Comparison of different normalization assumptions for analyses of DNA methylation data from the cancer genome

Nowadays, some researchers normalized DNA methylation arrays data in order to remove the technical artifacts introduced by experimental differences in sample preparation, array processing and other factors. However, other researchers analyzed DNA methylation arrays without performing data normalization considering that current normalizations for methylation data may distort real differences between normal and cancer samples because cancer genomes may be extensively subject to hypomethylation and the total amount of CpG methylation might differ substantially among samples. In this study, using eight datasets by Infinium HumanMethylation27 assay, we systemically analyzed the global distribution of DNA methylation changes in cancer compared to normal control and its effect on data normalization for selecting differentially methylated (DM) genes. We showed more differentially methylated (DM) genes could be found in the Quantile/Lowess-normalized data than in the non-normalized data. We found the DM genes additionally selected in the Quantile/Lowess-normalized data showed significantly consistent methylation states in another independent dataset for the same cancer, indicating these extra DM genes were effective biological signals related to the disease. These results suggested normalization can increase the power of detecting DM genes in the context of diagnostic markers which were usually characterized by relatively large effect sizes. Besides, we evaluated the reproducibility of DM discoveries for a particular cancer type, and we found most of the DM genes additionally detected in one dataset showed the same methylation directions in the other dataset for the same cancer type, indicating that these DM genes were effective biological signals in the other dataset. Furthermore, we showed that some DM genes detected from different studies for a particular cancer type were significantly reproducible at the functional level.     

A two-CpG-based prognostic signature for oral squamous cell carcinoma overall survival

Oral squamous cell carcinoma (OSCC) represents one of the most common head and neck cancer that with dire prognosis due partly to the lack of reliable prognostic biomarker. Here, we aimed to develop a CpG site–based prognostic signature through which we could accurately predict overall survival (OS) of patients with OSCC. We obtained OSCC-related DNA methylation and gene expression data sets from the public accessible Gene Expression Omnibus. Correlations between methylation level of CpG sites and OS of patients with OSCC were assessed by univariate Cox regression analysis followed by robust likelihood-based survival analysis on those CpG sites with permutation P < 0.05 for further screening the optimal CpG sites for OSCC OS prediction based on the risk score formula that composed of the methylation level of optimal CpG sites weighted by their regression coefficients. Besides, differential expression genes (DEGs) and differential methylation genes (DMGs) in OSCC samples compared with normal samples were obtained and shared genes were considered as vital genes in OSCC tumorgenesis and progression. As a result, two CpG sites including cg17892178 and cg17378966 that located in NID2 and IDO1, respectively, were identified as the optimal prognostic signatures for OSCC OS. In addition, 12 overlapping genes between DEGs and DMGs that closely associated with inflammation or blood and tissue development–related biological processes were obtained. In conclusions, this study should provide valuable signatures for OSCC diagnosis and treatment.     

ABCC9, NKAPL,and TMEM132C are potential diagnostic and prognostic markers in triple‐negative breast cancer

Triple‐negative breast cancer (TNBC) is a highly heterogeneous disease. The aim of this study is to identify the diagnostic and poor prognostic signatures in TNBC by exploring the aberrant DNA methylation and gene expression. Differential expression and methylation analysis of the TNBC and paracancer samples from The Cancer Genome Atlas were performed. Gene set enrichment and protein–protein interaction (PPI) network analysis was used to explore the mechanisms of TNBC. Methylation‐gene expression correlation analysis was performed, and multivariate Cox analysis and receiver operating characteristics analysis were used to further screen the hub genes for TNBC. We identified 1,525 differentially expressed genes and 150 differentially methylated genes between TNBC and paracancer samples. About 96.64% of the methylation sites were located on the CpG island. A total of 17 Gene Ontology biological process terms and 18 signal pathways were significantly enriched. GNG4, GNG11, PENK, MAOA, and AOX1 were identified as the core genes of the PPI network. Methylation‐expression correlations revealed that ABCC9 (cg06951626), NKAPL (cg18675097, cg01031101, and cg17384889), and TMEM132C (cg03530754) showed promise as diagnostic and prognostic markers in TNBC. ABCC9 (cg06951626), NKAPL (cg18675097, cg01031101, and cg17384889), and TMEM132C (cg03530754) were potential diagnostic and prognostic markers in TNBC.     

Genome-wide DNA methylation profiling of stomach cancer in the ethnic population of Mizoram,North East India

Stomach cancer is the fifth most common cancer in terms of prevalence and incidence and the fourth leading cause of mortality in men and women worldwide. It is well-established that aberrant DNA methylation in cells can lead to carcinogenesis. The primary objective of our study was to investigate the aberrant DNA methylation status of genes associated with stomach cancer with a particular reference to the ethnic population of Mizoram, North East India. The site-level analysis identified 2883 CpG sites differentially methylated, representing ～922 genes. Out of which 476 Differentially Methylated Positions (DMPs) were promoter-associated, 452 DMPs were hypermethylated, and 24 were hypomethylated. The region-level analysis identified 462 Differentially Methylated Regions (DMRs) corresponding to ～320 genes, of which ～281 genes were hypermethylated and ～40 genes were hypomethylated. TCGA analysis showed that some of the genes had been previously implicated in other cancers including stomach cancer. Five hypermethylated genes were selected as candidate genes for further investigations and they have shown to be novel and could serve as candidate hypermethylation biomarkers for stomach cancer in this particular ethnic group.     

Comparative genome-wide DNA methylation analysis of colorectal tumor and matched normal tissues

Aberrant DNA methylation often occurs in colorectal cancer (CRC). In our study we applied a genome-wide DNA methylation analysis approach, MethylCap-seq, to map the differentially methylated regions (DMRs) in 24 tumors and matched normal colon samples. In total, 2687 frequently hypermethylated and 468 frequently hypomethylated regions were identified, which include potential biomarkers for CRC diagnosis. Hypermethylation in the tumor samples was enriched at CpG islands and gene promoters, while hypomethylation was distributed throughout the genome. Using epigenetic data from human embryonic stem cells, we show that frequently hypermethylated regions coincide with bivalent loci in human embryonic stem cells. DNA methylation is commonly thought to lead to gene silencing; however, integration of publically available gene expression data indicates that 75% of the frequently hypermethylated genes were most likely already lowly or not expressed in normal tissue. Collectively, our study provides genome-wide DNA methylation maps of CRC, comprehensive lists of DMRs, and gives insights into the role of aberrant DNA methylation in CRC formation.     

Comparative genome-wide DNA methylation analysis of colorectal tumor and matched normal tissues

Aberrant DNA methylation often occurs in colorectal cancer (CRC). In our study we applied a genome-wide DNA methylation analysis approach, MethylCap-seq, to map the differentially methylated regions (DMRs) in 24 tumors and matched normal colon samples. In total, 2687 frequently hypermethylated and 468 frequently hypomethylated regions were identified, which include potential biomarkers for CRC diagnosis. Hypermethylation in the tumor samples was enriched at CpG islands and gene promoters, while hypomethylation was distributed throughout the genome. Using epigenetic data from human embryonic stem cells, we show that frequently hypermethylated regions coincide with bivalent loci in human embryonic stem cells. DNA methylation is commonly thought to lead to gene silencing; however, integration of publically available gene expression data indicates that 75% of the frequently hypermethylated genes were most likely already lowly or not expressed in normal tissue. Collectively, our study provides genome-wide DNA methylation maps of CRC, comprehensive lists of DMRs, and gives insights into the role of aberrant DNA methylation in CRC formation.     

The underlying pathophysiology association between the Type 2-diabetic and hepatocellular carcinoma

Type 2-diabetic (T2D) disease has been reported to increase the incidence of liver cancer, however, the underlying pathophysiology is still not fully understood. Here, we aimed to reveal the underlying pathophysiology association between the T2D and hepatocellular carcinoma (HCC) and, therefore, to find the possible therapeutic targets in the occurrence and development of HCC. The methylation microarray data of T2D and HCC were extracted from the Gene Expression Omnibus and The Cancer Genome Atlas. A total of 504 differentially methylated genes (DMGs) between T2D samples and the controls were identified, whereas 6269 DMGs were identified between HCC samples and the control groups. There were 336 DMGs coexisting in diabetes and HCC, among which 86 genes were comethylated genes. These genes were mostly enriched in pathways as glycosaminoglycan biosynthesis, fatty acid, and metabolic pathway as glycosaminoglycan degradation and thiamine, fructose and mannose. There were 250 DMGs that had differential methylation direction between T2D DMGs and HCC DMGs, and these genes were enriched in the Sphingolipid metabolism pathway and immune pathways through natural killer cell-mediated cytotoxicity and ak-STAT signaling pathway. Eight genes were found related to the occurrence and development of diabetes and HCC. Moreover, the result of protein-protein interaction network showed that CDKN1A gene was related to the prognosis of HCC. In summary, eight genes were found to be associated with the development of HCC and CDKN1A may serve as the potential prognostic gene for HCC.     

Analysis of DNA methylation and gene expression in radiation-resistant head and neck tumors

Resistance to radiation therapy constitutes a significant challenge in the treatment of head and neck squamous cell cancer (HNSCC). Alteration in DNA methylation is thought to play a role in this resistance. Here, we analyzed DNA methylation changes in a matched model of radiation resistance for HNSCC using the Illumina HumanMethylation450 BeadChip. Our results show that compared to radiation-sensitive cells (SCC-61), radiation-resistant cells (rSCC-61) had a significant increase in DNA methylation. After combining these results with microarray gene expression data, we identified 84 differentially methylated and expressed genes between these 2 cell lines. Ingenuity Pathway Analysis revealed ILK signaling, glucocorticoid receptor signaling, fatty acid α-oxidation, and cell cycle regulation as top canonical pathways associated with radiation resistance. Validation studies focused on CCND2, a protein involved in cell cycle regulation, which was identified as hypermethylated in the promoter region and downregulated in rSCC-61 relative to SCC-61 cells. Treatment of rSCC-61 and SCC-61 with the DNA hypomethylating agent 5-aza-2''deoxycitidine increased CCND2 levels only in rSCC-61 cells, while treatment with the control reagent cytosine arabinoside did not influence the expression of this gene. Further analysis of HNSCC data from The Cancer Genome Atlas found increased methylation in radiation-resistant tumors, consistent with the cell culture data. Our findings point to global DNA methylation status as a biomarker of radiation resistance in HNSCC, and suggest a need for targeted manipulation of DNA methylation to increase radiation response in HNSCC.     

DNA methylation at differentially methylated regions of imprinted genes is resistant to developmental programming by maternal nutrition

The nutritional environment in which the mammalian fetus or infant develop is recognized as influencing the risk of chronic diseases, such as type 2 diabetes and hypertension, in a phenomenon that has become known as developmental programming. The late onset of such diseases in response to earlier transient experiences has led to the suggestion that developmental programming may have an epigenetic component, because epigenetic marks such as DNA methylation or histone tail modifications could provide a persistent memory of earlier nutritional states. One class of genes that has been considered a potential target or mediator of programming events is imprinted genes, because these genes critically depend upon epigenetic modifications for correct expression and because many imprinted genes have roles in controlling fetal growth as well as neonatal and adult metabolism. In this study, we have used an established model of developmental programming—isocaloric protein restriction to female mice during gestation or lactation—to examine whether there are effects on expression and DNA methylation of imprinted genes in the offspring. We find that although expression of some imprinted genes in liver of offspring is robustly and sustainably changed, methylation of the differentially methylated regions (DMRs) that control their monoallelic expression remains largely unaltered. We conclude that deregulation of imprinting through a general effect on DMR methylation is unlikely to be a common factor in developmental programming.     

DNA methylation at differentially methylated regions of imprinted genes is resistant to developmental programming by maternal nutrition

The nutritional environment in which the mammalian fetus or infant develop is recognized as influencing the risk of chronic diseases, such as type 2 diabetes and hypertension, in a phenomenon that has become known as developmental programming. The late onset of such diseases in response to earlier transient experiences has led to the suggestion that developmental programming may have an epigenetic component, because epigenetic marks such as DNA methylation or histone tail modifications could provide a persistent memory of earlier nutritional states. One class of genes that has been considered a potential target or mediator of programming events is imprinted genes, because these genes critically depend upon epigenetic modifications for correct expression and because many imprinted genes have roles in controlling fetal growth as well as neonatal and adult metabolism. In this study, we have used an established model of developmental programming—isocaloric protein restriction to female mice during gestation or lactation—to examine whether there are effects on expression and DNA methylation of imprinted genes in the offspring. We find that although expression of some imprinted genes in liver of offspring is robustly and sustainably changed, methylation of the differentially methylated regions (DMRs) that control their monoallelic expression remains largely unaltered. We conclude that deregulation of imprinting through a general effect on DMR methylation is unlikely to be a common factor in developmental programming.     

Sequential changes in genome-wide DNA methylation status during adipocyte differentiation

DNA methylation is an epigenetic mark on the mammalian genome. There are numerous tissue-dependent and differentially methylated regions (T-DMRs) in the unique sequences distributed throughout the genome. To determine the epigenetic changes during adipocyte differentiation, we investigated the sequential changes in DNA methylation status of 3T3-L1 cells at the growing, confluent, postconfluent and mature adipocyte cell stages. Treatment of 3T3-L1 cells with 5-aza-2′-deoxycytidine inhibited differentiation in a stage-dependent manner, supporting the idea that formation of accurate DNA methylation profile, consisting of methylated and unmethylated T-DMRs, may be involved in differentiation. Analysis by methylation-sensitive quantitative real-time PCR of the 65 known T-DMRs which contain NotI sites detected 8 methylations that changed during differentiation, and the changes in the patterns of these methylations were diverse, confirming that the differentiation process involves epigenetic alteration at the T-DMRs. Intriguingly, the dynamics of the methylation change vary depending on the T-DMRs and differentiation stages. Restriction landmark genomic scanning detected 32 novel T-DMRs, demonstrating that differentiation of 3T3-L1 cells involves genome-wide epigenetic changes by temporal methylation/demethylation, in addition to maintenance of a static methylated/demethylated state, and both depend on differentiation stage.     

Exploring genome-wide DNA methylation profiles altered in hepatocellular carcinoma using Infinium HumanMethylation 450 BeadChips

Hepatocellular carcinoma (HCC) incidence has increased in the US and also has one of the fastest growing death rates of any cancer. The purpose of the current study was to discover novel genome-wide aberrant DNA methylation patterns in HCC tumors that are predominantly HCV-related. Infinium HumanMethylation 450K BeadChip arrays were used to examine genome-wide DNA methylation profiles in 66 pairs of HCC tumor and adjacent non-tumor tissues. After Bonferroni adjustment, a total of 130,512 CpG sites significantly differed in methylation level in tumor compared with non-tumor tissues, with 28,017 CpG sites hypermethylated and 102,495 hypomethylated in tumor tissues. Absolute tumor/non-tumor methylation differences ≥ 20% were found in 24.9% of the hypermethylated and 43.1% of the hypomethylated CpG sites; almost 10,000 CpG sites have ≥ 30% DNA methylation differences. Most (60.1%) significantly hypermethylated CpG sites are located in CpG islands, with 21.6% in CpG shores and 3.6% in shelves. In contrast, only a small proportion (8.2%) of significantly hypomethylated CpG sites are situated in islands, while most are found in open sea (60.2%), shore (17.3%) or shelf (14.3%) regions. A total of 2,568 significant CpG sites (2,441 hypermethylated and 127 hypomethylated) covering 589 genes are located within 684 differentially methylated regions defined as regions with at least two significant CpG sites displaying > 20% methylation differences in the same direction within 250-bp. The top 500 significant CpG sites can significantly distinguish HCC tumor from adjacent tissues with one misclassification. Within adjacent non-tumor tissues, we also identified 75 CpG sites significantly associated with gender, 228 with HCV infection, 17,207 with cirrhosis, and 56 with both HCV infection and cirrhosis after multiple comparisons adjustment. Aberrant DNA methylation profiles across the genome were identified in tumor tissues from US HCC cases that are predominantly related to HCV infection. These results demonstrate the significance of aberrant DNA methylation in HCC tumorigenesis.     

Hierarchical Clustering of Breast Cancer Methylomes Revealed Differentially Methylated and Expressed Breast Cancer Genes

Oncogenic transformation of normal cells often involves epigenetic alterations, including histone modification and DNA methylation. We conducted whole-genome bisulfite sequencing to determine the DNA methylomes of normal breast, fibroadenoma, invasive ductal carcinomas and MCF7. The emergence, disappearance, expansion and contraction of kilobase-sized hypomethylated regions (HMRs) and the hypomethylation of the megabase-sized partially methylated domains (PMDs) are the major forms of methylation changes observed in breast tumor samples. Hierarchical clustering of HMR revealed tumor-specific hypermethylated clusters and differential methylated enhancers specific to normal or breast cancer cell lines. Joint analysis of gene expression and DNA methylation data of normal breast and breast cancer cells identified differentially methylated and expressed genes associated with breast and/or ovarian cancers in cancer-specific HMR clusters. Furthermore, aberrant patterns of X-chromosome inactivation (XCI) was found in breast cancer cell lines as well as breast tumor samples in the TCGA BRCA (breast invasive carcinoma) dataset. They were characterized with differentially hypermethylated XIST promoter, reduced expression of XIST, and over-expression of hypomethylated X-linked genes. High expressions of these genes were significantly associated with lower survival rates in breast cancer patients. Comprehensive analysis of the normal and breast tumor methylomes suggests selective targeting of DNA methylation changes during breast cancer progression. The weak causal relationship between DNA methylation and gene expression observed in this study is evident of more complex role of DNA methylation in the regulation of gene expression in human epigenetics that deserves further investigation.     

Genome wide DNA methylation profiling for epigenetic alteration in coronary artery disease patients

Background

The alteration in the epigenome forms an interface between the genotype and the environment. Epigenetic alteration is expected to make a significant contribution to the development of cardiovascular disease where environmental interactions play a key role in disease progression. We had previously shown that global DNA hypermethylation per se is associated with coronary artery disease (CAD) and is further accentuated by high levels of homocysteine, a thiol amino acid which is an independent risk factor for cardiovascular disease and is also a key modulator of macromolecular methylation.

Results

We have identified 72 differentially methylated regions (DMRs) that were hypermethylated in CAD patients in the background of varying homocysteine levels. Following deep bisulfite sequencing of a few of the selected DMRs, we found significantly higher methylation in CAD cases. We get six CpG sites in three DMRs that included the intronic region of C1QL4 gene and upstream region of CCDC47 and TGFBR3 genes.

Conclusion

To the best of our knowledge, this is the first study to identify hypermethylated regions across the genome in patients with coronary artery disease. Further validation in different populations is necessary for this information to be used for disease risk assessment and management.     

Methylation profiling identified novel differentially methylated markers including OPCML and FLRT2 in prostate cancer

To develop new methods to distinguish indolent from aggressive prostate cancers (PCa), we utilized comprehensive high-throughput array-based relative methylation (CHARM) assay to identify differentially methylated regions (DMRs) throughout the genome, including both CpG island (CGI) and non-CGI regions in PCa patients based on Gleason grade. Initially, 26 samples, including 8 each of low [Gleason score (GS) 6] and high (GS ≥7) grade PCa samples and 10 matched normal prostate tissues, were analyzed as a discovery cohort. We identified 3,567 DMRs between normal and cancer tissues, and 913 DMRs distinguishing low from high-grade cancers. Most of these DMRs were located at CGI shores. The top 5 candidate DMRs from the low vs. high Gleason comparison, including OPCML, ELAVL2, EXT1, IRX5, and FLRT2, were validated by pyrosequencing using the discovery cohort. OPCML and FLRT2 were further validated in an independent cohort consisting of 20 low-Gleason and 33 high-Gleason tissues. We then compared patients with biochemical recurrence (n=70) vs. those without (n=86) in a third cohort, and they showed no difference in methylation at these DMR loci. When GS 3+4 cases and GS 4+3 cases were compared, OPCML-DMR methylation showed a trend of lower methylation in the recurrence group (n=30) than in the no-recurrence (n=52) group. We conclude that whole-genome methylation profiling with CHARM revealed distinct patterns of differential DNA methylation between normal prostate and PCa tissues, as well as between different risk groups of PCa as defined by Gleason scores. A panel of selected DMRs may serve as novel surrogate biomarkers for Gleason score in PCa.     

DNA methylation biomarkers for head and neck squamous cell carcinoma

DNA methylation plays an important role in the etiology and pathogenesis of head and neck squamous cell carcinoma (HNSCC). The current study aimed to identify aberrantly methylated-differentially expressed genes (DEGs) by a comprehensive bioinformatics analysis. In addition, we screened for DEGs affected by DNA methylation modification and further investigated their prognostic values for HNSCC. We included microarray data of DNA methylation (GSE25093 and GSE33202) and gene expression (GSE23036 and GSE58911) from Gene Expression Omnibus. Aberrantly methylated-DEGs were analyzed with R software. The Cancer Genome Atlas (TCGA) RNA sequencing and DNA methylation (Illumina HumanMethylation450) databases were utilized for validation. In total, 27 aberrantly methylated genes accompanied by altered expression were identified. After confirmation by The Cancer Genome Atlas (TCGA) database, 2 hypermethylated-low-expression genes (FAM135B and ZNF610) and 2 hypomethylated-high-expression genes (HOXA9 and DCC) were identified. A receiver operating characteristic (ROC) curve confirmed the diagnostic value of these four methylated genes for HNSCC. Multivariate Cox proportional hazards analysis showed that FAM135B methylation was a favorable independent prognostic biomarker for overall survival of HNSCC patients.