Estimation of the fraction of cancer cells in a tumor DNA sample using DNA methylation

Low-density lipoprotein receptor-related protein 5/6 promotes endometrial cancer progression and cancer cell immune escape

The study investigated the potential association of the low-density lipoprotein (LDL) genome with endometrial cancer progression based on the Gene Expression Omnibus data set and The Cancer Genome Atlas data set. Differential and weighted gene coexpression network analysis was performed on endometrial cancer transcriptome datasets GSE9750 and GSE106191. The protein-protein interaction network was built using LDL-receptor proteins and the top 50 tumor-associated genes. Low-density lipoprotein-related receptors 5/6 (LRP5/6) in endometrial cancer tissues were correlated with oncogenes, cell cycle-related genes, and immunological checkpoints using Spearman correlation. MethPrimer predicted the LRP5/6 promoter CpG island. LRP2, LRP6, LRP8, LRP12, low-density lipoprotein receptor-related protein-associated protein, and LRP5 were major LDL-receptor-related genes associated with endometrial cancer. LRP5/6 was enriched in various cancer-related pathways and may be a key LDL-receptor-related gene in cancer progression. LRP5/6 may be involved in the proliferation process of endometrial cancer cells by promoting the expression of cell cycle-related genes. LRP5/6 may be involved in the proliferation of endometrial cancer cells by promoting the expression of cell cycle-related genes. LRP5/6 may promote the immune escape of cancer cells by promoting the expression of immune checkpoints, promoting endometrial cancer progression. The MethPrimer database predicted that the LRP5/6 promoter region contained many CpG islands, suggesting that DNA methylation can occur in the LRP5/6 promoter region. LRP5/6 may aggravate endometrial cancer by activating the phosphoinositide 3-kinase/protein kinase B pathway.

DNA Methylation Biomarkers for Prediction of Response to Platinum-Based Chemotherapy: Where Do We Stand?

Simple Summary

Platinum-based agents are one of the most widely used chemotherapy drugs for various types of cancer. However, one of the main challenges in the application of platinum drugs is resistance, which is currently being widely investigated. Epigenetic DNA methylation-based biomarkers are promising to aid in the selection of patients, helping to foresee their platinum therapy response in advance. These biomarkers enable minimally invasive patient sample collection, short analysis, and good sensitivity. Hence, improved methodologies for the detection and quantification of DNA methylation biomarkers will facilitate their use in the choice of an optimal treatment strategy.

Abstract

Platinum-based chemotherapy is routinely used for the treatment of several cancers. Despite all the advances made in cancer research regarding this therapy and its mechanisms of action, tumor resistance remains a major concern, limiting its effectiveness. DNA methylation-based biomarkers may assist in the selection of patients that may benefit (or not) from this type of treatment and provide new targets to circumvent platinum chemoresistance, namely, through demethylating agents. We performed a systematic search of studies on biomarkers that might be predictive of platinum-based chemotherapy resistance, including in vitro and in vivo pre-clinical models and clinical studies using patient samples. DNA methylation biomarkers predictive of response to platinum remain mostly unexplored but seem promising in assisting clinicians in the generation of more personalized follow-up and treatment strategies. Improved methodologies for their detection and quantification, including non-invasively in liquid biopsies, are additional attractive features that can bring these biomarkers into clinical practice, fostering precision medicine.

DNA methylation marker to estimate ovarian cancer cell fraction

Evaluation of a cancer cell fraction is important for accurate molecular analysis, and pathological analysis is the gold standard for evaluation. Despite the potential convenience, no established molecular markers for evaluation are available. In this study, we aimed to identify ovarian cancer cell fraction markers using DNA methylation highly specific to ovarian cancer cells. Using genome-wide DNA methylation data, we screened candidate marker genes methylated in 30 ovarian cancer FFPE samples and 12 high-grade serous ovarian cancer cell lines, and unmethylated in two female leucocytes and two normal fallopian epithelial cell samples. Methylation levels of two genes, SIM1, and ZNF154, showed high correlation with pathological cancer cell fractions among the 30 ovarian cancer FFPE samples (R = 0.61 for SIM1, 0.71 for ZNF154). For cost-effective analysis of FFPE samples, pyrosequencing primers were designed, and successfully established for SIM1 and ZNF154. Correlation between a pathological cancer cell fraction and methylation levels obtained by pyrosequencing was confirmed to be high (R = 0.53 for SIM1, 0.64 for ZNF154). Finally, an independent validation cohort of 29 ovarian cancer FFPE samples was analyzed. ZNF154 methylation showed a high correlation with the pathological cancer cell fraction (R = 0.77, P < 0.0001). Therefore, the ZNF154 methylation level was considered to be useful for the estimation of ovarian cancer cell fraction, and is expected to help accurate molecular analysis.

Tracing the evolution of aneuploid cancers by multiregional sequencing with CRUST

Clonal deconvolution of mutational landscapes is crucial to understand the evolutionary dynamics of cancer. Two limiting factors for clonal deconvolution that have remained unresolved are variation in purity and chromosomal copy number across different samples of the same tumor. We developed a semi-supervised algorithm that tracks variant calls through multi-sample spatiotemporal tumor data. While normalizing allele frequencies based on purity, it also adjusts for copy number changes at clonal deconvolution. Absent à priori copy number data, it renders in silico copy number estimations from bulk sequences. Using published and simulated tumor sequences, we reliably segregated clonal/subclonal variants even at a low sequencing depth (~50×). Given at least one pure tumor sample (>70% purity), we could normalize and deconvolve paired samples down to a purity of 40%. This renders a reliable clonal reconstruction well adapted to multi-regionally sampled solid tumors, which are often aneuploid and contaminated by non-cancer cells.

A Four-Gene-Based Prognostic Model Predicts Overall Survival in Patients With Cutaneous Melanoma

Background

Cutaneous melanoma (CM) is one of the most aggressive cancers with highly metastatic ability. To make things worse, there are limited effective therapies to treat advanced CM. Our study aimed to investigate new biomarkers for CM prognosis and establish a novel risk score system in CM.

Methods

Gene expression data of CM from Gene Expression Omnibus (GEO) datasets were downloaded and analyzed to identify differentially expressed genes (DEGs). The overlapped DEGs were then verified for prognosis analysis by univariate and multivariate COX regression in The Cancer Genome Atlas (TCGA) datasets. Based on the gene signature of multiple survival associated DEGs, a risk score model was established, and its prognostic and predictive role was estimated through Kaplan-Meier (K-M) analysis and log-rank test. Furthermore, the correlations between prognosis related genes expression and immune infiltrates were analyzed via Tumor Immune Estimation Resource (TIMER) site.

Results

A total of 103 DEGs were obtained based on GEO cohorts, and four genes were verified in TCGA datasets. Subsequently, four genes (ADAMDEC1, GNLY, HSPA13, and TRIM29) model was developed by univariate and multivariate Cox regression analyses. The K-M plots showed that the high-risk group was associated with shortened survival than that in the low-risk group (P < 0.0001). Multivariate analysis suggested that the model was an independent prognostic factor (high-risk vs. low-risk, HR= 2.06, P < 0.001). Meanwhile, the high-risk group was prone to have larger breslow depth (P< 0.001) and ulceration (P< 0.001).

Conclusions

The four-gene risk score model functions well in predicting the prognosis and treatment response in CM and will be useful for guiding therapeutic strategies for CM patients. Additional clinical trials are needed to verify our findings.

contamDE-lm: linear model-based differential gene expression analysis using next-generation RNA-seq data from contaminated tumor samples

MOTIVATION

Tumor and adjacent normal RNA samples are commonly used to screen differentially expressed genes between normal and tumor samples or among tumor subtypes. Such paired-sample design could avoid numerous confounders in differential expression (DE) analysis, but the cellular contamination of tumor samples can be an important noise and confounding factor, which can both inflate false-positive rate and deflate true-positive rate. The existing DE tools that use next-generation RNA-seq data either do not account for cellular contamination or are computationally extensive with increasingly large sample size.

RESULTS

A novel linear model was proposed to avoid the problem that could arise from tumor-normal correlation for paired samples. A statistically robust and computationally very fast DE analysis procedure, contamDE-lm, was developed based on the novel model to account for cellular contamination, boosting DE analysis power through the reduction in individual residual variances using gene-wise information. The desired advantages of contamDE-lm over some state-of-the-art methods (limma and DESeq2) were evaluated through the applications to simulated data, TCGA database and Gene Expression Omnibus (GEO) database.

AVAILABILITY AND IMPLEMENTATION

The proposed method contamDE-lm was implemented in an updated R package contamDE (version 2.0), which is freely available at https://github.com/zhanghfd/contamDE.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

FGF5 methylation is a sensitivity marker of esophageal squamous cell carcinoma to definitive chemoradiotherapy

Definitive chemoradiotherapy (dCRT) is the major treatment for esophageal squamous cell carcinoma (ESCC), and prediction of the response to dCRT is important so as not to miss an opportunity to cure an ESCC. Nevertheless, few validated markers are available. Here, we aimed to identify a highly reproducible marker using multi-layer omics analysis. 117 ESCC samples from 67 responders and 50 non-responders were divided into screening, validation, and re-validation sets. In the screening cohort (n = 41), somatic mutations in 114 genes showed no association with dCRT response. Genome-wide DNA methylation analysis using Infinium HumanMethylation450 BeadChip array identified four genic regions significantly associated with dCRT response. Among them, FGF5 methylation was validated to be associated with dCRT response (n = 34; P = 0.001), and further re-validated (n = 42; P = 0.020) by bisulfite-pyrosequencing. The sensitivity and specificity in the combined validation and re-validation sets (n = 76) were 45% and 90%, respectively, by using the cut-off value established in the screening set, and FGF5 methylation had predictive power independent from clinicopathological parameters. In ESCC cell lines, FGF5 promoter methylation repressed its expression. FGF5 expression was induced by cisplatin (CDDP) treatment in three unmethylated cell lines, but not in two methylated cell lines. Exogenous FGF5 overexpression in a cell line with its methylation conferred resistance to CDDP. In non-cancerous esophageal tissues, FGF5 was not expressed, and its methylation was present in a small fraction of cells. These results showed that FGF5 methylation is a validated marker for ESCC sensitivity to dCRT.

DNA methylation marker to estimate the breast cancer cell fraction in DNA samples

Estimation of the cancer cell fraction in breast cancer tissue is important for exclusion of samples unsuitable for multigene prognostic assays and a variety of molecular analyses for research. Here, we aimed to establish a breast cancer cell fraction marker based on DNA methylation. First, we screened genes unmethylated in non-cancerous mammary tissues and methylated in breast cancer tissues using microarray data from the TCGA database, and isolated 12 genes. Among them, four genes were selected as candidate marker genes without a high incidence of copy number alterations and with broad coverage across patients. Bisulfite pyrosequencing analysis of additional breast cancer biopsy specimens purified by laser capture microdissection (LCM) excluded two genes, and a combination of SIM1 and CCDC181 was finally selected as a fraction marker. In further additional specimens without LCM purification, the fraction marker was substantially methylated (≥ 20%) with high incidence (50/51). The cancer cell fraction estimated by the fraction marker was significantly correlated with that estimated by microscopic examination (p < 0.0001). Performance of a previously established marker, HSD17B4 methylation, which predicts therapeutic response of HER2-positive breast cancer to trastuzumab, was improved after the correction of cancer cell fraction by the fraction marker. In conclusion, we successfully established a breast cancer cell fraction marker based on DNA methylation.

Detect differentially methylated regions using non-homogeneous hidden Markov model for methylation array data

Motivation

DNA methylation is an important epigenetic mechanism in gene regulation and the detection of differentially methylated regions (DMRs) is enthralling for many disease studies. There are several aspects that we can improve over existing DMR detection methods: (i) methylation statuses of nearby CpG sites are highly correlated, but this fact has seldom been modelled rigorously due to the uneven spacing; (ii) it is practically important to be able to handle both paired and unpaired samples; and (iii) the capability to detect DMRs from a single pair of samples is demanded.

Results

We present DMRMark (DMR detection based on non-homogeneous hidden Markov model), a novel Bayesian framework for detecting DMRs from methylation array data. It combines the constrained Gaussian mixture model that incorporates the biological knowledge with the non-homogeneous hidden Markov model that models spatial correlation. Unlike existing methods, our DMR detection is achieved without predefined boundaries or decision windows. Furthermore, our method can detect DMRs from a single pair of samples and can also incorporate unpaired samples. Both simulation studies and real datasets from The Cancer Genome Atlas showed the significant improvement of DMRMark over other methods.

Availability and implementation

DMRMark is freely available as an R package at the CRAN R package repository.

Contact

xfan@cuhk.edu.hk.

Supplementary information

Supplementary data are available at Bioinformatics online.

AP-2β inhibits hepatocellular carcinoma invasion and metastasis through Slug and Snail to suppress epithelial-mesenchymal transition

Transcription factor AP-2β plays an important role in human cancer, but its clinical significance in hepatocellular carcinogenesis is largely unknown.

Methods: AP-2β expression was detected in human hepatocellular cancer (HCC) tissues and cell lines. The effects of AP-2β on HCC proliferation, migration, invasion, tumor formation and metastasis were evaluated by MTT, colony formation and transwell assays in vitro and mouse experiments in vivo. The association between AP-2β and miR-27a/EMT markers in HCC cell lines and tissues was analyzed.

Results: AP-2β expression was decreased in HCC tissues and cell lines. Reduced expression of AP-2β was significantly associated with more advanced tumor stages and larger tumor sizes. The overexpression of AP-2β reduced HCC proliferation, migration, invasion, tumor formation and metastasis in vitro and in vivo. Additionally, AP-2β overexpression increased the sensitivity of HCC cells to cisplatin. Moreover, AP-2β modulates the levels of EMT markers through Slug and Snail in HCC cell lines and tissues. Furthermore, oncogenic miR-27a inhibits AP-2β expression by binding to the AP-2β 3′ untranslated region (UTR) and reverses the tumor suppressive role of AP-2β.

Conclusion: These results suggested that AP-2β is lowly expressed in HCC by inhibiting EMT signaling to regulate HCC cell growth and migration. Therefore, AP-2β in the novel miR-27a/AP-2β/Slug/EMT regulatory axis enhances the chemotherapeutic drug sensitivity of HCC and might represent a potential target for evaluating the treatment and prognosis of human HCC.

Accumulated promoter methylation as a potential biomarker for esophageal cancer

We performed a two-stage molecular epidemiological study to explore DNA methylation profiles for potential biomarkers of esophageal squamous cell carcinoma (ESCC) in a Chinese population. Infinium Methylation 450K BeadChip was used to identify genes with differentially methylated CpG sites. Sixteen candidate genes were validated by sequencing 1160 CpG sites in their promoter regions using the Illumina MiSeq platform. When excluding sites with negative changes, 10 genes (BNIP3, BRCA1, CCND1, CDKN2A, HTATIP2, ITGAV, NFKB1, PIK3R1, PRDM16 and PTX3) showed significantly different methylation levels among cancer lesions, remote normal-appearing tissues, and healthy controls. PRDM16 had the highest diagnostic value with the AUC (95% CI) of 0.988 (0.965–1.000), followed by PIK3R1, with the AUC (95% CI) of 0.969 (0.928–1.000). In addition, the methylation status was higher in patients with advanced cancer stages. These results indicate that aberrant DNA methylation may be a potential biomarker for the diagnosis of ESCC.

Screening pathogenic genes in oral squamous cell carcinoma based on the mRNA expression microarray data

Oral squamous cell carcinoma (OSCC) is one of the most common malignancies and its survival rate has barely improved over the past few decades. The purpose of this study was to screen pathogenic genes of OSCC via microarray analysis. The mRNA expression microarray datasets (GSE2280 and GSE3524) were downloaded from the Gene Expression Omnibus (GEO) database. In GSE2280, there were 22 OSCC samples without metastasis and 5 OSCC samples with lymph node metastasis. In GSE3524, there were 16 OSCC samples and 4 normal tissue samples. The differentially expressed genes (DEGs) in OSCC samples with lymph node metastasis compared with those without metastasis (named as DEGs-1), and the DEGs in OSCC samples compared with normal tissue samples (named as DEGs-2), were obtained via limma package. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to perform the functional enrichment analyses of DEGs-1 and DEGs-2. The miRNA-gene pairs of overlaps among DEGs were screened out with the TargetScan database, and the miRNA-gene regulated network was constructed by Cytoscape software. A total of 233 and 410 DEGs were identified in the sets of DEGs-1 and DEGs-2, respectively. DEGs-1 were enriched in 188 Gene Ontology (GO) terms and 8 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and DEGs-2 were enriched in 228 GO terms and 6 KEGG pathways. In total, 126 nodes and 135 regulated pairs were involved in the miRNA-gene regulated network. Our study indicated that transglutaminase 2 (TGM2) and Islet 1 (ISL1) may be biomarkers of OSCC and their metastases. Moreover, it provided some potential pathogenic genes (e.g. P2RY2 and RAPGEFL1) in OSCC.

HPV16 integration probably contributes to cervical oncogenesis through interrupting tumor suppressor genes and inducing chromosome instability

Background

The integration of human papilloma virus (HPV) into host genome is one of the critical steps that lead to the progression of precancerous lesion into cancer. However, the mechanisms and consequences of such integration events are poorly understood. This study aims to explore those questions by studying high risk HPV16 integration in women with cervical intraepithelial neoplasia (CIN) and cervical squamous cell carcinoma (SCC).

Methods

Specifically, HPV integration status of 13 HPV16-infected patients were investigated by ligation-mediated PCR (DIPS-PCR) followed by DNA sequencing.

Results

In total, 8 HPV16 integration sites were identified inside or around genes associated with cancer development. In particular, the well-studied tumor suppressor genes SCAI was found to be integrated by HPV16, which would likely disrupt its expression and therefore facilitate the migration of tumor. On top of that, we observed several cases of chromosome translocation events coincide with HPV integration, which suggests the existence of chromosome instability. Additionally, short overlapping sequences were observed between viral derived and host derived fragments in viral-cellular junctions, indicating that integration was mediated by micro homology-mediated DNA repair pathway.

Conclusions

Overall, our study suggests a model in which HPV16 might contribute to oncogenesis not only by disrupting tumor suppressor genes, but also by inducing chromosome instability.

Electronic supplementary material

The online version of this article (doi:10.1186/s13046-016-0454-4) contains supplementary material, which is available to authorized users.

Spatial intratumoral heterogeneity and temporal clonal evolution in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is among the most common malignancies, but little is known about its spatial intratumor heterogeneity (ITH) and temporal clonal evolutionary processes. To address this, we performed multiregion whole-exome sequencing on 51 tumor regions from 13 ESCCs, and multiregion global methylation profiling on three of these 13 cases. We found an average of 35.8% heterogeneous somatic mutations with strong evidence of ITH. Half of driver mutations located on the branches targeted oncogenes, including PIK3CA, NFE2L2, MTOR, etc. By contrast, the majority of truncal and clonal driver mutations occurred in tumor suppressor genes, including TP53, KMT2D, ZNF750, etc. Interestingly, the phyloepigenetic trees robustly recapitulated the topologic structures of the phylogenetic ones, indicating the possible relationship between genetic and epigenetic alterations. Our integrated investigations of the spatial ITH and clonal evolution provide an important molecular foundation for enhanced understanding of the tumorigenesis and progression of ESCC.

Establishment of a DNA methylation marker to evaluate cancer cell fraction in gastric cancer

BACKGROUND

Tumor samples are unavoidably contaminated with coexisting normal cells. Here, we aimed to establish a DNA methylation marker to estimate the fraction of gastric cancer (GC) cells in any DNA sample by isolating genomic regions specifically methylated in GC cells.

METHODS

Genome-wide and gene-specific methylation analyses were conducted with an Infinium HumanMethylation450 BeadChip array and by quantitative methylation-specific PCR, respectively. Purified cancer and noncancer cells were prepared by laser-capture microdissection. TP53 mutation data were obtained from our previous study using next-generation target sequencing.

RESULTS

Genome-wide DNA methylation analysis of 12 GC cell lines, 30 GCs, six normal gastric mucosae, one sample of peripheral leukocytes, and four noncancerous gastric mucosae identified OSR2, PPFIA3, and VAV3 as barely methylated in normal cells and highly methylated in cancer cells. Quantitative methylation-specific PCR using 26 independent GCs validated that one or more of them was highly methylated in all of the GCs. Using four pairs of purified cells, we confirmed the three genes were highly methylated (85 % or more) in cancer cells and barely methylated (5 % or less) in noncancer cells. The cancer cell fraction assessed by the panel of the three genes showed good correlation with that assessed by the TP53 mutant allele frequency in 13 GCs (r = 0.77). After correction of the GC cell fraction, unsupervised clustering analysis of the genome-wide DNA methylation profiles yielded clearer clustering.

CONCLUSIONS

A DNA methylation marker-namely, the panel of the three genes-is useful to estimate the cancer cell fraction in GCs.

Early-Stage Induction of SWI/SNF Mutations during Esophageal Squamous Cell Carcinogenesis

The SWI/SNF chromatin remodeling complex is frequently inactivated by somatic mutations of its various components in various types of cancers, and also by aberrant DNA methylation. However, its somatic mutations and aberrant methylation in esophageal squamous cell carcinomas (ESCCs) have not been fully analyzed. In this study, we aimed to clarify in ESCC, what components of the SWI/SNF complex have somatic mutations and aberrant methylation, and when somatic mutations of the SWI/SNF complex occur. Deep sequencing of components of the SWI/SNF complex using a bench-top next generation sequencer revealed that eight of 92 ESCCs (8.7%) had 11 somatic mutations of 7 genes, ARID1A, ARID2, ATRX, PBRM1, SMARCA4, SMARCAL1, and SMARCC1. The SMARCA4 mutations were located in the Forkhead (85Ser>Leu) and SNF2 family N-terminal (882Glu>Lys) domains. The PBRM1 mutations were located in a bromodomain (80Asn>Ser) and an HMG-box domain (1,377Glu>Lys). For most mutations, their mutant allele frequency was 31–77% (mean 61%) of the fraction of cancer cells in the same samples, indicating that most of the cancer cells in individual ESCC samples had the SWI/SNF mutations on one allele, when present. In addition, a BeadChip array analysis revealed that a component of the SWI/SNF complex, ACTL6B, had aberrant methylation at its promoter CpG island in 18 of 52 ESCCs (34.6%). These results showed that genetic and epigenetic alterations of the SWI/SNF complex are present in ESCCs, and suggested that genetic alterations are induced at an early stage of esophageal squamous cell carcinogenesis.

Integrated analysis of DNA methylation and mutations in esophageal squamous cell carcinoma

The recent development of next-generation sequencing technology for extensive mutation analysis, and beadarray technology for genome-wide DNA methylation analysis has made it possible to obtain integrated pictures of genetic and epigenetic alterations, using the same cancer samples. In this study, we aimed to characterize such a picture in esophageal squamous cell carcinomas (ESCCs). Base substitutions of 55 cancer-related genes and copy number alterations (CNAs) of 28 cancer-related genes were analyzed by targeted sequencing. Forty-four of 57 ESCCs (77%) had 64 non-synonymous somatic mutations, and 24 ESCCs (42%) had 35 CNAs. A genome-wide DNA methylation analysis using an Infinium HumanMethylation450 BeadChip array showed that the CpG island methylator phenotype was unlikely to be present in ESCCs, a different situation from gastric and colon cancers. Regarding individual pathways affected in ESCCs, the WNT pathway was activated potentially by aberrant methylation of its negative regulators, such as SFRP1, SFRP2, SFRP4, SFRP5, SOX17, and WIF1 (33%). The p53 pathway was inactivated by TP53 mutations (70%), and potentially by aberrant methylation of its downstream genes. The cell cycle was deregulated by mutations of CDKN2A (9%), deletions of CDKN2A and RB1 (32%), and by aberrant methylation of CDKN2A and CHFR (9%). In conclusion, ESCCs had unique methylation profiles different from gastric and colon cancers. The genes involved in the WNT pathway were affected mainly by epigenetic alterations, and those involved in the p53 pathway and cell cycle regulation were affected mainly by genetic alterations. © 2016 Wiley Periodicals, Inc.

Poor survival is associated with the methylated degree of zinc-finger protein 545 (ZNF545) DNA promoter in gastric cancer

Zinc-finger protein 545 (ZNF545) was identified as a gastric tumour suppressor and potentially independent prognostic factor. At the present study, we found that lower expression of ZNF545 was specific in gastric cancer (GC) tissues, and the inconsistently methylated levels of ZNF545 promoter were identified in the gastric cancer tissues. In the methylation-specific PCR (MSP) analysis cohort, we found that GC patients with hypermethylated ZNF545 promoter exhibited significantly shorter median OS than those with unmethylated ZNF545 promoter and those with hypomethylated ZNF545 promoter. In the other cohort, we also demonstrated that GC patients with three or more methylated CpG sites in the ZNF545 promoter were significantly associated with poor survival by using the bisulphite gene sequencing (BGS). The methylated degrees of five CpG sites (−232, −214, −176, −144 and −116) could also provide distinct survival discrimination of patients with GC. These findings indicated that the methylated CpG sites of the ZNF545 promoter could be used for the clinical prediction of the prognosis of GC.

Transcription factor activating protein 2 beta (TFAP2B) mediates noradrenergic neuronal differentiation in neuroblastoma

Neuroblastoma is an embryonal pediatric tumor that originates from the developing sympathetic nervous system and shows a broad range of clinical behavior, ranging from fatal progression to differentiation into benign ganglioneuroma. In experimental neuroblastoma systems, retinoic acid (RA) effectively induces neuronal differentiation, and RA treatment has been therefore integrated in current therapies. However, the molecular mechanisms underlying differentiation are still poorly understood. We here investigated the role of transcription factor activating protein 2 beta (TFAP2B), a key factor in sympathetic nervous system development, in neuroblastoma pathogenesis and differentiation. Microarray analyses of primary neuroblastomas (n = 649) demonstrated that low TFAP2B expression was significantly associated with unfavorable prognostic markers as well as adverse patient outcome. We also found that low TFAP2B expression was strongly associated with CpG methylation of the TFAP2B locus in primary neuroblastomas (n = 105) and demethylation with 5-aza-2'-deoxycytidine resulted in induction of TFAP2B expression in vitro, suggesting that TFAP2B is silenced by genomic methylation. Tetracycline inducible re-expression of TFAP2B in IMR-32 and SH-EP neuroblastoma cells significantly impaired proliferation and cell cycle progression. In IMR-32 cells, TFAP2B induced neuronal differentiation, which was accompanied by up-regulation of the catecholamine biosynthesizing enzyme genes DBH and TH, and down-regulation of MYCN and REST, a master repressor of neuronal genes. By contrast, knockdown of TFAP2B by lentiviral transduction of shRNAs abrogated RA-induced neuronal differentiation of SH-SY5Y and SK-N-BE(2)c neuroblastoma cells almost completely. Taken together, our results suggest that TFAP2B is playing a vital role in retaining RA responsiveness and mediating noradrenergic neuronal differentiation in neuroblastoma.

Applicability of the methylated CpG sites of paired box 5 (PAX5) promoter for prediction the prognosis of gastric cancer

Paired box gene 5 (PAX5), a member of the paired box gene family, is involved in control of organ development and tissue differentiation. In previous study, PAX5 promoter methylation was found in gastric cancer (GC) cells and tissues. At present study, we found that the inconsistently methylated levels of PAX5 promoter were identified in the different GC tissues. The methylated CpG site count and the methylated statuses of four CpG sites (-236, -183, -162, and -152) were significantly associated with the survival of 460 GC patients, respectively. Ultimately, the methylated CpG -236 was the optimal prognostic predictor of patients identified by using the Cox regression with AIC value calculation. These findings indicated that the methylated CpG -236 of PAX5 promoter has the potential applicability for clinical evaluation the prognosis of GC.

The survival decrease in gastric cancer is associated with the methylation of B-cell CLL/lymphoma 6 member B promoter

The methylation of B-cell CLL/lymphoma 6 member B (BCL6B) DNA promoter was detected in several malignancies. Here, we quantitatively detect the methylated status of CpG sites of BCL6B DNA promoter of 459 patients with gastric cancer (GC) by using bisulfite gene sequencing. We show that patients with three or more methylated CpG sites in the BCL6B promoter were significantly associated with poor survival. Furthermore, by using the Akaike information criterion value calculation, we show that the methylated count of BCL6B promoter was identified to be the optimal prognostic predictor of GC patients.

Frequent involvement of chromatin remodeler alterations in gastric field cancerization

A field for cancerization, or a field defect, is formed by the accumulation of genetic and epigenetic alterations in normal-appearing tissues, and is involved in various cancers, especially multiple cancers. Epigenetic alterations are frequently present in chronic inflammation-exposed tissues, but information on individual genes involved in the formation of a field defect is still fragmental. Here, using non-cancerous gastric tissues of cancer patients, we isolated 16 aberrantly methylated genes, and identified chromatin remodelers ACTL6B and SMARCA1 as novel genes frequently methylated in non-cancerous tissues. SMARCA1 was expressed at high levels in normal gastric tissues, but was frequently silenced by aberrant methylation in gastric cancer cells. Moreover, somatic mutations of additional chromatin remodelers, such as ARID1A, SMARCA2, and SMARCA4, were found in 30% of gastric cancers. Mutant allele frequency suggested that the majority of cancer cells harbored a mutation when present. Depletion of a chromatin remodeler, SMARCA1 or SMARCA2, in cancer cell lines promoted their growth. These results showed that epigenetic and genetic alterations of chromatin remodelers are induced at an early stage of carcinogenesis and are frequently involved in the formation of a field defect.

ZNF695 methylation predicts a response of esophageal squamous cell carcinoma to definitive chemoradiotherapy

PURPOSE

Definitive chemoradiotherapy (dCRT) is one of the standard treatments for esophageal squamous cell carcinoma. Patients with a response to dCRT have a better prognosis than those resistant to dCRT while survival benefits for patients with residual tumors are limited. Nevertheless, few molecular markers to predict the response to dCRT are currently available. Here, we aimed to establish a DNA methylation marker to predict the response to dCRT.

METHODS

A total of 104 patients were divided into screening (n = 43) and validation (n = 61) sets. A genome-wide DNA methylation analysis was performed using an Infinium HumanMethylation450 BeadChip array. Methylation levels were measured by quantitative methylation-specific PCR and normalized by the fraction of cancer cells in a sample.

RESULTS

The genome-wide methylation analysis of seven responders and eight non-responders identified 18 genomic regions specifically (un)methylated in the responders. Among these, methylation of the promoter CpG island of ZNF695 was significantly associated with the response to dCRT in the screening set (P = 0.004), and a cutoff value was determined. In the validation set, the association was successfully validated (P = 0.021), and a high specificity (90 %) for the prediction of responders was obtained using the prefixed cutoff value. In addition, a multivariate analysis showed that ZNF695 methylation was an independent predictive factor for the response to dCRT (OR 7.55, 95 % CI 2.12-26.9, P = 0.002).

CONCLUSION

ZNF695 methylation was significantly associated with the response to dCRT and is a promising predictive marker for the response to dCRT.

Methylated CpG site count of dapper homolog 1 (DACT1) promoter prediction the poor survival of gastric cancer

OBJECTIVE

To elucidate the clinical significance of the methylated status of CpG sites of dapper homolog 1 (DACT1) promoter in the survival prediction in gastric cancer (GC).

METHODS

The large scale GC patients (n=459) were analyzed for the quantitatively methylated status of CpG sites of DACT1 DNA promoter with the bisulphite sequencing PCR (BSP). With gene sequencing analysis, the methylated statuses of 12 cytosine-phosphate-guanine (CpG) sites in DACT1 promoter were detected to supply detailed information for the precisely prognostic prediction. Associations between molecular, clinicopathologic, and survival data were analyzed.

RESULTS

With the MSP detection, different methylated levels of DACT1 promoter were identified in the 25 GC tissues, while none of 25 normal gastric mucosal tissues were found to be methylated. DACT1 promoter methylation was found in 28.32% in 459 patients. GC patients with 4 or more methylated CpG sites of DACT1 promoter was significantly associated with the poorer survival (P=0.19). The methylated statuses of CpG -515, CpG -435, and CpG -430 sites were also identified to provide the elaborate survival discrimination for 459 GC patients, respectively (P=0.049, =0.006, and =0.037). In addition, we demonstrated that the methylated CpG site count had smallest AIC and BIC values than other three methylated status of CpG sites for prediction the survival of 459 GC patients.

CONCLUSIONS

The methylated CpG site count of DACT1 promoter had the significant applicability for clinical evaluation the prognosis of GC.

Clinical significance of the methylated cytosine-phosphate-guanine sites of protocadherin-10 promoter for evaluating the prognosis of gastric cancer

BACKGROUND

Protocadherin-10 (PCDH10) has been identified as a tumor suppressor gene in multiple carcinomas. In this study, we intended to elucidate the clinical applicability of the methylation of CpG sites of PCDH10 promoter for prognostic prediction in gastric cancer (GC).

STUDY DESIGN

Qualitative and quantitative detections of PCDH10 promoter methylation were performed with methylation-specific polymerase chain reaction (MSP) and bisulphite genomic sequencing, respectively. The methylated statuses of 27 cytosine-phosphate-guanine (CpG) sites in PCDH10 promoter were detected in a series of 458 GC tissues to supply precise information of prognostic prediction. Associations between molecular, clinicopathologic, and survival data were analyzed.

RESULTS

Protocadherin-10 promoter methylation was found in 91.92% in all patients. Gastric cancer patients with 5 or more methylated CpG sites of PCDH10 promoter was significantly associated with poorer survival (p = 0.038). Meanwhile, methylation of combined CpG (-115, -108, -13, and +3) sites was also identified to provide elaborate survival discrimination for GC patients (p = 0.044). On multivariate survival analysis, methylation of combined CpG (-115, -108, -13, and +3) sites (hazard ratio [HR] = 1.255; p = 0.049) was identified to be an independent prognostic indicator of GC, as were N stage and T stage. Additionally, the methylation of combined CpG (-115, -108, -13, and +3) sites had smaller Akaike information criterion (AIC) and Bayesian information criterion (BIC) values than the other 2 independent predictors of the survival. Ultimately, we demonstrated that the methylation of combined CpG (-115, -108, -13, and +3) sites was negatively associated with PCDH10 expression in GC tissues.

CONCLUSIONS

The methylated CpG sites of PCDH10 promoter had significant applicability for clinical evaluation of the prognosis of GC.

DNA methylation study of fetus genome through a genome-wide analysis

Background

DNA methylation is a crucial epigenetic modification of the genome which is involved in embryonic development, transcription, chromatin structure, X chromosome inactivation, genomic imprinting and chromosome stability. Consistent with these important roles, DNA methylation has been demonstrated to be required for vertebrate early embryogenesis and essential for regulating temporal and spatial expression of genes controlling cell fate and differentiation. Further studies have shown that abnormal DNA methylation is associated with human diseases including the embryonic development diseases. We attempt to study the DNA methylation status of CpG islands in fetus related to fetus growth and development.

Methods

GeneChip® Human Tiling 2.0R Array set is used for analysis of methylated DNA in a whole-genome wide in 8 pairs amniotic fluid and maternal blood DNA samples.

Results

We found 1 fetus hypermethylation DNA markers and 4 fetus hypomethylation DNA markers though a Genome-wide analysis. These DNA markers all found to be associated with the critical genes for fetus growth and development (SH2D3C gene, EML3 gene, TRIM71 gene, HOXA3 gene and HOXA5 gene).

Conclusions

These genes can be used as a biomarker for association studying of embryonic development, pathological pregnancy and so on. The present study has provided new and fundamental insights into the roles that DNA methylation has in embryonic development and in the pathological pregnancy.