Genome-scale analysis of DNA methylation in colorectal cancer using Infinium HumanMethylation450 BeadChips

Illumina’s Infinium HumanMethylation450 BeadChip arrays were used to examine genome-wide DNA methylation profiles in 22 sample pairs from colorectal cancer (CRC) and adjacent tissues and 19 colon tissue samples from cancer-free donors. We show that the methylation profiles of tumors and healthy tissue samples can be clearly distinguished from one another and that the main source of methylation variability is associated with disease status. We used different statistical approaches to evaluate the methylation data. In general, at the CpG-site level, we found that common CRC-specific methylation patterns consist of at least 15,667 CpG sites that were significantly different from either adjacent healthy tissue or tissue from cancer-free subjects. Of these sites, 10,342 were hypermethylated in CRC, and 5,325 were hypomethylated. Hypermethylated sites were common in the maximum number of sample pairs and were mostly located in CpG islands, where they were significantly enriched for differentially methylated regions known to be cancer-specific. In contrast, hypomethylated sites were mostly located in CpG shores and were generally sample-specific. Despite the considerable variability in methylation data, we selected a panel of 14 highly robust candidates showing methylation marks in genes SND1, ADHFE1, OPLAH, TLX2, C1orf70, ZFP64, NR5A2, and COL4A. This set was successfully cross-validated using methylation data from 209 CRC samples and 38 healthy tissue samples from The Cancer Genome Atlas consortium (AUC = 0.981 [95% CI: 0.9677–0.9939], sensitivity = 100% and specificity = 82%). In summary, this study reports a large number of loci with novel differential methylation statuses, some of which may serve as candidate markers for diagnostic purposes.     

Validation of DNA methylation profiling in formalin-fixed paraffin-embedded samples using the Infinium HumanMethylation450 Microarray

A formalin-fixed paraffin-embedded (FFPE) sample usually yields highly degraded DNA, which limits the use of techniques requiring high-quality DNA, such as Infinium Methylation microarrays. To overcome this restriction, we have applied an FFPE restoration procedure consisting of DNA repair and ligation processes in a set of paired fresh-frozen (FF) and FFPE samples. We validated the FFPE results in comparison with matched FF samples, enabling us to use FFPE samples on the Infinium HumanMethylation450 Methylation array.     

Validation of DNA methylation profiling in formalin-fixed paraffin-embedded samples using the Infinium HumanMethylation450 Microarray

A formalin-fixed paraffin-embedded (FFPE) sample usually yields highly degraded DNA, which limits the use of techniques requiring high-quality DNA, such as Infinium Methylation microarrays. To overcome this restriction, we have applied an FFPE restoration procedure consisting of DNA repair and ligation processes in a set of paired fresh-frozen (FF) and FFPE samples. We validated the FFPE results in comparison with matched FF samples, enabling us to use FFPE samples on the Infinium HumanMethylation450 Methylation array.     

An evaluation of analysis pipelines for DNA methylation profiling using the Illumina HumanMethylation450 BeadChip platform

The proper identification of differentially methylated CpGs is central in most epigenetic studies. The Illumina HumanMethylation450 BeadChip is widely used to quantify DNA methylation; nevertheless, the design of an appropriate analysis pipeline faces severe challenges due to the convolution of biological and technical variability and the presence of a signal bias between Infinium I and II probe design types. Despite recent attempts to investigate how to analyze DNA methylation data with such an array design, it has not been possible to perform a comprehensive comparison between different bioinformatics pipelines due to the lack of appropriate data sets having both large sample size and sufficient number of technical replicates. Here we perform such a comparative analysis, targeting the problems of reducing the technical variability, eliminating the probe design bias and reducing the batch effect by exploiting two unpublished data sets, which included technical replicates and were profiled for DNA methylation either on peripheral blood, monocytes or muscle biopsies. We evaluated the performance of different analysis pipelines and demonstrated that: (1) it is critical to correct for the probe design type, since the amplitude of the measured methylation change depends on the underlying chemistry; (2) the effect of different normalization schemes is mixed, and the most effective method in our hands were quantile normalization and Beta Mixture Quantile dilation (BMIQ); (3) it is beneficial to correct for batch effects. In conclusion, our comparative analysis using a comprehensive data set suggests an efficient pipeline for proper identification of differentially methylated CpGs using the Illumina 450K arrays.     

Comparison of genome-scale DNA methylation profiles in hepatocellular carcinoma by viral status

Hepatocellular carcinoma (HCC) incidence has steadily increased in the US over the past 30 years. Our understanding of epigenetic regulation in HCC is still limited, especially the impact of hepatitis B virus (HBV) or hepatitis C virus (HCV) infection on aberrant DNA methylation. We performed genome-wide DNA methylation profiling in 33 fresh frozen tumor samples, including 10 HBV-HCC, 13 HCV-HCC, and 10 non-infected (NIV-HCC) using the Illumina HumanMethylation450 BeadChip. Gene expression profiling was also performed using the Illumina whole-genome DASL HT Assay. Biological influences and gene networks of the differentially-methylated (DM) CpG loci were predicted using the Ingenuity Pathway Analysis. Genome-wide methylation analysis identified 7, 26, and 98 DM loci between HBV-HCC vs. HCV-HCC, HBV-HCC vs. NIV-HCC, and HCV-HCC vs. NIV-HCC, respectively, at P < 5 × 10^?5 for each. Overall, the DM loci were highly enriched for enhancers (48%), promoters (37%), or CpG islands and surrounding regions (37%). Most DM loci were hypermethylated in HCV-HCC compared to HBV-HCC or NIV-HCC. The DM loci were associated with a variety of biological functions including Cell Morphology (HBV-HCC vs. NIV-HCC), Cell Death/ Survival (HBV-HCC vs. NIV-HCC), or Cellular Growth and Proliferation (HCV-HCC vs. NIV-HCC). A subset of the DM loci were correlated (either positively or negatively) with their gene expression or associated with alcohol consumption, BMI, cirrhosis, diabetes, and cigarette smoking. Our findings of differential methylation by viral infection lend insights into the potential effects of viral infection on the epigenetic regulation and further the development and progression of HCC.     

Comparison of DNA methylation measured by Illumina 450K and EPIC BeadChips in blood of newborns and 14-year-old children

Analysis of DNA methylation helps to understand the effects of environmental exposures as well as the role of epigenetics in human health. Illumina, Inc. recently replaced the HumanMethylation450 BeadChip (450K) with the EPIC BeadChip, which nearly doubles the measured CpG sites to >850,000. Although the new chip uses the same underlying technology, it is important to establish if data between the two platforms are comparable within cohorts and for meta-analyses. DNA methylation was assessed by 450K and EPIC using whole blood from newborn (n = 109) and 14-year-old (n = 86) participants of the Center for the Health Assessment of Mothers and Children of Salinas. The overall per-sample correlations were very high (r >0.99), although many individual CpG sites, especially those with low variance of methylation, had lower correlations (median r = 0.24). There was also a small subset of CpGs with large mean methylation β-value differences between platforms, in both the newborn and 14-year datasets. However, estimates of cell type proportion prediction by 450K and EPIC were highly correlated at both ages. Finally, differentially methylated positions between boys and girls replicated very well by both platforms in newborns and older children. These findings are encouraging for application of combined data from EPIC and 450K platforms for birth cohorts and other population studies. These data in children corroborate recent comparisons of the two BeadChips in adults and in cancer cell lines. However, researchers should be cautious when characterizing individual CpG sites and consider independent methods for validation of significant hits.     

Reducing the risk of false discovery enabling identification of biologically significant genome-wide methylation status using the HumanMethylation450 array

Background

The Illumina HumanMethylation450 BeadChip (HM450K) measures the DNA methylation of 485,512 CpGs in the human genome. The technology relies on hybridization of genomic fragments to probes on the chip. However, certain genomic factors may compromise the ability to measure methylation using the array such as single nucleotide polymorphisms (SNPs), small insertions and deletions (INDELs), repetitive DNA, and regions with reduced genomic complexity. Currently, there is no clear method or pipeline for determining which of the probes on the HM450K bead array should be retained for subsequent analysis in light of these issues.

Results

We comprehensively assessed the effects of SNPs, INDELs, repeats and bisulfite induced reduced genomic complexity by comparing HM450K bead array results with whole genome bisulfite sequencing. We determined which CpG probes provided accurate or noisy signals. From this, we derived a set of high-quality probes that provide unadulterated measurements of DNA methylation.

Conclusions

Our method significantly reduces the risk of false discoveries when using the HM450K bead array, while maximising the power of the array to detect methylation status genome-wide. Additionally, we demonstrate the utility of our method through extraction of biologically relevant epigenetic changes in prostate cancer.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-51) contains supplementary material, which is available to authorized users.     

The landscape of DNA methylation in hepatocellular carcinoma

Better understanding of the relationship between changes in the overall methylation status of hepatocellular carcinoma (HCC) and disease progression will help us find good strategies for the early detection and treatment of HCC patients. The purpose of the study was to study the relations between the methylation status changes in HCC patients and progression of the disease to enable early detection and treatment of HCC patients. First, the DNA methylation data of 50 HCC samples and the surrounding normal samples were extracted and the change pattern of methylation status in the DNA promoter region of HCC samples against that of normal samples was studied. Then, some DNA methylation genes that could accurately identify cancer and cancer-adjacent tissues were identified using the k-top scoring pair method. Also, a prognostic signature that could predict the survival of HCC patients was constructed based on the overall survival time and death information of the early HCC patients. Finally, the obtained prognostic signature was verified. In conclusion, this study described the changes in the methylation spectrum during the development of HCC and identified genes associated with HCC progression and prognosis, which may offer new opportunities for the diagnosis and treatment of HCC.     

Predicting overall survival of patients with hepatocellular carcinoma using a three‐category method based on DNA methylation and machine learning

Hepatocellular carcinoma (HCC) is closely associated with abnormal DNA methylation. In this study, we analyzed 450K methylation chip data from 377 HCC samples and 50 adjacent normal samples in the TCGA database. We screened 47,099 differentially methylated sites using Cox regression as well as SVM‐RFE and FW‐SVM algorithms, and constructed a model using three risk categories to predict the overall survival based on 134 methylation sites. The model showed a 10‐fold cross‐validation score of 0.95 and satisfactory predictive power, and correctly classified 26 of 33 samples in testing set obtained by stratified sampling from high, intermediate and low risk groups.     

Genome-wide aberrant DNA methylation of microRNA host genes in hepatocellular carcinoma

Mature microRNAs (miRNAs) are a class of small non-coding RNAs involved in posttranslational gene silencing. Previous studies found that downregulation of miRNAs is a common feature observed in solid tumors, including hepatocellular carcinoma (HCC). We employed a genome-wide approach to test the hypothesis that DNA methylation alterations in miRNA host genes may cause deregulated miRNA expression in HCC. We analyzed tumor and adjacent non-tumor tissues from 62 Taiwanese HCC cases using Infinium HumanMethylation27 DNA Analysis BeadChips that include 254 CpG sites covering 110 miRNAs from 64 host genes. Expression levels of three identified miRNAs (miR-10a, miR-10b and miR-196b) were measured in a subset of 37 HCC tumor and non-tumor tissues. After Bonferroni adjustment, a total of 54 CpG sites from 27 host genes significantly differed in DNA methylation levels between tumor and adjacent non-tumor tissues with 53 sites significantly hypermethylated in tumor tissues. Among the 54 significant CpG sites, 15 sites had more than 2-fold tumor/non-tumor changes, 17 sites had differences > 10%, and 10 sites had both features [including 8 significantly hypermethylated CpG sites in the host genes of miR-10a, miR-10b and miR-196b (HOXB4, HOXD4 and HOXA9, respectively)]. Significant downregulation of miR-10a was observed in tumor compared with non-tumor tissues (0.50 vs. 1.73, p = 0.031). The concordance for HOXB4 methylation alteration and dysregulation of miR-10a was 73.5%. No significant change was observed for miR-10b expression. Unexpectedly, miR-196b was significantly upregulated in tumor compared with non-tumor tissues (p = 0.0001). These data suggest that aberrant DNA methylation may lead to dysregulation of miR-10a in HCC tumor tissues.     

Genome-wide aberrant DNA methylation of microRNA host genes in hepatocellular carcinoma

Mature microRNAs (miRNAs) are a class of small non-coding RNAs involved in posttranslational gene silencing. Previous studies found that downregulation of miRNAs is a common feature observed in solid tumors, including hepatocellular carcinoma (HCC). We employed a genome-wide approach to test the hypothesis that DNA methylation alterations in miRNA host genes may cause deregulated miRNA expression in HCC. We analyzed tumor and adjacent non-tumor tissues from 62 Taiwanese HCC cases using Infinium HumanMethylation27 DNA Analysis BeadChips that include 254 CpG sites covering 110 miRNAs from 64 host genes. Expression levels of three identified miRNAs (miR-10a, miR-10b and miR-196b) were measured in a subset of 37 HCC tumor and non-tumor tissues. After Bonferroni adjustment, a total of 54 CpG sites from 27 host genes significantly differed in DNA methylation levels between tumor and adjacent non-tumor tissues with 53 sites significantly hypermethylated in tumor tissues. Among the 54 significant CpG sites, 15 sites had more than 2-fold tumor/non-tumor changes, 17 sites had differences > 10%, and 10 sites had both features [including 8 significantly hypermethylated CpG sites in the host genes of miR-10a, miR-10b and miR-196b (HOXB4, HOXD4 and HOXA9, respectively)]. Significant downregulation of miR-10a was observed in tumor compared with non-tumor tissues (0.50 vs. 1.73, p = 0.031). The concordance for HOXB4 methylation alteration and dysregulation of miR-10a was 73.5%. No significant change was observed for miR-10b expression. Unexpectedly, miR-196b was significantly upregulated in tumor compared with non-tumor tissues (p = 0.0001). These data suggest that aberrant DNA methylation may lead to dysregulation of miR-10a in HCC tumor tissues.     

A systematic study of normalization methods for Infinium 450K methylation data using whole-genome bisulfite sequencing data

DNA methylation plays an important role in disease etiology. The Illumina Infinium HumanMethylation450 (450K) BeadChip is a widely used platform in large-scale epidemiologic studies. This platform can efficiently and simultaneously measure methylation levels at ∼480,000 CpG sites in the human genome in multiple study samples. Due to the intrinsic chip design of 2 types of chemistry probes, data normalization or preprocessing is a critical step to consider before data analysis. To date, numerous methods and pipelines have been developed for this purpose, and some studies have been conducted to evaluate different methods. However, validation studies have often been limited to a small number of CpG sites to reduce the variability in technical replicates. In this study, we measured methylation on a set of samples using both whole-genome bisulfite sequencing (WGBS) and 450K chips. We used WGBS data as a gold standard of true methylation states in cells to compare the performances of 8 normalization methods for 450K data on a genome-wide scale. Analyses on our dataset indicate that the most effective methods are peak-based correction (PBC) and quantile normalization plus β-mixture quantile normalization (QN.BMIQ). To our knowledge, this is the first study to systematically compare existing normalization methods for Illumina 450K data using novel WGBS data. Our results provide a benchmark reference for the analysis of DNA methylation chip data, particularly in white blood cells.     

Improved reproducibility in genome-wide DNA methylation analysis for PAXgene-fixed samples compared with restored formalin-fixed and paraffin-embedded DNA

Formalin fixation has been the standard method for conservation of clinical specimens for decades. However, a major drawback is the high degradation of nucleic acids, which complicates its use in genome-wide analyses. Unbiased identification of biomarkers, however, requires genome-wide studies, precluding the use of the valuable archives of specimens with long-term follow-up data. Therefore, restoration protocols for DNA from formalin-fixed and paraffin-embedded (FFPE) samples have been developed, although they are cost-intensive and time-consuming. An alternative to FFPE and snap-freezing is the PAXgene Tissue System, developed for simultaneous preservation of morphology, proteins, and nucleic acids. In the current study, we compared the performance of DNA from either PAXgene or formalin-fixed tissues to snap-frozen material for genome-wide DNA methylation analysis using the Illumina 450K BeadChip. Quantitative DNA methylation analysis demonstrated that the methylation profile in PAXgene-fixed tissues showed, in comparison with restored FFPE samples, a higher concordance with the profile detected in frozen samples. We demonstrate, for the first time, that DNA from PAXgene conserved tissue performs better compared with restored FFPE DNA in genome-wide DNA methylation analysis. In addition, DNA from PAXgene tissue can be directly used on the array without prior restoration, rendering the analytical process significantly more time- and cost-effective.     

Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray

DNA methylation, an important type of epigenetic modification in humans, participates in crucial cellular processes, such as embryonic development, X-inactivation, genomic imprinting and chromosome stability. Several platforms have been developed to study genome-wide DNA methylation. Many investigators in the field have chosen the Illumina Infinium HumanMethylation microarray for its ability to reliably assess DNA methylation following sodium bisulfite conversion. Here, we analyzed methylation profiles of 489 adult males and 357 adult females generated by the Infinium HumanMethylation450 microarray. Among the autosomal CpG sites that displayed significant methylation differences between the two sexes, we observed a significant enrichment of cross-reactive probes co-hybridizing to the sex chromosomes with more than 94% sequence identity. This could lead investigators to mistakenly infer the existence of significant autosomal sex-associated methylation. Using sequence identity cutoffs derived from the sex methylation analysis, we concluded that 6% of the array probes can potentially generate spurious signals because of co-hybridization to alternate genomic sequences highly homologous to the intended targets. Additionally, we discovered probes targeting polymorphic CpGs that overlapped SNPs. The methylation levels detected by these probes are simply the reflection of underlying genetic polymorphisms but could be misinterpreted as true signals. The existence of probes that are cross-reactive or of target polymorphic CpGs in the Illumina HumanMethylation microarrays can confound data obtained from such microarrays. Therefore, investigators should exercise caution when significant biological associations are found using these array platforms. A list of all cross-reactive probes and polymorphic CpGs identified by us are annotated in this paper.     

A novel DNA methylation-based model that effectively predicts prognosis in hepatocellular carcinoma

Purpose: To build a novel predictive model for hepatocellular carcinoma (HCC) patients based on DNA methylation data.Methods: Four independent DNA methylation datasets for HCC were used to screen for common differentially methylated genes (CDMGs). Gene Ontology (GO) enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were used to explore the biological roles of CDMGs in HCC. Univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) Cox analysis were performed to identify survival-related CDMGs (SR-CDMGs) and to build a predictive model. The importance of this model was assessed using Cox regression analysis, propensity score-matched (PSM) analysis and stratification analysis. A validation group from the Cancer Genome Atlas (TCGA) was constructed to further validate the model.Results: Four SR-CDMGs were identified and used to build the predictive model. The risk score of this model was calculated as follows: risk score = (0.01489826 × methylation level of WDR69) + (0.15868618 × methylation level of HOXB4) + (0.16674959 × methylation level of CDKL2) + (0.16689301 × methylation level of HOXA10). Kaplan–Meier analysis demonstrated that patients in the low-risk group had a significantly longer overall survival (OS; log-rank P-value =0.00071). The Cox model multivariate analysis and PSM analysis identified the risk score as an independent prognostic factor (P<0.05). Stratified analysis results further confirmed this model performed well. By analyzing the validation group, the results of receiver operating characteristic (ROC) curve analysis and survival analysis further validated this model.Conclusion: Our DNA methylation-based prognosis predictive model is effective and reliable in predicting prognosis for patients with HCC.     

Report on the Infinium 450k Methylation Array Analysis Workshop

A new platform for DNA methylome analysis is Illumina's Infinium HumanMethylation450. This technology is an extension of the previous HumanMethylation27 BeadChip and allows the methylation status of 12 samples per chip and 4 to 8 chips (total of 48 to 96 samples) to be assessed simultaneously for more than 480,000 cytosines across the genome. The platform incorporates two different probe types using different assay designs (InfiniumI and InfiniumII). Although this has allowed the assessment of more CpG sites, it has also introduced technical variation between the two probe types, which has complicated the analysis process. Many groups are working on normalization methods and analysis pipelines while many others are struggling to make sense of their new data sets. This motivated the organization of a meeting held at University College London that focused solely on the analysis methods and problems related to this new platform. The meeting was attended by 125 computational and bench scientists from 11 countries. There were 10 speakers, a small poster session and a discussion session.     

Comparison of Methyl-capture Sequencing vs. Infinium 450K methylation array for methylome analysis in clinical samples

Interindividual variability in the epigenome has gained tremendous attention for its potential in pathophysiological investigation, disease diagnosis, and evaluation of clinical intervention. DNA methylation is the most studied epigenetic mark in epigenome-wide association studies (EWAS) as it can be detected from limited starting material. Infinium 450K methylation array is the most popular platform for high-throughput profiling of this mark in clinical samples, as it is cost-effective and requires small amounts of DNA. However, this method suffers from low genome coverage and errors introduced by probe cross-hybridization. Whole-genome bisulfite sequencing can overcome these limitations but elevates the costs tremendously. Methyl-Capture Sequencing (MC Seq) is an attractive intermediate solution to increase the methylome coverage in large sample sets. Here we first demonstrate that MC Seq can be employed using DNA amounts comparable to the amounts used for Infinium 450K. Second, to provide guidance when choosing between the 2 platforms for EWAS, we evaluate and compare MC Seq and Infinium 450K in terms of coverage, technical variation, and concordance of methylation calls in clinical samples. Last, since the focus in EWAS is to study interindividual variation, we demonstrate the utility of MC Seq in studying interindividual variation in subjects from different ethnicities.     

Novel imprinted single CpG sites found by global DNA methylation analysis in human parthenogenetic induced pluripotent stem cells

Genomic imprinting is the process of epigenetic modification whereby genes are expressed in a parent-of-origin dependent manner; it plays an important role in normal growth and development. Parthenogenetic embryos contain only the maternal genome. Parthenogenetic embryonic stem cells could be useful for studying imprinted genes. In humans, mature cystic ovarian teratomas originate from parthenogenetic activation of oocytes; they are composed of highly differentiated mature tissues containing all three germ layers. To establish human parthenogenetic induced pluripotent stem cell lines (PgHiPSCs), we generated parthenogenetic fibroblasts from ovarian teratoma tissues. We compared global DNA methylation status of PgHiPSCs with that of biparental human induced pluripotent stem cells by using Illumina Infinium HumanMethylation450 BeadChip array. This analysis identified novel single imprinted CpG sites. We further tested DNA methylation patterns of two of these sites using bisulfite sequencing and described novel candidate imprinted CpG sites. These results confirm that PgHiPSCs are a powerful tool for identifying imprinted genes and investigating their roles in human development and diseases.     

Epigenome-wide profiling identifies significant differences in DNA methylation between matched-pairs of T- and B-lymphocytes from healthy individuals

Multiple reports now describe changes to the DNA methylome in rheumatoid arthritis and in many cases have analyzed methylation in mixed cell populations from whole blood. However, these approaches may preclude the identification of cell type-specific methylation, which may subsequently bias identification of disease-specific changes. To address this possibility, we conducted genome-wide DNA methylation profiling using HumanMethylation450 BeadChips to identify differences within matched pairs of T-lymphocytes and B-lymphocytes isolated from the peripheral blood of 10 healthy females. Array data were processed and differential methylation identified using NIMBL software. Validation of array data was performed by bisulfite pyrosequencing. Genome-wide DNA methylation was initially determined by analysis of LINE-1 sequences and was higher in B-lymphocytes than matched T-lymphocytes (69.8% vs. 65.2%, P ≤ 0.01). Pairwise analysis identified 679 CpGs, representing 250 genes, which were differentially methylated between T-lymphocytes and B-lymphocytes. The majority of sites (76.6%) were hypermethylated in B-lymphocytes. Pyrosequencing of selected candidates confirmed the array data in all cases. Hierarchical clustering revealed perfect segregation of samples into two distinct clusters based on cell type. Differentially methylated genes showed enrichment for biological functions/pathways associated with leukocytes and T-lymphocytes. Our work for the first time shows that T-lymphocytes and B-lymphocytes possess intrinsic differences in DNA methylation within a restricted set of functionally related genes. These data provide a foundation for investigating DNA methylation in diseases in which these cell types play important and distinct roles.