Research Article Genome-Wide Scan for Methylation Profiles ...downloads.hindawi.com/journals/dm/2015/943176.pdf · Research Article Genome-Wide Scan for Methylation Profiles in Keloids

Research ArticleGenome-Wide Scan for Methylation Profiles in Keloids

Lamont R Jones1 William Young2 George Divine3 Indrani Datta4 Kang Mei Chen1

David Ozog5 and Maria J Worsham1

1Department of Otolaryngology-Head and Neck Surgery Henry Ford Hospital Detroit MI 48202 USA2Proliance Eastside ENT Kirkland WA 98033 USA3Department of Public Health Sciences Henry Ford Health System Detroit MI 48202 USA4Center for Bioinformatics Henry Ford Health System Detroit MI 48202 USA5Department of Dermatology Henry Ford Hospital Detroit MI 48202 USA

Correspondence should be addressed to Lamont R Jones ljones5hfhsorg

Received 28 January 2015 Accepted 28 April 2015

Academic Editor Irene Rebelo

Copyright copy 2015 Lamont R Jones et alThis is an open access article distributed under theCreativeCommonsAttributionLicensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Keloids are benign fibroproliferative tumors of the skin which commonly occur after injury mainly in darker skinned patientsMedical treatment is fraught with high recurrence rates mainly because of an incomplete understanding of the biologicalmechanisms that lead to keloidsThe purpose of this project was to examine keloid pathogenesis from the epigenome perspective ofDNA methylation Genome-wide profiling used the Infinium HumanMethylation450 BeadChip to interrogate DNA from 6 freshkeloid and 6 normal skin samples from 12 anonymous donors A 3-tiered approach was used to call out genes most differentiallymethylated between keloid and normal When compared to normal of the 685 differentially methylated CpGs at Tier 3 510 werehypomethylated and 175 were hypermethylated with 190 CpGs in promoter and 495 in nonpromoter regions The 190 promoterregion CpGs corresponded to 152 genes 96 (63) were hypomethylated and 56 (37) hypermethylated This exploratory genome-wide scan of the keloid methylome highlights a predominance of hypomethylated genomic landscapes favoring nonpromoterregions DNA methylation as an additional mechanism for gene regulation in keloid pathogenesis holds potential for noveltreatments that reverse deleterious epigenetic changes As an alternative mechanism for regulating genes epigenetics may explainwhy gene mutations alone do not provide definitive mechanisms for keloid formation

1 Introduction

Keloids are benign fibroproliferative tumors that are uniqueto humans [1] The exact mechanism of keloid formation isunknown There is up to a 20 incidence in Blacks Asiansand Hispanics [2ndash7] Dysregulations of genes important inapoptosis extracellularmatrix formation and immunity havebeen described in the pathogenesis of keloids [8 9] Howeverno clear-cut genetic alterations or involvement have emergedfor keloids Clinical outcomes for the treatment of keloidsare disappointing Surgical excision of keloids has a 50ndash100recurrence [10] Furthermore the recurrence rate of surgicalexcision combined with adjuvant therapy such as steroidinjection silicone therapy pressure therapy radiotherapyand anticancer drugs remains high with up to 50 reportedin the literature [3] The failure of adjuvant therapies despitebeing based on current clinical histological or molecular

observations underscores the heterogeneity of keloid forma-tion and the need for insight into the molecular pathogenesisof keloids to account for its complexity

Keloid molecular studies have focused primarily ongenetic mechanisms These approaches have yielded sometangible results albeit with large gaps in our understandingof keloid pathogenesis [11] Epigenetics is the study of genealteration that occurs without altering the DNA sequenceFor example DNA hypermethylation is used to turn offgenes in normal human development such as imprinting andX chromosomal inactivation [12ndash14] Aberrant methylationthe addition of a methyl group (CH

3) at cytosine bases

of DNA (hypermethylation) or removal (hypomethylation)can lead to genomic instability and tumorigenesis [15]Hypermethylation in the cytosine-phosphodiester bond-guanine (CpG) islands of a genersquos promoter region can resultin gene inactivation whereas hypomethylation can cause

Hindawi Publishing CorporationDisease MarkersVolume 2015 Article ID 943176 7 pageshttpdxdoiorg1011552015943176

2 Disease Markers

gene activation [16ndash18] Recent evidence suggests that DNAmethylation changes may underlie numerous complex traitsanddiseases [19ndash21] As an alternativemechanism for regulat-ing genes epigenetics may explain why gene mutations alonedo not provide definitive mechanisms for keloid formation

Historically the molecular pathogenesis of disease hasbeen teased out one gene at a time The development ofseveral new high-throughput methods for the analysis ofDNA mRNA and proteins within a cell has permitteda more detailed molecular characterization of the cancergenome Given the tumor-like behavior of keloids it isplausible that similar techniques could be applied to thestudy of keloid pathogenesis Studies have shown downreg-ulation of apoptotic genes in keloid tissue including thosethat both promote and inhibit apoptosis [22] Furthermoreimmunohistochemistry data indicate upregulation of tumorsuppressor genes such as p53 and protooncogenes suchas bcl2 [16] However these methods have not adequatelyaddressed the complexity of the disease A combination ofgenomic epigenomic and environmental factors more likelyunderscores the pathogenesis of complex diseases such askeloids

The objective of this study was to gain insight intokeloid pathogenesis from the epigenome perspective of DNAmethylation This study used a global discovery strategyto characterize the keloid methylome and identify keloid-specific methylated markers to aid in the understanding ofthe disease

2 Materials and Methods

Discarded anonymous human keloid and normal skin tissuewas obtained from patients via a protocol approved by theinstitutional review board Six fresh keloid and 6 normal skinsamples from the head and neck area from 12 anonymousdonors were obtained for the study cohort Normal skinwas chosen as a control because keloids form from normalskin Genome-wide profiling was done using the InfiniumHumanMethylation450 BeadChip platform

21 Distribution and Classification of the 450000 CytosineSites in the Human Genome The Infinium HumanMethyla-tion450 BeadChip platform provides coverage of 99 of Ref-erence Sequence genes The Reference Sequence collectionaims to provide a comprehensive integrated nonredundantwell-annotated set of sequences including genomic DNAtranscripts and proteins [23] The 450K DNA methylationarray includes 485764 cytosine positions in the humangenome From these cytosine sites 482421 positions (993)are CpG dinucleotides while 3343 sites (07) correspond tonon-CpG targets The interrogated CpG sites are distributedamong all human 22 autosomal and 1 sex chromosome pairs[23] From the functional genome distribution standpoint200339 CpGs (41) are located in proximal promoters andbecame the focus of analyses for this study

22 Processing Samples for the Infinium HumanMethyla-tion450 The Infinium HumanMethylation450 assays were

performed at the Applied Genomics Technology CenterWayne State University Detroit MI DNA was extractedaccording to the manufacturerrsquos protocol (Qiagen IncChatsworth CA) Following DNA quality checks of orig-inal DNA quality quantification and bisulfite conversion4 120583L of bisulfite-converted DNA was used for hybridizationaccording to Illumina Infinium methylation protocols Datawere normalized using the Controls Normalization method(Illumina San Diego CA) The methylation score for eachCpG was represented as a beta (120573) value according to thefluorescent intensity ratio Every 120573-value in the InfiniumHumanMethylated450 BeadChip platform was accompaniedby a detection 119875 value 120573-values may take any value between0 (nonmethylated) and 1 (completely methylated) and weredetermined using the Genome Studio V20092 MethylationModule Version 155 Version 32 (Illumina San Diego CA)Probes were discarded if this detection119875 value wasmore than005 The only corrections that were made to the data werebackground subtraction and normalization

The resulting 120573-values were exported into MicrosoftExcel JMP and SAS (SAS Institute Cary NC) for dataanalysis All genome-wide comparisons were corrected formultiple comparisons using the method of Benjamini andHochberg [24]

23 Data Analysis To identify differentially methylatedkeloid-specific genes a three-tiered approach was devel-oped [25] Our goal for a 3-Tier system was to provide aframework to increase statistical rigor in the detection ofbiologically relevantmethylationmarkersThe latter achievestwo outcomes (1) exclusion of CpGs likely increases the riskof false discoveries and (2) serves as a strategy to reducethe number of genesCpGs for confirmation especially forstudy cohorts with DNA and RNA sources challenged byformalin-fixation or meager amounts of tissue availabilityfor molecular characterization [25] In Tier 1 we computedadjusted false discovery rate values for all CpGs and requiredthis to be 005 or lower In Tier 2 in order to heuristicallymove from Tier 1 we filtered the Tier 1 CpGs to includeonly those with a twofold change (ratio ge 20 or le 05)Tier 3 added another CpG filter to include only those withan absolute difference between the mean 120573 of ge02 A CpGwas classified as associated with a promoter region if theIllumina annotation for any of the associated gene isoformswas designated as translation start site (TSS) 200 TSS150051015840untranslated region (UTR) or 1st exon Nonpromoterregions included gene body 31015840UTR and others (intergenic)The addition of Tier 2 and 3 criteria was intended to downsizethe number of CpGsgenes whose differential methylationlikely represented themost robust of biologically significanceThis study focused on promoter region CpGs therefore onlyTier 3 CpGs were correlated for associated genes

3 Results

With respect to this sample set gt997 of the 485577Illumina probes had detection 119875 values under 005 Of the485577 cytosine positions when compared to normal Tier

Disease Markers 3

175(26)

510(74)

(a)

190(28)

495(72)

(b)

62(33)

128(67)

(c)

TSS200(29)

First exon(4)

TSS1500(26)

5998400UTR

(41)

(d)

56(37)

96(63)

(e)

Figure 1 (a) Methylation status of the 685 differentially methylated CpGs (cytosine-phosphodiester bond-guanine) at Tier 3 (26hypermethylated 74 hypomethylated) (b) 685-CpG distributions in promoter versus nonpromoter (28 promoter 72 nonpromoter) (c)Methylation status of 190 promoter CpGs (33 hypermethylated 67 hypomethylated) (d) 190-CpG distribution in promoter regions (4151015840UTR 29TSS200 26TSS1500 and 4 1st exon) (e)Methylation status of 152 genes associated with the 190 CpGs (37 hypermethylated63 hypomethylated)

1 yielded 29722 CpGs (24280 hyper- and 5442 hypomethy-lated) Tier 2 yielded 1534 differentially methylated CpGs(551 hyper- and 983 hypomethylated) and Tier 3 yielded 685differentially methylated CpGs Of the CpGs at Tier 3 175were hypermethylated and 510 were hypomethylated with190 CpGs (28) in promoter and 495 (72) in nonpromoterregions The predominant location of differentially methy-lated CpGs in nonpromoter regions as compared to promoterregions was also observed for CpGs at Tier 1 and Tier 2 levels(Figure 1 Table 1)

Of the 190 promoter region CpGs 128 were hypomethy-lated and 62 were hypermethylated with a functional distri-bution of 29 in TSS200 26 in TSS1500 41 in 51015840UTRand 4 in the first exonic region The 190 Tier 3 CpGsmapped to 197 CpGgene combinations which involve 152genes The 152 genes include 96 (63) hypomethylated and56 (37) hypermethylated (Figure 1 Table 1 and Supplemen-tary Table 1 in Supplementary Material available online athttpdxdoiorg1011552015943176)

4 Discussion

Keloids share many similarities with the process of tumorige-nesis Morphologically keloid pathogenesis is characterized

by overgrowth Hyperplasia is a key trait and almost always isa precursor in tumorigenesis along a malignancy continuumAnalogies can be drawn between keloids andmalignancies interms of their biological behavior such as rapid proliferationand aberrant genetic profiles for example the upregulationof tumor suppressor genes such as p53 and protooncogenessuch as bcl2 [22] Keloids thus can be described as being pseu-domalignant in nature Studies support methylated genesnot only as biomarkers of benign tumors such as sinonasal[26] and respiratory papillomas [27 28] but also along acontinuum from normal to benign to malignant [29 30] Wehypothesized that the analogy of an epigenetic milieu mightextend to keloids as well

Of the two types of aberrant methylation patterns presentin cancer cells [31 32] one is gene-specific hypermethylationwhere CpG islands in the promoter regions of genes acquireincreased methylation generally leading to reduced expres-sion of the gene The other is genome-wide hypomethyla-tion a large percentage of which occurs in repetitive DNAelements such aslong interspersed nuclear element (LINE)and short interspersed nuclear element (SINE called Aluin primates) in a variety of cancer cell lines and primarytumor samples [31 33] In malignancy aberrant gene-specificmethylation is often increased while global methylation is

4 Disease Markers

Table 1 Breakdown of 685 differentially methylated Tier 3 CpGs1

A methylation status of 685 CpGsHypermethylated 175 (26)Hypomethylated 510 (74)

B 685-CpG distribution in promoter versusnonpromoter

Promoter 190 (28)Nonpromoter 495 (72)

C methylation status of 190 promoter CpGsHypermethylated 62 (33)Hypomethylated 128 (67)

D 190-CpG distribution in promoterregions

TSS200 29TSS1500 2651015840UTR 41First exon 4

E methylation status of 152 genes associatedwith the 190 CpGs

Hypermethylated 56 (37)Hypomethylated 96 (63)

1CpG (cytosine-phosphodiester bond-guanine) TSS (transcription startsite) UTR (untranslated region)

often aberrantly reduced [31 32] While DNA methylation isgenerally associated with transcriptional silencing the effectsof reduced global methylation or genome-wide hypomethy-lation can lead to chromosomal instability and an increase inthe frequency of DNA strand breaks [34]

From a genome-wide perspective the emergence of amore hypomethylated keloid gene promoter landscape showssimilarity with nonmalignant as well as normal develop-mental processes such as successful placentation [35] Ahypomethylated keloid genomic landscape contrasts withmalignant tumor genomes such as in breast cancer [36]which shows more hypermethylated than hypomethylatedgenes Promoter DNA hypomethylation often results in geneactivation The progression of scars in normal skin afterinjury to a keloid pseudo tumor state may be explained bygene silencing from hypomethylation Our study suggeststhat benign tumors adopt hypomethylation as a mechanismfor gene activation rather than gene silencing to cross thresh-olds into more malignant states The latter was illustratedfor peptidase activity shown to be hypomethylated acrosscancers and required for the tumor cells to break throughthe extracellular matrix and basement membrane barriersto become invasive and thus its predicted upregulationvia hypomethylation to promote metastasis [37] Otherhypomethylated concepts such as epidermal and keratinocytedevelopment and differentiation have been linked to worsesurvival prognosis and increased local invasiveness [38] Theoverall global hypomethylation status of the differentiallymethylated keloid genes despite a small discovery sample setis a novel contrast with cancers such as breast and head andneck which are predominantly hypermethylated genomes

Another observation is the predominant location ofdifferentially methylated CpGs in nonpromoter regions suchas gene body 31015840UTR and intergenic as compared to promoterregions at all three tier levels DNAmethylation at intergenicsequences may play roles in regulating gene expressionandor chromosome compaction during cell division andmeiosis [39] Recent genome-wide approaches indicate thatDNA methylation can frequently occur in regions outsideof proximal promoters including intergenic sequences [4041] Evolutionarily conserved nonprotein coding regions thatwere also tissue differentially methylated regions were shownto have locations of up to 100 kb from the nearest anno-tated gene consistent with potential long-range regulatoryelements such as silencers or enhancers [42]

Of the differentially methylated genes in our exploratorymethylome scan more than a third were hypermethylatedSeveral human therapeutic intervention trials are underwayto reverse deleterious hypermethylated epigenetic changesExamples include epigenetic therapeutic trials to treat T-cell lymphoma based on reactivation of tumor suppressorgenes [43] and similar trials to prevent colorectal cancer byinhibiting the enzyme responsible for DNAmethylation [44]Such therapies have shown promise in halting tumor growthby reactivation of the tumor suppressor gene or by blockingprogression of precancerous epigenetic lesions

Epigenomic biomarkers are also becoming far morepractical than genomic biomarkers Our group has shownthat promoter hypermethylation is amenable to polymerasechain reaction- (PCR-) basedmethylation assays using wholegenomic DNA from freshfrozen tissue and cell lines as wellas formalin-fixed paraffin tissue DNA [26ndash28] Methylationof CpG islandsmay serve as a relatively simple ldquoyes-nordquo signalfor the presence of tumor and potentially the pathogenesisof keloid tissue when examined for under optimal assayconditions by sensitive PCR techniques [26ndash29] Addition-ally aberrant promoter hypermethylation always occurs invirtually the same location within an affected gene allowinga single PCR primer to be applicable to all patients forexamination of the methylation status of a specific gene[32] This sharply contrasts with genomic biomarkers suchas DNA mutations in genes such as p53 or mitochondrialgenes [29] which often involvemyriad different base changesat many locations within the gene even in cancers of thesame histologic types Classification based on promotermethylation profilingmaywell be amore promising approachthan expression profiling since these DNA-based techniquesare not subject to the problems of tissue preservation andthe potential pitfalls of tissue heterogeneity Aberrant DNAmethylation as a stable biomarker of keloid pathogenesisor a potential target could be easily detected by PCR-basedmethods Furthermore methylation profiles may representan early marker for the initiation development andorprogression of keloid pathogenesis

Of the differentially methylated genes in our exploratorymethylome scan more than a third were hypermethylatedThe potential reversibility of DNA methylation patternsmay serve as a target for therapy or as a marker foradjuvant therapy or as an adjunct to more conventionaltreatments such as surgical excision and steroid injections

Disease Markers 5

Several human therapeutic intervention trials are underwayto reverse deleterious hypermethylated epigenetic changesExamples include epigenetic therapeutic trials to treat T-cell lymphoma based on reactivation of tumor suppressorgenes [43] and similar trials to prevent colorectal cancer byinhibiting the enzyme responsible for DNAmethylation [44]Such therapies have shown promise in halting tumor growthby reactivation of the tumor suppressor gene or by blockingprogression of precancerous epigenetic lesions

As a corollary to hypermethylation the predominance ofhypomethylation in our keloid genome-wide scan suggestingactivated oncogene transcription rather than tumor suppres-sor silencing mechanisms in the promotion of tumorigenesisopens up opportunities for drug therapies already mature inoncogenic drug discovery pipelines This is illustrated for S-adenosylmethionine (SAM) which serves as a major methyldonor in biological transmethylation events In gastric cancercells and colon cancer cells with hypomethylated c-myc andh-ras promoters treatment with SAM resulted in increasedpromoter methylation and consequent downregulation ofmRNA and protein levels of c-myc and h-ras [45] The studyfound no influence on mRNA and protein levels of p16(INK4a) with and without SAM treatment supporting SAMas an effective inhibitor of tumor cell growth by reversingDNA hypomethylation

This study provides new information about the pathogen-esis of keloids highlighting a predominance of hypomethy-lated genomic landscapes favoring nonpromoter regionsUtilizing the Infinium HumanMethylation450 BeadChip kit(Illumina Inc San Diego CA) the differentially methylatedCpGs indicated 152 keloid-specific promoter region genesof which 63 (96) are hypomethylated as compared to 37(56) hypermethylated Despite a study limitation of a smallsample size the combination of the 450K array with a robustthree-tier data analysis approach identified a relatively largenumber of statistically significant differentially methylatedgenes A strength of this study is its strategy as a discoveryapproach starting from the most comprehensive currentlyavailable human methylome platform providing not onlynew information of previously unreported genes but alsosupporting studies of genes already reported in keloids aswell as some genes implicated in the pathogenesis of othertumors For example ITGB7 is a gene that was identifiedin this pilot study as differentially methylated in keloidscompared to normal skin ITGB7 is a member of the integrinfamily which has been found to be upregulated in keloidtissue and keloid fibroblast [46] Likewise microRNA genesMIR199A2 MIR609 and MIR938 were also differentiallymethylated in this pilot study These genes are part of afamily of short noncoding RNA genes involved in generegulation Downregulation of members of MIR7 gene hasbeen implicated in the overproduction of collagen in keloidsand local scleroderma [47] Furthermore altered expressionof MIR199A has been implicated in cervical carcinoma andsuggests a role in tumorigenesis [48]

Another limitation of the study is the anonymous natureof the sample collection This prevented stratification basedon demographics treatment or primary or recurrence statusand did not allow for patients to serve as their own control

Matched normal and keloid from the same individuals wouldhave likely allowed for less variation Robust statistical meth-ods employed in this study were aimed at minimizing thesevariations In the context of a pilot study this comprehensivescan of the keloid methylome was attempted as an initialproof of concept to generate a knowledge base for insightinto the biological complexity of keloids from a genome-wide promoter methylation perspective It should serve as animportant step in the further exploration of methylated land-scapes including gene promoter and nonpromoter regionsas relevant areas of focus in the pathogenesis and potentialtreatment of keloids Keloids are by far the worst scarsfollowing injury to the skinThe use of epigenetics to identifya role for methylation in keloids may allow for a betterunderstanding of keloid pathogenesis and could lead us closerto scarless surgery

5 Conclusion

Keloid genomes overall are more hypomethylated thanhypermethylated occurring more often in nonpromotergenomic regions Further unraveling of the regionallymethy-lated genomic landscape in keloids should provide a betterunderstanding of the contribution of the DNA methylometo keloid pathogenesis as an additional mechanism for generegulation supporting the contribution of both genetic andepigenetic changes in keloid pathogenesis with the potentialfor novel and more effective therapeutic strategies

Data Access

All normalized and raw data were submitted to GEO (GeneExpression Omnibus NCBI) according to the instructionsprovided (GEO accession numbers GSE56420) For GEOlinking and citing please refer to httpwwwncbinlmnihgovgeoinfolinkinghtml

Conflict of Interests

The authors state no conflict of interests

Acknowledgment

This study was supported by a Henry Ford Health SystemMentored Physician-Scientist Award to Dr Lamont Jones

References

[1] D E Morris L Wu L L Zhao et al ldquoAcute and chronic animalmodels for excessive dermal scarring quantitative studiesrdquoPlastic and Reconstructive Surgery vol 100 no 3 pp 674ndash6811997

[2] S B Russell K M Trupin S Rodrıguez-Eaton J D Russelland J S Trupin ldquoReduced growth-factor requirement of keloid-derived fibroblasts may account for tumor growthrdquo Proceedingsof the National Academy of Sciences of the United States ofAmerica vol 85 no 2 pp 587ndash591 1988

6 Disease Markers

[3] B S Atiyeh M Costagliola and S N Hayek ldquoKeloid orhypertrophic scar the controversy review of the literaturerdquoAnnals of Plastic Surgery vol 54 no 6 pp 676ndash680 2005

[4] C S Nirodi R Devalaraja L B Nanney et al ldquoChemokineand chemokine receptor expression in keloid and normalfibroblastsrdquo Wound Repair and Regeneration vol 8 no 5 pp371ndash382 2000

[5] A G Marneros J E C Norris B R Olsen and E Reichen-berger ldquoClinical genetics of familial keloidsrdquo Archives of Der-matology vol 137 no 11 pp 1429ndash1434 2001

[6] D Bloom ldquoHeredity of keloids review of the literature andreport of a family withmultiple keloids in five generationsrdquoNewYork state journal of medicine vol 56 no 4 pp 511ndash519 1956

[7] W G Young M J Worsham C L Joseph G W Divine andL R Jones ldquoIncidence of keloid and risk factors following headand neck surgeryrdquo JAMAFacial Plastic Surgery vol 16 no 5 pp379ndash380 2014

[8] B Shih and A Bayat ldquoGenetics of keloid scarringrdquo Archives ofDermatological Research vol 302 no 5 pp 319ndash339 2010

[9] P D ButlerM T Longaker andG P Yang ldquoCurrent progress inkeloid research and treatmentrdquo Journal of the American Collegeof Surgeons vol 206 no 4 pp 731ndash741 2008

[10] C J Chike-Obi P D Cole and A E Brissett ldquoKeloidspathogenesis clinical features and managementrdquo Seminars inPlastic Surgery vol 23 no 3 pp 178ndash184 2009

[11] S B Russell J D Russell K M Trupin et al ldquoEpigeneticallyalteredwound healing in keloid fibroblastsrdquo Journal of Investiga-tive Dermatology vol 130 no 10 pp 2489ndash2496 2010

[12] J F Costello and C Plass ldquoMethylation mattersrdquo Journal ofMedical Genetics vol 38 no 5 pp 285ndash303 2001

[13] E Li C Beard and R Jaenisch ldquoRole for DNA methylation ingenomic imprintingrdquo Nature vol 366 no 6453 pp 362ndash3651993

[14] E Li T H Bestor and R Jaenisch ldquoTargeted mutation of theDNA methyltransferase gene results in embryonic lethalityrdquoCell vol 69 no 6 pp 915ndash926 1992

[15] M Esteller ldquoCancer epigenomics DNA methylomes andhistone-modificationmapsrdquoNature Reviews Genetics vol 8 no4 pp 286ndash298 2007

[16] A P Feinberg and B Tycko ldquoThe history of cancer epigeneticsrdquoNature Reviews Cancer vol 4 no 2 pp 143ndash153 2004

[17] PW Laird ldquoOncogenic mechanisms mediated by DNAmethy-lationrdquo Molecular Medicine Today vol 3 no 5 pp 223ndash2291997

[18] P W Laird and R Jaenisch ldquoThe role of DNA methylation incancer genetics and epigeneticsrdquoAnnual Review of Genetics vol30 pp 441ndash464 1996

[19] M J Fackler C B Umbricht D Williams et al ldquoGenome-wide methylation analysis identifies genes specific to breastcancer hormone receptor status and risk of recurrencerdquo CancerResearch vol 71 no 19 pp 6195ndash6207 2011

[20] D J Martino M K Tulic L Gordon et al ldquoEvidence for age-related and individual-specific changes in DNA methylationprofile of mononuclear cells during early immune developmentin humansrdquo Epigenetics vol 6 no 9 pp 1085ndash1094 2011

[21] C G Bell A E Teschendorff V K Rakyan A P MaxwellS Beck and D A Savage ldquoGenome-wide DNA methylationanalysis for diabetic nephropathy in type 1 diabetes mellitusrdquoBMCMedical Genomics vol 3 article 33 2010

[22] D N Sayah C Soo W W Shaw et al ldquoDownregulation ofapoptosis-related genes in keloid tissuesrdquo Journal of SurgicalResearch vol 87 no 2 pp 209ndash216 1999

[23] J Sandoval H A Heyn S Moran et al ldquoValidation of a DNAmethylation microarray for 450000 CpG sites in the humangenomerdquo Epigenetics vol 6 no 6 pp 692ndash702 2011

[24] Y Benjamini and Y Hochberg ldquoControlling the false discoveryrate a practical and powerful approach to multiple testingrdquoJournal of the Royal Statistical Society Series B Methodologicalvol 57 no 1 pp 289ndash300 1995

[25] M J Worsham D Chitale K M Chen I Datta and G DivineldquoCell signaling events differentiate ER-negative subtypes fromER-positive breast cancerrdquo Medical Oncology vol 32 no 5 p565 2015

[26] J K Stephen L E Vaught K M Chen et al ldquoEpigenetic eventsunderlie the pathogenesis of sinonasal papillomasrdquo ModernPathology vol 20 no 10 pp 1019ndash1027 2007

[27] J K Stephen L E Vaught M C Kang et al ldquoAn epigeneticallyderived monoclonal origin for recurrent respiratory papillo-matosisrdquo Archives of OtolaryngologymdashHead and Neck Surgeryvol 133 no 7 pp 684ndash692 2007

[28] J K Stephen K M Chen V Shah et al ldquoConsistent DNAhypermethylation patterns in laryngeal papillomasrdquo Interna-tional Journal of Head and Neck Surgery vol 1 no 2 pp 69ndash772010

[29] M J Worsham J K Stephen K M Chen et al ldquoDelineating anepigenetic continuum in head and neck cancerrdquo Cancer Lettersvol 342 no 2 pp 178ndash184 2014

[30] M Pease C Ling W J Mack K Wang and G Zada ldquoThe roleof epigenetic modification in tumorigenesis and progression ofpituitary adenomas a systematic review of the literaturerdquo PLoSONE vol 8 no 12 Article ID e82619 2013

[31] P A Jones and S B Baylin ldquoThe epigenomics of cancerrdquo Cellvol 128 no 4 pp 683ndash692 2007

[32] P A Jones and S B Baylin ldquoThe fundamental role of epigeneticevents in cancerrdquoNature Reviews Genetics vol 3 no 6 pp 415ndash428 2002

[33] J Tost ldquoDNA methylation an introduction to the biologyand the disease-associated changes of a promising biomarkerrdquoMolecular Biotechnology vol 44 no 1 pp 71ndash81 2010

[34] C Schmutte and R Fishel ldquoGenomic instability first step tocarcinogenesisrdquo Anticancer Research vol 19 no 6 pp 4665ndash4696 1999

[35] M J Janatpour M F Utset J C Cross et al ldquoA repertoire ofdifferentially expressed transcription factors that offers insightinto mechanisms of human cytotrophoblast differentiationrdquoDevelopmental Genetics vol 25 no 2 pp 146ndash157 1999

[36] S Dedeurwaerder D Fumagalli and F Fuks ldquoUnravelling theepigenomic dimension of breast cancersrdquo Current Opinion inOncology vol 23 no 6 pp 559ndash565 2011

[37] D I Rodenhiser ldquoEpigenetic contributions to cancer metasta-sisrdquoClinical and ExperimentalMetastasis vol 26 no 1 pp 5ndash182009

[38] J P Volkmer D Sahooa and R K Chin ldquoThree differentiationstates risk-stratify bladder cancer into distinct subtypesrdquo Pro-ceedings of the National Academy of Sciences of the United Statesof America vol 109 pp 2078ndash2083 2012

[39] K M Niles D Chan S la Salle C C Oakes and J M TraslerldquoCritical period of nonpromoter DNA methylation acquisitionduring prenatal male germ cell developmentrdquo PLoS ONE vol 6no 9 Article ID e24156 2011

[40] H Wu V Coskun J Tao et al ldquoDnmt3a-dependent nonpro-moter DNA methylation facilitates transcription of neurogenicgenesrdquo Science vol 329 no 5990 pp 444ndash448 2010

Disease Markers 7

[41] R Lister M Pelizzola R H Dowen et al ldquoHuman DNAmethylomes at base resolution show widespread epigenomicdifferencesrdquo Nature vol 462 no 7271 pp 315ndash322 2009

[42] F Eckhardt J Lewin R Cortese et al ldquoDNA methylationprofiling of human chromosomes 6 20 and 22rdquoNature Geneticsvol 38 no 12 pp 1378ndash1385 2006

[43] K Garber ldquoBreaking the silence the rise of epigenetic therapyrdquoJournal of the National Cancer Institute vol 94 no 12 pp 874ndash875 2002

[44] L Kopelovich J A Crowell and J R Fay ldquoThe epigenome asa target for cancer chemopreventionrdquo Journal of the NationalCancer Institute vol 95 no 23 pp 1747ndash1757 2003

[45] J Luo Y-N Li F Wang W-M Zhang and X Geng ldquoS-adenosylmethionine inhibits the growth of cancer cells byreversing the hypomethylation status of c-myc and H-ras inhuman gastric cancer and colon cancerrdquo International Journalof Biological Sciences vol 6 no 7 pp 784ndash795 2010

[46] E Suarez F Syed T Alonso-Rasgado P Mandal and ABayat ldquoUp-regulation of tension-related proteins in keloidsknockdown of hsp27 12057221205731-integrin and pai-2 shows convinc-ing reduction of extracellular matrix productionrdquo Plastic andReconstructive Surgery vol 131 no 2 pp 158endash173e 2013

[47] M Etoh M Jinnin K Makino et al ldquoMicroRNA-7 down-regulation mediates excessive collagen expression in localizedsclerodermardquo Archives of Dermatological Research vol 305 no1 pp 9ndash15 2013

[48] J-W Lee C H Choi J-J Choi et al ldquoAltered MicroRNAexpression in cervical carcinomasrdquo Clinical Cancer Researchvol 14 no 9 pp 2535ndash2542 2008

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Volume 2014Hindawi Publishing Corporationhttpwwwhindawicom

2 Disease Markers

gene activation [16ndash18] Recent evidence suggests that DNAmethylation changes may underlie numerous complex traitsanddiseases [19ndash21] As an alternativemechanism for regulat-ing genes epigenetics may explain why gene mutations alonedo not provide definitive mechanisms for keloid formation

Historically the molecular pathogenesis of disease hasbeen teased out one gene at a time The development ofseveral new high-throughput methods for the analysis ofDNA mRNA and proteins within a cell has permitteda more detailed molecular characterization of the cancergenome Given the tumor-like behavior of keloids it isplausible that similar techniques could be applied to thestudy of keloid pathogenesis Studies have shown downreg-ulation of apoptotic genes in keloid tissue including thosethat both promote and inhibit apoptosis [22] Furthermoreimmunohistochemistry data indicate upregulation of tumorsuppressor genes such as p53 and protooncogenes suchas bcl2 [16] However these methods have not adequatelyaddressed the complexity of the disease A combination ofgenomic epigenomic and environmental factors more likelyunderscores the pathogenesis of complex diseases such askeloids

The objective of this study was to gain insight intokeloid pathogenesis from the epigenome perspective of DNAmethylation This study used a global discovery strategyto characterize the keloid methylome and identify keloid-specific methylated markers to aid in the understanding ofthe disease

2 Materials and Methods

Discarded anonymous human keloid and normal skin tissuewas obtained from patients via a protocol approved by theinstitutional review board Six fresh keloid and 6 normal skinsamples from the head and neck area from 12 anonymousdonors were obtained for the study cohort Normal skinwas chosen as a control because keloids form from normalskin Genome-wide profiling was done using the InfiniumHumanMethylation450 BeadChip platform

21 Distribution and Classification of the 450000 CytosineSites in the Human Genome The Infinium HumanMethyla-tion450 BeadChip platform provides coverage of 99 of Ref-erence Sequence genes The Reference Sequence collectionaims to provide a comprehensive integrated nonredundantwell-annotated set of sequences including genomic DNAtranscripts and proteins [23] The 450K DNA methylationarray includes 485764 cytosine positions in the humangenome From these cytosine sites 482421 positions (993)are CpG dinucleotides while 3343 sites (07) correspond tonon-CpG targets The interrogated CpG sites are distributedamong all human 22 autosomal and 1 sex chromosome pairs[23] From the functional genome distribution standpoint200339 CpGs (41) are located in proximal promoters andbecame the focus of analyses for this study

22 Processing Samples for the Infinium HumanMethyla-tion450 The Infinium HumanMethylation450 assays were

performed at the Applied Genomics Technology CenterWayne State University Detroit MI DNA was extractedaccording to the manufacturerrsquos protocol (Qiagen IncChatsworth CA) Following DNA quality checks of orig-inal DNA quality quantification and bisulfite conversion4 120583L of bisulfite-converted DNA was used for hybridizationaccording to Illumina Infinium methylation protocols Datawere normalized using the Controls Normalization method(Illumina San Diego CA) The methylation score for eachCpG was represented as a beta (120573) value according to thefluorescent intensity ratio Every 120573-value in the InfiniumHumanMethylated450 BeadChip platform was accompaniedby a detection 119875 value 120573-values may take any value between0 (nonmethylated) and 1 (completely methylated) and weredetermined using the Genome Studio V20092 MethylationModule Version 155 Version 32 (Illumina San Diego CA)Probes were discarded if this detection119875 value wasmore than005 The only corrections that were made to the data werebackground subtraction and normalization

The resulting 120573-values were exported into MicrosoftExcel JMP and SAS (SAS Institute Cary NC) for dataanalysis All genome-wide comparisons were corrected formultiple comparisons using the method of Benjamini andHochberg [24]

23 Data Analysis To identify differentially methylatedkeloid-specific genes a three-tiered approach was devel-oped [25] Our goal for a 3-Tier system was to provide aframework to increase statistical rigor in the detection ofbiologically relevantmethylationmarkersThe latter achievestwo outcomes (1) exclusion of CpGs likely increases the riskof false discoveries and (2) serves as a strategy to reducethe number of genesCpGs for confirmation especially forstudy cohorts with DNA and RNA sources challenged byformalin-fixation or meager amounts of tissue availabilityfor molecular characterization [25] In Tier 1 we computedadjusted false discovery rate values for all CpGs and requiredthis to be 005 or lower In Tier 2 in order to heuristicallymove from Tier 1 we filtered the Tier 1 CpGs to includeonly those with a twofold change (ratio ge 20 or le 05)Tier 3 added another CpG filter to include only those withan absolute difference between the mean 120573 of ge02 A CpGwas classified as associated with a promoter region if theIllumina annotation for any of the associated gene isoformswas designated as translation start site (TSS) 200 TSS150051015840untranslated region (UTR) or 1st exon Nonpromoterregions included gene body 31015840UTR and others (intergenic)The addition of Tier 2 and 3 criteria was intended to downsizethe number of CpGsgenes whose differential methylationlikely represented themost robust of biologically significanceThis study focused on promoter region CpGs therefore onlyTier 3 CpGs were correlated for associated genes

3 Results

With respect to this sample set gt997 of the 485577Illumina probes had detection 119875 values under 005 Of the485577 cytosine positions when compared to normal Tier

Disease Markers 3

175(26)

510(74)

(a)

190(28)

495(72)

(b)

62(33)

128(67)

(c)

TSS200(29)

First exon(4)

TSS1500(26)

5998400UTR

(41)

(d)

56(37)

96(63)

(e)




4 Discussion




4 Disease Markers

















Disease Markers 5






5 Conclusion


Data Access




Acknowledgment


References



6 Disease Markers







































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of






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OncologyJournal of





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Disease Markers 3

175(26)

510(74)

(a)

190(28)

495(72)

(b)

62(33)

128(67)

(c)

TSS200(29)

First exon(4)

TSS1500(26)

5998400UTR

(41)

(d)

56(37)

96(63)

(e)




4 Discussion




4 Disease Markers

















Disease Markers 5






5 Conclusion


Data Access




Acknowledgment


References



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of






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OncologyJournal of





PPAR Research



Journal of

ObesityJournal of
















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5 Conclusion


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References



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PPAR Research



Journal of

ObesityJournal of
















Disease Markers 5






5 Conclusion


Data Access




Acknowledgment


References



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OncologyJournal of





PPAR Research



Journal of

ObesityJournal of
















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Journal of

ObesityJournal of
















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OncologyJournal of





PPAR Research



Journal of

ObesityJournal of





















of






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OncologyJournal of





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Journal of

ObesityJournal of
















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Research Article Genome-Wide Scan for Methylation Profiles ...downloads.hindawi.com/journals/dm/2015/943176.pdf · Research Article Genome-Wide Scan for Methylation Profiles in Keloids