Comparative DNA methylation analysis in normal and tumour tissues and in cancer cell lines using differential methylation hybridisation

Immortalized human cancer cell lines are widely used as tools and model systems in cancer research but their authenticity with regard to primary tissues remains a matter of debate. We have used differential methylation hybridisation to obtain comparative methylation profiles from normal and tumour tissues of lung and colon, and permanent cancer cell lines originally derived from these tissues. Average methylation differences only larger than 25% between sample groups were considered for the profiles and with this criterion approximately 1000 probesets, around 2% of the sites represented on the array, indicated differential methylation between normal lung and primary lung cancer tissue, and approximately 700 probesets between normal colon and primary colon cancer tissue. Both hyper- and hypomethylation was found to differentiate normal tissue from cancer tissue. The profiles obtained from these tissue comparisons were found to correspond largely to those from the corresponding cancer cell lines, indicating that the cell lines represent the methylation pattern of the primary tissue rather well. Moreover, the cancer specific profiles were found to be very similar for the two tumour types studied. Tissue specific differential methylation between lung and colon tissues, in contrast, was found to be preserved to a larger extent only in the malignant tissue, but was not preserved well in the cancer cell lines studied. Overall, our data therefore provide further evidence that permanent cell lines are good model systems for cancer specific methylation patterns, but deviate with regard to tissue-specific methylation.     

DNA methylation in the promoter regions of the laminin family genes in normal and breast carcinoma tissues

Molecular Biology - Extracellular glycoproteins of the laminin family are essential components of basement membranes involved in a number of biological processes, including tissue differentiation,...     

Tissue specific DNA methylation of CpG islands in normal human adult somatic tissues distinguishes neural from non-neural tissues

Although most CpG islands are generally thought to remain unmethylated in all adult somatic tissues, recent genome-wide approaches have found that some CpG islands have distinct methylation patterns in various tissues, with most differences being seen between germ cells and somatic tissues. Few studies have addressed this among human somatic tissues and fewer still have studied the same sets of tissues from multiple individuals. In the current study, we used Restriction Landmark Genomic Scanning to study tissue specific methylation patterns in a set of twelve human tissues collected from multiple individuals. We identified 34 differentially methylated CpG islands among these tissues, many of which showed consistent patterns in multiple individuals. Of particular interest were striking differences in CpG island methylation, not only among brain regions, but also between white and grey matter of the same region. These findings were confirmed for selected loci by quantitative bisulfite sequencing. Cluster analysis of the RLGS data indicated that several tissues clustered together, but the strongest clustering was in brain. Tissues from different brain regions clustered together, and, as a group, brain tissues were distinct from either mesoderm or endoderm derived tissues which demonstrated limited clustering. These data demonstrate consistent tissue specific methylation for certain CpG islands, with clear differences between white and grey matter of the brain. Furthermore, there was an overall pattern of tissue specifically methylated CpG islands that distinguished neural tissues from non-neural.     

Robust prediction of gene regulation in colorectal cancer tissues from DNA methylation profiles

DNA methylation is recognized as one of several epigenetic regulators of gene expression and as potential driver of carcinogenesis through gene-silencing of tumor suppressors and activation of oncogenes. However, abnormal methylation, even of promoter regions, does not necessarily alter gene expression levels, especially if the gene is already silenced, leaving the exact mechanisms of methylation unanswered. Using a large cohort of matching DNA methylation and gene expression samples of colorectal cancer (CRC; n = 77) and normal adjacent mucosa tissues (n = 108), we investigated the regulatory role of methylation on gene expression. We show that on a subset of genes enriched in common cancer pathways, methylation is significantly associated with gene regulation through gene-specific mechanisms. We built two classification models to infer gene regulation in CRC from methylation differences of tumor and normal tissues, taking into account both gene-silencing and gene-activation effects through hyper- and hypo-methylation of CpGs. The classification models result in high prediction performances in both training and independent CRC testing cohorts (0.92<AUC<0.97) as well as in individual patient data (average AUC = 0.82), suggesting a robust interplay between methylation and gene regulation. Validation analysis in other cancerous tissues resulted in lower prediction performances (0.69<AUC<0.90); however, it identified genes that share robust dependencies across cancerous tissues. In conclusion, we present a robust classification approach that predicts the gene-specific regulation through DNA methylation in CRC tissues with possible transition to different cancer entities. Furthermore, we present HMGA1 as consistently associated with methylation across cancers, suggesting a potential candidate for DNA methylation targeting cancer therapy.     

Tissue specific DNA methylation of CpG islands in normal human adult somatic tissues distinguishes neural from non-neural tissues

Although most CpG islands are generally thought to remain unmethylated in all adult somatic tissues, recent genome-wide approaches have found that some CpG islands have distinct methylation patterns in various tissues, with most differences being seen between germ cells and somatic tissues. Few studies have addressed this among human somatic tissues and fewer still have studied the same sets of tissues from multiple individuals. In the current study, we used Restriction Landmark Genomic Scanning to study tissue specific methylation patterns in a set of 12 human tissues collected from multiple individuals. We identified 34 differentially methylated CpG islands among these tissues, many of which showed consistent patterns in multiple individuals. Of particular interest were striking differences in CpG island methylation, not only among brain regions, but also between white and grey matter of the same region. These findings were confirmed for selected loci by quantitative bisulfite sequencing. Cluster analysis of the RLGS data indicated that several tissues clustered together, but the strongest clustering was in brain. Tissues from different brain regions clustered together, and, as a group, brain tissues were distinct from either mesoderm or endoderm derived tissues which demonstrated limited clustering. These data demonstrate consistent tissue specific methylation for certain CpG islands, with clear differences between white and grey matter of the brain. Furthermore, there was an overall pattern of tissue specifically methylated CpG islands that distinguished neural tissues from non-neural.Key words: Tissue specific methylation, CpG island methylation, neural, brain tissue, grey matter, white matter     

A DNA microarray survey of gene expression in normal human tissues

Background  

Numerous studies have used DNA microarrays to survey gene expression in cancer and other disease states. Comparatively little is known about the genes expressed across the gamut of normal human tissues. Systematic studies of global gene-expression patterns, by linking variation in the expression of specific genes to phenotypic variation in the cells or tissues in which they are expressed, provide clues to the molecular organization of diverse cells and to the potential roles of the genes.     

Characterization of age signatures of DNA methylation in normal and cancer tissues from multiple studies

Background

DNA methylation (DNAm) levels can be used to predict the chronological age of tissues; however, the characteristics of DNAm age signatures in normal and cancer tissues are not well studied using multiple studies.

Results

We studied approximately 4000 normal and cancer samples with multiple tissue types from diverse studies, and using linear and nonlinear regression models identified reliable tissue type-invariant DNAm age signatures. A normal signature comprising 127 CpG loci was highly enriched on the X chromosome. Age-hypermethylated loci were enriched for guanine–and-cytosine-rich regions in CpG islands (CGIs), whereas age-hypomethylated loci were enriched for adenine–and-thymine-rich regions in non-CGIs. However, the cancer signature comprised only 26 age-hypomethylated loci, none on the X chromosome, and with no overlap with the normal signature. Genes related to the normal signature were enriched for aging-related gene ontology terms including metabolic processes, immune system processes, and cell proliferation. The related gene products of the normal signature had more than the average number of interacting partners in a protein interaction network and had a tendency not to interact directly with each other. The genomic sequences of the normal signature were well conserved and the age-associated DNAm levels could satisfactorily predict the chronological ages of tissues regardless of tissue type. Interestingly, the age-associated DNAm increases or decreases of the normal signature were aberrantly accelerated in cancer samples.

Conclusion

These tissue type-invariant DNAm age signatures in normal and cancer can be used to address important questions in developmental biology and cancer research.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-997) contains supplementary material, which is available to authorized users.     

Familial hypercholesterolaemia: mutations in the gene for the low-density-lipoprotein receptor

Familial hypercholesterolaemia is a co-dominant inherited disorder of lipoprotein metabolism, in which defects in the gene for the low-density-lipoprotein (LDL) receptor result in a twofold increase in the plasma concentration of cholesterol and moderate-to-severe premature coronary heart disease. Many mutations in the gene for the LDL receptor that have different effects on the structure and function of this multifunctional protein have been found, but it is not yet clear whether the nature of the mutation determines the severity of the disorder. This question is being answered by comparing patients with well-characterized mutations, and recent work suggests that other genetic or environmental factors may be important in modulating the effect of the defect in LDL-receptor function in patients who are heterozygous for the disorder.     

Associations between genetic variation in one-carbon metabolism and LINE-1 DNA methylation in histologically normal breast tissues

Genome-wide DNA hypomethylation is an early event in the carcinogenic process. Percent methylation of long interspersed nucleotide element-1 (LINE-1) is a biomarker of genome-wide methylation and is a potential biomarker for breast cancer. Understanding factors associated with percent LINE-1 DNA methylation in histologically normal tissues could provide insight into early stages of carcinogenesis. In a cross-sectional study of 121 healthy women with no prior history of cancer who underwent reduction mammoplasty, we examined associations between plasma and breast folate, genetic variation in one-carbon metabolism, and percent LINE-1 methylation using multivariable regression models (adjusting for race, oral contraceptive use, and alcohol use). Results are expressed as the ratio of LINE-1 methylation relative to that of the referent group, with the corresponding 95% confidence intervals (CI). We found no significant associations between plasma or breast folate and percent LINE-1 methylation. Variation in MTHFR, MTR, and MTRR were significantly associated with percent LINE-1 methylation. Variant allele carriers of MTHFR A1289C had 4% lower LINE-1 methylation (Ratio 0.96, 95% CI 0.93–0.98), while variant allele carriers of MTR A2756G (Ratio 1.03, 95% CI 1.01–1.06) and MTRR A66G (Ratio 1.03, 95% CI 1.01–1.06) had 3% higher LINE-1 methylation, compared to those carrying the more common genotypes of these SNPs. DNA methylation of LINE-1 elements in histologically normal breast tissues is influenced by polymorphisms in genes in the one-carbon metabolism pathway. Future studies are needed to investigate the sociodemographic, environmental and additional genetic determinants of DNA methylation in breast tissues and the impact on breast cancer susceptibility.     

The prediction of tumor and normal tissues based on the DNA methylation values of ten key sites

Abnormal DNA methylation can alter the gene expression to promote or inhibit tumorigenesis in colon adenocarcinoma (COAD). However, the finding important genes and key sites of abnormal DNA methylation which result in the occurrence of COAD is still an eventful task. Here, we studied the effects of DNA methylation in the 12 types of genomic features on the changes of gene expression in COAD, the 10 important COAD-related genes and the key abnormal DNA methylation sites were identified. The effects of important genes on the prognosis were verified by survival analysis. Moreover, it was shown that the important genes were participated in cancer pathways and were hub genes in a co-expression network. Based on the DNA methylation levels in the ten sites, the least diversity increment algorithm for predicting tumor tissues and normal tissues in seventeen cancer types are proposed. The better results are obtained in jackknife test. For example, the predictive accuracies are 94.17 %, 91.28 %, 89.04 % and 88.89 %, respectively, for COAD, rectum adenocarcinoma, pancreatic adenocarcinoma and cholangiocarcinoma. Finally, by computing enrichment score of infiltrating immunocytes and the activity of immune pathways, we found that the genes are highly correlated with immune microenvironment.     

DNA methylation profiling of the vascular tissues in the setting of atherosclerosis

Currently, the question of epigenetic mechanisms of gene regulation in the context of cardiovascular diseases is of considerable interest. Here, DNA methylation profiles of vascular tissues of atherosclerotic patients have been analyzed for the first time using the Infinium Human Methylation27 BeadChip microarray (Illumina, United States). As the result, within 286 genes, 314 CpG sites that varied significantly in the level of DNA methylation between the tissue samples of carotid (in the area of atherosclerotic plaques and nearby macroscopically intact tissues of the vascular wall) and mammary arteries, as well as saphenous veins have been identified. The most pronounced differences in the methylation level was registered for CpG sites of homeobox genes HOXA2 and HOXD4, as well as the imprinted MEST gene. In particular, these genes were found to be hypomethylated in the carotid atherosclerotic plaques compared to their methylation patterns in intact tissues of internal mammary arteries and saphenous veins.     

Integrated epigenome profiling of repressive histone modifications, DNA methylation and gene expression in normal and malignant urothelial cells

Epigenetic regulation of gene expression is commonly altered in human cancer. We have observed alterations of DNA methylation and microRNA expression that reflect the biology of bladder cancer. This common disease arises by distinct pathways with low and high-grade differentiation. We hypothesized that epigenetic gene regulation reflects an interaction between histone and DNA modifications, and differences between normal and malignant urothelial cells represent carcinogenic events within bladder cancer. To test this we profiled two repressive histone modifications (H3K9m3 and H3K27m3) using ChIP-Seq, cytosine methylation using MeDIP and mRNA expression in normal and malignant urothelial cell lines. In genes with low expression we identified H3K27m3 and DNA methylation each in 20-30% of genes and both marks in 5% of genes. H3K9m3 was detected in 5-10% of genes but was not associated with overall expression. DNA methylation was more closely related to gene expression in malignant than normal cells. H3K27m3 was the epigenetic mark most specifically correlated to gene silencing. Our data suggest that urothelial carcinogenesis is accompanied by a loss of control of both DNA methylation and H3k27 methylation. From our observations we identified a panel of genes with cancer specific-epigenetic mediated aberrant expression including those with reported carcinogenic functions and members potentially mediating a positive epigenetic feedback loop. Pathway enrichment analysis revealed genes marked by H3K9m3 were involved with cell homeostasis, those marked by H3K27m3 mediated pro-carcinogenic processes and those marked with cytosine methylation were mixed in function. In 150 normal and malignant urothelial samples, our gene panel correctly estimated expression in 65% of its members. Hierarchical clustering revealed that this gene panel stratified samples according to the presence and phenotype of bladder cancer.