RESEARCH

Quantitative tandem massskin tissue reveals putativ

2,

ritis, which takes its name from its association with thecutaneous, autoimmune inflammatory disease, psoriasis.

disease [1-3]. The diagnosis of PsA presents a challenge,largely due to its heterogeneous clinical presentation [4,5];

CLINICALPROTEOMICS

Cretu et al. Clinical Proteomics 2015, 12:1http://www.clinicalproteomicsjournal.com/content/12/1/1proposed [7-11]; however there exists no single or panelToronto, Ontario, CanadaFull list of author information is available at the end of the articleIt occurs in 30% of psoriasis patients and has a predictedprevalence of up to 1% in the general population. PsA isa complex, potentially disabling musculoskeletal disorderoften arising early in age. Patients with PsA have an

however, early diagnosis and prognosis of PsA is essentialfor prevention of joint damage and disability [6].The key to early diagnosis is a better recognition of PsA

in patients with psoriasis, since its presence indicates ahigh risk for current or future development of PsA [3].Soluble biomarkers represent an ideal means for screeningpatients for PsA. With improvements in high-throughputgenomic platforms, a number of putative markers, rangingfrom susceptibility genes to mRNA profiles have been

* Correspondence: vchandra@uhnresearch.ca5Psoriatic Arthritis Program, Centre for Prognosis Studies in the RheumaticDiseases, Toronto Western Hospital, 399 Bathurst Street, Room 1E 416,Toronto, Ontario M5T 2S8, Canada6Division of Rheumatology, Department of Medicine, University of Toronto,Background: Psoriatic arthritis (PsA) is a distinct inflammatory arthritis occurring in 30% of psoriasis patients.There is a high prevalence of undiagnosed PsA in psoriasis patients; therefore, identifying soluble biomarkers forPsA could help in screening psoriasis patients for appropriate referral to a rheumatologist. Potential PsA biomarkerslikely originate in sites of inflammation, such as the skin, and subsequently enter systemic circulation. Our goal wasto identify candidate PsA biomarkers by comparing the proteome of skin biopsies obtained from patients with PsAto that from patients with psoriasis without PsA.

Methods: Skin biopsies were obtained from involved and uninvolved skin of 10 PsA and 10 age/gender-matchedpsoriasis patients without PsA (PsC). Using strong cation exchange chromatography, followed by label-free quantitativetandem mass spectrometry, we characterized the proteomes of pooled skin samples. Extracted ion current intensitieswere used to calculate protein abundance ratios, and these were utilized to identify differentially regulated proteins.

Results: Forty-seven proteins were elevated in PsA-derived skin compared to PsC-derived skin. Selected reactionmonitoring assays were developed to quantify these potential PsA markers in individual skin samples, and 8 markerswere confirmed in an independent sample set. ITGB5 and POSTN were measured in serum samples from 33 PsA and15 PsC patients, using enzyme-linked immunosorbent assays. ITGB5 was significantly elevated in PsA serum (P < 0.01),and POSTN showed a trend. ITGB5 and POSTN correlated significantly in both patient groups (r = 0.472, P < 0.001).

Conclusion: Proteomic analysis of PsA and PsC skin identified eight new candidate biomarkers. These markers needto be validated with a larger and independent cohort, in order to delineate their clinical utility in PsA patients. Theseproteins may also uncover unknown aspects of PsA pathobiology.

Keywords: Psoriatic arthritis, Cutaneous psoriasis, Proteomics, Mass spectrometry, Biomarker

BackgroundPsoriatic arthritis (PsA) is a distinct inflammatory arth-

increased risk for a spectrum of co-morbidities, such asobesity, metabolic syndrome, diabetes and cardiovascularbiomarkersDaniela Cretu1,2, Kun Liang3, Punit Saraon1,2, Ihor Batruch

Abstract 2015 Cretu et al.; licensee BioMed Central. TCommons Attribution License (http://creativecreproduction in any medium, provided the orDedication waiver (http://creativecommons.orunless otherwise stated.Open Access

-spectrometry ofe psoriatic arthritis

Eleftherios P Diamandis1,2,4 and Vinod Chandran5,6*his is an Open Access article distributed under the terms of the Creativeommons.org/licenses/by/4.0), which permits unrestricted use, distribution, andiginal work is properly credited. The Creative Commons Public Domaing/publicdomain/zero/1.0/) applies to the data made available in this article,

Cretu et al. Clinical Proteomics 2015, 12:1 Page 2 of 8http://www.clinicalproteomicsjournal.com/content/12/1/1of specific markers, or mediating factor(s). Much of theresearch, therefore, focuses on the discovery and validationof PsA biomarkers [7,12-14]. Identifying these factorswould not only facilitate diagnosis and prognosis of PsA,but also provide further insight into disease pathogenesis.Mass spectrometry (MS)-based quantitative proteomic

approaches are well-suited for the discovery of proteinmediators and biomarkers of disease [15,16]. Specifically,label-free quantification (LFQ) methods have been recentlyoptimized, where quantification is based on the differentialpeak intensity [extracted ion current (XIC)] of the peptidesin each MS scan [17,18]. Such experiments often resultin tens to hundreds of candidate biomarkers, therefore, inthis context of biomarker discovery, high-throughput massspectrometry-based proteomics is a powerful tool forobtaining disease-specific proteome profiles of biologicalmaterials [19]. While human plasma represents a diverseproteome and is an excellent source of potential diseasemarkers, proteins secreted by tissues are diluted in blood,and are often undetectable by current MS methods [19].Much interest has been given to the analysis of proximalfluids and tissues, such as synovial fluid and skin [19-21].Cutaneous psoriasis develops simultaneously or precedes

the onset of PsA in up to 90% of PsA patients, and in orderto move forward in the search for PsA screening bio-markers, we must consider the preceding cutaneouspsoriasis stage in PsA patients. Therefore, hypothesizingthat there are differences in the skin proteome of patientswith PsA compared to those with psoriasis but withoutPsA (PsC), comparative analysis of skin between thesetwo patient groups represents a reasonable experimentalworkflow. In a pilot study, our group demonstrated thatproteins elevated in the inflamed skin, are likewise up-regulated at the serum level, and may serve as putativemarkers of psoriasis [22].In the current study, we performed label-free quantita-

tion of skin proteins from PsA and PsC patients. Usingselected reaction monitoring assays (SRM) we confirmedthe elevation of some proteins in an independent set ofsamples from patients with PsA. Following a small-scalevalidation in serum using enzyme-linked immunosorbentassays (ELISA), we confirmed a significant elevation of 5Integrin (ITGB5) in the serum of PsA patients. Periostin(POSTN) also showed a similar trend. These proteins mayserve as potential PsA biomarkers and also shed new lightinto the pathogenesis of PsA.

ResultsDelineating the PsA skin proteomeOur LC-MS/MS analysis yielded 1922 quantifiable proteins(Additional file 1: Table S1). Students t-tests, and a falsediscovery rate (FDR) threshold of 0.2, were utilized to iden-

tify upregulated proteins between the PsA and PsC lesionalgroups (PsA L, and PsC L, respectively). This comparativeanalysis generated a total of 62 proteins (Additional file 2:Table S2). Generally, these proteins exhibited a fold changeratio above 4.0. Comparison between PsA and PsC non-lesional skin (PsA N, and PsC N, respectively), at thesame FDR, demonstrated elevated expression of 131proteins (Additional file 2: Table S2). By comparing theproteins identified from the two independent analyses(PsA L vs PsC L, and PsA N vs. PsC N), only 7 of theseproteins were common (Additional file 2: Table S2). Thesewere PSME3, C1QC, RENBP, GRHPR, POLE, POSTN,and IGLV3-21.Since our scope was to identify potential biomarkers

present in PsA skin, we decided to focus on the 62 pro-teins overexpressed in the lesional PsA skin, whichincluded the seven proteins elevated in non-lesionalskin, since they are more likely to represent mediatorsand potential biomarkers of PsA. We further focused onproteins displaying strong expression in skin, bone, andimmune regulatory cells, and excluded immunoglobulins,unknown proteins and high abundance serum proteinsfrom further analysis. Additional file 3: Table S3 presentsthe final list of 47 proteins, corresponding fold changes(FC) between PsA and PsC samples, P-Values and FDRvalues. These were then assessed and quantified, using amultiplexed selected reaction monitoring assay, in individ-ual skin samples included in the discovery set (Set I), aswell as in an independent set of 10 samples (Set II).

SRM Verification of putative markers in individual skinsamplesWe developed a multiplexed SRM assay to verify thedifferences in protein expression between lesional PsAand PsC skin. Assays were developed for 47 peptidesrepresentative of the 47 proteins with increased expres-sion in the skin of PsA patients, as well as 4 peptidesrepresenting 2 housekeeping proteins (ACTB, TUBB)(Additional file 4: Table S4). Consistent with our LC-MS/MS analysis of the pooled samples, overexpression of 12out of the 47 proteins was also verified in the individualPsA lesional skin samples (Set I), when compared tolesional PsC samples. Each sample consisted of two tech-nical replicates. The mean fold change of each confirmedprotein in the lesional and non-lesional PsA and PsC skinsamples, as well as the associated P-values are depicted inTable 1. The proteins included C16ORF62, SNCA, LZIC,SRP14, ITGB5, POSTN, SRPX, FHL1, PPP2R4, CPN2,GPS1, and PAFAH1B2. The distribution of these, and thehousekeeping proteins across the Set I skin samples, arerepresented in Additional file 5: Figure S1.Additionally, we further confirmed the elevation of 8

of the aforementioned 12 proteins, in an independentset of 5 PsA, and 5 PsC lesional skin samples (Set II). In

this case, we utilized a heavy-labeled peptide in order toobtain the absolute concentration of these peptides in

Table 1 Fold change (FC) of candidate markers in Set I and Set II* skin following SRM quantification

Set I Set II

Lesional Non-lesional Lesional

Protein name PsA:PsC FC** P-value*** PsA:PsC FC P-value PsA:PsC FC P-value

CPN2 17.4

POSTN in PsC serum (Spearman r = 0.637, P = 0.013),and in PsA serum (Spearman r = 0.433, P = 0.012). Figure 2displays the correlation between POSTN and ITGB5 in allsamples (Spearman r = 0.472, P < 0.001).

DiscussionRecent advances in mass spectrometry-based proteomicsfacilitated the identification of putative novel biomarkersand mediators from a variety of tissues, and for variousclinical applications [15,16,23]. In this study, we conductedhigh-throughput quantitative proteomics to identify differ-entially expressed proteins between skin derived fromPsA and PsC patients. According to our filtering criteria,forty-seven proteins were elevated in the PsA group, whencompared to the PsC group. Eight proteins were verifiedusing a multiplexed selected reaction monitoring assay, inan independent skin sample set. None of these potential

Periostin is a matricellular protein belonging to the fasci-lin family [26]. It interacts with several integrin moleculeson cell surfaces, one of which is 55 Integrin, and providessignals for tissue development and remodeling [27]. Morespecifically, it is thought that POSTN interacts with 55 toinduce pro-inflammatory cytokine production via the Akt/NF-B signaling pathway [28]. In support of this, deficiencyof POSTN or inhibition of 5 integrin (ITGA5) preventeddevelopment or progression of skin inflammation in anatopic dermatitis mouse model [28]. Additionally, POSTNhas been shown to also act on immune cells, leading totheir enhanced transmigration, chemotaxis, and adhesion[29], all of which further implicate this molecule in inflam-matory processes relevant to PsA.Apart from acting as a POSTN ligand (along with

ITGA5), ITGB5 has also been implicated in rheumatoidarthritis, where it serves as a ligand for Cyr61 [30]. Cyr61is a molecule secreted by fibroblast-like synoviocytes in

Cretu et al. Clinical Proteomics 2015, 12:1 Page 4 of 8http://www.clinicalproteomicsjournal.com/content/12/1/1markers has been described before in the context of PsAor psoriasis. Since serum measurement of these proteinsusing SRMs is not efficient due to the high complexityof the fluid [18], we utilized available enzyme-linkedimmunosorbent assays to measure two biomarker can-didates in serum (ITGB5, and POSTN).Cumulative evidence strongly supports the involvement

of Interleukin (IL)-23/IL-17 axis in the pathogenesis ofPsA, and a number of compounds that target componentsof these pathways have been recently used in PsA clinicaltrials. IL-23 acts synergistically with IL-6 and TGF- topromote rapid Th17 development and IL-17 release[24,25], which, in turn, plays a central role in sustainingchronic inflammation [24]. Both POSTN and ITGB5have been implicated with this pathway.Figure 2 Correlation between ITGB5 and POSTN across the PsA and PsCr indicates the Spearmans rank correlation coefficient.the joint, and stimulates IL-6 production via ITGA5-ITGB5/Akt/NF-B signaling pathway [29]. As describedearlier, IL-6, along with IL-23 and TGB-, trigger Th17differentiation and IL-17 production [24,25] in inflamma-tory processes, including PsA. Based on this data, wesuggest that POSTN and ITGB5 are attractive moleculesto investigate further as PsA biomarkers.Following a small-scale serum validation of POSTN and

ITGB5, we determined that only ITGB5 was significantlyelevated in PsA serum, although POSTN also showed atrend. Additionally, Spearman correlation showed thatserum ITGB5 correlates well with POSTN (r = 0.472,p < 0.001), which indicates that these two markers may,in the future, be used as part of a panel of markers toscreen for PsA in PsC patients.serum sets. Dots represent serum samples from individual subjects.

Cretu et al. Clinical Proteomics 2015, 12:1 Page 5 of 8http://www.clinicalproteomicsjournal.com/content/12/1/1Although our findings are promising, the work reportedhere has some limitations. First, pooling of the skinsamples in the discovery phase has advantages and dis-advantages. While pooling allows for a more extensivecoverage of disease heterogeneity, by increasing thelikelihood of identifying proteins that are otherwiseundetectable in some individual samples, it may also maskmeaningful discrepancies among the different individualskin proteomes [19,31]. To minimize this effect, sampleswere pooled to obtain two distinct pools in both, PsA andPsC groups. Additionally, all pool-derived candidates werefurther examined in all individual samples using a targetedand more sensitive mass spectrometry technique. As ourresults indicate, the correlation between the discovery dataand SRM data is not ideal, whereby only 12 proteins wereverified in the discovery set. This is due in part, to thepooling effects previously discussed. Our SRM data fromindividual samples identified several skin samples that hadprominently higher protein concentrations. These samplesmost probably affected (increased) the final concentrationof proteins in the pooled samples, which were used forour initial selection of candidates. Thus, analysis of indi-vidual samples via SRM assay allowed for elimination ofsuch artifacts.Second, the identified markers were only tested on a

small number of serum samples (n = 48), and only 20 ofthese were distinct from the Set I and Set II sample sets.Therefore, to assess their accuracy in serum, thesemarkers still need to be tested in a large-scale verificationstudy. In addition, as discussed previously, only two of theexisting eight proposed markers have been investigated inserum due to the lack of ELISAs or antibodies for the rest.Hence, strategies to enable measurement of the remainderof the markers will be employed in the future.Finally, the 47 proteins we investigated using SRM, repre-

sent few of the candidates we have presently identified. Pro-teins that were elevated in non-lesional skin also representinteresting candidates, and must be measured in the future.Taken together, our current observations are consistent

with the notion that label-free quantitative LC-MS/MScan be utilized to quantify proteins in tissues, which canthen be shed into the circulation and serve as serummarkers of PsA. Further studies to validate these findingsare underway, in a larger and independent serum cohort.Investigating these proposed markers further, may not onlyresult in the identification of PsA screening biomarkers,but may also uncover aspects of PsA pathobiology that arecurrently unknown.

MethodsSkin proteomic analysisClinical samples

Samples were collected with informed consent after re-search ethics board approval from the University HealthNetwork, Toronto, Canada. For the discovery phase, skinbiopsies were obtained from 10 cases with PsA (6 males,4 females; age range 38-73 years) and 10 PsC patients(6 males, 4 females; age range 28-77 years) (Set I). PsApatients had psoriasis and satisfied the CASPAR classifica-tion criteria [32], while the PsC patients were assessedby a rheumatologist, to exclude PsA. Patients were notundergoing treatment with methotrexate (MTX) or anti-TNF agents. One 6mm punch biopsy was obtained fromunaffected (non-lesional) skin, and one from affected(lesional) skin from each PsA and PsC patient, amountingto a total of 40 samples.For the verification (quantification) phase, an independ-

ent set of skin samples was obtained from 5 PsA patients(all males; age range 49-63 years), and 5 PsC patients(3 males, 2 females; age range 49-67 years) (Set II). Inclu-sion criteria were the same as described above.For the small-scale validation, serum samples were

obtained from 33 PsA patients (22 males, 11 females;age range 21-76 years), and 15 PsC controls (9 males, 6females, age range 28-77 years). Inclusion criteria werethe same as described above.

Pre-analytical sample processingSkin samples were snap-frozen in liquid nitrogen andstored at -80C until use. Samples were suspended in0.05% RapiGest (Waters, Milford, MA, USA) buffer, andthe tissue was homogenized and sonicated for proteinextraction. The tissue lysates were spun at 11,000g andtotal protein was measured by the Bradford assay (PierceBiotechnology, Rockford, IL, USA), in the resulting super-natants. Equal protein amounts from each sample werepooled to create eight different pools of five samples each[2 PsA lesional (PsA L) vs. 2 PsA non-lesional (PsA N) vs.2 PsC lesional (PsC L) vs. 2 PsC non-lesional (PsC N)].Proteins in each pool were denatured and reduced with5 mM dithiothreitol at 60C for 45 minutes and alky-lated with 15 mM iodoacetamide, in the dark, at roomtemperature, for 45 minutes. Sequencing grade trypsin(Promega, Madison, WI, USA) was added in a 1:50 (tryp-sin: protein) ratio, and allowed to digest for 18 hoursat 37C. Trifluoroacetic acid (1%) was added to cleaveRapiGest and inhibit trypsin activity, and samples werecentrifuged at 11,000g for 20 minutes prior to highperformance liquid chromatography (HPLC) using strongcation exchange (SCX), to reduce peptide mixture com-plexity. During the initial stages of SCX, buffer blankswere run after each sample, and the resulting fractionswere assessed for peptide carryover; apart from peptidescorresponding to a few high abundance proteins, we foundvery few peptides (data not shown). The peptide fractionsresulting from HPLC-SCX were collected, pooled, and

subjected to liquid chromatography and tandem massspectrometry (LC-MS/MS), and was followed by protein

Gene names of the upregulated proteins were checked

atio

Cretu et al. Clinical Proteomics 2015, 12:1 Page 6 of 8http://www.clinicalproteomicsjournal.com/content/12/1/1against gene [BioGPS (http://biogps.org/#goto=welcome)[34]], and protein [Human Protein Atlas (http://www.proteinatlas.org/) [35] databases, to identify proteins withstrong expression in PsA-associated tissues and cell types(skin, bone, immune cells). The Plasma Proteome Data-identification and quantification. Experimental detailsregarding HPLC-SCX, LC-MS/MS, and protein identifi-cation and quantification, were previously published[31], and are also outlined in Additional file 7.

Bioinformatic analysisTo detect upregulated proteins in the PsA group, one-sided Students t-tests were used between PsA L and PsCL, and PsA N and PsC N after log transformation of XICvalues. Only proteins displaying significant differences[False discovery rate (FDR)

21. Tilleman K, Van Beneden K, Dhondt A, Hoffman I, De Keyser F, Veys E, et al.

Cretu et al. Clinical Proteomics 2015, 12:1 Page 7 of 8http://www.clinicalproteomicsjournal.com/content/12/1/1Additional file 5: Figure S1. Distribution of markers across the PsA andPsC skin Set I. Dots represent skin samples from individual subjects; thinhorizontal lines depict the mean, and vertical lines the SD. **** indicatesP < 0.0001; ***P < 0.001; **P < 0.01; *P < 0.05; ns:non-significant.

Additional file 6: Figure S2. Distribution of markers across the PsA andPsC skin Set II. Dots represent skin samples from individual subjects; thinhorizontal lines depict the mean, and vertical lines the SD. **** indicatesP < 0.0001; ***P < 0.001; **P < 0.01; *P < 0.05; ns:non-significant.

Additional file 7: Supplementary Materials and Methods.

AbbreviationsACE: Angiotensin-converting enzyme; ACN: Acetonitrile; ACTB: Beta-actin;ACTH: Adrenocorticotropic hormone; C16ORF62: Chromosome 16 openreading frame 62; C1QC: Complement C1q; CASPAR: Classification criteriafor Psoriatic Arthritis; CPN2: Carboxypeptidase N, polypeptide 2;ELISA: Enzyme-linked immunosorbent assay; FA: Formic Acid; FC: Fold change;FDR: False discovery rate; FHL1: Four and a half LIM domain1 1; GPS1: G-proteinpathway suppressor 1; GRHPR: Glyoxylate reductase/hydroxypyruvate reductase;HPLC: High-performance liquid chromatography; IGLV3-21: ImmunoglobulinLambda Variable 3-21; IL: Interleukin; ITGA5: Integrin alpha 5; ITGB5: Integrin-beta5; LC-MS/MS: Liquid chromatography and tandem mass spectrometry; LFQ:Label-free quantification; LZIC: Leucine Zipper and CTNNBIP1 Domain-ContainingProtein; MS: Mass-Spectrometry; MTX: Methotrexate; PAFAH1B2: Platelet-activatingfactor acetylhydrolase 1b, catalytic subunit 2; POLE: DNA Polymerase II Subunit A;POSTN: Periostin; PPP2R4: Protein phosphatase 2A activator, regulatory subunit 4;PsA L: Lesional Psoriatic Arthritis; PsA N: Non-lesional Psoriatic Arthritis;PsA: Psoriatic Arthritis; PsC L: Lesional Cutaneous Psoriasis; PsC N: Non-lesionalCutaneous Psoriasis; PsC: Cutaneous Psoriasis; PSME3: Activator of MulticatalyticProtease Subunit 3; SCX: Strong cation exchange; SD: Standard deviation;SNCA: Alpha synuclein; SRM: Selected reaction monitoring; SRP14: Signalrecognition particle 14kDa; SRPX: Sushi-repeat containing protein;TFA: Trifluoroacetic acid; TGF: Transforming growth factor; TNF: Tumor necrosisfactor; TUBB: Beta-tubulin; XIC: Extracted Ion Current.

Competing interestsThe authors declare that they have no competing interests.

Authors contributionsDC, VC, and EPD participated in the conception and design of the study. KLperformed statistical analysis. VC provided PsA and PsC samples. DC, PS, and IBperformed proteomic analysis, and developed SRM assays. DC and IB analyzeddata and interpreted proteomic results. DC developed and performed ELISAs,and interpreted data. DC drafted the manuscript. DC, KL, EPD and VC preparedthe final version of the manuscript. All authors read and approved the finalmanuscript.

AcknowledgmentsWe would like to thank Dr. Dafna Gladman for her support and helpfulsuggestions, and Daniel Pereira and Fatima Abji for their ongoing assistancein sample collection.

Funding sourcesThis work was supported by grants from the Canadian Institutes of HealthResearch (CIHR) [Funding Reference Number 115719], Abbvie Canada, TheKrembil Foundation, and the Laboratory Medicine and Pathobiologyprogram at University of Toronto.

Author details1Department of Laboratory Medicine and Pathobiology, University ofToronto, Toronto, Ontario, Canada. 2Department of Pathology andLaboratory Medicine, Mount Sinai Hospital, Toronto, Ontario, Canada.3Department of Statistics and Actuarial Science, University of Waterloo,Waterloo, Ontario, Canada. 4Department of Clinical Biochemistry, UniversityHealth Network, Toronto, Ontario, Canada. 5Psoriatic Arthritis Program, Centre

for Prognosis Studies in the Rheumatic Diseases, Toronto Western Hospital,399 Bathurst Street, Room 1E 416, Toronto, Ontario M5T 2S8, Canada.6Division of Rheumatology, Department of Medicine, University of Toronto,Toronto, Ontario, Canada.Chronically inflamed synovium from spondyloarthropathy and rheumatoidarthritis investigated by protein expression profiling followed by tandemmass spectrometry. Proteomics. 2005;5:224757.Received: 24 September 2014 Accepted: 15 December 2014Published: 13 January 2015

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doi:10.1186/1559-0275-12-1Cite this article as: Cretu et al.: Quantitative tandem mass-spectrometryof skin tissue reveals putative psoriatic arthritis biomarkers. ClinicalProteomics 2015 12:1.Submit your manuscript at www.biomedcentral.com/submit

AbstractBackgroundMethodsResultsConclusion

BackgroundResultsDelineating the PsA skin proteomeSRM Verification of putative markers in individual skin samplesSmall-scale ELISA validation in serumCorrelation amongst biomarkers

DiscussionMethodsSkin proteomic analysisClinical samplesPre-analytical sample processingBioinformatic analysis

Verification of identified proteins using SRMValidation of verified proteinsEnzyme-linked immunosorbent assays (ELISA)Statistical analysis

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