Gene Network Rewiring to Study Melanoma Stage Progression and Elements Essential for Driving ...

30 Pages·2015·1.7 MB·English

RESEARCHARTICLE
Gene Network Rewiring to Study Melanoma
Stage Progression and Elements Essential for
Driving Melanoma
AbhinavKaushik1,YashumaBhatia1,ShakirAli2,DineshGupta1*
1 BioinformaticsLaboratory,StructuralandComputationalBiologyGroup,InternationalCentreforGenetic
EngineeringandBiotechnology,NewDelhi,110067,India,2 DepartmentofBiochemistry,Facultyof
Science,JamiaHamdard,NewDelhi,110062,India
*[email protected]
Abstract
Metastaticmelanomapatientshaveapoorprognosis,mainlyattributabletotheunderlying
heterogeneityinmelanomadrivergenesandalteredgeneexpressionprofiles.Thesechar-
acteristicsofmelanomaalsomakethedevelopmentofdrugsandidentificationofnovel
drugtargetsformetastaticmelanomaadauntingtask.Systemsbiologyoffersanalternative
OPENACCESS
approachtore-explorethegenesorgenesetsthatdisplaydysregulatedbehaviourwithout
Citation:KaushikA,BhatiaY,AliS,GuptaD(2015)
beingdifferentiallyexpressed.Inthisstudy,wehaveperformedsystemsbiologystudiesto
GeneNetworkRewiringtoStudyMelanomaStage
ProgressionandElementsEssentialforDriving enhanceourknowledgeabouttheconservedpropertyofdiseasegenesorgenesets
Melanoma.PLoSONE10(11):e0142443. amongmutuallyexclusivedatasetsrepresentingmelanomaprogression.Wemeta-ana-
doi:10.1371/journal.pone.0142443
lysed642microarraysamplestogeneratemelanomareconstructednetworksrepresenting
Editor:RogerChammas,UniversidadedeSão fourdifferentstagesofmelanomaprogressiontoextractgeneswithalteredmolecularcir-
Paulo,BRAZIL
cuitrywiringascomparedtoanormalcellularstate.Intriguingly,amajorityofthemelanoma
Received:July20,2015 network-rewiredgenesarenotdifferentiallyexpressedandthediseasegenesinvolvedin
Accepted:October21,2015 melanomaprogressionconsistentlymodulateitsactivitybyrewiringnetworkconnections.
Wefoundthattheshortlisteddiseasegenesinthestudyshowstrongandabnormalnetwork
Published:November11,2015
connectivity,whichenhanceswiththediseaseprogression.Moreover,thedeviatednetwork
Copyright:©2015Kaushiketal.Thisisanopen
propertiesofthediseasegenesetsallowranking/prioritizationofdifferentenriched,dysre-
accessarticledistributedunderthetermsofthe
CreativeCommonsAttributionLicense,whichpermits gulatedandconservedpathwaytermsinmetastaticmelanoma,inagreementwithprevious
unrestricteduse,distribution,andreproductioninany findings.Ouranalysisalsorevealspresenceofdistinctnetworkhubsindifferentstagesof
medium,providedtheoriginalauthorandsourceare
metastasizingtumorforthesamesetofpathwaysinthestatisticallyconservedgenesets.
credited.
Thestudyresultsarealsopresentedasafreelyavailabledatabaseathttp://bioinfo.icgeb.
DataAvailabilityStatement:ProcessedDataare
res.in/m3db/.Theweb-baseddatabaseresourceconsistsofresultsfromtheanalysispre-
availableathttp://dx.doi.org/10.6084/m9.figshare.
sentedhere,integratedwithcytoscapewebanduser-friendlytoolsforvisualization,retrieval
1577546.
andfurtheranalysis.
Funding:DGconceivedandreceivedagrantfrom
theDepartmentofBiotechnology(DBT)-Indiagrants
(Grantno.BT/BI/25/066/2012).AKreceivedresearch
fellowshipfromCouncilofScientificandIndustrial
Research(CSIR)-India.
CompetingInterests:Theauthorshavedeclared
thatnocompetinginterestsexist.
PLOSONE|DOI:10.1371/journal.pone.0142443 November11,2015 1/30
GeneNetworkRewiringtoStudyMelanomaStageProgression
Introduction
Advancemalignantmelanomarepresentsadeadlycancerstateduetoitshighdissemination
potentialandincreasingtherapyresistance[1].Ingeneral,melanomainitiateswithmarkeddis-
ruptionofcellularhomeostaticmechanismsleadingtoamalignanttransformationofskin
melanocytes(cutaneousnon-metastatic;CnM).Melanomainitiationisfollowedbyitsprolifer-
ationtodifferentlayersofskinviamultiplegrowthphases(cutaneousmetastasis;CM)and
finallytolymphnodes(LN),whichmetastasizetumourtodifferentorgans[2].
Aftertheadventofthe‘omics’era,despiteseveralattemptstoidentifygenesignaturesand
geneticchangesinmelanoma,inconsistenciesintheresultsstillexists[3–5].Thelikelyreason
fortheinconsistencyisthediversehistologicaltypesandmultivariatenatureofmelanoma,
makingconsensusviewaboutmelanomageneexpressionbehaviour,achallenge,whichalso
hindersdevelopmentofnovelanti-melanomatherapies.
Historically,high-throughput(HT)melanomastudieshavebeenmainlyconfinedtoidenti-
ficationandvalidationofmutatedgenesandmultitudeofDifferentiallyExpressed(DE)genes
forvariousclassifiedmelanomasormelanomasub-types.AlthoughtheinformationaboutDE
genesenhanceourunderstandingofdiseases,recentstudiesindicatethatalterationingene
activityisnotlimitedtoitsfoldchangeinexpressionaloneandtheinteractomesundergore-
wiringasaresultofcellularoradaptiveresponse[6].Systemsbiologyoffersarangeofalterna-
tivemethodsthatallowsidentificationofsuchdiseaselinkedgenescharacterisedbyabnormal
linkedbehaviour.Thenewsystemsbiologymethodsbasedongeneco-expressionvaluesallows
predictionofgeneessentialitybeyondmodulesandhubs;whichevenhelpsgeneratenovel
hypothesesfordiseasemechanisms[7].
Ithasbeenfoundthatinanormalcellularhomeostasis,thegenesdisplayarobustsetofcor-
relatedoscillations,hereinreferredasnetworkconnections,whicharedisruptedindiseases[7,
8].Thus,dysregulationlinkedwithdiseasestatescausedifferentialcorrelationofvariousgenes
duetotheiralteredgeneexpressionpatternleadingtoreformationofnetworkwiringcircuitry
[9].Itisexpectedthatthegenesthatamplifyitsconnectivityorexpressionindiseaseascom-
paredtothatincontrolstagesaremorelikelytobeinvolvedindiseaseprogression.Insuch
stressconditions,severalgenesloseconnectionsintheperturbednetworkwhilesomemay
evengainalternatesetsofconnections[10].Fig1illustratesthedifferentialconnectivityinnet-
work-1ascomparedtonetwork-2,whichshowsthatsomeconnectionsarelostwhilenewcon-
nections(evennewnodes)maybeestablishedinthealterednetwork-2.Additional
experimentalevidenceforthisconceptisareportbyHudsonetal.[11],whoconducteddiffer-
entialwiringanalysisofexpressiondatatocorrectlypredictmyostatinasthegenecontaining
thecausalmutation,characterisedbydifferentialwiringratherthandifferentialexpression.
Anglanietal.describedthelossofgeneconnectionsasameasureofitsmoleculardysfunction
infivedifferentcancers,whichoccurswhengenesloseitsroleasaneffector[12].Thestudy
highlightedthatoncogenicalterationsincodingregionsandpost-translationalmodifications
canmodifygeneconnectionsandhencefunctions,withoutanychangesinexpressionlevels.In
anotherstudy,Kimetal.correlatedthegeneessentialitywithrewiringinyeastandmouse
interactomeandsuggestedthatcircuitryrewiringallowgenestointegrateintoalternativepath-
ways[13].Asimilarstudyutilizesthenumberofconnectionsgainedandlostbyagenetomea-
sureitsoverallrewiringscore[8].Theanalysisrevealedthatthediseasegenestendtorewireits
networkcircuitandhencegene-rewiringscoresaresuitableforgeneprioritization.Moreover,
previouslyitwasfoundthatERK-MAPKactivityinmelanomaleadstopathwayrewiring
whichresultsinitsconnectionofERKtoJNKpathways-thisobservationleadtoidentification
ofadditionalmelanomatherapeutictargets[14].Thus,theavailableliteraturesuggeststhatnot
onlygenesbuttheassociatedpathwaystoogetdysregulatedafterconnectionrewiring,
PLOSONE|DOI:10.1371/journal.pone.0142443 November11,2015 2/30
GeneNetworkRewiringtoStudyMelanomaStageProgression
Fig1.Geneconnectionsinbiologicalnetworksaredynamicandmayshowalteredco-expression
undervariableconditions,evenifgenesshowsnosignificantdifferentialco-expression.Gene
connectionsaremarkedaslines,newgenesmarkedashollowcircles(markedwitharrows)anddottedlines
representnewconnections.
doi:10.1371/journal.pone.0142443.g001
understandingofwhichisacriticalstepindesigningnovelandmoreeffectivetherapeutics
[15].Anadditionaladvantageofexploitingthenetworkbasedsystembiologyapproachforthe
predictionofgenesinvolvedindiseaseisthatthesensitivityofreconstructednetworkincreases
withheterogeneityinexpressiondataset,whichisacommonfeatureofmelanomasamples[5,
16].
Thereisnoreportofanystudy,whichattemptstoidentifyandmeasurethenetworkdepen-
dentdynamicityandreproducibilityofsuchpotentialandnoveldiseasegenesorgenesets(i.e.
pathways)involvedinmelanomaprogression,basedontheanalysisofheterogeneousmela-
nomadatasets.Inthisstudyweexploitedthepubliclyavailablecross-platformmelanomatran-
scriptomicdata(samplesize>600,groupedintofourdifferentstagespersemelanoma
progression),todecipherdifferentiallywiredgenesineachstage.
Inthisstudywehaveidentifiedgenesetsthatarerewiredandconnectedsimilarlyinmutu-
allyexclusivedatasets.Moreover,wehaveinvestigatedthedifferentialnetworkpropertiesof
functionalclustersdevelopedfromtheshortlisteddiseasegenes.Thedeviatednetworkprofile
analysisassistedinidentificationofimportantstagespecificpathwaytermsinvolvedinstage
transition.Wedemonstratethatthereisasuddenincreaseinquantitativecomplexityofthe
predictedpathwayswithtumourprogressionespeciallyaftertheonsetofmetastasis.Suchpri-
oritized/rankedgeneclusterswerefoundtopossessstrongdiseaseassociationonthebasisof
diseaselinkageanalysis.Wealsoattemptedtounderstandthedynamicityandflowofranked
pathwaytermsenrichedduringmelanomaprogression.Thecompleteresultsarepresentedas
aSQLdatabaseusingDHTMLandcytoscape-web[17]foruserfriendlyvisualization,retrieval
andfurtheranalysis.Thedatabaseresourceisfreelyavailableathttp://bioinfo.icgeb.res.in/
m3db/.
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GeneNetworkRewiringtoStudyMelanomaStageProgression
Table1. Datasetdescription.
Melanomastage Datasetsize Series Platforms†
Normal 97 13 07[a,b,c,d,e,f,g]
Cutaneousnon-Metastatic 183 09 05[d,e,f,h,g]
CutaneousMetastatic 246 10 05[d,e,f,h,g]
LymphNodeMetastatic 116 07 05[a,c,d,e,h,i]
†Microarrayplatformsusedbysubmitter.
a:GPL10558
b:GPL4133
c:GPL5175
d:GPL570
e:GPL571
f:GPL6883
g:GPL96
h:GPL1708
i:GPL6884
doi:10.1371/journal.pone.0142443.t001
Results
Melanomageneexpressiondatacollectedfrompubliclyavailabledatarepositorieswasmanu-
allystratifiedintofourdifferentstages,intheorderofmelanomaprogressioninvolvingnormal
skinmelanocytes(N)andthethreetransitionevents{N!CnM!CM!LN}.Table1shows
thenumberofcross-platformgeneexpressiondatasetsizesandseries,representingeachstage
anddifferentsources(fordetailsofeachofthestudydataset,seeS1File).Weperformedesti-
mationandremovalofbatcheffectresultingfromdifferentexperimentalconditions,priorto
thedataanalysis.TheresultsaresummarizedinS1Fig,whichsuggeststhatalargeproportion
ofgeneswereaffectedwithbatcheffect,removedbyComBatbatchadjustment(seematerials
andmethods).
Meta-analysisrevealedanovelDEmelanomagenesignature
Weinitiatedtheanalysisbycheckingthedatasetqualityandvalidationbypredictionofknown
melanomamarkersamongststatisticallysignificantDEgenes(logFC>1andadj.p<0.05)
betweencontrol(N)anddifferentstagesofmelanoma(CnM,CMandLN).Comparativeanal-
ysishighlightsseveralstagespecificchanges(Fig2).Weidentified324,622and1398DEgenes
inCnM,CMandLN,respectively.Weobservedthatdespitethelowfoldchangethreshold,
only55genesareexpressedacrossallthestagesofmelanomaandindicatethatthegenesare
essentiallyrequiredformelanomaprogression.
Welookedformelanomabiomarkersandknowncancerrelatedgenesintheconserved
geneset(n=55)andfoundseveraluniquesetsofgenespreviouslyreportedtobemelanomaor
cancerlinked.Thegenesetisenrichedwithseveralmelanoma-associatedgenesincluding
MAGEA1,MAGEA12,IL8,FOXD1,IL1B,POSTN,PRAME,MMP9,SERPINEandCTGF.
Genesconservedbetweenmetastaticstages(n=67)tooholdsseveralkeyregulatorsofmela-
nomalikeVEGFA,GDF15,SPP1,UPP1,SPRY4,FGF2,CENPN,SERPINA3,BUB1.Thecom-
pletelistofbothgenesetsalongwithitsdescriptionisgivenintheS2File.Despite
heterogeneityintheconditionsusedtogeneratethedatasets,themeta-analysisshowsthat
thesefewbiomarkersandknowncancerlinkedgenesshowconsistentupregulation,whichnot
onlystatisticallyrevalidatestheirsignificanceandessentialsimilaritiesinthedatasetbutalso
revealsnovelmelanomaassociatedgenes.
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GeneNetworkRewiringtoStudyMelanomaStageProgression
Fig2.A.Scatterplotoflog2ratio(foldchange;FC)versusadjustedp-valuetomeasuretheassociatedsignificantdifferentialexpressionofeach
gene.Geneswhicharesignificantlydifferentiallyexpressed(DE;log(FC)>1or<1;adj.pvalue<0.05)areshownindarkbluecolorB.Significantly
DEgenecount(up-anddown-regulated)ineachstage.C.Numberofup-regulatedgenesconservedacrossdifferentmelanomastages.
doi:10.1371/journal.pone.0142443.g002
Tofurthervalidatethereliabilityofthestudydatasetsandanalysisresults,wecomparedthe
foldchangeanalysisofDEgenesacrossdifferentstages(Fig2A).Theaveragefoldchanges
observedforCnM,CMandLNare~0.4,~0.5and~0.7,respectively.Thetotalnumberofup-
regulatedgenesinLNisalsomuchhigherthananyoftheotherstages,asevidentfromthe
majordriftinfoldchangevolcanoplot,whereas,CnMcontainstheleastnumberofDEgenes.
Foldchangeanalysissuggestsasignificantdown-regulationofgeneexpressionincutaneous
melanomastages,especiallyduringdiseasemetastasis(S2Fig).CloserinvestigationoftheDE
genelistforeachstagerevealedseveralmelanomabiomarkersandassociatedgenes.Forexam-
ple,theMAGEfamilygenes(fewofwhichareconsideredasmelanomabiomarkers)andIL8(a
well-knowncancerrelatedgene)areamongthetop-rankedgenesenrichedinoursignificantly
up-regulatedgenelist[18–21].Table2highlightsthetop20DEup-regulatedgenesindecreas-
ingorderoffoldchangeineachstage.Itisnotasurprisethataknownmelanomabiomarker
genePRAME[22]isconsistentlyfoundtobetopmostup-regulatedgeneinallthemelanoma
stages.AmongtheMAGEfamilygenes,MAGEA12isconsistentlyhighlyup-regulatedinall
themelanomastages,whereasMAGEA1isup-regulatedonlyinthemetastaticmelanoma
stages.CnMisalsocharacterisedbytheexpressionofseveralkeratinfamilygenesinvolvedin
buildingstructuralframeworkofepithelialcellsalongwithS100familygenes,involvedin
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GeneNetworkRewiringtoStudyMelanomaStageProgression
Table2. DifferentiallyExpressedGenes(inthedecreasingorderoffoldchange).
CnM CM LN
PRAME PRAME PRAME
S100A7 SPP1 SPP1
S100A8 IL8 IL8
S100A9 MAGEA12 MAGEA12
SPRR1B FOXD1 POSTN
KRT14 POSTN IGFBP3
KRT16 IGFBP3 TNC
KRT6B MAGEA1 GJC1
POSTN FAM198B CTGF
FAM198B SULF1 LILRB1
SERPINB3 IL13RA2 HLA-DRA
CXCL10 CTGF IL13RA2
SERPINB4 GDF15 FAM198B
FOXD1 HAS2 SERPINA3
LPPR4 CDH2 EIF2S3
CXCL9 PLAT ID3
CSTA SNX10 CD74
IL8 CCL20 MAGEA1
KRT5 SDC3 SULF1
MAGEA12 IL1B CCL5
doi:10.1371/journal.pone.0142443.t002
calciumbindingandcellularimmuneresponses.Apartfromthegenesmentionedabove,sev-
eralothergenesthatareknowntobeexpressedinmelanomaarealsorepresentedinthetop-20
genelist,whichincludesGDF-15,CDH2,CTGF,SERPINA3andPOSTN.Interestingly,POSTN
(Periostin)isreportedtoplayaroleinacceleratingmelanomametastasisviatheintegrin/mito-
gen-activatedproteinkinase(MAPK)signallingpathway[23].
WealsoinvestigatedthelikelyglobalchangesduetoDEgenes,byperforminggeneontology
(GO)enrichmentanalysis(usingathresholdp<0.01).Afterthefirsttransition,themost
over-representedGOtermcorrespondstoskindevelopmentandimmuneresponse(S3Fig).
However,asmelanomaprogresses,therepresentationofGOtermsassociatedwithbloodvessel
developmentandadhesionincreases,whereastherepresentationofskindevelopmentrelated
GOtermsdecreases.InLN,themostover-representedGOtermsforup-regulatedgenesare
immuneresponserelatedprocessesandcellcycle.
Inanutshell,theDEanalysisshowsexpectedoutcomesandfromthelargesetofDEgenes
onlyasmallnumberofgenesareconserved,howevertheconservedgenesetcontainsseveral
knownmelanomaandcancerassociatedgeneswhichvalidatestheauthenticityofourdatapro-
cessingprocedureandqualityoftheprocesseddata.
Co-expressionnetworks
Forfurtheranalysisandpredictionofnoveldysregulatedgenes,fourgeneinteractionmaps
wereconstructedusinggenepair-wisePearsonCorrelationCoefficient(PCC;seematerialsand
methods).ThereasonforchoosingPCCisthatitisthemostwidelyusedmethodtoidentify
thelinearrelationshipbetweentworandomvariablesandcapturedsignificantrelationships
evenwhenthegeneshavenon-normaldistribution[24].Weidentifiedthecorrelationcoeffi-
cient(r)distributionandalsoestimatedthep-valueandFalseDiscoveryRate(FDR)associated
witheachcorrelationcoefficientwhichissummarizedinS4Fig.Moreover,theanalysisoffree
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GeneNetworkRewiringtoStudyMelanomaStageProgression
Table3. Fundamentalnetworkproperties.
Normal CnM CM LN
Samplesize 97 183 246 116
Edges 4,269,800 368,136 1,605,642 1,835,739
Unconnectednodes 488 2406 2546 1228
Clusteringcoefficient 0.57 0.39 0.53 0.53
Density 0.04 0.004 0.15 0.02
Centralization(degree) 0.166 0.06 0.12 0.12
doi:10.1371/journal.pone.0142443.t003
nodecountatdifferentnetworkthresholdshelpedusindecidingthereferencenetworkthresh-
old,i.e.r>=0.5andFDR<=0.05(seeS5Fig).
Next,weevaluatedthenetworkqualitiesbycomparingitstopologicalpropertieswithran-
domnetworksofthesameaveragedegreeandgenes.Randomnetworksweregeneratedusing
Erdos-Renyimodel[25],whichcreateseverypossibleedgewithequalprobability'p',indepen-
dentofotheredges.ThedegreeofavertexinsucharandomgraphfollowsaPoissondistribu-
tionwithmostnodeshavingapproximatelysamenumberoflinks.Kolmogorov-Smirnovtest
[26],whichevaluatesthesignificanceofdeviation,suggestsignificantdeviationoftheinferred
genenetworkfromrandomnetworks(P<2.2e-16,FigureAinS6Fig).
Generallyinbiologicalsystems,afewgeneshaveasignificantlyhighernumberofconnec-
tionsascomparedtotheothergenesinthenetworki.e.theyactashubgenes.Suchscalefree
topologysignifiesthenetworkrobustnessanditsresistancetorandomgeneknockout.Any
scalefreenetworkisgenerallycharacterizedby“heavytailed”natureofnodedegreedistribu-
tion(FigureBinS6Fig)[27].Weobserveasimilardistributionofdecreasingdegreedistribu-
tionwithincreasinglinks,markingthepresenceofgeneswithfewconnectionstothe'hub'
genes.Wethenperformedastatisticalmeasuretocheckscalefreetopologybytestingpower
lawdistributionfittoeachofthenetworkmodelusingbootstrappinghypothesistest[28].We
foundthattheNormalandCMnetworksdonotsignificantlyfittoapowerlawmodel
(P<0.1),andhencethenetworksarenotscale-free.However,“heavytailed”degreedistribution
oftheentirenetworkandtheirdeviationfromtherandomnetworksprovidesthecharacteristic
ofatruecomplexbiologicalnetwork.Otherfundamentalnetworktopologicalparametersare
givenintheTable3.Itisobservedthatdatasizehasnosignificantimpactonfundamental
topologicalnetworkpropertieswithnormalbeingthemostconnectednetworkmodeland
CnM,theleastconnected.Althoughasignificantvariabilityamongthefournetworkmodels
exists,yetmetastaticsamplesarecloselyrelatedtoeachotherowningtosimilartopological
propertieslikeedges,clusteringcoefficientanddegreecentralization.Overall,thesetopological
propertiessuggestthedifferencesintheexpressionorconnectivityprofilesofthesamegenes
undervariableconditions.
Differentialnetworkanalysis
Mostofthedifferentialnetworkanalysis,notspecifictomelanoma,reliesonthegenedegree
difference(DifferentialConnectivity;DC)acrosstwoormorenetworkstoelucidatealtered
geneset.InordertostudyDCinmelanomagenes,wemeasuredeachgeneDCacrossdifferent
stagesofmelanomawithrespecttothenormalnetworkanditsstatisticalsignificanceinterms
ofp-valueandfalsediscoveryrate(adj.porFDRadjustedp<0.01).Asexpected,asignificantly
highdegreelossisobservedindifferentmelanomastages(Fig3A).Foreachmelanomastage,
morethanatwo-foldincreaseinnumberofgeneswithconnectivitylossthangainexists.Ana-
lysingthedifferentialconnectivityasafunctionofp-valuesuggeststhatamajorityofthegenes
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GeneNetworkRewiringtoStudyMelanomaStageProgression
Fig3.A.Numberofgenessignificantlydifferentiallyconnected(DC;eitherlossorgain)ineachtumorstagewithrespecttothenormalstage
network.B.ForeachgeneDCisplottedwithitsstatisticalsignificance(FDRadj.p-value)andwithdiseaseprogression,numberofgeneswith
increasednetworkconnectivityincreasesunderthesignificantp-value(p<0.01)asrevealedbyhorizontallineonthepositivex-axis.C.Foreach
gene,thecalculatedgainedco-expression(Rw)isplottedwithitsoverallDCscore.Thegraphexplainsthatwithdiseaseprogression,genestends
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GeneNetworkRewiringtoStudyMelanomaStageProgression
tointensifythealterationsintheconnectiontypesbygainingaswellasloosingconnectionswhichmayormaynotalteritsDC.Fourquadrants
suggestthatgenesmaygainnoveledgeswithincreasedDC(quadrantI)orgainnovelconnectiondespitelosingoverallDC(quadrantII)orlose
edgeswithdecreasedDC(quadrantIII)orshowincreasedDCdespitelosingconnections(quadrantIV).Inthegraphsinglegenewasplottedtwo
timestocorrelateRw(+ve)versusDCandRw(-ve)versusDCasbothofthetermswerefoundtobeindependent.
doi:10.1371/journal.pone.0142443.g003
withhighdifferentialconnectivityhavesignificantlylowp-value(Fig3B).Thehigherlossof
connectionswithlowp-valuestatisticallyconfirmstheedgelossfromnormaltocancertissue.
Also,theasymmetricalnatureofthegraphssuggeststhepresenceofgeneswithahighernum-
beroflostconnectionsthangained.Boththemetastaticstagesarecharacterizedbyanearly
symmetricalgraph,whereasthenon-metastaticstageisasymmetric.
Differentialconnectivityvsedgesrewiring
Wedecipheredthealteredconnectiontypesineachofthemelanomastagesascomparedto
thatinthenormal,byoverlappingtherespectivenetworks.Inordertoscrutinizetheassump-
tionwhetheredgerewiringproducesdifferentresultsthanDC,wecomparedtheresultspre-
sentedbythetwoapproaches.
Foreachofthemelanomastages,wefoundahighnumberofgeneswithnovelconnections
in-spiteoftheoveralldegreelossascomparedtothatinthecontrol(Fig3C;IIquadrant).Each
comparisonischaracterisedbyadiagonalrelationshipbetweenconnectivitylossandnodes
lost(EL);connectivitygainandnovelnodesgain(EG).Thedensenatureofthegraphreflects
highproportionsofedgerewiringduringmetastasis,LNthemostgene-rewiredstate.Thus,
melanocytetomelanomatransformationbeginswithsignificantlossofnetworkrobustness,
however,progressiontometastatictransformationoccursonlyaftermulti-edgegains.We
believethatthemulti-edgegain,displayedbyagenesetcouldbeanimportantphenomenon
fortransformedbiologicalactivityandcanhelpidentificationofgenesinthemostaberrantly
rewirednetworks.Therefore,intheupcomingpartofthismanuscript,wewillprimarilyfocus
ontheshortlistedDCgeneswithsignificantlygainednovelconnections.
Multi-edgerewiringinmelanomaprogression
Forelucidationofaberrantlynetworkedgenes,networkconnectivityrewiringanalysiswasper-
formedforastage-wiseassessmentoftheedgerewiring.Theanalysisrevealsthatmelanocyte
tomelanomaconversioninitiateswithasignificantedgesloss(highestEL=2059)ascompared
tothenumberofedgesgained(highestEG=422).Weobserveasuddenincreaseingenesdis-
playingEG,whilemaintainingitsconnectivitylossafterthesecondtransition(Fig4A).Box-
plotanalysisclearlyillustratestheeffectofmelanomaongeneconnections,thenumberof
edgeslostisfoundtobeashighas~2000inallthestagesofmelanoma(Fig4B).Inorderto
confirmifthegeneswithlostconnectionsinCnMretainitsconnectivityprofileinlaterstages,
wecomparedthegenesthatlostmorethan20edges(arbitrarilyselectedvalue)acrossdifferent
stagesofmelanoma.Morethan90%oftheCnMgenesthatdisplayedELcontinuetoloose
edgesinCMandLN(Fig4C).Thus,globalanalysissuggeststhatalargesetofgenesactively
rewiresitsconnectiontypes,manyofwhichgainnovelconnectionsand,ifnotsignificantly
down-regulated,mayactivelybeinvolvedinaberrantnetworksinmelanomaprogression,
especiallyinthecellsprogrammedformetastasis.
Acloseranalysisoftheresultsrevealthatthegenethatgainedmaximumedgesduringthe
firsttransitionisKIDINS220(EG=422,EL=211)whilethegenewiththehighestlossofcon-
nectionsisC1orf216(EG=4,EL=2059).Duringthenon-metastatictometastatictransition,
thegeneLRP5gainedthehighestnumberofconnections(EG=1283,EL=113),while
C1orf216continuedtobethegenewiththehighestedgeloss(EG=0,EL=2065).Afterthe
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GeneNetworkRewiringtoStudyMelanomaStageProgression
Fig4.A.Linegraphtoobservethedifferencebetweenedgeslost(color:green)andgain(color:red)byasinglegeneindifferentmelanoma
stages.Theobservedtrendsuggestsconsistentandsignificantincreaseinnoveledgesgain,aftertheonsetofmetastasis.B.Boxplotshowing
thedifferencesinthenumberofnoveledgesgained(color:red)andlost(color:green)bygenesineachstage.C.Comparisonforthegenesthat
displayedconnectivityloss(edgeloss>20)acrossdifferentmelanomastages.Venndiagramsuggestsremarkablesimilarityofgenebehavior
acrossmutuallyexclusivedatasetsandlossofconnectionsisaconservedphenomenon.
doi:10.1371/journal.pone.0142443.g004
thirdtransition,geneASNSD1gainedthehighestnumberofedges(EG=1254,EL=32)
whereasgeneARMC9(EG=19,EL=1924)lostmaximumnumberofedges.However,the
analysisoftopfiverewiredgenesdonotlistanyknownrecognizedmelanomamarker,thus
suchgenesmaybeexploredaspotentialtargets.
Diseasegenesaresignificantlyrewired
Bycomparingthedatasetofeachstagewiththenormaldataset,wegeneratedagenelistofdis-
easegenesthatareeithersignificantlyupregulatedorabnormallyconnected(seematerialsand
methods).Ouraimwastoderiveanovelgenesetthatcouldpossiblyaccountforstage-wise
networkaberrationsduringmelanomaprogression.Interestingly,themetastaticstagesinclude
averyhighnumberofshortlistedgenes(i.e.diseasegenes).Thehighestnumberofputativedis-
easegenesisfoundinLNascomparedtothatinotherstages(Fig5A–5E).Itisevidentthatthe
highnumberofdiseasegenesmayhelpustounderstandthemetastaticbehaviourofthegenes
inthedatasetandidentifynovelassociatedbiomarkers.Itisfoundthat60%oftheCnMgenes
retainitsactivityprofileinoneoftheothertwometastaticstages.Wefoundthat59%ofthe
uniquelystagespecificdiseasegenesinLNthatmaximallyshares1317geneswithCM.
PLOSONE|DOI:10.1371/journal.pone.0142443 November11,2015 10/30