Review

The cancer secretome, current status and ocolorectal cancer context

. Lsteer In

Cancer secretomeProteomicsSecreted protein biomarkerTumor microenvironmentClinical application

ts ocangt be detectable in blood or other biouids. Furthermore, the cancer secretome inicroenvironment that plays a key role in tumor promoting processes such as an-

h with

Biochimica et Biophysica Acta 1834 (2013) 22422258

Contents lists available at ScienceDirect

Biochimica et Bi

j ourna l homepage: www.e lsmore than one million new cases for each in 2008 [1,2]. The overallincidence of cancer is still rising due to aging, population growthand an increase in cancer-related habits, such as smoking and alcoholconsumption, in economically developing countries [2]. Survival ratesdepend on tumor type, age, disease stage at initial diagnosis and gen-der (see also Fig. 1), as well as on ethnic race and world region [3,4].

Cancer is a result of the accumulation of genetic damage (eitherinduced and/or inherited) [5]. As a consequence, carcinogenesis is alengthy, multi-step process that requires a series of essential geneticaberrations in order to give rise to an invasive tumor. In theory, thiswould allow for sufcient time to detect the tumor and provide plen-tiful biological targets to attack the tumor. In fact, in most cases atumor develops without symptoms and thus remains undetecteduntil the nal phases. Furthermore, the diverse genetic aberrationsare hard to fully map in a diagnostic setting for each individual pa-tient and lead to heterogeneous tumors that are difcult to eradicate.

One way to improve clinical management of cancer is through

Abbreviations: LC-MS/MS, liquid chromatography tandem mass spectrometry; MS,mass spectrometry; SCLC, small cell lung cancer; NSCLC, non-small cell lung cancer;AC, adenocarcinoma; SCC, squamous cell carcinoma; NAF, nipple aspirate uid; TIF,tumor/tissue interstitial uid; CM, conditioned medium; (M)PE, (malignant) pleuraleffusion; 2D-(DI)GE, two-dimensional (difference in) gel electrophoresis; 1D-GE,

one-dimensional gel electrophoresis; miR, microRNA; Wreaction monitoring; NIF, normal interstitial uid; IHC, This article is part of a Special Issue entitled: An Up Corresponding author at: OncoProteomics Laborat

Oncology, VU University Medical Center, De BoelelaanThe Netherlands. Tel.: +31 204442340.

E-mail address: c.jimenez@vumc.nl (C.R. Jimnez).URL: http://www.oncoproteomics.nl (C.R. Jimnez).

1570-9639/$ see front matter 2013 Elsevier B.V. Alhttp://dx.doi.org/10.1016/j.bbapap.2013.01.029an estimated 7.6 millionlung, breast and colorec-es with an incidence of

have not improved accordingly and cancer is still a deadly disease.Clearly, the cumulative worldwide cancer burden has great socialand economic consequences.deaths worldwide each year [1,2]. Currently,tal cancer are the most common cancer typUnconventional secretion

1. Introduction

Cancer is the leading cause of deatinterstitial uid or tumor proximal body uids, can be studied comprehensively by nanoLC-MS/MS-basedapproaches. Here, we outline the importance of current cancer secretome research and describe the massspectrometry-based analysis of the secretome. Further, we provide an overview of cancer secretome researchwith a focus on the three most common cancer types: lung, breast and colorectal cancer. We conclude thatthe cancer secretome research eld is a young, but rapidly evolving research eld. Up to now, the focushas mainly been on the discovery of novel promising secreted cancer biomarker proteins. An interestingnding that merits attention is that in cancer unconventional secretion, e.g. via vesicles, seems increased.Renement of current approaches and methods and progress in clinical validation of the current ndingsare vital in order to move towards applications in cancer management. This article is part of a Special Issueentitled: An Updated Secretome.

2013 Elsevier B.V. All rights reserved.

Although our knowledge of the carcinogenic process, tumor biologyand clinical management of cancer is rapidly growing, survival ratesKeywords: giogenesis and invasion. The cancer secretome, sampled as conditioned medium from cell lines, tumor/tissueAvailable online 31 January 2013biomarkers since they mighpart represents the tumor mTieneke B.M. Schaaij-Visser a,b, Meike de Wit a, Siu Wa OncoProteomics Laboratory, Dept. of Medical Oncology, VU University Medical Center, Amb Division of Molecular Genetics and Centre for Biomedical Genetics, The Netherlands Canc

a b s t r a c ta r t i c l e i n f o

Article history:Received 13 November 2012Received in revised form 18 January 2013Accepted 23 January 2013

Despite major improvemenNovel biomarkers for betterteins secreted, shed or leakiB, western blot; SRM, selectedimmunohistochemistrydated Secretome.ory, CCA1.60, Dept. of Medical1117, 1081 HV, Amsterdam,

l rights reserved.pportunities in the lung, breast and

am a, Connie R. Jimnez a,rdam, The Netherlandsstitute, Amsterdam, The Netherlands

n the knowledge and clinical management, cancer is still a deadly disease.ncer detection, diagnosis and treatment prediction are urgently needed. Pro-from the cancer cell, collectively termed the cancer secretome, are promising

ophysica Acta

ev ie r .com/ locate /bbapapidentication of biomarkers that can be applied for early detection,diagnosis, prognosis, treatment response prediction or treatmentmonitoring [6]. Further, drug targets for personalized treatment areurgently warranted, as is comprehensive knowledge on tumor biolo-gy. Proteins reect the functional and post-translational cell biologyand can be studied comprehensively by large-scale nano-liquidchromatography tandem mass spectrometry (nanoLC-MS/MS)-based

proteomics. Therefore, they hold great promise as cancer biomarkersor drug targets and can add substantially to our knowledge on cancerbiology [7]. It has become increasingly clear that not only cellular pro-teins (i.e. the proteome), but also proteins secreted or shed into thetumor microenvironment (i.e. the secretome) play a key role in theprocesses that shape the malignant nature of a tumor (Fig. 2). Amajor advantage of studying the secretome, compared to the cellularproteome, is that proteins secreted by tumor cells or tissue are morelikely to end up in blood or other body uids in a measurableconcentration. Since a main interest in cancer research is to identify

Fig. 1. Distribution of stage at rst diagnosis and ve-year survival rates per disease stage fextracted from Siegel et al. [4].

2243T.B.M. Schaaij-Visser et al. / Biochimica et Biophysica Acta 1834 (2013) 22422258biomarkers that can be used for blood-based diagnostics, secretomeanalysis is a very promising approach and therefore often appliedfor biomarker discovery in the recent years. Another advantage isthe reduced sample complexity of secretome samples enabling abroader dynamic range of detection. In addition, secretome studiescan provide insights in the biology of the tumor micro-environment,(tumor) cellcell interactions and mechanisms of invasion andmetastasis (Fig. 2).

With this review we aim to outline the importance of secretomeresearch in the cancer context. We provide a general background oncancer secretome proteomics and describe the practicalities of ananoLC-MS/MS-based workow to study the cancer secretome. Fur-ther, we provide a broad overview of mass spectrometry (MS)-basedFig. 2. Hallmarks of the cancer secretome.cancer secretome studies aimed at either biomarker discovery orstudying (extracellular) tumor biology.

2. Cancer background and clinical needs

Fig. 1 presents the percentage of patients per disease stage at ini-tial diagnosis and the corresponding ve-year survival rates for eachof the three cancer types.

Lung cancer is the deadliest malignancy worldwide accounting for18% of all cancer deaths in 2008 [1,2]. The overall ve-year survivalrate is approximately 15% and has barely increased in the last decades[8]. This poor overall survival is mainly due to late detection of thetumor, which causes the majority of patients to present with metasta-sized disease (Fig. 1). Treatment options for these patients are limitedand therapy resistance is common. Histologically, lung cancer is di-vided into small cell lung cancer (SCLC, 20% of patients) andnon-small cell lung cancer (NSCLC, 80% of patients). NSCLC is furthersubdivided into three main histological subtypes: adenocarcinoma(AC, 40% of patients), squamous cell carcinoma (SCC, 25% of patients)and large cell carcinoma (15% of patients). Currently, there are nopopulation-based screening programs for lung cancer and personal-ized therapies are only available for distinct, small patient groups,e.g. specic tyrosine kinase inhibitors for patients with sensitizingEGFR mutations or ELM4-ALK fusion genes [9,10]. To improve lungcancer survival rates, biomarkers for early detection, treatment re-sponse prediction and personalized therapy are urgently needed.

Female breast cancer is the most common cancer in women with acancer death rate of approximately 14% in 2008 [1,2]. The prognosisof localized breast cancer is generally favorable with an overallve-year survival rate exceeding 80% [11]. However, about 5% of pa-tients present with metastatic breast cancer and 30% of patients even-tually develop recurrent or metastatic disease. The majority of thesepatients die within ve years after diagnosis (Fig. 1) [11].

or the three main cancer types. Numbers are based on data from the United States andFurthermore, the incidence of breast cancer is expected to rise inthe coming years [12]. Population-wide breast cancer screeningbased on mammography has been implemented in many countriesaiming to detect breast cancer at an early stage. However, it isstill under debate whether this screening leads to a reduction ofbreast cancer mortality [13,14]. These ndings highlight the needfor additional biomarker-based screening methods to complementthe current image-based strategy. Further, individual variations intreatment response and toxicity necessitate renement of patientstratication for systemic therapies. Biomarker proteins related toresponse to systemic therapy may be useful for treatment selectionand/or monitoring.

Colorectal cancer is the second most common cancer worldwide,representing 8% of all cancer deaths [1,2]. For early stage disease theve-year survival rates are up to 90%, whereas the ve-year survivalrates for patients with metastasized disease are as low as 8% contrib-uting to the high overall mortality (Fig. 1) [15]. Similar to lung cancer,

the clinical symptoms mostly arise at a late stage, limiting the treat-ment options [15]. Screening programs for colorectal cancer, basedon stool or colonoscopy, are being implemented in various countries[16]. Detection of tumor-derived biomarker proteins that are secret-ed/excreted or otherwise externalized and end up in stool or serumcould aid the development of better screening tests. Currently, CEAis the marker of choice for monitoring response to systemic therapyin metastatic disease [17]. However, addition of more specic bio-markers could lead to a more accurate estimation of disease status.

In general, genomic mutations that underlie cancer progressioncan lead to altered protein expression patterns that reect tumorbiology. These specic changes in protein expression, detected inserum or other body uids, could improve the sensitivity and specic-ity of the currently available methods for early detection, diseasemonitoring and treatment response prediction.

[23]. In recent years, special interest has emerged in secretion throughvesicles, like exosomes, that can be isolated from crude secretomes andare thought to play an important role in many tumor biologicalprocesses (Fig. 3, and also elsewhere in this special issue) [2426].

4. Cancer secretome proteomics

Analysis of the cancer secretome by nanoLC-MS/MS-basedmethodsrequires several considerations as compared to the analysis of thecellular proteome. These considerations mainly relate to the choice ofsample type and preparation, the actual MS analysis and processingof the acquired data.

4.1. Secretome sample types

es eme

2244 T.B.M. Schaaij-Visser et al. / Biochimica et Biophysica Acta 1834 (2013) 224222583. The signicance of the cancer secretome

Cancer cells acquire several capabilities to fully develop theirmalignant phenotype such as growth stimulation, manipulation ofstroma and immune response, induction of angiogenesis and invasionleading to metastasis [5]. For many of these abilities, the arsenal ofsecretory factors of the cell is of utmost importance, if not crucial,and together they represent the hallmarks of the cancer secretome(Fig. 2). Identication of secreted proteins that are functionallyinvolved in these processes will not only provide new putativebiomarkers and drug targets. It will also add tremendously to ourknowledge of carcinogenesis and tumor biology.

The term secretome was rst coined in 2000 by Tjalsma et al.,studying signal peptide-dependent protein transport in Bacillussubtilis [18] and Gronborg et al. rst mentioned the cancer secretomein 2006 [19]. However, in 2004, Celis et al. were the rst to present amethod to study the secretome of breast tumors [20]. They describedan approach to analyze the breast tumor interstitial uid (TIF) byincubating small pieces of tumor tissue in PBS and subsequently mea-suring the protein prole of the PBS (i.e. the tumor tissue secretome).This approach is still widely used to study the cancer tissuesecretome. Further, Volmer et al. used conditioned medium (CM)from cancer cell lines in order to identify and compare proteinssecreted by cancer cells [21,22]. These reports were the rst topresent a differential cancer secretome analysis.

Currently, the term cancer secretome is used to describe all pro-teins secreted, shed or leaking from a cancer cell or tissue under certainconditions and at a certain time. It is a semi-complex biological samplecontaining both soluble proteins and protein-containing vesicles. Se-cretion of proteins can follow the conventional (or classical) secretorypathway that requires the protein to contain a signal peptide. Further,there is increasing knowledge about several routes of unconventional(or non-classical) protein secretion involving translocation across theplasma membrane, lysosome or microvesicle-dependent secretion

Fig. 3. Transmission electron micrograph of exosome secretion. A, Multivesicular bodienlargement of the exosomes. B, The arrows show the invaginations where new exoso

the cell membrane and D, exosomes are secreted. Images were adapted from Sahoo et al. aThe term cancer secretome in fact is a very broad term that collec-tively comprises a multitude of sample types. In this section, we willintroduce different sample types that can be employed for cancersecretome analysis and describe the possibilities and limitations.

The most straightforward and as a result most studied secretometype is the CM from (cancer) cell lines [27]. In general, cells arewashed to remove serum proteins from the medium, cultured for arestricted time in serum-free medium (e.g. 24 or 48 h) and the medi-um is concentrated and further processed for MS analysis. The advan-tages of this approach are that relatively large sample amounts can beobtained and that it allows for quantitative comparisons after manip-ulation of cancer cells. For example, the CM of cell lines with or with-out certain mutations [28,29]; or the effect of coculturing tumor cellswith stroma cells [30]; or differences according to drug response[31,32] can be studied. The number of identied proteins from asingle CM sample has increased substantially and is nowadaysapproaching 2,500 [33].

TIF is the most direct manner to analyze proteins secreted or shedby actual tumor and/or stroma cells. TIF is a uid phase located in thetumor interstitium. This uid surrounds tumor cells and stromal cellsand is believed to be important for intercellular communication.Signaling molecules can be released locally into TIF by tumor cellsand may play a key role in tumor progression or metastasis. To obtainTIF, small pieces of fresh tumor tissue are incubated in PBS as rstdescribed by Celis et al. [20]. After pelleting the tissue parts and celldebris by centrifugation, the supernatant contains all secreted andshed proteins. The incubation time should not be too long, preferably1 h, and the temperature should be kept at 37 C to prevent massivecell death. Up to 1500 proteins have been identied from a single TIFsample so far [34].

Tumor proximal body uids are very promising for biomarker dis-covery as they represent a reservoir of tumor secreted proteins in vivowithout the large dynamic range and complexity of plasma or serum.Proximal uids relevant for lung, breast and colon cancer are pleuraleffusion (PE), nipple aspirate uid (NAF), stool and ascites uid.

nclosing numerous exosomes are lined up at the cell membrane. The insert shows ans bud off of the multivesicular body membrane. C, The multivesicular body fuses with

nd kindly provided by Dr. S. Sahoo, permission to reuse was granted [106].

2245T.B.M. Schaaij-Visser et al. / Biochimica et Biophysica Acta 1834 (2013) 22422258PE is the pathological accumulation of the pleural uid betweenthe two sheets of tissue that line the lungs.PE samples can beobtained by aspiration followed by centrifugation and yielded up to500 proteins so far [35].

NAF is produced by epithelial cells lining the breast duct system,from which the great majority of breast cancer (ductal carcinoma)arises. The collection of NAF can be performed noninvasively by vac-uum aspiration. The aspiration procedure causes little discomfort andcan be successfully performed in most women after oxytocin admin-istration [36]. Up to 777 proteins were identied in a tumor NAF sam-ple by Pavlou et al. [37]. Few studies are published on proteomeanalysis of stool in the context of colon cancer [3841] and so far upto 800 proteins were detected. Stool protein proling seems challeng-ing and preparation protocols are still being developed [42]. Otherpromising, but yet to be further investigated, tumor proximal uidsmight be saliva (lung), lavage uid (lung, breast) [43] and ascitesuid (colon).

4.2. Special considerations for nanoLC-MS/MS-based analysis of thecancer secretome

For an optimal experiment the following is necessary: optimalbalance between protein amount, protein concentration and samplevolume (depending on the approach to be used), limited backgroundof high abundant proteins, consistent sample collection, and anoptimized well-suited proteomics approach (also reviewed in otherpapers in this issue). Makridakis et al. provided an extensive overviewof procedures for collection, concentration and separation of secretomesamples, mainly CM [44]. For patient-derived materials, e.g. TIF andproximal uids, standardized (and preferably fast and simple) collec-tion procedures are essential. Further, patient details and details onthe collected samples should be thoroughly registered and consideredin the nal selection of samples to be analyzed. For proximal uidssuch as PE and NAF, abundant protein depletion and subsequentprefractionation can increase sensitivity tremendously [37].

In brief, current proteomics approaches consist of either a combina-tion of two-dimensional (difference in) gel electrophoresis (2D-(DI)GE)and MS identication of differential protein spots or one-dimensionalgel electrophoresis (1D-GE) (or a different type of prefractionation)combined with nanoLC-MS/MS [45]. Prefractionation, preferably by1D-GE, followed by nanoLC-MS/MS identication and quanticationwould provide a higher number of identied proteins and permithigh-throughput analysis [45]. However, the current generation ofmass spectrometers has gained tremendously in sensitivity and mightbe able to prole less complex secretome samples without upfrontfractionation, enabling faster and more extensive experiments.

To conrm the detection of secreted proteins software tools suchas SignalP or SecretomeP are often used to predict if proteins are se-creted (see also elsewhere in this special issue) [46]. This can providean overview of the quality of the data and the probability of identiedproteins to be detected in the circulation. However, proteins are sub-ject to extensive shuttling and trafcking, so care should be taken indrawing conclusions based on only the predicted protein location.Contamination with nuclear proteins might in fact be the excitingdiscovery of novel locations and functions of known nuclearproteins. Also, the currently available tools mainly consider classicalsecretion (by means of a signal peptide), while increasing evidenceemerges that supports the idea that cancer cells in fact usenon-classical protein secretion (e.g. vesicle secretion) to manipulatetheir environment [2426].

5. Applications of secretome proteomics in the context of lung,breast and colon cancer

Tables 1, 2 and 3 provide an overview of all lung, breast and colon

cancer secretome studies described in this review ordered by thetype of sample used for secretome analysis. We used a combinationof the following (and similar) terms to search in PubMed: lung cancer,NSCLC, SCLC, breast cancer, colorectal cancer, secretome, secreted pro-teins, conditioned media, proximal uid, proteomics, nanoLC-MS/MS,mass spectrometry, tumor interstitial uid, nipple aspirate uid, stool,pleural effusion. Most studies used CM of cell lines or cultures andaimed to identify cancer biomarkers, for example focusing at markersto be detected in blood or markers for early stage cancer detection. Aminority of papers described experiments intended to further clarifytumor biology processes, such as metastasis [47,48], tumor cellcell in-teractions [30,49] and specic signaling pathways involving p53[29,50], Smad4 [21,22] and c-Myc [51]. In the following sections,most important results are discussed organized by tumor and sampletypes.

5.1. Progress in lung cancer secretome proteomics research

5.1.1. Studies performed with conditioned media (aimed at biomarkerdiscovery)

The most common aim of studies analyzing CM of cell lines was toidentify protein biomarkers that can be used for blood-based detectionof lung cancer (Table 1) [5256]. To that end, the CM of cancer cell lineswas proled in order to generate lists of proteins secreted by lungtumor cells and therefore possibly detectable in blood. Planque et al.did an extensive effort by prolling the CM of four cell lines of differentorigin, i.e. AC, SCC, large cell carcinoma and SCLC, and identiedbetween 700 and 1000 proteins in each secretome [54]. The proteinexpression of ve potential biomarkers (Osteoprotegerin, sTNFRI,Follistatin, Pentraxin 3 and ADAM-17) was demonstrated to be signi-cantly higher in blood of NSCLC patients (N=25) compared to healthycontrols (N=25).

In another study, the CM of 23 different tumor cell lines was ana-lyzed including two lung adenocarcinoma cell lines [57]. This allowedthe selection of lung cancer-specic secreted proteins that were sub-sequently checked for expression in the appropriate tissue in theHuman Protein Atlas [58]. Increased expression of Stromal-derivedfactor 1 was conrmed in the serum of lung cancer patients (N=44) versus healthy controls (N=44). The same authors publishedone study in which they integrated the secretomes of the two celllines used in the previous study with an AC tissue proteome [59]and one study for which they integrated the same cell line secretomeswith a PE protein prole [55]. With validation studies they show thatImportin subunit alpha-2 and Retinoblastoma-associated bindingprotein 46 are signicantly increased in serum of NSCLC patients(AUC=0.63 and AUC=0.717, respectively). Apart from clinical vali-dation they also performed functional assays to demonstrate a poten-tial role for both markers in cancer development.

A few studies were aimed to identify biomarkers for early detec-tion of lung SCC and for these cell line models for squamous cell car-cinogenesis were employed [53,60,61]. Lou et al. analyzed thesecretome of different passages of a SV40-transformed human bron-chial epithelial cell line as model for SCC development [53]. Theyidentied Cathepsin D as candidate marker and validated its differen-tial expression in blood of SCC patients versus healthy controls. Fur-ther, they showed that serum Cathepsin D expression correlatedwith patients' lymph node status. A sophisticated three-dimensionalorganotypic airliquid interface culturing method was employed toidentify proteins secreted by squamous metaplasia, an early stage ofSCC development [61]. Two of the most promising candidate proteins,SCCA1 and SCCA2, were validated in patient material showingmoder-ate specicity for SCC as compared to other lung cancer subtypes.

5.1.2. Studies performed with conditioned media (aimed to study tumorbiology)

In total, we found eight publications that describe experiments

using lung (cancer) secretome proteomics to unravel tumor biology

Table 1Overview of lung cancer secretome studies.

First author [ref] Year Aim Comparison/sample types Pre-MS workow MS workow No. of proteinsidentied/differential

Validation

Conditioned media of cell lines/cultures (tumor/altered cells (vs normal))

Huang [52] 2006 To identify serum biomarkers forNSCLC

CM of A549 (AC) 2D-GE MALDI-TOF Total IDs specic forA549 CM: 14 (versusonly culture medium)

DDH levels in serum of NSCLC patients (30 AC,34 SCC) were signicant higher compared tolevels in serum of benign lung disease patients(n=20) or healthy controls (n=20).

Kim [60] 2008 To identify lung cancer biomarkers CM of four cell lines from the same originrepresenting multistage bronchial epithelialcarcinogenesis (BEAS-2B, immortalizednormal bronchial epithelial cells; 1799,non-transformed cells; 1198 and 1170-I,transformed cells)

2D-GE MALDI-TOF Total no. of spots: 600,Total differential IDs:20

Validation of PGP9.5, TCTP, TIMP2 and TPI intissues (n=11 matched normal and tumortissue) and plasma (23 SCC patients versus 17healthy controls) from patients.

Kim [61] 2007 To identify proteins uniquely secretedby metaplastic squamous bronchialepithelial cells

Apical surface uid of metaplastic versusnormal human tracheobronchial epithelialcells cultured by a three-dimensionalorganotypic air-liquid interface method(SCC)

2D-GE LC-MS/MS Total of differentiallyexpressed spots: 174;differential IDs: 22(upregulated inmetaplastic cells)

Expression of SCCA1 and SCCA2 was validatedin a cell line model for bronchial epithelial cellcarcinogenesis (Kim et al., 2008), was shownto be specic for SCC cell lines and was shownto be negative in normal tissue andupregulated in 114 SCC tissue. Also expressionwas observed in 30% of 189 AC tissues.

Lou [53] 2007 To identify serum biomarkers for lungcancer at early stage

CM of three different passages of aSV40T-transformed human bronchial epi-thelial cell line (SCC)

2D-GE MALDI-TOF Total no of spots:250 per passage;differential IDs: 40

Expression of Cathepsin D was validated inplasma of SCC patients (n=104) versushealthy controls (n=36) and non-malignantlung disease (n=15) and plasma levels cor-related with presence of LNM, also CathepsinD expression was signicant higher in SCCtissue (n=306) versus normal tissue (n=40)and correlated with presence of LNM andstage of disease.

Luo [107] 2011 To establish a high-quality secretomeof A549 cells by using the proteome asreference and to test the merits of thisapproach for NSCLC biomarkeridentication

CM of the A549 cell line rened bysubtracting this cell line's proteome (AC)

1D-GE LC-MS/MS Total IDs CM: 889; IDsrened secretome:382

C4BP serum expression was upregulated incancer patients (n=89) compared to controls(n=40) and correlated with disease stage.

Planque [54] 2009 To identify secreted ormembrane-bound potential novel lungcancer biomarkers

CM of four cell lines with differenthistological types (H23, AC; H530, SCC;H460, large cell; H1688, SCLC)

In solution digest, SCX LC-MS/MS Total IDs: 1830; (965,871, 726 and 847 fromH1688, H23, H460 andH520, respectively)

Serum levels of ve potential biomarkers(ADAM-17, osteoprotegerin, pentraxin 3,follistatin and tumor necrosis factor receptorsuperfamily member 1A) were elevated in 25patients versus 25 healthy controls.

Wang [59] 2011 To identify protein biomarkers that areupregulated in lung cancer tissue andsecreted by lung cancer cells byintegrating the data sets of two cell lineCMs and one tissue expressionmicroarray

CM of two cell lines (CL1-0 and CL1-5)integrated with an adenocarcinomatissue transcriptome (AC)

none none 285 upregulatedgenes, 35 of thebelonging proteinswere present in atleast one of the cellline CMs

The expression of several candidates wasmeasured in tissue (WB, IHC), serum (ELISA)and PE (ELISA) and KPNA2 was the best can-didate. Knockdown of KPNA2 resulted in adecrease of migration and cell viability.

Wang [55] 2009 To identify serum NSCLC markers CM of two cell lines (CL1-0 and CL1-5)integrated with a pleural effusion proteomicdata set (AC)

1D-GE LC-MS/MS Total IDs: 1096(CL1-0) and 1830(CL1-5); 22 proteinsin overlap withpleural effusionprotein prole

Differential expression of RbAp46 wasvalidated in tissue (154 paired tumor andnormal tissue), serum (108 patients versus 71healthy controls). Elevated serum RbAp46 wascorrelated with metastasis. Migration assaysafter knockdown or overexpression of RbAp46demonstrated a functional rol in migration.

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Wu [57] 2010 To generate a comprehensive cancercell secretome and identifycancer-specic and pan-cancerbiomarkers

CM of 23 different cancer cell lines (of 11different cancer types); two NSCLC celllines, CL1-0 and CL1-5 (AC)

1D-GE LC-MS/MS Total IDs: 4584, onaverage 1300 per cellline, 1096 in CL1-0 and1830 in CL1-5, 109unique for lung AC

Marker candidates with expression in tissueaccording to the Human Protein Atlas wereselected; signicant elevated serum levels ofStromal-derived factor 1 were measured in 44lung cancer patients versus 44 healthy controls.

Xiao [56] 2005 To provide pilot data from a noveltumor cell protein detection methodand to identify lung cancer-relatedprotein blood proles

CM of lung cancer primary cell and organcultures versus that of adjacent normalbronchus

1D-GE LC-MS/MS Primary cultures, totalIDs: 231; Organcultures, total IDs:117; differential: notmentioned

Thirteen proteins were selected forvalidation in plasma samples of 413 lungcancer patients, 75 non-malignant lungdisease patients and 134 non-cancer controlpatients, and for eight of them differentialexpression in either one of the patientgroups was validated.

Conditioned media of cell lines (tumor biology)

Schliekelman [33] 2011 To determine mechanisms responsiblefor epithelialmesenchymal transitionand metastasis regulated by themicroRNA-200 family

Whole lysate, cell surface and CM fractionsof a metastatic versus a non-metastaticmouse model derived adenocarcinoma cellline in the context of EMT by loss ofmiR-200(AC)

POROS R1/10 column,SILAC

LC-MS/MS Total IDs quantied inCM in a single experi-ment: 2449; differen-tial: 222

Extensive data mining and verication inother either mesenchymal or epithelial celllines.

Chen [47] 2006 To identify biomarkers related to lungcancer metastasis

CM of H226 cell line versus CM of its brainmetastatic subline (SCC)

1D-GE MALDI-TOF Total differential IDs:12

Differential expression of LDHB wasvalidated with ELISA in serum of patients(n=105, AC, SCC and SCLC) versus benignlung disease patients (n=41), othercancer patients (n=93) and healthycontrols (n=65) and correlated withclinical stage of disease.

Chenau [50] 2009 To identify p53-modulated secretedproteins

CM of the H358 cell line, containing ahomozygous deletion of p53, versus itstransfected inducible p53 wildtypecounterpart (AC)

iTRAQ labeling,in-solution digest,OFFGEL IEF, RP-LC(2D-GE for detection ofPTM's)

MALDI-TOF Total IDs: 909;p53-modulated: 91(no p53-modulatedPTM's identied)

GDF-15, FGF-19 and VEGF were validated intissue of xenograft mice, GDF-15 was alsovalidated in blood of xenograft mice.

Chiu [48] 2011 To develop a strategy of gel-aidedprotein purication combined withiTRAQ labeling to identify secretedmetastasis-associated proteins

CM of a non-metastatic (CL1-0) versus CM ofa metastatic (CL1-5) cell line (AC)

1D-stacking-GE, iTRAQpeptide labeling

LC-MS/MS Total IDs: 353;Metastasis-associated:7

Functional validation (migration+invasionassay) of COL6A1 as metastasis-associatedprotein.

Chang [62] 2012 To identify metastasis-associated pro-teins secreted by lung adenocarcinomacells

CM of a non-metastatic (CL1-0) versus CM ofa metastatic (CL1-5) cell line (AC)

1D-Stacking-GE LC-MS/MS, IonIntensityQuantication

Total IDs: 66;differential: 68

Expression of A1AT in tissue of lungadenocarcinomas was shown to correlatedwith overall TNM stage and N stage. Extensivefunctional assays (in CL1-0 and CL1-5 cell lines)to demonstrate a role of A1AT in invasion, mi-gration and colonization of lung cancer cells.

Shin [49] 2012 To clarify paracrine mechanismsinvolved in crosstalk between humanadipose tissue-derived mesenchymalstem cells and A549 cancer cells

CM of LPA-stimulated and unstimulatedhuman adipose tissue-derived mesenchy-mal stem cells

In solution digest LC-MS/MS, IonIntensityQuantication

Total IDs: 146;LPA-induced: 16

Functional validation (silencing,overexpression, immunodepletion) ofstimulating effect of LPA-induced TGFBI/ig-H3 secretion of hASC's on A549 cancercells (adhesion/proliferation).

Yu [29] 2006 To identify proteins secreted by cells ina p53-dependent manner after DNAdamage

CM of H460 cell line (wt p53) versus H1299cell line (mutated p53) after irradiation

1D-GE MALDI-TOF Total differential IDs:9

Functional assays were done to show thatwith wt p53 upon DNA damage proteins aresecreted through vesicle transport and TSAP6plays a role in this secretion of exosomes.

Zhong [30] 2008 To dene interactions between stromalcells and K-ras mutant lung cancercells that promote tumorigenesis

CM of cocultures of a K-ras mutant cancercell line with three different stromal celllines (broblast, endothelial cell,macrophage) (AC)

SILAC, 1D-GE LC-MS/MS Total IDs: 181;differential: notmentioned

None for the MS-identied proteins, func-tional validation of proteins identied bymultiplexed antibody bead assay.

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Table 1 (continued)

First author [ref] Year Aim Comparison/sample types Pre-MS workow MS workow No. of proteinsidentied/differential

Validation

(Malignant) pleural effusion

Bard [64] 2004 To determine if malignant pleuraleffusion contains exosomes and if soidentify their protein content

Exosome fraction of malignant pleuraleffusion of one mesothelioma, one lungcancer and one breast cancer patient (AC)

Sucrose GradientUltracentrifugation,1D-GE

MALDI-TOF Total IDs for lungcancer: 18

The presence of MHC class II molecules, HSP90and two immunoglobulins was conrmed byWB.

Hsieh [67] 2006 To identify differential proteinsbetween malignant and transudativepleural effusion

Fourteen malignant pleural effusions (lungcancer, tongue cancer, oesophageal cancer,breast cancer) versus thirteen transudativepleural effusions (due to heart failure,kidney disease and liver disease)(AC+1SCLC)

2D-DIGE MALDI-TOF,LC-MS/MS

Total no. of spots: 643;differential spots: 7;differential IDs: 2

Verication of decreased PEDF expression inmalignant pleural effusions versustransudatives by WB and ELISA.

(Malignant) pleural effusion

Pernemalm [68] 2009 To evaluate narrow-range peptideiso-electric focusing in combinationwith LC-MS/MS for body uid proteo-mics and to use this method to assessthe potential of pleural effusion asbiomarker source

Blood and PE of three adenocarcinoma pa-tients and three patients with inammatorylung disease (AC)

Protein depletion (sevenproteins) by afnitycolumn, in-solution di-gest, iTRAQ labeling, SCXcleanup, narrow-rangeIEF or FFE

LC-MALDI-TOF-TOF Total IDs PE: 300; totalIDs plasma: 282; inoverlap: 189;differential proteins incancer versuspleuritis: 20

NPC-2 was validated by IHC in tissue of 48patients versus tissue from 14 benign lungdisease patients.

Rodrguez-Pieiro[69]

2010 To compare the serum and pleuraleffusion proteome of cancer patients tothat of pneumonia and tuberculosispatients, resp.

Serum proteome of NSCLC patients (n=4)versus pneumonia patients (n=4), pleuraleffusion proteome of NSCLC patients (n=4)versus tuberculosis patients (n=4)

Protein depletion,2D-DIGE

MALDI-TOF Average no of spots:2299; differentialspots: 41; differentialIDs: 18

Immunodetection and quantication of PEDFin the same samples.

Soltermann [70] 2008 To detect biomarkers by generatingpleural effusion N-glycosylated proteinproles

Pleural effusion from ve patients versuspleural effusion from 5 non-malignant con-trols (AC)

N-glycoprotein capture,in solution digest

LC-MS/MS Total IDs: 170 with88% glycoproteins;differential IDs: notmentioned

Only verication.

Tyan [65] 2005 To present proteomics proling data ofhuman pleural effusion obtained by 2DnanoLC-MS/MS

Pool of pleural effusion of 43 patients (AC) Extra 2D-GE 2D LC-MS/MS,LC-MS/MS after2D-GE

Total IDs: 127 highcondence

None.

Tyan [66] 2005 To present a global proteomic analysisof human pleural effusion

Pool of pleural effusion of seven patients(AC)

2D-GE LC-MS/MS Total no of spots: 472;total IDs: 161(minimal condencelevels) and 44 (highcondence levels)

None.

Wang [71] 2012 To identify differentially expressedproteins in malignant effusions andbenign inammatory effusions using highabundant protein depletion and 2D-DIGE

Ten malignant effusions versus 10 benigneffusions (six from tuberculosis, 4 frompneumonia) (AC)

Protein depletion,2D-DIGE

MALDI-TOF On average 2000protein spots persample; differentialIDs: 16

JMJD5 was validated in normal versus tumortissue of ten patients.

Yu [35] 2011 To generate a comprehensivemalignant pleural effusion proteomeand identify potential biomarkersoriginating from malignant cells

Combine and integrate proteomes ofthirteen pooled pleural effusions from lungadenocarcinoma patients and datasets ofCM of three cell lines (CL1-0, CL1-5 andH23) (AC)

Protein depletion (sixproteins) by afnitycolumn, 1D-GE

LC-MS/MS Total IDs MPE-pool:482; overlapMPE+three cell lineCM's+predicted se-creted proteins: 107

AHSG, ANG, CST3 and IGFBP2 were selectedand IGFBP2 was validated in 30 MPE's versus30 PMPE's and in MPE's (including from othercancer types) versus PMPE's (including othercancer types) and PE's from benign disease.

SALIVA

Xiao [108] 2012 To identify saliva protein biomarkersfor lung cancer

Pooled saliva from ten lung cancer patientsversus ten healthy controls (NSCLC+SCLC)

2D-DIGE MALDI-TOF,LC-MS/MS

Total differential IDs:18

Increased expression of HP, AZGP1 andcalprotectin was validated in saliva of patients(n=26) versus healthy controls (n=26) andin lung cancer cell line CM versus normal cells.

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2249T.B.M. Schaaij-Visser et al. / Biochimica et Biophysica Acta 1834 (2013) 22422258(Table 1). Differentially secreted proteins between metastatic andnon-metastatic cancer cells were identied using either a cell lineand its metastatic counterpart or two similar cell lines with differentmetastatic capacities [33,47,48,62]. A study by Schiekelman et al.stands out as the authors proled whole lysate, cell surface fractionsand CM of mouse-derived metastatic and non-metastatic cell linesin addition to metastatic and non-metastatic mouse tumors [33]. Inprevious work, the authors established that the metastatic characterwas a result of epithelialmesenchymal transition caused by loss ofmicroRNA-200 (miR-200) (the non-metastatic cells display function-al miR-200) [63]. Proteins involved in extracellular matrix, peptidasesand cell adhesion proteins were found to be differentially expressedbetween metastatic and non-metastatic cells, and integrationof the results from the three cell lines fractions revealed a strongupregulation of a TGFB1 centered network of proteins. Further, theauthors restored miR-200 expression in the cell lines with lowmiR-200 expression to identify proteins and processes directly regu-lated by miR-200. This demonstrated that miR-200 expression altersprotein secretion and shedding resulting in modulation of the tumormicroenvironment. The authors combined proteome analyses on dif-ferent fractions of a well-dened cell line coupled with functionalmanipulation of the cell lines and integration with RNA expressiondata. In this way, they could map the role of miR-200, in the contextof epithelialmesenchymal transition and metastasis, on the intracel-lular, cell membrane and extracellular level.

The p53 pathway, often modulated in tumors, is involved inapoptosis and in general considered to exhibit its function initially inthe nucleus leading then to cellular effects. Two published studies com-pared CM of p53 mutated and p53 wildtype cell lines [29,50]. Interest-ingly, Yu et al. studied the p53 dependent secreted proteins in thecontext of irradiation [29]. They found an increase in secreted proteinsin the CM of the p53 wildtype cell lines and showed that this effect wasnot a result of apoptosis. With a series of follow-up experiments theyfurther demonstrated that in cells with functional p53, increasedexosome secretion after irradiation was TSAP6 dependent.

Two studies report on the interaction between lung tumor cells andtheir microenvironment. Shin et al. aimed to clarify paracrine mecha-nisms between human adipocyte tissue-derived mesenchymal stemcells and cancer cells by proling the secretome of the human adipo-cyte tissue-derived mesenchymal stem cells that were stimulated bylysophosphatidic acid [49]. They discovered that lysophosphatidicacid-induced TGFBI secretion of human adipocyte tissue-derived mes-enchymal stem cells had a stimulating effect on tumorigenic propertiesof cancer cells. The crosstalk between stromal cells and lung cancercells was examined by Zhong et al. who cocultured a K-ras mutantcell lines with three different stromal cell lines (broblasts, endothelialcells and macrophages) and used a nanoLC-MS/MS-based method toidentify the proteins in the CM [30]. They identied multiple proteinsinvolved in various extracellular processes such as cell adhesion,invasion and angiogenesis.

5.1.3. Studies performed with (malignant) pleural effusion (PE)Since PE cannot be obtained from healthy persons, MPE proteome

studies either provide a list of proteins (and in some cases the overlapwith other secretome identied proteins) [35,6466] or compare MPEto non-malignant PE [6771]. The latter seems most useful, but alsomost challenging. Since a variety of pathological conditions can leadto PE (inammatory lung disease, heart failure, infections etc.) it is im-portant to carefully choose patient and control groups. For example,Hsieh et al. [67], Rodriguez-Piero et al. [69] and Pernemalm et al.[68] compared lung cancer PE to either (transudative) PE from patientswith heart-, kidney- or liver disease; PE from tuberculosis patients; orPE from patients with inammatory pleuritis, respectively. Hsieh etal. identied two proteins with decreased expression inMPE, i.e. brin-ogen and PEDF. These proteins (plus sixteen more) were also detected

to be differentially expressed by Rodriguez-Piero et al. However, theyfound that PEDF was in fact higher expressed in MPE compared to PEfrom tuberculosis patients. In both studies the differential (but oppo-site) expression of PEDF was veried by antibody-based methods.This indicates that control samples should be well considered whendrawing conclusions. Future validation studies of possible PE proteinbiomarkers should be carefully designed to contain sufcient samplesand include a variety of control samples.

The current most comprehensive PE protein prole consists of 482proteins identied in a pool of MPE of thirteen patients [35]. Fromthese 482 proteins, the authors selected 107 proteins that were presentin the CM of three AC cell lines and were predicted to be secreted. Theauthors performed validation assays for ve of these proteins andshowed that IGFBP2 expression was signicantly increased in MPEcompared to para-malignant (not associated with invasive cancer)and benign PE, and that IGFBP2 was functionally involved in migration.

An interesting approach is presented by Soltermann et al. whochose to use N-glycoprotein capture to reduce PE protein complexityand with that lower the detection limit to the gng/ml range [70].They identied 170 proteins with high condence of which 88%contained at least one glycopeptide, and conrmed expression ofperiostin and CD166 in tissue of one patient. Since glycoproteins ingeneral present to be successful biomarkers, this approach might bepromising for biomarker discovery in combination with PE as bio-marker source.

The rst proteomics study on MPE was published in 2004 and is sofar the only report on exosomes in pleural effusion or in any kind oflung cancer secretome [64]. For this publication, Bard et al. aimed todetermine whether MPE contains exosomes and if so what wouldbe their protein content. Therefore, they performed sucrose gradientultracentrifugation on MPE of one AC lung cancer patient, one meso-thelioma patient and one breast cancer patient. Exosomes were pres-ent in MPE as shown by electron microscopy and eighteen proteins,mainly immunoglobulins and complement factors, were identiedand partially veried in the exosome fraction of the lung cancer PE.

5.2. Progress in breast cancer secretome proteomics research

5.2.1. Studies performed with conditioned media (aimed at biomarkerdiscovery)

Breast cancer cell lines have been widely used as in vitro modelsto investigate differentially secreted proteins related to malignanttransformation of breast cells (Table 2). These differentially secretedproteins may provide insights in the underlying neoplastic processesand represent potential biomarkers for early breast cancer detection.Mbeunkui et al. analyzed CM from isogenic cell line series representingdened stages of breast cancer progression [72]. A list of 37 secretedproteins with signicant differences in abundance across the cell lineswas provided. Of those, four proteins were subsequently veriedby western blot (WB). Similar proteome comparisons between non-tumorigenic and tumorigenic breast cell lines were performed byother investigators resulting in the identication of cyclophilin A,14-3-3 delta, peroxiredoxin [73], SerpinE2, OSF-2 [74] and endorepellinLG3 fragment [75] as potential secreted biomarkers for early detectionof breast cancer. Chang et al. usedWB and selected reactionmonitoring(SRM) to demonstrate that expression of endorepelin LG3 fragmentwas decreased in plasma from breast cancer patients (N=6) comparedto healthy controls (N=6) [75]. Ahn et al. proled N-glycoproteinspresent in the secretome of a single breast cancer cell line and aimedto identify glycoproteins that might be used as diagnostic markers[76]. They used WB and targeted nanoLC-MS/MS (for predeterminedprecursors) to validate the presence of nine out of thirteen glycopro-teins in plasma from six breast cancer patients.

Development of resistance to chemotherapy is a key problem inthe treatment of breast cancer and it is currently not possible to pre-dict response to certain chemotherapeutics. Yao et al. characterized

the secretomes of one doxorubicin-sensitive and one -resistant breast

Table 2Overview of breast cancer secretome studies.

First author[ref]

Year Aim Comparison/sample types Pre-MS workow MS workow No. of proteins identied/differential

Validation

Conditioned medium of cell lines/cultures (tumor/altered cells (vs normal))

Kulasingam[109]

2007 To identify secreted breast cancerspecic proteins

CM of three breast cell lines (MCF-10A,BT474, and MDA-MB-468)

In solution digest,2D chromatography

LC-MS/MS Total IDs: 1139 Validation by ELISA.

Mbeunkui[72]

2007 To discover highly secreted proteinswhich changed signicantly inabundance corresponding withaggressiveness

CM of isogenic series of breast cancercell lines representing progressionfrom non-tumorigenic towards a met-astatic phenotype

Small reverse phaseC2 columnfractionation, trypticdigestion

LC-MS/MS Selected abundantlysecreted IDs: 37

Four of ve proteins were veried by WB in CM: AACT,AAT, SPARC, and MSLN.

Chang [75] 2008 To identify serological biomarkers forbreast cancer

CM of one non-tumorigenic(Hs578Bst) and one malignant(Hs578T) breast cancer cell line

2D-GE MALDI-TOF Differential IDs: 8 proteinswith more than two-foldchange

Validation by WB and SRM in plasma of six breastcancer patients and six healthy controls: endorepellinLG3 fragment.

Liang [74] 2009 To identify serum-based biomarkers fordiagnosis

CM of a normal (HTB-125) andmalignant (HTB-126) breast cell line

SILAC+1D-GE LC-MS/MS Total IDs: 380; differentialwith at least three-fold: 45

Verication by WB in CM: SerpinE2 and OSF-2.

Ahn [76] 2010 To identify N-glycoproteins for diagnosisand for better understanding of breastcancer biology

CM of one breast cancer cell line(Hs578T)

N-glycoproteincapture, SCX

LC-MS/MS Total N-glycoproteins: 132 Validation of eight proteins by WB and targeted LC-MS/MS in depleted plasma samples from six breast cancerpatients.

Lai [73] 2010 To identify proteins linked totumorigenesis of breast cancer

CM of a normal breast cell lline(MCF-10A), a noninvasive breast cancercell line (MCF-7) and an invasive breastcancer cell line (MB-MDA-231)

2D-DIGE MALDI-TOF Differential IDs: 50 Verication by WB in CM: cyclophilin A, 14-3-3deltaand peroxiredoxin.

Wu [57] 2010 To generate a comprehensive cancer cellsecretome and identify cancer-specicand pan-cancer biomarkers

CM of 23 different cancer cell lines (of11 different cancer types); two breastcancer cell lines, MCF-7 andMDA-MB-435S

1D-GE LC-MS/MS Total ID's: 4584, on average1300 per cell line, 1318 inMCF-7 and 1780 inMDA-MB-435S, 153 uniquefor breast cancer

None for breast cancer.

Yao [32] 2011 To identify secreted proteins associatedwith drug resistance which can be used aspotential serumbiomarkers or drug targets

CM of doxorubicin-sensitive (MCF-7)and -resistant (MCF-7/Dox) breastcancer cell lines

1D-GE LC-MS/MS Total IDs: 2084; differential:89

Validation by RT-PCR and ELISA in cell lysate and cm andby ELISA in lysates of tumors from twelve breast cancerpatients who received neoadjuvant chemotherapy.

Chevalier[77]

2012 To identify secreted proteins followingirradiation that may be involved in celldeath signaling

CM of a irradiated and non-irradiatedbreast cancer cell line (T47D)

2D-GE MALDI-TOF,LC-MS/MS

Differential IDs: 17 Verication by WB in CM of six breast cancer cell lines:CyPA.

Whelan[110]

2012 To identify biomarkers for early breastcancer detection

CM of seven breast cancer cell linesrepresenting three breast cancersubtypes (T47D, MCF-7, MCF-7HER2,SKBR-3, MDA-MB-453, MDA-MB-468and MDA-MB-231)

In solution digest LC-MS/MS Total IDs: 249 Seven proteins were veried in cell lysate and CM byWB: thrombospondin 1, galectin-3 binding protein,cathepsin D, vimentin, zinc- 2-glycoprotein (ZAG),CD44 and EGFR.

Conditioned medium of cell lines (tumor biology)

Toillon [80] 2007 To identify proapoptosis proteinssecreted by normal breast epithelial cells

CM of normal breast epithelial cells Ultracentrifugation,HPLC, 1D-GE

LC-MS/MS IGFBP-3 and Maspin wereidentied asapoptosis-inducing factors

Verication by WB in CM and lysate from normal breastepithelial cells and MCF-7 cells.

Butler [84] 2008 To gain further insight into thebiological function of MMPs andto evaluate effects of MMPI

CM of MMP-14 transfectedMDA-MB-231 cells treated with MMPIversus control

ICAT labeling, insolution digest, SCX,

LC-MS/MS Total IDs: 269 Cleavage assay was performed to conrm novelproteins as direct substrates of MMP-14.

Jacobs [81] 2008 To characterize extracellular proteinsexpressed in human mammaryepithelial cells and to identifyEGFR-regulated secreted proteins

CM of human mammary epithelialcells treated with PMA versus EGFRinhibitor versus PMA+EGFR inhibitorversus control

Lyophilization,desalting column,in-solution digest,SCX

LC-MS/MS Total IDs: 889; specic forextracellular compartment:151

Verication by ELISA in CM from HMEC cells upon PMAand/or EGFR inhibitor treatment: MMP-1, MMP-9 andMMP-10.

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Perera [83] 2008 To investigate the role of leptin in breastcancer progression and to identifypotential mechanisms underlying therelationship between obesity and breastcancer morbidity

CM of MCF-7 cells treated with orwithout leptin

2D-GE MALDI-TOF Differential IDs: 9 Verication by RT-PCR in MCF7-cells on mRNA level:Collagen IV, FGF-9 and TGFB3.

Xu [78] 2010 To investigate the TGFB1 mediatedmechanisms regulating stromal-epithelialinteraction in breast cancer

CM of murine mammary broblastswith or without intact TGF-beta type IIreceptor

SILAC, 1D-GE LC-MS/MS Total IDs: 1786; differential:54

Verication by WB and ELISA of some proteins.Functional validation of CXCL10 for proliferation andmigration in PyVmT cells.

Bronisz[79]

2012 To investigate the molecularmechanisms of Pten loss in stromabroblasts on breast cancer cells

CM of Pten-null murine mammary -broblasts with or without miR-320expression

Not mentioned LC-MS/MS Differential IDs: 51 Functional validation of blocking of MMP9 andEMILIN2 for proliferation and migration.In silico validation of the 54-secretome prole on micro-array data showing correlation with patients outcome.

Tumor/tissue interstitial fuid

Celis [20] 2004 To explore TIF as a potential new sourceof biomarkers and to provide an over-view of the TIF proteome

TIF of sixteen breast tumors 2D-GE Proteins wereidentied using acombination ofMS-based andother methods

Total IDs: 267 None

Celis [86] 2005 To identify adipocyte-secreted and tis-sue proteins and to gain insights into therole of adipocytes in the breast tumorenvironment

Fat interstitial uid and fat tissuecollected from sites next to the breasttumor obtained from twelve breastcancer patients

2D-GE Proteins wereidentied using acombination ofMS-based andother methods

Total IDs: 359 None

Cortesi [31] 2009 To identify predictive biomarkers forchemotherapy response

TIF and NIF from ten responders andfour non-responders to chemotherapy

2D-GE LC-MS/MS Total IDs: 55 None

Gromov[87]

2010 To identify abundantly secreted proteinsin breast cancer

Two phases approach:First phase: Comparison TIF and NIFfrom one patient to identifyupregulated proteins in TIF.Second phase: Further selection ofupregulated proteins found in rstphase in TIF samples from 68 breastcancer patients

Four methods wereperformed forprotein separationand enrichmentbefore LC-MS/MS

MALDI-TOF,LC-MS/MS

First phase: Total IDs: 623;differential: 110Second phase: 26 proteinswere detected in >90% ofTIF samples

Validation byIHC on commercially available TMA containing 70breast carcinoma: calreticulin, cellular retinoicacid-binding protein II, chloride intracellular channelprotein 1, EF-1-beta, galectin 1, peroxiredoxin-2,platelet-derived en- dothelial cell growth factor, pro-tein disulde isomerase and ubiquitincarboxyl-terminal hydrolase 5.

Raso [88] 2012 To develop a combined massspectrometry and bioinformatic strategyto analyze TIF and NIF

Paired TIF and NIF from three breastcancer patients

TmT labeling,in solution digest

LC-MS/MS Differential IDs: 339, 1 and564 for three patientsrespectively

Verication by WB in lysates of the same tumors:GAPDH, PCNA, YWHAZ, GDI-1, and HNRNPD.

Nipple aspirate uid

Varnum[111]

2003 To evaluate a novel method for obtainingNAF and to provide an overview of theNAF proteome

Pooled NAF samples from ten healthywomen

Protein depletion, insolution digest, SCX

LC-MS/MS Total IDs: 64 None.

Alexander[112]

2004 To describe the NAF proteome and toidentify breast cancer biomarkers in NAF

NAF samples from ten patients withbreast cancer and ten healthy controls

2D-GE MALDI-TOF Differential IDs: 7 Validation by ELISA in 105 NAF samples from 52 normalbreasts andfrom 52 breasts with DCIS or invasive cancer for threeproteins, of which AAG showed signicantly consistentresults, whereas GCDFP-15 showed an inverse correlation

Pawlik [89] 2006 To identify differentially expressedproteins in NAF from tumor-bearing andcontralateral healthy breasts of patientswith early-stage breast cancer

Paired NAF samples from tumorbearing-breast and disease-free breastobtained from ten patients with pri-mary breast cancer

ICAT labeling, 1D-GE LC-MS/MS Total IDs: 39; differential:35

Validation byWB in NAF obtained from an independentcohort of four healthy controls and eight women withearly-stage breast cancer: vitamin D-binding protein.

Pavlou [37] 2010 To characterize the NAF proteome inorder to aid the identication of novelcancer biomarkers

NAF samples obtained from threehealthy women and three patientswith breast cancer

Each NAF sample wasfractionated with adifferent method

LC-MS/MS Total IDs: 412 and 777 inNAF from healthy controlsand breast cancer patients,respectively

None.

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Table 3Overview of colorectal cancer secretome studies.

First author[ref]

Year Aim Comparison/sample types Pre-MSworkow

MS workow No. of proteins identied/differential Validation

Conditioned media of cell lines/cultures (tumor/altered cells (vs normal))

Xue [90] 2010 To identify biomarkers forthe prediction of colorectalcancer metastasis

CM and cell lysates of two cell linesfrom the same tumor: SW480(derived from the primary tumor)and SW620 (derived from a lymphnode metastasis)

In solutiondigest

LC-MS/MS Total IDs: 910; differential: 145 withFC of 1.5 and 75 upregulated inSW620

ELISAs were performed for TFF3 and GDF15 inserum of colorectal cancer patients (n=144)and controls (n=156). TFF3 had a sensitivityof 53.3% and a specicity of 97.4%. GDF15 hada sensitivity of 77.8% and a specicity of99.4%.IHC conrmed an association of theseproteins with lymph node metastasis.

Karagiannis[92]

2012 To gain more insight oninvasive front autocrineand paracrine events

CM of four colorectal cancer cell lines:SW480, SW620, HCT116, HT29 and anormal colon broblast line CCDC18Co;both single as well as co-cultured

In solutiondigest, SCX

LC-MS/MS Total IDs: 2142 KLK6, KLK7, KLK10 and MCM2 were validatedby ELISA in CM; colXII mRNA overexpressionin colorectal cancer compared to normal bycDNA array and protein overexpressopn byIHC.

Wu [57] 2010 To generate a comprehensivecancer cell secretome andidentify cancer-specic andpan-cancer biomarkers

CM of 23 different cancer celllines (of 11 different cancer types);three colorectal cancer celllines, Colo205, SW480and SW620

1D-GE LC-MS/MS Total IDs: 4584, on average 1300per cell line, 1322 in Colo205, 857in SW480 and 1440 in SW620, 109unique for colorectal cancer

None for colorectal cancer.

Wu [91] 2008 To identify colorectal cancerbiomarkers by comparing theCM of 21 cancer cell lines

CM of 21 cell lines including two coloncancer cell lines (Colo205 and SW480).

1D-GE MALDI-TOF Total IDs: 40 for Colo205 and 33 forSW480; differential: 2 (CRMP-2 andglutathione synthase)

For CRMP-2 validation was performed withRT-PCR (on cell lysates), WB on CM and IHCon tissues. ELISA was performed on plasmafrom colorectal cancer patients (n=201) andhealthy controls (n=201).

Yao [113] 2012 To identify biomarkers witha lectin based afnity approach

The Con A and WGA lectin bindingproteins in CM of nine colon tumorsand matched normal colon

1D-GE LC-MS/MS Total IDs: 1446; secreted: 413, ofthese 123 were differential

EFEMP2 was validated by mRNA expressionlevel analysis in colon cancer tissues, by WBon the CMs, by IHC on 123 colon tissues, andnally by ELISA which revealed a sensitivityof 82.8% and specicity of 93.7%.

Conditioned media of cell lines (tumor biology)

Pocsfalvi [51] 2011 To investigate the effect ofsustained c-Myc expressionon the secretome of anontransformed humanepithelial cell line

CM of a cell line with induciblec-Myc expression

c-ICAT, 1D-GE LC-MS/MS Total IDs: 125; differential: 61 WB on six of the downregulated proteins andin silico validation by mRNA expression inadenomas and carcinomas and a number ofcell lines.

Volmer [22] 2005 To identify SMAD4 regulatedsecreted biomarkers

CM of SW480 (SMAD4 decient)and a SW480 cell line in whichSMAD4 was re-expressed

2D-DIGE MALDI-TOF Total differential IDs: 20 Cathepsin D, stratin and calumenin werevalidated by northern blot and WB on celllysates as well as WB on CMs, and 2D WB forcathepsin D on both the lysates and thesecretomes to reveal the pro-form and themature form.

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Mathivanan[93]

2012 To identify mutated secretedproteins

CM of a panel of 18 colorectalcancer cell lines

1D-GE LC-MS/MS Total IDs: 2728; on average981 IDs per cell line

Mutations were validated by RT-PCR andcDNA sequencing.

Lim [28] 2012 To examine the effects of mutationand truncation of APC on(extracellular) exosome proteinexpression and Wnt signaling

Exosomes isolated from CM fromcolorectal cancer cell lines SW480APC(restored APC gene) and SW480(mutant APC allele)

1D-GE LC-MS/MS Total IDs: 563 for SW480 and497 for SW480APC cells; 47 Idsuniquely identied in SW480APCcell

Increased expression of DKK4 in SW480APCwas shown at the mRNA level by RT-PCR and atthe protein level by WB. Presence in exosomeswas conrmed by immunogold electronmicroscopy.

Conditioned media/ascites (focus on exosomes)

Choi [94] 2007 To determine the global proteomeof highly puried microvesiclesfrom a human colorectal cancercell line

Microvesicles from HT29 colorectalcancer cell line

1D-GE LC-MS/MS Total IDs: 547 For eight proteins (-actin, ezrin, HSP90,LAMP1, -catenin, NG2, Galectin-4, JUP)expression was validated in cell lysates(WB) and microvesicles (WB).

Tauro [96] 2012 To provide a comprehensiveevaluation of current methodsfor exosome isolation

Exososomes isolated from colon cancercell line LIM1863 by three differentmethods: Ultracentifugation,Density-basedseparation, immunoafnity capture

1D-GE LC-MS/MS Total IDs: 627 in Immunoafnitycapture prep, 571 in Density-basedprep and 728 in Ultracentrifugationprep

None.

Choi [97] 2011 To gain insight into the pathologicalfunctions of microvesicles

Ascites uid from three colorectalcancer patients

1D-GE LC-MS/MS Total IDs: 846 None.

Mathivanan[95]

2010 To better understand the physiologicalrole of exosomes in colon cancerbiology

Exosomes from a colorectal cancercell line LIM1215, murine mast cellsand human urine

1D-GE LC-MS/MS Total IDs: 285 and 394 in the crudeand pure exosomes, resp.

None.

Tumor/tissue interstitial uid and stool

Shi [98] 2009 To distinguish proteins derivedfrom necrotic cells or plasma fromde novo synthesized secreted proteins

TIF and de novo synthesized secretedproteins of explants of normal colontissue (n=3) and colorectal cancerliver matastasis tissue (n=3); also,CM of four colorectal cancer cell lines

2D-GE MALDI-TOF Total spots: 93; differential: 31 None.

Fijneman [34] 2012 To identify protein biomarkers forthe early diagnosis of colorectalcancer

TIF of three colon tumors and threenormal pieces of colon from Apc15lox/+

C57BL/6 mice

1D-GE LC-MS/MS Total IDs: 2172; differential: 192 MCM4 and S100A9 were validated by IHC.CHI3L1 by ELISA in 86 serum samples ofhealthy controls, adenoma and colorectalcancer patients.

Ang [38] 2010 To investigate the potential offecal proteomics to identify coloncancer associated proteins andpeptides

Feces of three Apcmin/+ old mice(24 weeks), two young mice(4 weeks) and 2control mice (C57BL)

1D-GE LC-MS/MS Total Ids: 336 proteins None.

Ang [39] 2010 To validate fecal colorectal cancerbiomarkers that can complementdetection of hemoglobin

Feces of ve colorectal cancerpatientsand ve healthy controls

1D-GE LC-SRM 60 proteins selected from literature,19 quantitated

None.

Ang [40] 2011 To identify protein biomarkers Feces of two colorectal cancer patientsand two controls

1D-GE, RP-HPLCand SEC,digestion withtrypsin

LC-MS/MS,SRM

Total IDs: 108 human fecal proteins By SRM on feces of eight colorectal cancerpatients and seven healthy volunteers; outof 40 candidates nine proteins were onlyfound in feces of cancer samples.

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2254 T.B.M. Schaaij-Visser et al. / Biochimica et Biophysica Acta 1834 (2013) 22422258cancer cell line aiming to nd predictive biomarkers [32]. A total of2084 proteins were identied, of which 89 proteins were differential-ly secreted between both cell lines. Elevated protein expression ofIL-18 was detected in breast tumor lysates obtained from patientswho were resistant to neoadjuvant doxorubicin-containing chemo-therapy compared to tumor lysates from responding patients.In vitro, drug resistance in the presence of recombinant humanIL-18 was shown and drug sensitivity upon IL-18 blockade demon-strating the functional role of IL-18 in doxorubicin resistance.

Radiation treatment after surgery has demonstrated to preventlocal recurrence. In order to identify biomarkers related to sensitivityto radiation treatment, Chevalier et al. analyzed proteins secreted bybreast cancer cells after radiation [77]. Comparison between irradiat-ed breast cancer cells that survived and controls resulted in a total ofseventeen differentially secreted proteins. Of those, the differentialexpression of CyPA after radiation was veried by WB analysis.

5.2.2. Studies performed with conditioned media (aimed to study tumorbiology)

Interaction of tumor cells with the surrounding microenviron-ment may contribute to breast cancer progression and metastasis. Intwo studies [78,79], CM was studied to understand underlying mech-anisms of interactions between stroma broblasts and tumor cells. Inthe rst study, Bronisz et al. identied several miR's includingmiR-320 to be signicantly regulated by Pten in mammary broblasts[79]. Subsequently, the authors compared CM from Pten-null bro-blasts with or without miR-320 overexpression using nanoLC-MS/MS and WB and identied a total of 54 secreted proteins potentiallyregulated by miR-320. This 54-secretome prole was validated insilico on a publicly available microarray dataset to show prognosticvalue. In the second study, Xu et al. compared CM frommurine mam-mary broblasts with and without intact TGF-beta type II receptorusing SILAC and nanoLC-MS/MS [78]. More than 1000 proteins wereidentied, of which 54 proteins were differentially secreted betweenthe two conditions and were specically modulated by TGF-beta typeII receptor deletion. Functional validation of one of the 54 differentialproteins, CXCL10, showed stimulating effects of this protein on prolif-eration and migration. Others studied the inuence of adjacentnormal breast epithelial cells on tumor apoptosis and identiedIGFBP-3 andMaspin as potential apoptosis-inducing factors [80]. Sim-ilarly, Jacobs et al. characterized CM from human breast epithelialcells and found 151 proteins specically located in the extracellularcompartment [81]. These proteins may be involved in autocrine orparacrine regulation of breast epithelial cells. Several matrixmetalloproteinases (MMP-1, MMP-9 and MMP-10) were veriedusing ELISA.

Obesity is associated with increased risk of breast cancer [82] andelevated levels of the adipocyte-derived hormone leptin have beenobserved in obese women [83]. To further understand the role of lep-tin in obesity and breast cancer, Perera et al. analyzed CM fromMCF-7cells with or without leptin stimulation [83]. The authors identiedfactors including Collagen IV, FGF-9 and TGFB3 to be potentiallyregulated by leptin.

Lastly, proteomic analysis on CM can be employed to study drugeffects. For example, Butler et al. employed isotope-coded afnitytag labeling MS to investigate the effects of matrix metalloproteinaseinhibitors, a group of novel drugs that showed antitumor activity invitro, but failed to show clinical benet in clinical trials [84,85]. Com-parison of CM from MMP-14 transfected MDA-MB-231 cells with orwithout matrix metalloproteinase inhibition revealed multipleknown substrates of MMP-14 as well as several novel substrates. Sev-eral of these novel substrates were conrmed to be direct targets ofMMP-14 and may expand our current understanding of matrixmetalloproteinase signaling. The results of this pharmacoproteomicstudy may enable the development of more specic matrix

metalloproteinase inhibitors showing clinical benet.5.2.3. Studies performed with tumor/tissue interstitial uid (TIF)Celis et al. were the rst to perform proteome analysis on TIF [20].

A total of sixteen TIF samples were measured using a combination ofantibody-based and MS-based approaches yielding 267 identiedproteins. Although the overall TIF proteome differed remarkablyfrom the serum proteome, a considerable number of TIF proteinswere also present in human serum. Subsequently, Celis et al.employed a similar method to collect fat interstitial uid derivedfrom mammary adipocytes that were in close proximity to breasttumor [86]. A total of 359 proteins were identied in the secretomeof adipocytes.

Recent studies recognized TIF as source for potential biomarkers.Gromov et al. conducted a comparative analysis of TIF and normal in-terstitial uid (NIF) aiming to identify abundantly secreted proteinsin breast cancer [87]. In the initial discovery phase, paired TIF andNIF derived from the same breast cancer patient were analyzed.This analysis resulted in the identication of 110 upregulated pro-teins in the TIF and provided an initial set of proteins for further pri-oritization. In the subsequent analysis, the presence of these 110proteins was analyzed in 68 TIF samples by 2D-GE based proteomics.From this analysis, 26 proteins were detected in >90% of the TIF sam-ples and the investigators concluded that these proteins had most po-tential to be common breast cancer biomarkers. Some proteinswere further validated by immunohistochemistry (IHC) on tissuemicroarrays. In a pilot study of Raso et al., a novel method consistingof tandem mass tags sample labeling prior to quantitative MS wasproposed for proteomic proling of interstitial uid [88]. Analysison paired TIF and NIF samples from three breast cancer patients iden-tied approximately 1700 proteins and resulted in the most compre-hensive interstitial uid proteome currently published. Selectedproteins were veried by WB. In a recent study, Cortesi et al. com-pared NIF and TIF from breast cancer patients who showed differentresponse to chemotherapy [31]. Comparison of protein expressionin both NIF and TIF from non-responders versus responders showeddecreased expression of seven proteins (LDHB, FIBBdx, G3P sx, TBB5, TPIS, CAH 2, PGK1dx) and increased expression of ve proteins(LDHA, 14-3-3-Z, G3Pdx, VIME, and PGK1sx) in responders.

5.2.4. Studies performed with nipple aspirate uid (NAF)To date, few in-depth proteomic analyses have been performed in

NAF. Pavlou et al. employed nanoLC-MS/MS to delineate the NAF pro-teome [37]. The NAF samples from breast cancer patients (N=3)and healthy controls (N=3) were subjected to three differentprefractionation methods prior to MS to assess the best method to re-duce sample complexity. A total of 700 and 400 proteins were identi-ed in NAF from breast cancer patients and healthy controls,respectively, providing the largest list of identied proteins in NAFso far. Among those, several breast cancer biomarkers (CA15.3, UPA,Cathepsin-D and TPA) were detected indicating that NAF is a promis-ing source for biomarker discovery. In another study, Pawlik et al. an-alyzed paired NAF samples from tumor-bearing and tumor-freebreasts of ten patients with unilateral breast cancer using isotope-coded afnity tag labeling and nanoLC-MS/MS [89]. A total of 39 dif-ferential proteins were detected, of which nineteen proteins wereupregulated in the NAF of tumor-bearing breasts. Among those, vita-min D-binding protein was validated by WB in an independent set ofNAF samples obtained from eight patients and four healthy controls.

5.3. Progress in colorectal cancer secretome proteomics research

5.3.1. Studies performed with conditioned media (aimed at biomarkerdiscovery)

Most studies on CM aimed at identication of novel protein bio-markers for the detection of colorectal cancer. Two commonly usedcolon cancer cell lines are SW480 and SW620, derived from the pri-

mary tumor and a lymph node metastasis from the same patient,

2255T.B.M. Schaaij-Visser et al. / Biochimica et Biophysica Acta 1834 (2013) 22422258respectively. Xue et al. proled the CM from both cell lines and vali-dated upregulated proteins in the (metastasis) SW620 cells com-pared to those in the SW480 cells in serum of patients [90]. Twocandidate biomarkers, GDF15 and TFF3, showed high potential forthe discrimination between colorectal cancer patients and healthycontrols with a specicity/sensitivity of 99.4%/53.3% and 97.4%/77.8%, respectively. Wu et al. investigated tumor specicity of secret-ed proteins by analysis of CM of several cancer types in two studies[57,91]. In the rst study, Wu et al. focused on the identication ofspecic markers for colorectal cancer. This revealed collapsing re-sponse mediator protein-2 (CRMP-2) [91]. Validation of this proteinby ELISA on 402 plasma samples from colorectal cancer patients andcontrols showed that this protein had a sensitivity of 60.5% and aspecicity of 65.2% for detection of colorectal cancer. The secondstudy presents a comprehensive analysis of CM derived from 23 dif-ferent cell lines representing 11 cancer types [57]. Of all proteins(N=4584) identied in this study, 109 proteins were uniquelyfound in colon cancer cell lines. Overall only 30% of the proteinswere found uniquely in a specic cancer type, indicating that differ-ent cancer types secrete the same proteins.

Apart from the common limitations of the use of cell line models itis striking that many colorectal cancer secretome studies investigatedthe same two cell lines (i.e. SW480 and SW620) thereby potentiallyintroducing a biased view [57,9092].

5.3.2. Studies performed with conditioned media (aimed to study tumorbiology)

Volmer et al. investigated the effect of re-expression of the tumorsuppressor gene Smad4 in the SW480 cell line, while induction ofexpression of c-Myc was studied by Pocsfalvi et al. [22,51]. A similarsetup was used by Lim et al. [28] only here the expression of theAPC tumor suppressor gene was restored in SW480 cells, and the au-thors isolated the exosomes from the collected CMs. Upregulation ofthe Wnt antagonist DKK4 was found in the APC restored cell line,which may point towards an exosome-mediated mechanism of inhi-bition of Wnt signaling. A recent interesting study by Mathivanan etal. [93] identied mutated tryptic peptides in the CM of eighteen dif-ferent colorectal cancer cell lines. In total, 112 mutations in 57 uniqueproteins were identied that were novel for colorectal cancer. Eight ofthese mutations were validated by RT-PCR and cDNA sequencing.This study also presented a publicly available mutation database(HPMD) created specically for the detection of mutated trypticpeptides, thereby facilitating further research into mutated proteins.

5.3.3. Studies performed with conditioned media/ascites (focused onexosomes)

Several studies proled the protein content of exosomes derivedfrom colorectal cancer cell lines [9496] and some studies isolatedexosomes from biouids such as ascites uid and urine. Ascites uidcan result from a colorectal tumor and this malignant ascites is associ-ated with poor survival. A study by Choi et al. used an immunoafnitycapture method to isolate the exosomes from ascites uid of threecolorectal cancer patients [97]. They identied 846 proteins of whichseveral, such as Ep-CAM, play a role in cell adhesion and proliferation.A comprehensive overview paper on the three mostly employedexosome isolation strategies was published by Tauro et al. [96]. Tauroet al. conclude based on the number of MS/MS spectra identied andthe spectral counts of exosome markers (such as ALIX, TSG101 andHSP70) that the immunoafnity capture method is the most effectiveapproach. That strategy was applied in a study by Mathivanan et al.[95] using an antibody specic for colon epithelium (A33). A compari-son between exosomes isolated from CM of a colorectal cancer cell line(LIM1215), from human urine and from murine mast cells revealedthat next to common exosome proteins, these vesicles also contain tis-

sue specic proteins, that may carry potential for diagnostic purposes.5.3.4. Studies performed with tumor interstitial uid and stoolTwo studies used tissues instead of cell lines, with different ap-

proaches, one by Fijneman et al. and another by Shi et al. [34,98].Fijneman et al. proled the proteome of TIF of colon tumors from con-ditional APC knockout mice and compared these to NIF derived fromnormal mucosae of healthy mice. CHI3L1 was identied and validatedin sera by ELISA, and demonstrated a sensitivity of 55% and 75% fordetection of advanced adenomas or colorectal cancer, respectively[34]. A strong point of this study was the inclusion of advanced ade-noma patients' sera to investigate the potential application ofCHI3L1 for early detection. Interestingly, a large part of the colorectalcancer secretome proteins was released via unconventional secretion,presumably exosomes, and included many nuclear proteins such asthe colorectal cancer marker MCM4 [99]. Shi et al. aimed for the iden-tication of de novo synthesized proteins [98]. They hypothesized thatmany proteins that end up in the TIF are actually derived from theplasma or from necrotic cells in the tumor, and will not reect thelow abundant tumor derived biomarker proteins. Therefore, theymade tumor and normal colon explants that were incubated in thepresence of a metabolic label ([35S]-methionine) in order to distin-guish the newly synthesized proteins from the others. They comparedcomplete secretomes of these explants to the de novo synthesizedproteins and found that the de novo proteins are present at a lowerconcentration and include less plasma proteins compared to the com-plete secretomes. Potential drawbacks of this study are that the meth-od is quite extensive and the tissues were incubated up to 20 hours ina culture dish. It could be that many of the identied proteins aresecreted as a result of stress more than natural tumor cell behavior.

Stool proteomics has been pioneered by the group of Ang et al.[3840]. They developed a protocol for stool protein isolation andproled several samples with different techniques in three publica-tions. The rst study was done on murine feces and described theidentication of 336 proteins by a combination of 1D-GE andnanoLC-MS/MS (GeLC-MS/MS) [38]. For the second study a panel of60 potential biomarkers was investigated by SRM in human feces[39]. Their most recent study included a new discovery approach inhuman feces, revealing a fecal library of 108 fecal proteins, followedby SRM assays for 40 proteins [40]. However, many of the identiedcandidate biomarkers were blood-related proteins and thus unlikelyto add sensitivity to the current available tests for detection of hemo-globin in stool. In our own work, we investigated proteome proles ofstool samples obtained from colorectal cancer patients and controls.This yielded a dataset of 830 human proteins, the largest stool proteindataset to date, of which 134 were signicantly enriched in thecolorectal cancer stool samples [41] (manuscript in preparation,Bosch et al.).

A potential limitation of the use of proximal uids is sample com-plexity as high abundant blood proteins may hamper the discovery oftumor-related proteins. However, there are many possibilities tocircumvent this issue and each of the studies described above hassuccessfully implemented an approach to reach meaningful results,e.g. sample fractionation [34,97], metabolic labeling [98] or SRMassays [39,40].

6. Conclusions, discussion and future prospects

Since the rst secretome proteomics studies were published,about one decade ago, the eld has rapidly developed and is currentlystill moving forward. Methods and approaches have been rened toenable high-throughput or more in-depth analysis of fractionatedsecretome samples by nanoLC-MS/MS. Now follow-up of the multi-tude of secretome discoveries is needed to move towards clinicalapplications.

Up to now, discovery studies in secretomes focused mainly onidentication of biomarkers for discrimination between normal and

tumor cells or healthy and cancer patients in general, especially

2256 T.B.M. Schaaij-Visser et al. / Biochimica et Biophysica Acta 1834 (2013) 22422258when using TIF or proximal uids. Studies aimed at identication ofmarkers for disease stage, prognosis, treatment response predictionor prediction of recurrence are warranted. For example, the study ofYao et al. that describes the identication of biomarkers for predictionof doxorubicin-resistance in breast cancer patients [32].

There are many good examples of how secretome proteomicsapproaches can contribute to deciphering tumor biological processes.These analyses are often embedded in a series of logical, consecutiveexperiments and nalized with elaborate functional validation of theidentied molecular processes and involved proteins [29,30,33]. It isexpected that secretome proteomics will increasingly be used intumor biology research.

PE, NAF and stool, have been comprehensively proled to establishtheir value as biomarker source and their potential for use in diagnos-tics [35,3741]. Proling of these and other proximal uids such asbroncho-alveolar lavage uid or sputum in relevant patient groupscan soon be expected [43].

For the current studies, software packages such as SecretomeP andSignalP are used to determine the proportion of proteins predicted tobe secreted [46]. A designated database for described exosome pro-teins, ExoCarta, is now available that can be used to identify secretedproteins possibly present in exosomes. It would be relevant to have asimilar database for proteins identied in secretomes and in vivoproximal uids. To provide a link between the secretome and(tumor) biological processes, more software tools specically aimedat secreted and shuttling proteins are necessary. Another emergingeld of interest is detection of mutated peptides. The database pub-lished by Mathivanan et al. provides us with a tool that can be appliedto further mine proteomic datasets for the identication of suchpeptides [93].

Discovery in biomarker-rich subfractions could aid to furtherdissect the secretome and identify valuable markers. For example, theglycoprotein subproteome [70,76] as well as the exosome proteome[64,94,96,97,100] might harbor promising protein biomarkers that arerelatively more stable in blood. The interest in exosome (and othermicrovesicle) secretion (Fig. 3) is growing in the last years, as cancercells employ this route to promote their tumorigenic capacities[2426]. This is supported by various studies that describe the presenceof exosome markers and exosome-related proteins in secretomes andeven an upregulation of exosomes or exosome proteins in the cancersecretome or in the blood of cancer patients [2426]. This could alsoexplain the relatively large percentage of unexpected (nuclear,cytoplasmic, unconventional secreted) proteins mentioned to befound in tumor secretomes that could actually be exosome cargo[34]. These ndings underline the importance of future studies on can-cer microvesicles and their content consisting not only of proteins, butalso of low-molecular weight peptides and nucleic acids [101,102].

In the papers reviewed here, mostly differential expression of a fewpromising protein biomarkers was validated with antibody-based as-says in blood or tissue of a limited series of cancer patients (sometimesfurther divided in to clinically relevant groups) compared to suitablecontrols. Validation by antibody-based methods is limited by the avail-ability and quality of antibodies and can therefore be laborious, costlyand, most important, biased. Nowadays, targeted mass spectrometrymethods as SRM, and emerging alternatives such as pseudo SRM andSWATH-MS, are antibody-independent methods for verication andselection of the best candidates for further validation [103105]. WithSRM tens of promising protein biomarkers can be measured in atargeted manner with high sensitivity, usually in a single nanoLC-MS/MS run, thus allowing an increase in sample size. With this approachthe few best performing protein biomarkers can be selected forantibody-based validation, increasing chances of success [7].

Finally, selection of sufcient validation samples of particular pa-tient groups such as patients with different stages of disease, patientswith different tumor subtypes (e.g. lung SCC and SCLC are consider-

ably underrepresented) or patients with different responses totreatment can provide specic biomarkers and give further insightsinto specic clinical applications. Discrimination between trainingand validation cohorts could provide necessary information on accu-racy of the potential markers.

To conclude, the current results have stressed the importance ofthe cancer secretome, delivered a plethora of potential biomarkersfor clinical purposes and provided insights in important tumormicro environmental processes. Current developments in methodolo-gy and approaches will armour the eld to move towards addressingmore specic tumor biology and clinical questions, delving deeperinto the cancer (sub)secretome and taking validation further towardsclinical applications.

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