0.05). These results suggested that combined quantitative measurement of serum IGFBP7 promoter methylation could enhance the diagnostic ability of AFP in distinguishing hepatitis B virus-associated HCC from CHB.

Electrochemical biosensing strategies for DNA methylation analysis

DNA methylation is one of the key epigenetic modifications of DNA that results from the enzymatic addition of a methyl group at the fifth carbon of the cytosine base. It plays a crucial role in cellular development, genomic stability and gene expression. Aberrant DNA methylation is responsible for the pathogenesis of many diseases including cancers. Over the past several decades, many methodologies have been developed to detect DNA methylation. These methodologies range from classical molecular biology and optical approaches, such as bisulfite sequencing, microarrays, quantitative real-time PCR, colorimetry, Raman spectroscopy to the more recent electrochemical approaches. Among these, electrochemical approaches offer sensitive, simple, specific, rapid, and cost-effective analysis of DNA methylation. Additionally, electrochemical methods are highly amenable to miniaturization and possess the potential to be multiplexed. In recent years, several reviews have provided information on the detection strategies of DNA methylation. However, to date, there is no comprehensive evaluation of electrochemical DNA methylation detection strategies. Herein, we address the recent developments of electrochemical DNA methylation detection approaches. Furthermore, we highlight the major technical and biological challenges involved in these strategies and provide suggestions for the future direction of this important field.

Epigenetic Biomarkers of Breast Cancer Risk: Across the Breast Cancer Prevention Continuum

Epigenetic biomarkers, such as DNA methylation, can increase cancer risk through altering gene expression. The Cancer Genome Atlas (TCGA) Network has demonstrated breast cancer-specific DNA methylation signatures. DNA methylation signatures measured at the time of diagnosis may prove important for treatment options and in predicting disease-free and overall survival (tertiary prevention). DNA methylation measurement in cell free DNA may also be useful in improving early detection by measuring tumor DNA released into the blood (secondary prevention). Most evidence evaluating the use of DNA methylation markers in tertiary and secondary prevention efforts for breast cancer comes from studies that are cross-sectional or retrospective with limited corresponding epidemiologic data, raising concerns about temporality. Few prospective studies exist that are large enough to address whether DNA methylation markers add to the prediction of tertiary and secondary outcomes over and beyond standard clinical measures. Determining the role of epigenetic biomarkers in primary prevention can help in identifying modifiable pathways for targeting interventions and reducing disease incidence. The potential is great for DNA methylation markers to improve cancer outcomes across the prevention continuum. Large, prospective epidemiological studies will provide essential evidence of the overall utility of adding these markers to primary prevention efforts, screening, and clinical care.

Epigenetic therapy for colorectal cancer

Aberrations in epigenome that include alterations in DNA methylation, histone acetylation, and miRNA (microRNA) expression may govern the progression of colorectal cancer (CRC). These epigenetic changes affect every phase of tumor development from initiation to metastasis. Since epigenetic alterations can be reversed by DNA demethylating and histone acetylating agents, current status of the implication of epigenetic therapy in CRC is discussed in this article. Interestingly, DNA methyltransferase inhibitors (DNMTi) and histone deacetylase inhibitors (HDACi) have shown promising results in controlling cancer progression. The information provided here might be useful in developing personalized medicine approaches.

Epigenetic modulation with HDAC inhibitor CG200745 induces anti-proliferation in non-small cell lung cancer cells

Histone modification plays a pivotal role on gene regulation, as regarded as global epigenetic markers, especially in tumor related genes. Hence, chemical approaches targeting histone-modifying enzymes have emerged onto the main stage of anticancer drug discovery. Here, we investigated the therapeutic potentials and mechanistic roles of the recently developed histone deacetylase inhibitor, CG200745, in non-small cell lung cancer cells. Treatment with CG200745 increased the global level of histone acetylation, resulting in the inhibition of cell proliferation. ChIP-on-chip analysis with an H4K16ac antibody showed altered H4K16 acetylation on genes critical for cell growth inhibition, although decreased at the transcription start site of a subset of genes. Altered H4K16ac was associated with changes in mRNA expression of the corresponding genes, which were further validated in quantitative RT-PCR and western blotting assays. Our results demonstrated that CG200745 causes NSCLC cell growth inhibition through epigenetic modification of critical genes in cancer cell survival, providing pivotal clues as a promising chemotherapeutics against lung cancer.

Sox17 promoter methylation in plasma DNA is associated with poor survival and can be used as a prognostic factor in breast cancer

Aberrant DNA methylation that leads to the inactivation of tumor suppressor genes is known to play an important role in the development and progression of breast cancer. Methylation status of cancer-related genes is considered to be a promising biomarker for the early diagnosis and prognosis of tumors. This study investigated the methylation status of the Sox17 gene in breast cancer tissue and its corresponding plasma DNA to evaluate the association of methylation levels with clinicopathological parameters and prognosis.The methylation status of the Sox17 gene promoter was evaluated with methylation-specific polymerase chain reaction (MSP) in 155 paired breast cancer tissue and plasma samples and in 60 paired normal breast tissue and plasma samples. Association of Sox17 methylation status with clinicopathological parameters was analyzed by χ tests. Overall and disease-free survival (DFS) curves were calculated using Kaplan-Meier analysis, and the differences between curves were analyzed by log-rank tests.The frequency of Sox17 gene methylation was 72.9% (113/155) in breast cancer tissues and 58.1% (90/155) in plasma DNA. Sox17 gene methylation was not found in normal breast tissues or in their paired plasma DNA. There was a significant correlation of Sox17 methylation between corresponding tumor tissues and paired plasma DNA (r = 0.688, P < 0.001). Aberrant Sox17 methylation in cancer tissues and in plasma DNA was significantly associated with the tumor node metastasis stage (P = 0.035 and P = 0.001, respectively) and with lymph node metastasis (P < 0.001 and P = 0.001, respectively). Kaplan-Meier survival curves showed that aberrant Sox17 promoter methylation in cancer tissues and plasma DNA was associated with poor DFS (P < 0.005) and overall survival (OS) (P < 0.005). Multivariate analysis showed that Sox17 methylation in plasma DNA was an independent prognostic factor in breast cancer for both DFS (P = 0.020; hazard ratio [HR] = 2.142; 95% confidence interval [CI]: 1.128-4.067) and for OS (P = 0.001; HR = 4.737; 95% CI: 2.088-10.747).Sox17 gene promoter methylation may play an important role in breast cancer progression and could be used as a prognostic biomarker to identify patients at risk of developing metastasis or recurrence after mastectomy.

Identification and validation of the methylation biomarkers of non-small cell lung cancer (NSCLC)

Background

DNA methylation was suggested as the promising biomarker for lung cancer diagnosis. However, it is a great challenge to search for the optimal combination of methylation biomarkers to obtain maximum diagnostic performance.

Results

In this study, we developed a panel of DNA methylation biomarkers and validated their diagnostic efficiency for non-small cell lung cancer (NSCLC) in a large Chinese Han NSCLC retrospective cohort. Three high-throughput DNA methylation microarray datasets (458 samples) were collected in the discovery stage. After normalization, batch effect elimination and integration, significantly differentially methylated genes and the best combination of the biomarkers were determined by the leave-one-out SVM (support vector machine) feature selection procedure. Then, candidate promoters were examined by the methylation status determined single nucleotide primer extension technique (MSD-SNuPET) in an independent set of 150 pairwise NSCLC/normal tissues. Four statistical models with fivefold cross-validation were used to evaluate the performance of the discriminatory algorithms. The sensitivity, specificity and accuracy were 86.3%, 95.7% and 91%, respectively, in Bayes tree model. The logistic regression model incorporated five gene methylation signatures at AGTR1, GALR1, SLC5A8, ZMYND10 and NTSR1, adjusted for age, sex and smoking, showed robust performances in which the sensitivity, specificity, accuracy, and area under the curve (AUC) were 78%, 97%, 87%, and 0.91, respectively.

Conclusions

In summary, a high-throughput DNA methylation microarray dataset followed by batch effect elimination can be a good strategy to discover optimal DNA methylation diagnostic panels. Methylation profiles of AGTR1, GALR1, SLC5A8, ZMYND10 and NTSR1, could be an effective methylation-based assay for NSCLC diagnosis.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-014-0035-3) contains supplementary material, which is available to authorized users.

A network-based, integrative approach to identify genes with aberrant co-methylation in colorectal cancer

Epigenetic changes, including aberrations in DNA methylation, are a common hallmark of many cancers. The identification and interpretation of epigenetic changes associated with cancers may benefit from integration with protein interactomes. Based on the assumption that genes implicated in a specific tumor phenotype will show high aberrant co-methylation patterns with their interacting partners, we propose an integrated approach to uncover cancer-associated genes by integrating a DNA methylome with an interactome. Aberrant co-methylated interactions were first identified in the specific cancer, and genes were then prioritized based on their enrichment in aberrant co-methylation. By applying this to a large-scale colorectal cancer (CRC) dataset, the proposed method increases the power to capture known genes. More importantly, genes possessing high aberrant co-methylation patterns, located at the topological center of the original protein-protein interaction network (PPIN), affect several cancer-associated pathways and form hotspots that are frequently hijacked in cancer. Additionally, the top-ranked candidate genes may also be useful as an indicator of CRC diagnosis and prognosis. Five fold cross-validation of the top-ranked genes in diagnosis reveals that it can achieve an area under the receiver operating characteristic (ROC) curve ranging from 82.2% to 98.4% in three independent datasets. Five of these genes form a core repressive module. CCNA1 and ESR1 in particular are evidently silenced by promoter hypermethylation in CRC cell lines and tissues, whose re-expression markedly suppresses tumor cell survival and clonogenicity. These results show that the network-centric method could identify novel disease biomarkers and model how oncogenic lesions mediate epigenetic changes, providing important insights into tumorigenesis.

Viability of lymph node samples obtained by echobronchoscopy in the study of epigenetic alterations in patients with lung cancer

INTRODUCTION

The diagnosis of microscopic lymph node metastasis in lung cancer is challenging despite the constant advances in tumor staging. The analysis of the methylation status of certain genes in lymph node samples could improve the diagnostic capability of conventional cyto-histological methods. The aim of this study was to demonstrate the feasibility of methylation studies using cytological lymph node samples.

METHODS

Prospective study including 88 patients with a diagnosis or strong suspicion of non-small cell lung cancer, in which an echobronchoscopy was performed on mediastinal or hilar lymph nodes for diagnostic and/or staging. DNA was extracted from cytological lymph node samples and sodium bisulfite modification was performed. Methylation studies for p16/INK4a and SHOX2 were accomplished by MS-qPCR and pyrosequencing.

RESULTS

The methodology used in our study yielded optimal/good DNA quality in 90% of the cases. No differences in DNA concentration were observed with respect to the lymph node biopsied and final diagnosis. Methylation analyses using MS-qPCR and pyrosequencing were not possible in a small number of samples mainly due to low DNA concentration, inadequate purity, fragmentation and/or degradation as a consequence of bisulfite conversion.

CONCLUSION

Methylation quantification using MS-qPCR and pyrosequencing of cytological lymph node samples obtained using echobronchoscopy is feasible if an appropriate DNA concentration is obtained, notably contributing to the identification of epigenetic biomarkers capable of improving decision-making for the benefit of potentially curable lung cancer patients.

Better cancer biomarker discovery through better study design

BACKGROUND

High-throughput laboratory technologies coupled with sophisticated bioinformatics algorithms have tremendous potential for discovering novel biomarkers, or profiles of biomarkers, that could serve as predictors of disease risk, response to treatment or prognosis. We discuss methodological issues in wedding high-throughput approaches for biomarker discovery with the case-control study designs typically used in biomarker discovery studies, especially focusing on nested case-control designs.

METHODS

We review principles for nested case-control study design in relation to biomarker discovery studies and describe how the efficiency of biomarker discovery can be effected by study design choices. We develop a simulated prostate cancer cohort data set and a series of biomarker discovery case-control studies nested within the cohort to illustrate how study design choices can influence biomarker discovery process.

RESULT

Common elements of nested case-control design, incidence density sampling and matching of controls to cases are not typically factored correctly into biomarker discovery analyses, inducing bias in the discovery process. We illustrate how incidence density sampling and matching of controls to cases reduce the apparent specificity of truly valid biomarkers 'discovered' in a nested case-control study. We also propose and demonstrate a new case-control matching protocol, we call 'antimatching', that improves the efficiency of biomarker discovery studies.

CONCLUSIONS

For a valid, but as yet undiscovered, biomarker(s) disjunctions between correctly designed epidemiologic studies and the practice of biomarker discovery reduce the likelihood that true biomarker(s) will be discovered and increases the false-positive discovery rate.

Investigating the effects of the presence of foreign DNA on DNA methylation and DNA repair events in cultured eukaryotic cells

Methylation of DNA in eukaryotic cells, global as well as gene-specific, is affected by endogenous and endogenous factors. In this paper, it is reported that deviations in DNA methylation and expression of genes involved in DNA repair and the cell cycle are affected in 143B cultured cells containing an expression vector. Global DNA methylation analysis with cytosine-extension assay revealed a decreased global DNA methylation in the presence of the expression vector. Less promoter-specific methylation, as measured by bisulfite-MS PCR, was observed for MGMT and p16INK4a in vector-containing cells. Comet assay investigations revealed a negative effect on the DNA repair capacity of both BER and NER in Complex III compromised cells. This was reflected in the down-regulation of hOGG1 and ERCC1 expression. The results presented in this paper support the existence of a strong relationship between impaired mitochondrial function and deviations in DNA methylation and extend this relationship to impaired DNA repair.

DNA methylation-based biomarkers in serum of patients with breast cancer

Alterations of genetic and epigenetic features can provide important insights into the natural history of breast cancer. Although DNA methylation analysis is a rapidly developing field, a reproducible epigenetic blood-based assay for diagnosis and follow-up of breast cancer has yet to be successfully developed into a routine clinical test. The aim of this study was to review multiple serum DNA methylation assays and to highlight the value of those novel biomarkers in diagnosis, prognosis and prediction of therapeutic outcome. Serum is readily accessible for molecular diagnosis in all individuals from a peripheral blood sample. The list of hypermethylated genes in breast cancer is heterogeneous and no single gene is methylated in all breast cancer types. There is increasing evidence that a panel of epigenetic markers is essential to achieve a higher sensitivity and specificity in breast cancer detection. However, the reported percentages of methylation are highly variable, which can be partly explained by the different sensitivities and the different intra-/inter-assay coefficients of variability of the analysis methods. Moreover, there is a striking lack of receiver operating characteristic (ROC) curves of the proposed biomarkers. Another point of criticism is the fact that 'normal' patterns of DNA methylation of some tumor suppressor and other cancer-related genes are influenced by several factors and are often poorly characterized. A relatively frequent methylation of those genes has been observed in high-risk asymptomatic women. Finally, there is a call for larger prospective cohort studies to determine methylation patterns during treatment and follow-up. Identification of patterns specific for a differential response to therapeutic interventions should be useful. Only in this way, it will be possible to evaluate the predictive and prognostic characteristics of those novel promising biomarkers.

Genome-wide methylation analysis

The disruption and alteration of genomic methylation patterns is a hallmark of cancer and other disease states. Understanding and characterizing genome-wide methylation will have a profound effect on our understanding of tumorigenesis and provide novel avenues for therapy. This chapter serves to describe techniques that examine genome-wide methylation patterns including luminometric methylation assay, restriction landmark genome scanning, and the cytosine extension assay, which utilize methylation-sensitive restriction enzymes. Additional techniques such as nucleotide separation assays (nearest neighbor analysis and high-performance capillary electrophoresis) and the infinium methylation assay are discussed. These techniques allow for the determination of changes in global methylation levels, as well as regional changes in methylation throughout the genome.

[Application of the duplex-specific nuclease for fast analysis of single nucleotide polymorphisms and detection of target DNA in complex PCR products]

We have developed a simple method for fast analysis of single nucleotide polymorphisms and identification of target clones from cloned complex PCR products. The method utilizes Kamchatka crab duplex-specific nuclease and universal fluorescent probe and is alternative to laborious screening procedures using radioactive probes, restriction analysis followed by gel electrophoresis or expensive sequencing. The method efficacy was demonstrated in several model experiments.

Cancer epigenetics: above and beyond

Epigenetics refers to the study of mechanisms that alter gene expression without altering the primary DNA sequence. Epigenetic mechanisms are heritable and reversible. Over the last few decades, epigenetics has obtained a large importance in cancer research. Epigenetic alterations are widely described as essential players in cancer progression. They comprise DNA methylation, histone modifications, nucleosome positioning, and small, noncoding RNAs (miRNA, siRNA). They are involved in transcriptional changes and decisive events that will determine cell fate and phenotype. Epigenetics not only offers light into cancer biological processes, but also represents an attractive opportunity of reverting cancer-specific alterations, which may lead, in the future, to a possibility of stopping this disease. Epigenetic changes have been identified as putative cancer biomarkers for early detection, disease monitoring, prognosis, and risk assessment. Other epigenetic alterations are promising therapeutic targets and even therapeutic agents. Emerging discoveries in this area are already contributing to cancer management and monitoring, and a lot more progresses are expected in the future.

DNA methylation in cancer development, diagnosis and therapy--multiple opportunities for genotoxic agents to act as methylome disruptors or remediators

The role of DNA methylation and recently discovered hydroxymethylation in the function of the human epigenome is currently one of the hottest topics in the life sciences. Progress in this field of research has been further accelerated by the discovery that alterations in the methylome are not only associated with key functions of cells and organisms, such as development, differentiation and gene expression, but may underlie a number of human diseases, including cancer. This review describes both well established and more recent observations concerning alterations in the methylome, i.e. the global and local distribution of 5-methylcytosines, involved in its normal functions. Then, the changes in DNA methylation pattern seen in cancer cells are discussed in the context of their utilisation in cancer diagnostics and treatment. On this basis, comparisons are made between natural covalent DNA modification and that induced by genotoxic agents, chemical carcinogens and antitumour drugs as regards their impact on epigenetic mechanisms. The available data suggest that DNA damage by genotoxins can mimic epigenetic markers and in consequence disrupt the proper function of the epigenome. On the other hand, the same processes in cancer cells, e.g. DNA demethylation as a result of DNA methyltransferase blocking or the induction of DNA repair by DNA adducts, may restore the activity of hypermethylated anticancer genes. The observed multiple mechanisms by which genotoxic agents directly affect methylome function suggest that chemical carcinogens act primarily as epigenome disruptors, whereas mutations are secondary events that occur at later stages of cancer development when genome-protecting mechanisms have already been deregulated.

The bottleneck in the cancer biomarker pipeline and protein quantification through mass spectrometry-based approaches: current strategies for candidate verification

BACKGROUND

Although robust discovery-phase platforms have resulted in the generation of large numbers of candidate cancer biomarkers, a comparable system for subsequent quantitative assessment and verification of all candidates is lacking. Established immunoassays and available antibodies permit analysis of small subsets of candidates; however, the lack of commercially available reagents, coupled with high costs and lengthy production and purification times, have rendered the large majority of candidates untestable.

CONTENT

Mass spectrometry (MS), and in particular multiple reaction monitoring (MRM)-MS, has emerged as an alternative technology to immunoassays for quantification of target proteins. Novel biomarkers are expected to be present in serum in the low (microg/L-ng/L) range, but analysis of complex serum or plasma digests by MS has yielded milligram per liter limits of detection at best. The coupling of prior sample purification strategies such as enrichment of target analytes, depletion of high-abundance proteins, and prefractionation, has enabled reliable penetration into the low microgram per liter range. This review highlights prospects for candidate verification through MS-based methods. We first outline the biomarker discovery pipeline and its existing bottleneck; we then discuss various MRM-based strategies for targeted protein quantification, the applicability of such methods for candidate verification, and points of concern.

SUMMARY

Although it is unlikely that MS-based protein quantification will replace immunoassays in the near future, with the expected improvements in limits of detection and specificity in instrumentation, MRM-based approaches show great promise for alleviating the existing bottleneck to discovery.

Variations in the composition of mammalian SWI/SNF chromatin remodelling complexes

The ATP-dependent chromatin remodelling complexes SWI/SNF alter the chromatin structure in transcriptional regulation. Several classes of mammalian SWI/SNF complex have been isolated biochemically, distinguished by a few specific subunits, such as the BAF-specific BAF250A, BAF250B and BRM, and the PBAF-specific BAF180. We have determined the complex compositions using low stringency immunoprecipitation (IP) and shown that the pattern of subunit interactions was more diverse than previously defined classes had predicted. The subunit association at five gene promoters that depend on the SWI/SNF activity varied and the sequential chromatin immunoprecipitations revealed that different class-specific subunits occupied the promoters at the same time. The low-stringency IP showed that the BAF-specific BAF250A and BAF250B and the PBAF-specific BAF180 co-exist in a subset of SWI/SNF complexes, and fractionation of nuclear extract on size-exclusion chromatography demonstrated that sub-complexes with unorthodox subunit compositions were present in the cell. We propose a model in which the constellations of SWI/SNF complexes are "tailored" for each specific chromatin target and depend on the local chromatin environment to which complexes and sub-complexes are recruited.

Genetic and epigenetic heterogeneity in cancer: a genome-centric perspective

Genetic and epigenetic heterogeneity (the main form of non-genetic heterogeneity) are key elements in cancer progression and drug resistance, as they provide needed population diversity, complexity, and robustness. Despite drastically increased evidence of multiple levels of heterogeneity in cancer, the general approach has been to eliminate the "noise" of heterogeneity to establish genetic and epigenetic patterns. In particular, the appreciation of new types of epigenetic regulation like non-coding RNA, have led to the hope of solving the mystery of cancer that the current genetic theories seem to be unable to achieve. In this mini-review, we have briefly analyzed a number of mis-conceptions regarding cancer heterogeneity, followed by the re-evaluation of cancer heterogeneity within a framework of the genome-centric concept of evolution. The analysis of the relationship between gene, epigenetic and genome level heterogeneity, and the challenges of measuring heterogeneity among multiple levels have been discussed. Further, we propose that measuring genome level heterogeneity represents an effective strategy in the study of cancer and other types of complex diseases, as emphasis on the pattern of system evolution rather than specific pathways provides a global and synthetic approach. Compared to the degree of heterogeneity, individual molecular pathways will have limited predictability during stochastic cancer evolution where genome dynamics (reflected by karyotypic heterogeneity) will dominate.

RASSF1A, APC, ESR1, ABCB1 and HOXC9, but not p16INK4A, DAPK1, PTEN and MT1G genes were frequently methylated in the stage I non-small cell lung cancer in China

PURPOSE

To identify the DNA methylation biomarkers for the detection of the stage I non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS

The methylated state of p16INK4A, ESR1, HOX9, RASSF1A, DAPK1, PTEN, ABCB1, MGMT, APC and MT1G genes that have been reported frequently methylated in lung cancer was determined using methylation-specific PCR in four lung cancer cell lines, 124 cancer tissues of the stage I NSCLC and 26 non-cancerous disease tissues.

RESULT

The RASSF1A (53/124, 42.74%), APC (49/123, 39.52%), ESR1 (37/124, 29.84%), ABCB1 (31/124, 24.19%, MT1G (25/124, 20.16%) and HOXC9 (17/124, 13.71%) genes were more frequently methylated in the lung tissue from the stage I NSCLC than the non-cancerous lesion patients (2/26, 7.69%, P < 0.01; 2/26, 7.69%, P < 0.01; 2/26, 7.69%, P < 0.05; 1/26, 3.85% P < 0.01; 0/26 0%, P value: <0.01; 0/26, 0%, P < 0.05, respectively). p16INK4A was methylated in 28/124 (22.56%) of cancer tissues and 2/26 (7.69%) of non-cancerous tissues (P value >0.05). No significant association between the methylated state of the genes and the smoking, age or the pathologic types (squamous carcinoma, adenoma and the mixed types) was found. However, p16INK4A methylation was more frequently detected in the male (23/80, 28.75%) than the female (5/44, 11.36%, P > 0.05) patients. MGMT was barely methylated: 1/67, 1.49%), while DAPK1 and PTEN were not at all methylated in the cancer groups.

CONCLUSIONS

Methylation analysis in tissue of RASSF1A, APC, ESR1, ABCB1 and HOXC9 genes confirmed 79.8% of the existing diagnosis for the stage I NSCLC at specificity: 73.1%. The insufficiency of predicting disease onset in China, using the previously recommended targets (MGMT, DAPK1 and PTEN) in the United States reflects a potential disease disparity between these two populations. Alternatively, methylated state of this set of genes may be more specific to the late rather than the early stage of NSCLC.