Analysis of DNA methylation in cancer: location revisited

ZNF671 DNA methylation as a molecular predictor for the early recurrence of serous ovarian cancer

Serous ovarian cancer is the most frequent type of epithelial ovarian cancer. Despite the use of surgery and platinum‐based chemotherapy, many patients suffer from recurrence within 6 months, termed platinum resistance. Currently, the lack of relevant molecular biomarkers for the prediction of the early recurrence of serous ovarian cancers is linked to the poor prognosis. To identify an effective biomarker for early recurrence, we analyzed the genome‐wide DNA methylation status characteristic of early recurrence after treatment. The patients in The Cancer Genome Atlas (TCGA) dataset who showed a complete response after the first therapy were categorized into 2 groups: early recurrence serous ovarian cancer (ERS, recurrence ≤12 months, n = 51) and late recurrence serous ovarian cancer (LRS, recurrence >12 months, n = 158). Among the 12 differently methylated probes identified between the 2 groups, we found that ZNF671 was the most significantly methylated gene in the early recurrence group. A validation cohort of 78 serous ovarian cancers showed that patients with ZNF671 DNA methylation had a worse prognosis (P < .05). The multivariate analysis revealed that the methylation status of ZNF671 was an independent factor for predicting the recurrence of serous ovarian cancer patients both in the TCGA dataset and our cohort (P = .049 and P = .021, respectively). Functional analysis revealed that the depletion of ZNF671 expression conferred a more migratory and invasive phenotype to the ovarian cancer cells. Our data indicate that ZNF671 functions as a tumor suppressor in ovarian cancer and that the DNA methylation status of ZNF671 might be an effective biomarker for the recurrence of serous ovarian cancer after platinum‐based adjuvant chemotherapy.

Factors Regulating microRNA Expression and Function in Multiple Myeloma

Intensive research has been undertaken during the last decade to identify the implication of microRNAs (miRNAs) in the pathogenesis of multiple myeloma (MM). The expression profiling of miRNAs in MM has provided relevant information, demonstrating different patterns of miRNA expression depending on the genetic abnormalities of MM and a key role of some miRNAs regulating critical genes associated with MM pathogenesis. However, the underlying causes of abnormal expression of miRNAs in myeloma cells remain mainly elusive. The final expression of the mature miRNAs is subject to multiple regulation mechanisms, such as copy number alterations, CpG methylation or transcription factors, together with impairment in miRNA biogenesis and differences in availability of the mRNA target sequence. In this review, we summarize the available knowledge about the factors involved in the regulation of miRNA expression and functionality in MM.

The trans-DATA study: aims and design of a translational breast cancer prognostic marker identification study

BACKGROUND

The effect of extended adjuvant aromatase inhibition in hormone-positive breast cancer after sequential tamoxifen, aromatase inhibitor treatment of 5 years was recently investigated by the DATA study. This study found no statistically significant effect of prolonged aromatase therapy. However, subgroup analysis showed post hoc statistically significant benefits in certain sub-populations. The trans-DATA study is a translational sub-study aiming to identify DNA methylation markers prognostic of patient outcome.

METHODS

Patients from the DATA study are included in the trans-DATA study. Primary breast tumour tissue will be collected, subtyped and used for DNA isolation. A genome-wide DNA methylation discovery assay will be performed on 60 patients that had a distant recurrence and 60 patients that did not have a distant recurrence using the Infinium Methylation EPIC Bead Chip platform. Differentially methylated regions of interest will be selected based on Akaike's Information Criterion, Gene Ontology Analysis and correlation between methylation and expression levels. Selected candidate genes will subsequently be validated in the remaining patients using qMSP.

DISCUSSION

The trans-DATA study uses a cohort derived from a clinical randomised trial. This study was designed to avoid common pitfalls in marker discovery studies such as selection bias, confounding and lack of reproducibility. In addition to the usual clinical risk factors, the results of this study may identify predictors of high recurrence risk in hormone receptor-positive breast cancer patients treated with sequential tamoxifen and aromatase inhibitor therapy.

Combined Targeted Resequencing of Cytosine DNA Methylation and Mutations of DNA Repair Genes with Potential Use for Poly(ADP-Ribose) Polymerase 1 Inhibitor Sensitivity Testing

Current molecular tumor diagnostics encompass panel sequencing to detect mutations, copy number alterations, and rearrangements. However, tumor suppressor genes can also be inactivated by methylation within their promoter region. These epigenetic alterations are so far rarely assessed in the clinical setting. Therefore, we established the AllCap protocol facilitating the combined detection of mutations and DNA methylation at the coding and promoter regions of 342 DNA repair genes in one experiment. We demonstrate the use of the protocol by applying it to ovarian cancer cell lines with different responsiveness to poly(ADP-ribose) polymerase inhibition. BRCA1, ATM, ATR, and EP300 mutations and methylation of the BRCA1 promoter were detected as potential predictors for therapy response. The required amount of input DNA was optimized, and the application to formalin-fixed, paraffin-embedded tissue samples was verified to improve the clinical applicability. Thus, by adding DNA methylation values to panel resequencings, the AllCap assay will add another important level of information to clinical tests and will improve stratification of patients for systemic therapies.

DNA methylation detection: recent developments in bisulfite free electrochemical and optical approaches

DNA methylation is one of the significant epigenetic modifications involved in mammalian development as well as in the initiation and progression of various diseases like cancer. Over the past few decades, an enormous amount of research has been carried out for the quantification of DNA methylation in the mammalian genome. Earlier, most of these methodologies used bisulfite treatment. However, the low conversion, false reading, longer assay time and complex chemical reaction are the common limitations of this method that hinder their application in routine clinical screening. Thus, as an alternative to bisulfite conversion-based DNA methylation detection, numerous bisulfite-free methods have been proposed. In this regard, electrochemical biosensors have gained much attention in recent years for being highly sensitive yet cost-effective, portable, and simple to operate. On the other hand, biosensors with optical readouts enable direct real time detection of biological molecules and are easily adaptable to multiplexing. Incorporation of electrochemical and optical readouts into bisulfite free DNA methylation analysis is paving the way for the translation of this important biomarker into standard patient care. In this review, we provide a critical overview of recent advances in the development of electrochemical and optical readout based bisulfite free DNA methylation assays.

Promoter hypermethylation of RARβ2, DAPK, hMLH1, p14, and p15 is associated with progression of breast cancer: A PRISMA-compliant meta-analysis

BACKGROUND

Numerous studies have investigated the associations between RARβ2, DAPK, hMLH1, p14, and p15 promoter hypermethylation and clinical progression of patients with breast cancer, however the results remained uncertain due to the small sample size. Therefore, we performed a meta-analysis to explore the role of RARβ2, DAPK, hMLH1, p14, and p15 promoter hypermethylation in the susceptibility and clinical progression of breast cancer.

METHODS

Eligible studies were obtained by searching Medicine, Embase, Web of knowledge, and Chinese National Knowledge Infrastructure (CNKI) databases. The odds ratios (OR) and 95% confidence intervals (CI) were calculated to evaluate the associations of RARβ2, DAPK, hMLH1, p14, and p15 promoter hypermethylation with breast cancer pathogenesis. Trial sequential analysis (TSA) was applied to observe the reliability of pooled results of RARβ2 gene, and obtain a conservative required information size (RIS).

RESULTS

In primary screened 445 articles, 39 literatures with 4492 breast cancer patients were finally enrolled in the final meta-analysis. The results indicated that the frequency of RARβ2 promoter hypermethylation in case group was significantly higher than the frequency of control group (OR = 7.21, 95% CI = 1.54-33.80, P < .05). The RARβ2 promoter hypermethylation had a significant association with lymph node metastasis of breast cancer (OR = 2.13, 95% CI = 1.04-4.47, P < .05). And, the RARβ2 promoter hypermethylation was more common in the breast cancer patients of TNM III-IV stage than those patients of TNM I-II stage (OR = 1.85, 95% CI = 1.33-2.57, P < .05). In addition, the promoter hypermethylation of DAPK, hMLH1, and p14 genes were significantly associated with the susceptibility of breast cancer (for DAPK, OR = 4.93, 95% CI = 3.17-7.65; for hMLH1, OR = 1.84, 95% CI = 1.26-1.29; for p14, OR = 22.52, 95% CI = 7.00-72.41; for p15, OR = 2.13, 95% CI = 0.30-15.07).

CONCLUSIONS

Our findings revealed that the RARβ2 promoter hypermethylation significantly increased the risk of breast cancer. In the meantime, the meta-analysis demonstrated that there were significant associations of RARβ2 promoter hypermethylation with lymph node metastasis and TNM-stage of breast cancer patients. In addition, DAPK, hMLH1, and p14 genes promoter hypermethylation were significantly associated with the susceptibility of breast cancer.

Large-scale analysis reveals a novel risk score to predict overall survival in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is a major cause of cancer mortality and an increasing incidence worldwide; however, there are very few effective diagnostic approaches and prognostic biomarkers.

Materials and methods

One hundred forty-nine pairs of HCC samples from Gene Expression Omnibus (GEO) were obtained to screen differentially expressed genes (DEGs) between HCC and normal samples. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, Gene ontology enrichment analyses, and protein–protein interaction network were used. Cox proportional hazards regression analysis was used to identify significant prognostic DEGs, with which a gene expression signature prognostic prediction model was identified in The Cancer Genome Atlas (TCGA) project discovery cohort. The robustness of this panel was assessed in the GSE14520 cohort. We verified details of the gene expression level of the key molecules through TCGA, GEO, and qPCR and used immunohistochemistry for substantiation in HCC tissues. The methylation states of these genes were also explored.

Results

Ninety-eight genes, consisting of 13 upregulated and 85 downregulated genes, were screened out in three datasets. KEGG and Gene ontology analysis for the DEGs revealed important biological features of each subtype. Protein–protein interaction network analysis was constructed, consisting of 64 nodes and 115 edges. A subset of four genes (SPINK1, TXNRD1, LCAT, and PZP) that formed a prognostic gene expression signature was established from TCGA and validated in GSE14520. Next, the expression details of the four genes were validated with TCGA, GEO, and clinical samples. The expression panels of the four genes were closely related to methylation states.

Conclusion

This study identified a novel four-gene signature biomarker for predicting the prognosis of HCC. The biomarkers may also reveal molecular mechanisms underlying development of the disease and provide new insights into interventional strategies.

DNA methylation and de-methylation using hybrid site-targeting proteins

DNA methylation plays important roles in determining cellular identity, disease, and environmental responses, but little is known about the mechanisms that drive methylation changes during cellular differentiation and tumorigenesis. Meanwhile, the causal relationship between DNA methylation and transcription remains incompletely understood. Recently developed targeted DNA methylation manipulation tools can address these gaps in knowledge, leading to new insights into how methylation governs gene expression. Here, we summarize technological developments in the DNA methylation editing field and discuss the remaining challenges facing current tools, as well as potential future directions.