J O U R N A L O F P R O T E O M I C S 9 6 ( 2 0 1 4 ) 6 7 – 8 1

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Phosphoproteome analysis reveals differences in

phosphosite profiles between tumorigenic andnon-tumorigenic epithelial cells

Flavia V. Wincka, Marília Bellonia, Bianca A. Paulettia, Jackeline de Lima Zanellaa,Romênia R. Dominguesa, Nicholas E. Shermanb, Adriana F. Paes Lemea,⁎aLaboratório Nacional de Biociências, LNBio, CNPEM, Campinas, SP, BrazilbSchool of Medicine, University of Virginia, Charlottesville, VA, USA

A R T I C L E I N F O

⁎ Corresponding author at: Laboratório Nacion19 3512 1006.

E-mail address: adriana.paesleme@lnbio.

1874-3919/$ – see front matter © 2013 Elseviehttp://dx.doi.org/10.1016/j.jprot.2013.10.039

A B S T R A C T

Article history:Received 31 May 2013Accepted 29 October 2013Available online 7 November 2013

Oral cancer disease represents a significant fraction of all human cancer types and its poorearly diagnosis contributes to reduced individual survival rate. The identification ofproteins modulated in tumorigenic cells and its post-translational modifications mayimprove our understanding of tumor development in epithelial cells. We have analyzedthe phosphoproteome of tumorigenic (SCC-9) and non-tumorigenic (HaCaT) cell linesusing MS-based approach in order to identify phosphopeptides with differing patternsof modifications and/or abundance. Our results revealed the identity of 4,206 proteinphosphorylation sites with sixty-two sites showing to be significantly modulated betweenthe two cell lines. The phosphoproteome data showed an overrepresentation of proteinswith a possible role in nuclear regulatory functions. Pathway analysis was furtherperformed on the phosphoproteome dataset and differences and commonalities of thefunctional pathways present in tumorigenic and non-tumorigenic cells were identified.Phosphopeptides that belong to the proteins lamina-associated polypeptide 2 isoform alphaand serine–arginine repetitive matrix protein 2 were identified with differential abundanceand they appear as promising tumor-related phosphopeptides. These two proteins may berelated to the structural alterations generally found in the nucleus of tumorigenic cells. Theidentification of phosphorylation sites in tumorigenic cells may contribute to disclose novelsignaling mechanisms associated with OSCC.

SignificanceOral Squamous Cell Carcinoma (OSCC) is an important cancer disease affecting thousandsof people worldwide. Many cellular processes related to the development of oral cancerremain unknown; however, the studies performed in vitro with cancer cells havecontributed to guide more specific research which may be further performed by using invivo approaches or clinical samples. To our knowledge, only few studies have beenpublished showing the results of phosphoproteome profiling of squamous cell carcinomamodels, and many signaling proteins must be identified and functionally characterized inorder to increase the knowledge available about the complexity of the signaling networksresponsible for oral cancer development and its progression. Furthermore, our knowledge

Keywords:PhosphoproteomeOral cancerProteomicsSignaling pathwaysNetworksHuman

al de Biociências, LNBio, CNPEM, 13083970 Campinas, Brazil. Tel.: +55 19 3512 1118; fax: +55

cnpem.br (A.F. Paes Leme).

r B.V. All rights reserved.

68 J O U R N A L O F P R O T E O M I C S 9 6 ( 2 0 1 4 ) 6 7 – 8 1

regarding proteins exclusive or very low abundant in cancer cells remains limited. A betterunderstanding of the differences between signaling pathways present in epithelial cell linesmay contribute to reveal the processes underlying the OSCC.

© 2013 Elsevier B.V. All rights reserved.

1. Introduction

Oral cancer is a disease which affects thousands of peopleworldwide every year and represents up to 2% of all types ofhuman cancer, being the Oral Squamous Cell Carcinoma(OSCC) the most frequent type of oral cancer [1]. Due to thedifficulty in the early diagnosis, the percentage of patientswho will survive for more than five years is quite lowcompared to other types of cancer. The development oflaboratory tests to improve diagnosis may contribute to theearly detection of cancer in the oral cavity andmay contributeto increase effectiveness of the medical treatments thusreducing mortality [1]. The identification of proteins involvedin tumorigenesis and the characterization of their possiblerole in regulating tumor development have been recognizedfor many years as an important approach to broadening ourknowledge about the cellular processes underlying cancerdisease [2]. It has been shown that many proteins involved inthe development and proliferation of tumor cells are part ofcomplex signaling cascades and they function as regulators ofcellular responses [3,4]. Within these signaling cascades,many proteins have shown to play a role in phosphorylationand autophosphorylation events, regulating signaling cas-cades at several different levels [4].

Several signaling pathways have been described so farincluding cancer-related proteins, such as ERK, EGFR andBCR-ABL1, which were described through proteomics approach[4]. These findings lead to a more holistic and dynamic view ofthe tumor development, showing that post-translational mod-ifications (PTMs) may play an essential role in the regulation ofcellular responses. Nevertheless, from the overall number ofphosphosites predicted in a cell, suggested to be around 100,000sites, most of them have probably not been described so fareven with the recent advances on proteomic techniques [5].Therefore, it is important to identify the phosphorylationevents in the proteome of a cell or tissue in order to disclosethe whole protein phosphorylation profiles of tumor cells.Furthermore, the identification of the phosphorylated proteinsin several differing tumorigenic and non-tumorigenic cell linesmay not only assist in the elucidation of the variations insignaling pathways responsible for tissue-specificity tumordevelopment but may also contribute to the identification ofphosphorylation events commonly occurring in different celllines. Recently, by comparing the phosphoproteome ofdevelopmental stages of skin cancer, proteins associatedwith early and late cellular responses were identified inmice,providing new insights into the progression of the disease [6].However, to our knowledge, no study has described thephosphoproteome of human epithelial cell lines used for invitro studies in oral cancer research. We have recentlydemonstrated that HaCaT and SCC-9 cell lines have differingproteome profiles of its secretome. Changes in cellularmigration and adhesion were observed in these two cell

lines. Extracellular matrix, membrane-bound and secretedproteins were identified to be differentially expressed intumorigenic (SCC-9) [7] and non-tumorigenic (HaCaT) [8]cells. Candidate proteins related to migration of SCC-9 cellswere verified [9]. The comparative proteome analysis ofsecretome from HaCaT and SCC-9 cell lines had nicelyillustrated that there are cellular mechanisms, which maybe particularly more evident in tumorigenic cells. However,changes in protein post-translation modifications in celllines have not been clearly demonstrated. HaCaT cells arespontaneously immortalized cells and retain their capacity toreconstitute a structured and stable epidermis in vivo, alsoshowing non-invasive behavior when transplanted to epi-dermis in vivo [8,10]. Therefore, these cells have an epidermalorigin and even with the differentiation suffered through theimmortalization process their non-invasive behavior wasretained. In contrast, the SCC-9 cell line which also has anepidermal origin, retained its invasiveness and capacity todevelop progressive tumors after transplantation in vivo [11].By comparing the phosphoproteome of HaCaT and SCC-9cells we may then disclose candidate proteins which play arole in signaling mechanisms related to the invasiveness oftumorigenic epithelial cells which should further contributeto a better understanding of tumor progression in OSCC. Inorder to deeply investigate the signaling mechanisms thatmay explain the differences between tumorigenic and non-tumorigenic cell lines, we performed a phosphoproteomeanalysis. Phosphopeptide enrichment and identificationanalysis were performed with titanium dioxide (TiO2) beadsfollowed by high resolution mass spectrometry (MS), respec-tively. We identified 4,206 high confident phosphosites, ofwhich 4,115 have been found deposited at Phosphositeannotation databases. Gene ontology (GO) term enrichmentanalysis was performed and revealed overrepresented func-tional GO categories related to RNA metabolism in SCC-9.Phosphoproteins identified in both cell lines have shown topossess general GO term enrichment for nuclear or transla-tional regulatory functions. Besides, pathways and networksrelated to phosphoproteins identified in our study wereretrieved through the use of Ingenuity knowledge base,showing important variations in the components of path-ways regulated in tumorigenic and non-tumorigenic cells.Moreover, phosphosites with differential abundance wereidentified and the possible functional role of these phos-phorylated proteins in tumorigenic cells is discussed.

2. Material and methods

2.1. Cell culture

The human Oral Squamous Cell Carcinoma (OSCC) cell lineSCC-9 [7] was obtained fromAmerican Type Culture Collection

Scheme 1 – Overview of phosphoproteome profiling intumorigenic and non-tumorigenic cells. Tumorigenic (SCC-9)and non-tumorigenic (HaCaT) cells were cultured up to 80%confluence and duplicated experiments were performed.Cells were harvested and total protein extracted anddigested. Phosphopeptide enrichment was achieved withcation exchange chromatography followed by titaniumdioxide chromatography. Phosphopeptides were eluted andidentified in a nanoLC–MS/MS instrument. Phosphositequantification and annotation of biological information wereperformed with bioinformatic tools. Biological pathways,network of co-expressed genes and functional annotationwere mined for data interpretation.

Table 1 – Summary of the phosphoproteome profiling.

Description

PhosphositesTotal phosphoprotein groupsTotal unique phosphopeptidesTotal peptides phosphorylated on serineTotal peptides phosphorylated on threonineTotal peptides phosphorylated on tyrosineUnique Peptide phosphorylated on serineUnique Peptide phosphorylated on threonineUnique Peptide phosphorylated on tyrosineDifferentially expressed phosphoprotein groups (p < 0.05)Phosphosites with differential abundance (p < 0.05)Monophosphorylated peptides (up to 1 Ph)Diphosphorylated peptides (up to 2 Ph)Multi-phosphorylated peptides species (3 or more Ph sites)Number of raw data files

69J O U R N A L O F P R O T E O M I C S 9 6 ( 2 0 1 4 ) 6 7 – 8 1

(ATCC, Manassas, VA, USA), and cultured as recommended.The HaCaT cells [8], an immortalized but not transformedepithelial cell line, was maintained in DMEM containing 10%fetal bovine serum (FBS) and antibiotics at 37 °C in a 5% CO2 airatmosphere.

2.2. Phosphoproteome sample preparation

The HaCaT and SCC-9 cells were cultured until 80% cellconfluence in 500-cm2 plates, washed with serum-free mediaand cultivated for 24 h. After 24 h, the cells were harvestedand the proteins were extracted. Briefly, cells were removedfrom culture plates with Trypsin, washed with PBS andlysed by sonication in a solution containing protease inhib-itors (1 mM NaF, 1 mM β-glycerophosphate, 1 mM sodiumorthovanadate, 10 mM sodium pyrophosphate, 1 mM PMSFand EDTA-free Complete mini protein inhibitors cocktail(Roche, Indianapolis, IN, USA) as previously described [12]).Total protein extracts (20 mg) were reduced, alkylated andtrypsin digested.

2.3. Mass spectrometry analysis

2.3.1. SCX liquid chromatographyAfter peptide desalting using reverse phase column Sep-Pak®(Waters, Milford, MA, US), the peptides were separated bycation exchange chromatography (SCX) using Mono S HR 5/5,buffer A (5 mMKH2PO4, 30% ACN, 0.1% TFA, pH 2.7) and bufferB (Buffer B + 350 mM KCl) at a flow rate of 1 mL/min.The elution of the peptides was performed with a gradient of0–30% B over 30 min. Twenty two 1-mL fractions werecollected as well as the flow through and pooled into 5fractions and dried. The samples were reconstituted in 20%acetonitrile solution containing 0.5% trifluoroacetic acid. Thephosphopeptide enrichment was performed with titaniumdioxide beads (TiO2) (GL Sciences, Tokyo, Japan). Each SCXfraction was then added to a 1-mL reaction tube containing5 mg of the TiO2 beads and incubated batch wise withend-over-end rotation for 30 min. After incubation, thebeads were spun down and washed two times with 80%acetonitrile solution containing 0.5% trifluoroacetic acid andtwo times with 0.5% trifluoroacetic acid. Bound peptides were

Total HaCaT SCC-9

4206 355 3631121 61 692488 193 1933828 317 332352 36 3026 2 1

2305 174 174294 23 1925 2 041 – –62 – –

474 49 481302 103 98712 41 4720 10 10

Table 2 – List of phosphosites with significant differential abundance.

Protein names Genenames

Aminoacid

Ratio(SCC-9/HaCaT)

T-testp value

Positions withinproteins

Modified sequence

Phosphosites less abundant in SCC-9 cellsCell division cycle protein 23 homolog CDC23 S 0.9393 0.02110895 588;470 _RVS(ph)PLNLSSVT(ph)P_Cell division cycle protein 23 homolog CDC23 T 0.9393 0.02110895 596;478 _RVS(ph)PLNLSSVT(ph)P_Chromodomain-helicase-DNA-binding protein 8 CHD8 S 0.9194 0.033453202 562;283 _NTSS(ph)DNS(ph)DVEVMPAQS(ph)PREDEESSIQK_HIRA-interacting protein 3 HIRIP3 S 0.9206 0.034059896 196 _QAREES(ph)EES(ph)EAEPVQR_HIRA-interacting protein 3 HIRIP3 S 0.9206 0.034059896 199 _QAREES(ph)EES(ph)EAEPVQR_Lamina-associated polypeptide 2, isoform alpha TMPO S 0.7598 0.012350761 159;66 _LREQGTES(ph)RS(ph)S(ph)TPLPTISSSAENTR_Neuroblast differentiation-associated protein AHNAK AHNAK S 0.9590 0.045810184 5745 _S(ph)S(ph)KASLGSLEGEAEAEASSPK_Neuroblast differentiation-associated protein AHNAK AHNAK S 0.9590 0.045810184 5746 _S(ph)S(ph)KASLGSLEGEAEAEASSPK_Neuroblast differentiation-associated protein AHNAK AHNAK S 0.9426 0.012595822 5749 _AS(ph)LGS(ph)LEGEAEAEASS(ph)PKGK_Protocadherin-1 PCDH1 S 0.8852 0.009390255 971;982;959;949 _S(ph)NSPLPSIQLQPQSPS(ph)ASK_Serine/arginine repetitive matrix protein 2 SRRM2 S 0.9332 0.036431218 377;342;281 _HGGS(ph)PQPLATT(ph)PLS(ph)QEPVNPPSEAS(ph)PT(ph)R_Serine/arginine repetitive matrix protein 2 SRRM2 T 0.8644 0.025504141 1003;255 _AQT(ph)PPGPSLSGSKS(ph)PCPQEK_Supervillin SVIL S 0.8829 0.016233439 66 _SNEEEETS(ph)DSS(ph)LEKQTR_SWI/SNF complex subunit SMARCC2 SMARCC2 S 0.8341 0.045917118 302 _S(ph)PS(ph)PSPTPEAK_Testis-specific Y-encoded-like protein 2 TSPYL2 S 0.9202 0.014401922 20 _RLS(ph)SSES(ph)PQRDPPPPPPPPPLLR_Tight junction protein ZO-2 TJP2 S 0.9369 0.021521346 1098;1067;1044;1034 _SILKPSTPIPPQEGEEVGES(ph)S(ph)EEQDNAPKTight junction protein ZO-2 TJP2 S 0.9369 0.021521346 1099;1068;1045;1035 _SILKPSTPIPPQEGEEVGES(ph)S(ph)EEQDNAPK

Phosphosites more abundant in SCC-9 cells182 kDa tankyrase-1-binding protein TNKS1BP1 S 1.0333 0.045145536 1620 _VPS(ph)S(ph)DEEVVEEPQSRR_182 kDa tankyrase-1-binding protein TNKS1BP1 S 1.0336 0.043930105 1621 _VPS(ph)S(ph)DEEVVEEPQSRR_Absent in Melanoma 1-like protein AIM1L S 1.2082 0.005474009 228 _MVPPVVVGS(ph)PPGS(ph)PSR_Afadin MLLT4 S 1.1407 0.000963995 1181;1182;1165;1166 _SSPNVANQPPS(ph)PGGK_Apoptotic chromatin condensation inducer in the nucleus ACIN1 S 1.3012 0.008139731 240;200 _LS(ph)EGS(ph)QPAEEEEDQETPSR_Apoptotic chromatin condensation inducer in the nucleus ACIN1 S 1.3012 0.008139731 243;203 _LS(ph)EGS(ph)QPAEEEEDQETPSR_ATP-binding cassette sub-family F member 1 ABCF1 T 1.0825 0.049930875 109;108;11 _KLS(ph)VPT(ph)S(ph)DEEDEVPAPKPR_BAG family molecular chaperone regulator 3 BAG3 S 1.0650 0.025524661 377 _VPPAPVPCPPPS(ph)PGPSAVPS(ph)SPK_Catenin alpha-1 CTNNA1 S 1.0470 0.029213825 655;640;552;285;333;286 _SRT(ph)S(ph)VQT(ph)EDDQLIAGQSAR_Catenin alpha-2 CTNNA2 S 1.0470 0.029213825 654;688 _SRT(ph)S(ph)VQT(ph)EDDQLIAGQSAR_

70JO

UR

NA

LO

FPR

OT

EO

MIC

S96

(2014)

67–81

Protein names

Genenames

Aminoacid

Ratio (SCC-9/HaCaT) T-testp value

Positions withinproteins

Modified sequence

Chromobox protein homolog 3 CBX3 S 1.0655 0.007733316 97 _SLS(ph)DS(ph)ES(ph)DDSKSK_DENN domain-containing protein 1A DENND1A S 1.1666 0.01529734 520 _RTS(ph)VPS(ph)PEQPQPYR_DENN domain-containing protein 1A DENND1A S 1.1666 0.01529734 523 _RTS(ph)VPS(ph)PEQPQPYR_EH domain-binding protein 1 EHBP1 S 1.1332 0.036777769 432;397 _DLS(ph)TSPKPS(ph)PIPS(ph)PVLGR_EH domain-binding protein 1 EHBP1 S 1.1332 0.036777769 436;401 _DLSTS(ph)PKPSPIPS(ph)PVLGR_Forkhead box protein K1 FOXK1 T 1.2305 0.02785476 247;130;84 _SMVSPVPSPT(ph)GT(ph)ISVPNS(ph)CPASPR_Forkhead box protein K1 FOXK1 T 1.1505 0.029496107 245;128;82 _SMVSPVPSPT(ph)GT(ph)ISVPNS(ph)CPASPR_Forkhead box protein K1 FOXK1 S 1.1173 0.009549378 445;328;282 _SGGLQTPECLS(ph)REGS(ph)PIPHDPEFGSK_Integrin beta-4 ITGB4 T 1.1783 0.005443339 1385;1455 _M(ox)DFAFPGS(ph)T(ph)NSLHR_Interferon regulatory factor 2-binding protein-like IRF2BPL S 1.1289 0.011855034 658 _RNSS(ph)S(ph)PVS(ph)PAS(ph)VPGQR_Lamina-associated polypeptide 2, isoform alpha TMPO S 1.1988 0.014528238 156;63 _EQGTES(ph)RS(ph)STPLPTISSSAENTR_MAP7 domain-containing protein 1 MAP7D1 S 1.2043 0.036828932 116;77 _RSS(ph)QPS(ph)PTAVPASDS(ph)PPTK_Myosin-14 MYH14 S 1.0598 0.01257198 2024;2016;1991;1983;1767 _LEEGVAS(ph)DEEAEEAQPGSGPS(ph)PEPEGS(ph)PPAHPQ_PH-interacting protein PHIP S 1.0866 0.045145675 1281;7 _VLS(ph)DS(ph)EDEEKDADVPGTSTR_PH-interacting protein PHIP S 1.0866 0.045145675 1283;9 _VLS(ph)DS(ph)EDEEKDADVPGTSTR_Phosphatase and actin regulator 4 PHACTR4 T 1.0621 0.004305278 359;349;333;348 _S(ph)PSPPLPT(ph)HIPPEPPRTPPFPAK_Protein FAM83H FAM83H S 1.0900 0.016065506 5 _RS(ph)QS(ph)S(ph)SQGDNPLAPGYLPPHYKEYYR_Protein IWS1 homolog IWS1 S 1.0220 0.024815711 398;351;191;405;73 _KAAVLS(ph)DS(ph)EDEEK_Protein IWS1 homolog IWS1 S 1.0220 0.024815711 400;353;193;407;75 _KAAVLS(ph)DS(ph)EDEEK_Protein PRRC2B PRRC2B S 1.1028 0.049851391 1132;428 _VAS(ph)ETHS(ph)EGSEYEELPK_Protein scribble homolog SCRIB S 1.1272 0.045385982 1348;1267;344;717 _AFAAVPTSHPPEDAPAQPPTPGPAAS(ph)PEQLSFR_SAFB-like transcription modulator SLTM S 1.1712 0.021550534 553;122 _ISS(ph)KS(ph)PGHMVILDQTK_Sentrin-specific protease 3 SENP3 S 1.0473 0.042954902 169 _NHLS(ph)PQQGGATPQVPS(ph)PCCR_Serine/arginine repetitive matrix protein 2 SRRM2 S 1.0873 0.009473769 2100;1352 _NHS(ph)GS(ph)RT(ph)PPVALNSSR_Serine/arginine repetitive matrix protein 2 SRRM2 S 1.0873 0.009473769 2102;1354 _NHS(ph)GS(ph)RT(ph)PPVALNSSR_Serine/arginine repetitive matrix protein 2 SRRM2 T 1.0873 0.009473769 2104;1356 _NHS(ph)GS(ph)RT(ph)PPVALNSSR_Smad nuclear-interacting protein 1 SNIP1 S 1.0999 0.014521522 54;38 _RPDHS(ph)GGS(ph)PS(ph)PPTSEPAR_Squamous cell carcinoma antigen recognized by T-cells 3 SART3 S 1.1221 0.00727551 10 _(ac)ATAAET(ph)S(ph)AS(ph)EPEAESK_Transforming acidic coiled-coil-containing protein 2 TACC2 S 1.0355 0.037167746 2321;2325;2321;2311;2276;

467;399;416;25;60;168_LDNT(ph)PASPPRS(ph)PAEPNDIPIAK_

tRNA (cytosine(34)-C(5))-methyltransferase NSUN2 S 1.0685 0.003865576 743;708;507 _AGEPNS(ph)PDAEEANS(ph)PDVTAGCDPAGVHPPR_tRNA (cytosine(34)-C(5))-methyltransferase NSUN2 S 1.0685 0.003865576 751;716;515 _AGEPNS(ph)PDAEEANS(ph)PDVTAGCDPAGVHPPR_Ubiquitin-conjugating enzyme E2 O UBE2O S 1.1400 0.028626674 399 _IMS(ph)CS(ph)PDTQCSR_Ubiquitin-conjugating enzyme E2 O UBE2O S 1.1400 0.028626674 401 _IMS(ph)CS(ph)PDTQCSR_Zinc finger CCCH domain-containing protein 13 ZC3H13 S 1.0620 0.033845793 238;54 _KTS(ph)AVSS(ph)PLLDQQR_Zinc finger CCCH domain-containing protein 13 ZC3H13 S 1.0620 0.033845793 242;58 _KTS(ph)AVSS(ph)PLLDQQR_

71JO

UR

NA

LO

FPR

OT

EO

MIC

S96

(2014)

67–81

Fig. 1 – Venn diagram of the total phosphorylation sites andphosphoproteins. (A) The total number of phosphositesidentified by LC–MS/MS in both cell lines, HaCaT and SCC-9, isindicated by the weighted Venn diagram. The phosphositesidentified in both cell lines (3488 phosphosites) and the onesexclusively identified in HaCaT cells (355 phosphosites) or inSCC-9 Cells (363 phosphosites) are shown. (B) Phosphoproteingroups identified in both cell lines and those exclusivelyidentified in HaCaT and SCC-9 cells are shown.

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eluted from the beads with 200 mM ammonium bicarbonatefollowed by 0.5% ammonium solution in 40% acetonitrile.

2.3.2. Nanoflow nLC–MS/MSThe samples were dried in a vacuum concentrator andreconstituted in 20 μL of 0.1% formic acid. An aliquot of4.5 μL was analyzed on an ETD enabled Orbitrap Velos massspectrometer (Thermo Fisher Scientific, Waltham, MA, USA)connected to the EASY-nLC system (Proxeon Biosystem, WestPalm Beach, FL, USA) through a Proxeon nanoelectrosprayion source. Peptides were separated by a 2–90% acetonitrilegradient in 0.1% formic acid using a pre-column EASY-Column (2 cm × id 100 μm, 5 μm particle size) and an analyt-ical column EASY-Column (10 cm × id 75 μm, 3 μm particlesize) at a flow rate of 300 nL·min−1 over 194 min. Thenanoelectrospray voltage was set to 1.7 kV and the sourcetemperature was 275 °C. All instrument methods were set upin the data dependent acquisition mode. The full scan MSspectra (m/z 300–2000) were acquired in the Orbitrap analyzerafter accumulation to a target value of 1e6. Resolution in theOrbitrap was set to r = 60,000 and the 20 most intense peptideions with charge states ≥2 were sequentially isolated to atarget value of 5,000 and fragmented in the linear ion trap bylow-energy CID (normalized collision energy of 35%). Thesignal threshold for triggering an MS/MS event was set to1,000 counts. Dynamic exclusion was enabled with anexclusion size list of 500, exclusion duration of 60 s, andrepeat count of 1. An activation q = 0.25 and activation time of10 ms were used.

2.3.3. Raw LC–MS/MS data analysisThe identification of phosphosites was performed withMaxQuant v.1.3.0.3 [13] against the Uniprot Human ProteinDatabase (release July 11th, 2012; 69,711 entries). Carbamido-methylation was set as fixed modification, and N-terminalacetylation, oxidation of methionine, phosphorylation ofserine, threonine and tyrosine as variable modifications,maximum 2 trypsin missed cleavage and a tolerance of20 ppm for precursor mass and 1 Da for fragment ions wereset for protein identification. Phosphosites and phosphopro-tein identifications were filtered for a maximum of 1% falsediscovery rate at peptide and protein levels, using reversetarget-decoy database strategy with reverse peptide se-quences as decoy entries. Using the application softwarePerseus v.1.2.7.4 [13] the list of phosphosites identified wasfiltered by minimum localization probability of 0.75 andreverse and contaminant entries were excluded from furtheranalysis. Comparative analysis of phosphopeptide abun-dance between HaCaT and SCC-9 cell lines was performedby Label-free quantification method based on the individualphosphopeptide intensities, which are proportional to theraw area under the peak. Matching between runs was set andapplied with a 2 min. window. Statistical analysis and proteinfunctional annotation of Phosphosites were also performedusing Perseus.

All mass spectrometric raw files and search parametersettings associated with this study are available fordownloading via FTP from the PeptideAtlas data repositoryby accessing the following link: http://www.peptideatlas.org/PASS/ PASS00316.

2.4. Gene ontology enrichment analysis and prediction ofco-expressed genes

Overrepresented GO terms were identified using BinGO pluginv.2.44 [14] and the software platform Cytoscape v.2.8.3 [15] wasemployed for network visualization. Global Homo sapiens GOannotation was used as a background annotation database forcalculating overrepresentationwith Benjamin and Hochberg [16]p-value correction. In addition, Fisher's test was also performedusing Perseus v.1.2.7.4 (http://maxquant.org/) to determine GOterm enrichment. A network of co-expressed genes was predict-ed with GeneMania plugin [17] based on genomics and proteo-mics data and literature information. Most gene co-expressioninformation was obtained from gene expression data retrievedfrom Gene-expression Omnibus (GEO). For the network build theautomatic weight was set and a maximum of 35 nodes wereallowed to be visualized in the network.

2.5. Motif search analysis

In order to verify the presence of potential novel phosphorylationsites the sequences of the 4,206 phosphosites identified wereselected as input data to aphosphositemotif search analysis. Thedata available in Perseus default motif dataset were retrieved forthe phosphosites identified and complemented by a new motifsearch against the most recent version of the PhosphoSitePlus®database (versionMarch 04th, 2013;www.phosphosite.org) [18]. Anumber of 4,105 phosphosites we identified have a knownphosphosite already described in PhosphoSitePlus database.Furthermore, phosphosite sequences without any match at thePhosphoSitePlus database were analyzed using the Motif-xanalysis tool (http://motif-x.med.harvard.edu/) with significancethreshold at 10E−5 [19,20].

2.6. Pathway and network analysis

Canonical pathways and sub-networks were generated throughthe use of IPA (Ingenuity® Systems, http://www.ingenuity.com).The Uniprot accession codes of the phosphoproteins that had atleast one phosphosite identified were uploaded into the IPAsystems, which generated the interaction networks and canon-ical pathways for the phosphoprotein datasets of commonphosphoproteins, and phosphoproteins exclusive for each cell

73J O U R N A L O F P R O T E O M I C S 9 6 ( 2 0 1 4 ) 6 7 – 8 1

line SCC-9 and HaCaT. The most significant interactions andpathways associated with the phosphoproteome datasets weredetermined using Fisher's test.

3. Results

3.1. Phosphoproteome profiles of tumorigenic andnon-tumorigenic cell lines

We have performed the comparative analysis of the phospho-proteome of two human cell lines with epithelial origin, HaCaT

Fig. 2 –Heatmap of phosphosites with differential abundance. Phnormalized by Z-score and clustered by Euclidean distancemethoHeat map and two main clusters can be observed showing high (the sample names and experimental replicates are indicated andPhosphoSitePlus motifs are shown between parentheses when a

and SCC-9. The human OSCC cell line SCC-9 is originated fromhuman squamous carcinoma from the tongue and is atumorigenic cell line, whereas HaCaT is a non-tumorigenichuman cell line immortalized originally obtained from skinkeratinocytes. As HaCaT cells cannot develop into a tumor, butpossess similar epithelial origin as the SCC-9 cells, we aimed toinvestigate the phosphoproteome of these two cell lines inorder to identify variations between their phosphopeptideprofiles and to investigate the target signaling pathwayspossibly affected or related to the tumorigenic characteristic ofSCC-9 cells (Scheme 1).

osphosites with differential abundance (T-test, p < 0.05) weredwith average linkage. The resulting clusters are shown as ared) or low (green) abundant phosphosites. In the upper tree,in the left cluster tree the protein names are indicated andvailable.

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The phosphoproteome analysis of SCC-9 and HaCaTcells resulted in the identification of 10,693 phosphoryla-tion sites, which were predicted based on MaxQuantalgorithm. Only phosphosites with phospholocalizationprobability score higher than 0.75 and with at least twoidentification evidences (4,206 phosphosites) were consid-ered on further data analysis (Supplementary Figs. 1 and 2).Phosphorylation sites identified in both cell lines (3,488phosphosites) and phosphosites exclusive for the cell linesanalyzed, SCC-9 (363 phosphosites) and HaCaT (355 phos-phosites), were further explored (Table S1). These phosphor-ylation sites contained in the dataset of 4,206 entries weremostly localized on Serine residues (91.01%), followedby Threonine (8.37%) and Tyrosine (0.62%) residues. Theanalysis of the distribution of the phosphorylation sites

Fig. 3 – Phosphoproteins with differential abundance. The relativevalues) was grouped by protein groups, normalized by Z-score, anshown as a Heatmap, applying the Euclidian distancemethod andtree. Vertical trees indicate the biological samples and correspondi

revealed that most of them are diphosphorylated (2,357sites), followed by triphosphorylated (1,193 sites) andmonophosphorylated (656 sites). The phosphoproteomeanalysis was performed for two independent experimentalreplicates and at least two quantification values werenecessary for the inclusion of the phosphosites on furtherstatistical analysis of their relative abundance. A summary ofthe phosphoproteome analysis is shown in Table 1. Statisti-cal significance of phosphosites was calculated using T-test(p < 0.05) applied on the Log2 normalized phosphositeintensity values from SCC-9 and HaCaT cells, resulting in 62phosphosites with differential abundance (Table 2). Thesephosphosites were further assigned to 1,121 protein groups,with 61 protein groups exclusively identified in the HaCaTcells and 69 exclusive to SCC-9 cells (Fig. 1).

abundance of the phosphosites (Log2 transformed intensityd differential abundance between SCC-9 and HaCaT cells isaverage linkage. Protein names are indicated in the horizontalng experimental replicates included in the clustering analysis.

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Data clustering was performed for phosphosites andphosphoprotein groups using Euclidean distance methodwith average linkage and the results are represented as heatmapsof the calculatedZ-score for thephosphopeptide intensityvalues (Fig. 2).

The intensity values (Log2 transformed) of all phospho-sites assigned to the same protein group were summed up foraccessing the statistical significance of the variation inabundance of their corresponding phosphoproteins applyingthe Z-score calculation [21]. Forty one phosphoprotein groupsshowed relative differential abundance (T-test, two-tailed,p < 0.05) and their protein names and relative significance inboth experimental replicates and cell lines are shown as aheat map of the calculated Z-score values (Fig. 3).

3.2. Gene ontology term enrichment analysis

Gene ontology (GO) enrichment analysis was performed forthe phosphoprotein and phosphosite datasets in order toidentify overrepresented GO categories using BinGO v.2.44[14], with Benjamini & Hochberg False Discovery Rate (FDR)p-value correction and significance level threshold of 0.05 [16].The three most significant overrepresented GO molecularfunction terms for the dataset of phosphoprotein groupswere “protein binding” (GOID5515, p-value 4.07E−25), “bind-ing” (GOID5488, p-value 1.12E−09) and “chromatin binding”(GOID3682, p-value 8.67E−09), whereas “protein binding”(GOID5515, p-value 4.95E−47), “binding” (GOID5488, p-value1.19E−22), and “nucleic acid binding” (GOID3676, p-value 1.81E−22) terms were found overrepresented for the completedataset of phosphosites. Graphic visualization of the networkof overrepresented GO categories was generated withCytoscape [22]. The first ten most significant overrepresentedGO terms are shown for both datasets (phosphosites andphosphoproteins); GO terms enriched in the phosphoproteingroups identified exclusively in SCC-9 and HaCaT cells arealso indicated (Table S2a). Estimation of enrichment of GOterms generated by Fisher's exact test using Perseus applica-tion was also performed for the phosphoprotein groups and

Table 3 – Significant networks for phosphoproteins identified in

ID Top functions Scorea

1 Gene expression, cellular assembly and organization,dermatological diseases and conditions

38 14-3HNRPMLTAC

2 Cellular assembly and organization, developmentaldisorder, hereditary disorder

36 AKTHOMLUCRPS6ZC3

3 Dermatological diseases and conditions,developmental disorder, organismal injury andabnormalities

36 ActiHistPGKSMN

4 DNA replication, recombination, and repair, nucleicacid metabolism, small molecule biochemistry

34 CHDJUNBPA2GRPLP

a Network score is calculated as − log10 (p-value).

phosphosite datasets based on GO molecular function anno-tation category (Table S2b). Both analyses indicated a highprobability that the phosphoproteins identified may have afunction related to regulatory mechanisms occurring in thecell nucleus.

3.3. Pathway analysis

By comparing the phosphosites identified in SCC-9 and HaCaTcells, 1,066 phosphosites with at least one quantified evidenceper cell line were identified as present in both cell lines. Thesephosphosites were corresponding to 1,486 possible proteins.These candidate proteins were analyzed using IPA knowledgebase system (http://www.ingenuity.com) for the identificationof possible common signaling pathways in both SCC-9 andHaCaT cell lines. A number of 1,477 phosphoproteins weremapped through IPA and the corresponding 406 assignedmolecules were included in the pathway prediction analysis,based only on experimental data and highly confidentpredicted annotations. These analysis revealed the compo-nents of the networks assigned to the phosphoproteinsidentified in both SCC-9 and HaCaT cell lines (Table 3). Furtheranalyses of these signaling pathways may contribute to theidentification of cellular mechanisms conserved in both celllines, which may not be specific for tumorigenic cells.

Additional pathways were analyzed through IPA havingthe phosphoprotein accessions from phosphosites identifiedexclusively in SCC-9 or HaCaT cells as input data (Fig. 4),revealing specific interactions and signaling sub-networkswhich may be specific to the tumorigenic SCC-9 cells.

Our results of the statistical significance analysis ofmolecular functions for the phosphoproteins, identified fromphosphosites exclusively in SCC-9, revealed that mechanismsrelated to RNA post-translational modification may bestatistically significant in SCC-9 cells. In HaCaT cells, DNAreplication, recombination and repair appeared as statisticallysignificant molecular functions whereas in SCC-9 cells thismolecular function does not represent a significant class,suggesting that phosphoproteins which are components of

both SCC-9 and HaCaT cell lines.

Molecules in network

-3, ARID1A, Ck2, COL17A1, DEK, HDAC1, HDAC2, Histone h4, HMGA2,NPU, ITGB4, KDM1A, MAP4, Mi2, MLL,NCOR1,NCOR2,P38 MAPK, PLEC,, PRPF4B,Ras homolog, SMARCC1, SMARCC2, SQSTM1, SRRM1, SUDS3,C2, TOP2A, TOP2B, TP63, TRIM28, YAP1,YBX1,ZBTB7A1S1,caspase,CAV2,CSDA,CyclinE,DHCR7,E2f,EIF4B,GAS2L1,HMGA1,ER3,IFI16,IFN Beta,IKK (complex),Interferon alpha, KIAA1967,7L3, MAVS,MFAP1,NFkB (complex), PDCD5, PPP2R5E, PRKD2, RPS6,KA3, SNIP1, SNW1, TBC1D4, TJP2,TSC22D3,UNC93B1,UTP3,WTAP,H13,ZC3H18n,AHNAK,CBX3,CTR9,DHX16,DKC1,DSP,ERK,estrogen receptor,HDGF,one h3, HNRNPK, IgG, JUND, KIDINS220, Lh,MAX, PBRM1, PCDH1,1, PKP1, POLR3E,PRKAR2A,PSIP1,PSMD1,SAFB,SF3B2,SMARCA4,SMN1/2,SRRM2,SSRP1,STMN1,THRAP3,thymidine kinase,TRIM161,CTNND1,CTTN,Cyclin A, DDB2, ERCC5, ERCC6, ERK1/2, HSPB1,, LATS1, LIG1, MCM3,mediator,MLLT4,NCAPD2,NCAPG,NCL,NPM1,4,PCM1,PP1-C,PTPN12,RABL6,Rb,RDBP,RNA polymerase II, Rnr,0, RPLP2, SCRIB, TFIIH, TSPYL2, XPC,ZFC3H1

A B

C D

Fig. 4 – Signaling pathways for identified phosphoproteins. The list of protein accession numbers assigned to the proteinscontaining phosphosites identified by MS was uploaded into the Ingenuity system, and signaling networks and pathwayswere generated through the use of Ingenuity knowledge base for the prediction of interaction partners and significantpathways. The most significant networks generated for the datasets containing phosphoproteins identified in both cell lines(SCC-9 and HaCaT) (A), phosphosites with differential abundance (B) and phosphoproteins exclusively identified in HaCaT(C) or SCC-9 (D) cell lines are shown.

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DNA repair mechanism may be impaired in SCC-9 cells.The absent of this molecular function in the top significantfunctions in SCC-9 cells indicated that phosphorylationevents normally occurring in non-tumorigenic cells maybe absent in tumorigenic cells (Table 4). Further functionalcharacterization of these phosphoproteins may reveal impor-tant regulatory proteins.

The most significant canonical pathways attributed to thephosphoproteins identified in both cell lines and identified

exclusively in HaCaT or SCC-9 cells are summarized inTable 5. Moreover, the sub-cellular location of the phospho-proteins was also assigned based on the IPA knowledge baseand the percentage distribution of the phosphoprotein locali-zation is shown in Fig. 5.

The sub-cellular protein annotation for the dataset ofphosphoproteins identified in common between SCC-9 andHaCaT cell lines showed that most of the phosphoproteins(50%)mayhave a nuclear localization, followed by cytoplasmic

Table 4 – Statistically significant molecular and cellular functions for phosphoproteins containing phosphosites exclusivelyidentified in tumorigenic (SCC-9) or non-tumorigenic (HaCaT) cells.

Molecular and cellular functions

Name p-Value Number of molecules

Phosphosites exclusive for HaCaT cellsDNA replication, recombination, and repair 2.10E−06–3.38E−02 22Gene expression 2.10E−06–3.47E−02 41Cellular assembly and organization 1.49E−05–3.47E−02 37Cellular function and maintenance 1.49E−05–3.47E−02 22Cell cycle 2.74E−05–4.22E−02 31

Phosphosites exclusive for SCC-9 cellsCell morphology 4.09E−07–4.45E−02 20Gene expression 1.27E−04–4.74E−02 36RNA post-transcriptional modification 1.27E−04–4.74E−02 12Cellular assembly and organization 4.51E−04–4.87E−02 33Cellular response to therapeutics 8.54E−04–1.21E−02 2

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localization, which represents 27% of the dataset. However,this percentage is different when we compare the phospho-proteins identified exclusively in SCC-9 or HaCaT cells. SCC-9cells have a reduced percentage of nuclear localized phospho-proteins and more phosphorylated proteins localized to thecytoplasm (Table S3).

3.4. Phosphosite sequence motifs

In order to verify if the phosphosites identified were indeednew phosphosites or have been described previously, weperformed a motif search analysis. Besides the annotation ofphosphosites performed directly by Perseus application, the

Table 5 – Significant canonical pathways generated through the

Pathway name

Phosphosites identified in both HaCaT and SCC-9 cell linesTight junction signalingDNA methylation and transcriptional repression signalingmTOR signalingTelomerase signalingATM signaling

Phosphosites with differential abundanceEpithelial adherens junction signalingTight junction signalingSertoli cell–Sertoli cell junction signalingGerm cell–Sertoli cell junction signalingEndometrial cancer signaling

Phosphosites exclusive for HaCaT cellsProstate cancer signalingSertoli cell–Sertoli cell junction signalingEstrogen receptor signalingInsulin receptor signalingGlioma signaling

Phosphosites exclusive for SCC-9 cellsRhoA signalingATM signalingCaveolar-mediated endocytosis signalingRegulation of actin-based motility by rhoSuperpathway of inositol phosphate compounds

phosphosite sequences were searched against the mostrecent version of the PhosphoSitePlus® database (versionMarch 04th, 2013; www.phosphosite.org) [18] in order tofind previously known phosphosites. From the initial 4,206phosphosites identified in our phosphoproteome analysis,97.5% had a match at the PhosphoSitePlus database (TableS4). Noteworthy, 105 phosphosites were not identified inPhosphoSitePlus database and did not retrieve any knownphosphosite when we used the Motif-x tool (http://motif-x.med.harvard.edu/) [20]. These phosphosites may representnovel candidate sites; however, further experimental valida-tion needs to be performed in order to confirm their functionand phosphorylation status.

use of IPA knowledge base for identified phosphosites.

p-Value Ratio

2.13E−05 14/157 (0.089)1.24E−03 4/23 (0.174)1.72E−03 12/189 (0.063)2.38E−03 8/99 (0.081)3.07E−03 6/61 (0.098)

3.47E−04 4/144 (0.028)4.26E−04 4/157 (0.025)7.1E−04 4/184 (0.022)

5.58E−03 3/157 (0.019)6.63E−03 2/55 (0.036)

3.45E−04 6/91 (0.066)1.02E−03 8/184 (0.043)3.64E−03 6/133 (0.045)3.93E−03 6/131 (0.046)4.91E−03 5/106 (0.047)

4.82E−04 7/115 (0.061)7.12E−04 5/61 (0.082)1.11E−02 4/81 (0.049)1.72E−02 4/86 (0.047)1.99E−02 6/192 (0.031)

A B C

Fig. 5 – Subcellular localization of phosphoproteins.Subcellular localization of phosphoproteins was obtainedbased on the annotation available in the Ingenuityknowledge base. The corresponding percentage ofphosphoproteins annotated to a subcellular localizationcategory is shown for identified phosphoproteins in both celllines (A), phosphoproteins exclusively identified in HaCaTcells (B) and phosphoproteins exclusively identified in SCC-9cells (C).

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3.5. Prediction of co-expressed proteins

The subset of phosphoproteins assigned to the phosphositeswith differential abundance, comprised of seventeen phos-phosites less abundant in SCC-9 cells and forty five phospho-sites more abundant in SCC-9 cells, were uploaded ontoGeneMania plugin in Cytoscape and a search for interactionpartners and co-expressed genes based on the GeneMania

Fig. 6 – Co-expression gene network. A network for the phosphodifferential abundance was generated using GeneMania plugin iwith Cytoscape (v.2.8.3) and GeneMANIA plugin v.3.2 (Human kn21,438 genes, 82,208,385 interactions). Query phosphoproteins (pindicated by green dots and co-expression is indicated by the bl

knowledge base was performed. With automatic weightednetwork prediction and Pearson correlation, it was possible toidentify information on co-expressed proteins/genes. Thenetwork of possible co-expressed proteins/genes was gener-ated based on experimental data previously reported. Fromthe sixty two proteins (gene IDs) uploaded into GeneMania,forty two were predicted to have at least one co-expressedpartner. A network showing the co-expressed genes are shownin Fig. 6 and the references for the gene co-expression patternsare included in Table S7, listing co-expressed genes and thesource of information on the gene expression pattern.

3.6. Manual inspection of phosphorylation sites

Two candidate phosphosites not previously reported showeddifferential abundance and at least one phosphosite withdiffering site localization in SCC-9 and HaCaT cells had theirphosphorylation sites inspected manually. The phosphopep-tide mass spectrum was visualized using the softwareMaxQuant Viewer v.1.3.0.5. Mass spectra for the candidatephosphosites were validated for b- or y-ion series (Supple-mentary Fig. 3).

4. Discussion

In the present study, we have analyzed the phosphoproteomeof two epithelial cell lines, HaCaT and SCC-9, in order toidentify changes in the phosphorylation sites that could helpto explain their distinct behavior regarding cell adhesion,cell migration and collagenase activity as well as tumori-genic properties [9]. Our results indicated the presence of

proteins assigned to the phosphosites, which presentedn Cytoscape. Data analysis and visualization were performedowledge data base v. 2012-08-02; containing 286 networks,roteins identified and indicated by their gene identifiers) areue edges. Gray nodes indicate predicted proteins/genes.

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phosphosites with differential abundance between the twocell lines and revealed possible candidate phosphoproteinsthat may contribute to the cancer development and itsprogression. We observed that many phosphoproteins iden-tified may be directly or indirectly related to nucleic acidbinding or chromatin binding events, indicating a potentialrole associated to the transcriptional control of the geneexpression in tumorigenic and non-tumorigenic cells. Theoverall overrepresented GO molecular function categoriesannotated for phosphoproteins, only identified in HaCaTcells, showed enrichment for kinase binding term, whileSCC-9 cells showed enrichment for 1-phosphatidylinositol4-kinase (PI4K) terms (Supplementary Fig. 4). PI4K proteinsare up regulated in many cancers and their function inregulating the Protein kinase C (PKC) and Protein kinase B(Akt) has been previously demonstrated in cancer cells.The signaling cascades controlled by PI4K regulatingPhospholipase C and 1-phosphatidylinositol 3-kinase (PI3)pathways have already been described in cancer and itsfunction has been related to angiogenesis, metastasis andcell proliferation [23].

In addition, according to the information from Ingenuityknowledge base, most phosphosites we identified in the wholephosphoproteome, comprising phosphosites identified in bothSCC-9 and HaCaT cells, belong to proteins with nuclearlocalization (Fig. 5). Moreover, the phosphoproteins identifiedexclusively in tumorigenic SCC-9 cells have a higher percentageof cytoplasm proteins compared to non-tumorigenic HaCaTcells. This may indicate a change in the PTM profile intumorigenic cells, with a general reduction of nuclear phospho-proteins in SCC-9 cells. It has been previously shown thatnuclear organization is modified in cancer cells and manymechanisms related to the control of gene expression aremodulated during cancer development [24]. The simultaneousregulation of phosphorylation events in response to thealterations in the nuclear environment of tumorigenic cellsmay suggest that phosphorylatedproteinsmay be related to thetranscriptional regulation of tumor-related genes. Other evi-dences on the pathway analysis indicated a higher significanceof the canonical pathways RhoA (p value = 4.82E−04) and ataxiatelangiectasia-mutated (ATM) signaling (p value = 7.12E−04) inSCC-9 cells (Table 5). RhoApathway is related to themodulationof cytoskeletal dynamics and cell cycle progression. RhoAup-regulation has been observed in several tumors, such asgastric, lung and melanomas and it was identified as beingimportant for the control of cellular Gi–S cell cycle arrest ingastric cancer, by modulating the activity of proteins fromcyclin-dependent kinase inhibitor (INK4) family [25]. Changeson cell cycle regulation may also lead to alterations on DNArepair processes. It is known that human cancer cells showstrong alterations in chromatin structure and architecturewhich may lead to the activation of DNA repair mechanismsinvolvingmolecules such as ATM protein kinase which triggersmany signaling cascades responsible for regulating the DNArepair mechanisms [26]. Molecular functions related to“cell morphology” (p value = 4.09E−07) and “gene expression”(p value =1.27E−04) were highly significant in SCC-9 cellswhereas HaCaT cells had “DNA replication”, “recombination”,“DNA repair” (p value = 2.10E−06) and “gene expression”(p value = 2.10E−06) as the most significant ones (Table 4).

Furthermore, our results revealed the presence of phos-phosites with varying abundance and differing phosphoryla-tion status in HaCaT and SCC-9 cells. Some of thesephosphopeptides may be modulated in opposite directionsin HaCaT and SCC-9 cells. Of note, two of these phosphositesbelong to the Lamina-associated polypeptide 2 (LAP2) isoformalpha protein and showed to have phosphosites with oppositerelative abundance between SCC-9 and HaCaT cells (Fig. 2).Lamina-associated polypeptide 2 is a type II integral protein ofthe inner nuclear membrane, which has been related tochromatin binding, providing docking sites, which may beinvolved in the structural chromosome reorganization[24,27]. It has been suggested that LAP2 can function as aregulator of the lamin assembly in normal nuclear envelope[28]. Evidences suggested that LAP2 beta interacts withmany transcriptional regulators leading to repression oftarget transcription factor genes [24]. It is then possiblethat LAP2 alpha also exerts a similar function in modulatinggene expression in tumorigenic SCC-9 cells. The identifica-tion of LAP2 interacting partners can assist in revealingthe chromosomal regions affected by the disruption ofchromosomal structure during cancer development. Previ-ous evidences showed that mechanisms of initiation andexecution of apoptosis are also related to organizationalalterations of nuclear lamins. Lamin assembly state maythus contribute to the proper regulation of cell apoptosis,which is one of the main cellular processes which sufferprofound alterations in tumorigenic cells. With the cleavageof lamins by caspases, the apoptosis may occur with thedisassembling of the lamina structure [29]. Moreover, thetwo phosphosites we identified belonging to LAP2 protein,“EQGTES(ph)RS(ph)STPLPTISSSAENTR” and “LREQGTES(ph)RS(ph)S(ph)TPLPTISSSAENTR”, may have a differing biolog-ical role due to alterations in their phosphorylation pattern,which may be modulated in tumorigenic cells. The di-phosphorylated form of this phosphopeptide has beenidentified as more abundant in SCC-9 cells, whereas thetri-phosphorylated form has been significantly more abundantin HaCaT cells. The mass spectra of these two phosphositeswere manually inspected (Supplementary Fig. 3). These twophosphopeptides have not been completely described so faraccording to the information deposited in the PeptideAtlasrepository. Previous evidences are available for the identifi-cation of the phosphopeptide “SS(ph)TPLPTISS(ph)SAENTR”from LAP2 and are deposited in the PhosphoPep repository(http://www.phosphopep.org/index.php). Nevertheless, thetri-phosphorylated form has not been described yet. Anothercandidate phosphopeptide belongs to a serine–argininerepetitivematrix protein 2 (SRRM2or SRm300) andare annotatedas localized in the nucleus speckle. The phosphoproteomeresults revealed that two forms of the phosphosites identifiedin SRRM2 have differential abundance in SCC-9 and HaCaTcells. The tri-phosphorylated sequence “NHS(ph)GS(ph)RT(ph)PPVALNSSR” was identified to be more abundant in SCC-9cells whereas a highly phosphorylated sequence “HGGS(ph)PQPLATT(ph)PLS(ph)QEPVNPPSEAS(ph)PT(ph)R” was identifiedto be more abundant in HaCaT cells. The peptide sequence“NHSGSRTPPVALNSSR” has been previously reported astriphosphorylated and the site of the phosphorylation iscoincident with the phosphorylation sites we identified. The

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tri-phosphorylated sequence “HGGS(ph)PQPLAT(ph)TPLSQEPVNPPSEAS(ph)PTR” was identified in previous phosphoproteomeexperiments; however, we identified in HaCaT cells theform of the same peptide with five phosphorylation events.The sequences of the phosphorylated peptides previouslyidentified in other phosphoproteome experiments are availablein PhosphoPep repository (http://www.phosphopep.org/index.php). SRRM2 has been reported to play a role in pre- andpost-mRNA splicing in the nuclear matrix environment [30] andit may be part of a multi-protein complex. Recently, SRRM4proteins have been reported as part of the alternative splicingregulatory machinery and its function seems to be important inmodulating gene expression of target genes via switchingthe functional role of transcriptional regulatory proteins duringneural differentiation [31]. No evidences were found fullydescribing the SRRM2 function in cancer. However, tran-scriptome analysis of human colorectal cancer showed thatSRRM2 gene expression is significantly modulated in cancercells, suggesting that alterations on normal splicing activityin cancer tissues may be related to alterations in splicingfactors [32]. Recent phosphoproteome analysis of squamouscell carcinoma in mouse has revealed that many phospho-sites are modulated in cancer cells, including phosphositesfrom LAP2 and SRRM2 [6]. Within the same study, proteinsrelated to regulation of translation and gene expressionshowed increased levels of phosphorylation [6]. Altogether, ourresults indicate that tumorigenic SCC-9 and non-tumorigenicHaCaT cell lines have differing phosphoproteome profiles. Weobserved that some candidate phosphosites may be importantto the assembly of the nuclear environment andmaymodulateproper nucleus and chromatin assembly. The changes in thephosphorylation sites found in our study may be important forthe regulation of the chromatin structure and may be related tothe maintenance of the heterochromatin as a stable stateusually found in tumorigenic cells, but further investigation isrequired to validate this hypothesis. Finally, themodifications onspecific phosphorylation sites identified may help to explain thedistinct behavior of the epithelial cell lines and may have director indirect effects on tumor development and its progression.

5. Conclusion

Within this study we have identified and compared thephosphoproteome profile a tumorigenic cell line (SCC-9) anda non-tumorigenic cell line (HaCaT), both with epithelialorigin. By performing a phosphopeptide enrichment withtitanium dioxide and protein identification by LC–MS/MSmore than 3,000 phosphosites were identified and quantifiedby label-free analyses. We compared the phosphosites identi-fied in both cell lines and we verified the presence ofphosphosites with differential abundance. We observed anoverrepresentation of proteins related to nuclear function,which suggest a possible regulatory role for the phosphopro-teins identified. This work may contribute to the identificationof the repertoire of proteins found to be common betweentumorigenic and non-tumorigenic cells, also revealing theidentity of phosphoproteins exclusively found in tumorigeniccells, complementing our understanding on the developmentand progression of Oral Squamous Cell Carcinoma.

Supplementary data to this article can be found online athttp://dx.doi.org/10.1016/j.jprot.2013.10.039.

Author contributions

MB, NS and APL designed the study; FVW and APL drafted themanuscript; FVW and APL performed the phosphoproteomedata analysis; MB and JLZ prepared the cell cultures andsamples; APL, RD and BAP performed the mass spectrometricexperiments. The manuscript was written through contribu-tions of all authors. All authors have given approval to thefinal version of the manuscript.

Funding sources

This work was supported by FAPESP Grants: 2009/54067-3,2010/19278-0, and 2009/52833-0 and CNPq Grants: 470567/2009-0, 470549/2011-4 and 301702/2011-0.

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