dna methylation is one of the epigenetic mechanisms that can control gene expression without incurring any change to genomic sequence during development and cell proliferation ( 1 ) . many studies have shown that dna methylation plays an important role in cancer biology and provides promising biomarkers for cancer diagnosis and prognosis evaluation ( 2,3 ) . recent studies have shown that epigenetics plays an important role in cancer biology , viral infections , somatic gene therapy , transgenic technologies , developmental abnormalities and genomic imprinting ( 4,5 ) . in recent decades for example , tp53 ( 6 ) and rb1 ( 7 ) are hypermethylated in glioma , wnt5a is hypomethylated in prostate cancer ( 8) , smn2 is hypermethylated in spinal muscular atrophy and hspb1 methylation is a biomarker in prostate cancer as well as in human breast cancer , colorectal cancer and malignant melanoma ( 9 ) . furthermore , dna methylation may serve as a tumor marker or diagnosis and therapy index in colorectal cancer ( 10,11 ) and ovarian cancer ( 12 ) . a wide range of techniques is used to detect dna methylation , including mass spectrometry , methylation specific pcr , chip - on - chip assays , methylated dna immunoprecipitation , microarray assay , pyrosequencing of bisulfite treated dna , whole genome bisulfite sequencing , etc . these methods can be divided into two categories , gene - specific approaches and genome - wide approaches . studies in recent years have produced copious amounts of dna methylation data , especially epigenome - wide array data and next - generation sequencing ( ngs ) data . collection of dna methylation and mrna / microrna expression data related to diseases produced by high - throughput approaches based on array and ngs will facilitate the discovery of potential methylation events in human diseases ( 13 ) . methdb is a database that stores manually curated experimental data on dna methylation and environmental epigenetic effects ( 14 ) . pubmeth is an annotated and reviewed database of methylation in cancer based on text mining of the published literature ( 15 ) . methycancer ( 16 ) contains dna methylation , cancer - related gene and cancer information from public data sources and large - scale experimental data sets produced from the cancer epigenome project in china . ngsmethdb ( 17 ) provides dna methylation data for humans , chimpanzees , mice and arabidopsis thaliana from publicly available data sets using the ngs bisulfite sequencing technique . diseasemeth ( 18 ) provides both locus - specific and high - throughput data sets for many human diseases . ment ( 19 ) is the first database to provide both dna methylation and gene expression information for diverse tumor tissues . microrna , a small non - coding rna , functions in rna silencing and post - transcriptional regulation of gene expression , and is frequently associated with cancers and may be an important causal factor . aberrant dna methylation has been found to silence microrna genes in breast cancer , such as mir-31 , mir-130a , mir-155 , mir-137 and mir-34b / mir-34c genes ( 20 ) , indicating the important role of dna methylation in microrna deregulation in cancer . recently , various high - throughput approaches based on array and ngs have been developed and applied in combination with bisulfite conversion of the dna for genome - wide dna methylation analysis in mammals and plants ( 21 ) , and a large number of dna methylation data has been rapidly accumulated . however , there are fewer databases that provide both dna methylation and gene expression information . thus , there is a great need for an integrated database that provides both dna methylation and mrna / microrna expression information in normal and tumor tissues . this paper describes a dna methylation and gene expression database in human cancer , methhc ( database of dna methylation and gene expression in human cancer ) . methhc is a web - based resource focused on the aberrant methylomes of human diseases . methhc integrates data including dna methylation , gene expression , microrna methylation , microrna expression and the correlation between dna methylation and gene expression from tcga ( the cancer genome atlas ) . figure 1 shows the data generation flow of the methhc database , which comprises two parts : ( i ) integration of experimental data source and ( ii ) integration of annotated databases . the dna methylation data sets used in methhc are mainly taken from tcga which was launched in 2006 with an investment of us$50 million from the national cancer institute and the national human genome research institute . the goal of tcga is to improve the ability to diagnose , treat and prevent cancer . therefore , tcga collects and analyzes high - quality tumor samples such as clinical information about participants , metadata about the samples , histopathology slide images of the sample and molecular information derived from the samples ( e.g. copy number variation , dna methylation , single - nucleotide polymorphism , protein expression , dna sequencing and mrna / microrna expression etc . ) . a pilot project developed and tested the research framework to systematically explore the entire spectrum of genomic changes involved in more than 20 types of human cancer . the resulting data are freely available through the tcga data portal and the cancer genomics hub ( cghub ) . tcga collects three types of array - based dna methylation platform data : illumina dna methylation cancer panel i , illumina humanmethylation27 beadchip and illumina humanmethylation450k beadchip . to obtain human dna methylation and gene expressions first , dna methylation data are specific to the illumina humanmethylation450k beadchip platform , because of the more probes in humanmethylation450k beadchip . methhc provides not only dna methylation and gene expression data for protein - coding genes , but also mirnas . the information for gene transcription start sites ( tss ) and microrna tss was taken from the ucsc genome browser ( 22 ) and the mirstart database ( 23 ) . mirstart integrates data from many tss - relevant experiments , offering reliable human microrna tsss for the further decipherment of microrna transcription regulation . to study dna methylation patterns , different regions and cpg islands however , hypermethylation in the gene body may not block and might even stimulate transcription elongation and exciting new evidence suggests that gene body methylation may have an impact on splicing . cpg island ( cgi ) hypermethylation of the tss is associated with long - term silencing ( 24 ) . the differential methylation level at the cpg island shore is tissue - specific ( 25 ) . most dna methylation - cancer studies have focused on promoters , cpg islands and sometimes a bit further out ( e.g. cpg shores ) , but mostly overlap with putative enhancer regions , and they are enriched in consensus binding sequences for important renal transcription factors ( 26 ) . therefore , we provide several different gene regions ( promoter , tss , untranslated region , exon , gene body and enhancer region ) and cgi regions ( cpg island , shore and shelf ) . finally , to complete the gene information the kegg ( kyoto encyclopedia of genes and genomes ) project was initiated in 1995 ( 27 ) and the kegg pathway database is a collection of manually drawn kegg pathway maps representing experimental knowledge for metabolism , genetics information processing , cellular processes , organism systems and human diseases . methhc allows users to select a particular kegg pathway and identify differentially methylated genes in a set of tumors . methhc is a web - based resource focused on the aberrant methylomes of human diseases . methhc integrates dna methylation data , gene expression data and microrna expression data from tcga . methhc currently comprises 6548 dna methylation data generated by illumina humanmethylation450k beadchip and 12 567 mrna / microrna expression data generated by rna - seq/ mirna - seq in 18 human cancers . table 1 provides a detailed list of the cancer and sample numbers , and the data include a greater number of samples in the breast invasive carcinoma cohort , thyroid carcinoma and head and neck squamous cell carcinoma . methhc contains 20 500 genes and 1040 mirnas , and each gene includes eight gene regions and five cgi regions . table 2 compares methhc with other methylation databases including methdb , pubmeth , methycancer , ngsmethdb , diseasemeth and ment . methdb only stores dna methylation data and makes these data readily available to the public . pubmeth is based on text mining of medline / pubmed abstracts and combined with manual reading and annotation of preselected abstracts . methycancer provides large - scale methylation data , cancer - related genes , mutation , cancer information and methylation status in cpg islands and promoter regions from multiple public sources . ngsmethdb provides sequence - based methylation data of six species samples in cpg islands and promoter regions obtained by ngs . diseasemeth is a human methylation database that provides both locus - specific and high - throughput data sets in 72 human diseases . ment was developed by collecting over 6000 samples from gene expression omnibus ( geo ) and tcga , and provides regression and correlation analysis . methhc collects dna methylation and mrna / microrna expression profiles in 18 human normal and tumor tissues . rna - seq and small rna - seq are applied to calculate the abundance of mrna / microrna expressions . to help investigators reveal new potential epigenetic biomarkers for cancer , methhc provides additional functions and multiplicity information , including several different gene regions ( promoter , tss , untranslated region , exon , gene body and enhancer region ) , cgi regions ( cpg island , shore and shelf ) and estimate of the dna methylation level methods ( average , maximum and median ) . to facilitate access to data and further analyses for the identification of differentially methylated genes , methhc provides a variety of interfaces and graphical visualizations . users can utilize top 250 analysis to identify the 250 hypermethylated and hypomethylated genes , yielding genes which are respectively hypermethylated and hypomethylated in tumors . hierarchical clustering is probably the most widely used clustering method for the detection of co - regulated methylation genes and the identification of cancer subtypes . in the hierarchical clustering graph , genes and samples with similar dna methylation patterns are grouped together ( figure 2b ) . in addition , methhc can submit a group of interested genes / mirnas or the name of a kegg pathway to identify differentially methylated genes in a set of tumors . a detailed view of each gene is demonstrated in the correlation of dna methylation and gene expression . aberrant dna methylation of mir-31 , mir-130a , let-7a-3/let-7b and mir-155 gene promoters in breast cancer is linked to silencing of mirna expression ( 20 ) . mir-9 family and mir-34 family were also reported to be silenced by dna methylation in various cancer ( 28 ) . our system shows the differential methylation status of each transcript in selected tumors by boxplot ( figure 2c ) . the correlation between methylation levels and expression status was shown by scatter plot ( figure 2d ) . methhc is an integrated and useful database comprising dna methylation and mrna / microrna expression profiles in 18 human normal and tumor tissues . we use various textual and graphical interfaces to demonstrate the methylation patterns in normal and tumor tissues and to analyze the correlation between methylation and expression . methhc also provides more multiplicity information , such as several different gene regions , cgi regions and estimate of the dna methylation level methods , to facilitate further investigation of genomic methylation status . to help investigators reveal new potential epigenetic biomarkers for cancer diagnosis and prognosis , prospective works of the proposed database are listed as follows : ( i ) to support more data resources from the geo and the international cancer genome consortium , ( ii ) to integrate clinical  pathological indicators from tcga and ( iii ) to collect bisulfate sequencing data from recent tcga releases . ministry of science and technology of the republic of china [ nsc 1012311-b-009005-my3 and nsc 1022627-b-009001 ] . ust - ucsd international center of excellence in advanced bio - engineering sponsored by the taiwan ministry of science and technology i - rice program [ nsc 1022911-i-009101 ] ; veterans general hospitals and university system of taiwan ( vghust ) joint research program [ vghust103-g512 ] . funding for open access charge : ministry of science and technology of the republic of china , taiwan  [ nsc101 - 2311-b-009 - 005-my3 ] .
we present methhc ( http://methhc.mbc.nctu.edu.tw ) , a database comprising a systematic integration of a large collection of dna methylation data and mrna / microrna expression profiles in human cancer . 
 dna methylation is an important epigenetic regulator of gene transcription , and genes with high levels of dna methylation in their promoter regions are transcriptionally silent . increasing 
 numbers of dna methylation and mrna / microrna expression profiles are being published in different public repositories . 
 these data can help researchers to identify epigenetic patterns that are important for carcinogenesis . 
 methhc integrates data such as dna methylation , mrna expression , dna methylation of microrna gene and microrna expression to identify correlations between dna methylation and mrna / microrna expression from tcga ( the cancer genome atlas ) , which includes 18 human cancers in more than 6000 samples , 6548 microarrays and 12 567 rna sequencing data .