Targeted proteomic approach in prostatic tissue: a panel of potential biomarkers for cancer detection

Donatella Aiello1,*, Francesca Casadonte2,*, Rosa Terracciano2, Rocco Damiano2, Rocco Savino2, Giovanni Sindona1, Anna Napoli1

1Department of Chemistry and Chemical Technologies, University of Calabria, Italy
2Department of Health Sciences, Magna Græcia University of Catanzaro, Catanzaro, Italy
*These authors have contributed equally to this work

Correspondence to: Anna Napoli, email: amc.napoli@unical.it

Keywords: PCa tissue, biomarker, metabolic pathway, bodily fluids, proteome

Received: May 29, 2016

Accepted: June 03, 2016

Published: July 08, 2016

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Prostate cancer (PCa) is the sixth highest causes of cancer-related deaths in men. The molecular events underlying its behavior and evolution are not completely understood. Prostate-specific antigen (PSA) is the only approved Food and Drug Administration biomarker. A panel of ten stage-specific tumoral and adjacent non tumoral tissues from patients affected by PCa (Gleason score 6, 3+3; PSA 10 ÷19 ng/ml) was investigated by MS-based proteomics approach. The proposed method was based on identifying the base-soluble proteins from tissue, established an efficient study, which lead to a deeper molecular perspective understanding of the PCa. A total of 164 proteins were found and 132 of these were evaluated differentially expressed in tumoral tissues. The Ingenuity Pathway Analysis (IPA) showed that among all dataset obtained, 105 molecules were involved in epithelial neoplasia with a p-value of 3.62E-05, whereas, only 11 molecules detected were ascribed to sentinel tissue and bodily fluids.


Prostate cancer (PCa) is the second most common cancer diagnosis worldwide and the sixth highest causes of cancer-related deaths in men [1]. Genetic, environmental factor, age, hormonal imbalance and diet denote the risk factor for PCa development. The detection and diagnosis of PCa are carried out by the measurement of serum prostate-specific antigen (PSA) level, digital rectal exam and histological inspection of prostate tissue biopsy [2]. PSA is the only biomarker approved by Food and Drug Administration (FDA). This test is useful for early diagnosis reducing the mortality, whereas the low sensitivity and specificity lead to overdiagnosis and overtreatment [3]. The misdiagnosis of PCa results in an non-predicable and aggressive treatment which may initiate a series of molecular events, which are not well understood. Therefore, to improve the diagnosis specificity and the clinical management the identification of additional biomarkers is desirable. DNA microarrays [4] can be used to measure PCa by providing the ability to compare changes in gene expression in the developing of PCa; however, they do not allow measurements of the protein levels. Proteomics represent a promising approach for the discovery and identification of specific molecules or set of proteins that are characteristics of a pathologic state [5]. Proteomics analysis of specific tissue can elucidate the mechanism of cells transformation from normal to cancerous status and provide a specific set of proteins to differentiate aggressive or indolent cancer forms. To date, analyses of protein levels in cancer have been performed by either using two-dimensional (2D) PAGE and/or surface enhanced laser desorption/ionization (SELDI) mass spectrometry [6]. Several studies describe the use of isobaric-tags for relative and absolute quantitation (iTRAQ) for the investigation of prostate tissue in order to identify potential markers for cancer diagnosis, prognosis or treatment. [7] Garbis et al. [8] analyzed prostate tissue from patients with benign prostatic hyperplasia (BPH) and with prostate cancer thought iTRAQ labelling. Sixty five differentially expressed proteins have been previously described as specific marker for prostate cancer cells. These were identified as: prostaglandin E synthase resulting from significant upregulation of proteins, alpha-1-antitrypsin, which is a well-known as biomarker for inflammation and α-methylacyl CoA racemase. Sun et al. [9] analysed prostate tissue from BPH, PCa and BPH with local prostatic intraepithelial neoplasm and identified periostin as a potential biomarker for prostate cancer. It is well known that carcinogenesis produces in biological fluids cancer molecular specific biomarkers. These biomarkers result from complex biological phenomena which are supported by a rich network of different cells such as fibroblasts, endothelial cells, immune and inflammatory cells, extra-cellular matrix and proteins produced by the malignant microenvironment [10]. In an effort to identify a set of specific molecules which are associated with cancer development, in prostate tissues and biological fluids, we have developed an alternative method based on the extraction of hydro-soluble tissue proteins followed by protein fractionation compatible with mass-spectrometry analysis. In addition, tumoral and histological adjacent benign tissues of prostate from patients with elevated PSA value and Gleason Grade were selected as case studies to identify and quantify potential prostate tumor markers [11, 12]. A selective solubilization procedure was adopted to extract hydrosoluble basic proteins from prostate tissue. Then, protein depletion was performed to remove interfering highly abundant proteins; this removal unmasks low abundance proteins of interest for further investigation. The proteins were then subjected to solution phase trypsin proteolysis followed by iTRAQ-labelling and finally analysed by LC-MALDI MS/MS. Using this approach we found 164 proteins. 132 proteins were differentially expressed, 11 proteins were expressed in bodily fluids and these can be used as potential cancer biomarkers for PCa diagnosis.


An alternative and rapid protocol has been developed for selective protein solubilization [13-15] from prostate tissue, followed by iTRAQ labelling, HPLC fractionation and MALDI MS/MS analysis to identify a set of specific markers for PCa diagnosis. The procedure was optimized on the swine prostate tissue which is considered the best classic biomedical model for human disease [16]. High abundant proteins were depleted by two different commercial columns using alternative MS-compatible buffers and the resulting fractions were visualized by SDS-PAGE in order to check the efficiency of the planned procedure (Figure S1). Multiple Affinity removal spin cartridge was chosen as the optimal depletion device because it is able to carry out several runs with no memory effect.

The optimized sample preparation procedure was used for human prostate tissue. SDS-PAGE and MALDI-TOF MS profiles of the resulting fractions are reported in Figure 1 and Figure SI2, respectively. The major proteins are removed providing access to the next level of protein (hLA) as shown in Figure 1. SDS-PAGE shows different protein profiling of whole protein extracts (Figure 1, lines 3, 5 and 7) and hLA fractions (Figure 1, lines 3, 4 and 6). The experimental conditions for i-TRAQ quantitative analysis were modified (see experimental section). A total of 164 proteins were identified and 132 were considered differentially expressed between T and NT prostate tissue, with ion ratio of either ≥ 2 or ≤ 0.5 at p-value less than 0.05 for statistical significance (Table 1). Proteins were identified and quantified with no minus of three labelled peptides. The experiments were performed in triplicate and all peptide sequences are reported in Table SI2 and SI3 (Supporting Information).

The input data set containing all identified proteins from the iTRAQ LC−MS/MS analysis was uploaded into IPA [19]. The founded top five significant Molecular and Cellular Function associations with proteins are involved in Cellular Movement, Cellular Assembly - Organization, Cellular Development, Cellular Growth - Proliferation, and Gene Expression. Otherwise the top five obtained networks are all related to cellular proliferation, cellular death/survival and cancer (Supporting Information, Table SI3 A-F). IPA analysis evidenced that among all dataset, 105 molecules are involved in epithelial neoplasia with a p-value of 3.62E-05 (Table 1).


A crucial step in cancer control and prevention is the detection of disease as early as possible in order to allow effective interventions and therapies. Biomarkers are important as molecular signposts of the physiological state in specific cell at a definite time. In an effort to develop a comprehensive approach for biomarker-based prevention research it became primordial to draft a modern proteomic platform technology for biomarkers discovery and validation. Several studies have been focused on prostate cancer research through MS-based proteomic approaches [8] but biomarkers discovery remains a difficult task related to the complexity of the samples and the dynamic concentration of proteins. The mass spectrometry based proteomic approach described in this work is focused on the extraction, identification and quantitation of a base-soluble proteins subset from prostate tissue useful for diagnosis of human PCa. The choice for the analysis of stage-specific tumours (T) and healthy tissues adjacent to the tumour (NT) area could help in the elucidation of the molecular networks and mechanisms involved in pathogenesis. T and NT prostate tissue from the same individual were analysed since tissue samples show a wide biological variability particularly when they derive from different patients. The identification of base-soluble proteins could have the main advantage to be directly correlated to body fluids such as urine, which is enriched with proteins from PCa cells, hence giving the option to develop an alternative non-invasive biomarkers discovering method. The experimental design was planned to generate a consistent data set and to reduce the number of analytes handling, minimizing the result variability. The introduction of a pre-fractionation step prior to proteomic analysis reduce the sample complexity and improve the detection sensitivity of low-abundant proteins [20]. The buffers supplied by manufacture contain surfactants and salts that interfere with MALDI-TOF MS analysis, therefore we have developed a novel depletion protocol adopting saline solutions MS-compatible.

Differentially expressed proteins

Table 1 lists 164 proteins that were identified and quantified by Protein Pilot Paragon methods. The identified proteins were grouped in different classes which were based on their cellular location (Figure 2). The major parts of the proteins originated from the cytoplasm (38,5%) and nucleus (31,7%). The presence of membrane related proteins (20,0%) confirms the high-throughput performance of the extraction step. The origins of the remaining proteins were as follows: secreted (4,4%), ubiquitous (1%) and -from extracellular space (2,9%), while only a small part (1,5%) was unspecified.

Table 1 list several proteins involved in transcriptional regulation. The transcription factors participate in the gene expression at the ends of all 19 of the know signal transduction and stress pathways. [21] An increase in the activity of the transcription factors is correlated with the various changes in the protein expression, protein stability, protein-protein interaction and post-translation modification [21]. The increase of many of these activities can affect the cancerous transformation by modifying the typical function of transcriptional co-activator or co-repressors. Among the family of the transcription receptor factor, the nuclear receptor coactivator 1 protein (NCOA1, Table 1 - row 91), also called SRC-1, identified as up-regulated,. SRC-1 is a co-activator of the androgen receptor (AR) mediated signalling pathway. The involvement of the NCOA1 in prostate cancer progression was supported by the recent study of Agoulnik et al. [22]. NCOA1 over expression in the metastatic prostate cancer occurs in primary tumors rather than the normal prostate. Agoulnik et al demonstrated that the ablation of NCOA1 in the androgen-dependent LNCaP prostate cancer cells, represses the activation of the AR target genes and it reduces the AR-dependent cellular proliferation. Prohibitin (PHB, Table 1 - row 108) is an evolutionary conserved multifunctional protein that is upregulated in PCa samples and is also implicated in many cellular process [23, 24, 25]. Several studies have shown that the essential function of PHB is for cell proliferation and it as a crucial protein used for cancer cell growth and survival [26]. In accordance with our result, Umanni et al. [27]. examined biopsy

The identification and quantitation of proteins were performed using the Protein Pilot Paragon Method The MS/MS data were processed using a mass tolerance of 10 ppm and 02 Da for the precursor and fragment ions respectively b According to “UniProtKB” (http://wwwuniprotorg/) c According to “Compute pI/MW” (http://webexpasyorg/compute_pi/) *Proteins involved in epithelial neoplasia (p-value=362E-05).samples from benign prostate hyperplasia (BPH) and PCa patients proving a significant up-regulation of prohibitin in tumoral samples. A significant alteration change was observed in the expression of Actin and microtubule Cytoskeleton proteins (Table 1 - rows 3, 37, 38, 39, 63, 81, 82, 83, 137, 146,149, 150). These proteins are able to organize the cytoplasmic organelles and the intracellular compartments in order to drive the chromosomal separation and the cell division during morphogenesis, cell cycle, and to generate forces during cell migration [28, 29]. Myosin filaments (Table 1, rows 81, 82, 83, 149, 150) determine cell surface contractions and muscle cell contraction in accordance with actin. The kinesin (Table 1, rows 64, 65) and dynein (Table 1, rows 37, 38) proteins carry numerous cellular function including the transport of vesicles and organelles within cells, the beating of flagella and cilia and within the mitotic and meiotic spindles to segregate replicated chromosomes. Within this protein family, kinesin ensures a crucial role in the occurrence and development of human cancer. A great number of proteins from the kinesin super-family show abnormal over-expression in various cancer cells and this expression level indicates as prognostic marker for breast and lung cancer [30, 31]. A change of expression of the members of the G protein coupled receptor proteins is evident (GPRs, Table 1 rows 42, 107, 110). The GPRs belong to a family of cell-surface molecules implicated in signal transmission. GPRs proteins are implicated in many biological process as cell proliferation, motility, angiogenesis and metastasis and it has been recently highlighted the they are over expressed in various cancer type and have an incisive role to tumor cell growth [32]. The upregulated activity of GPRs might contribute to transition from hormone dependent to hormone independent tumor for prostate and breast cancer. Marinissen et al., [33] suggested that in PCa cell, GPRs can stimulate ERK phosphorylation and increase the transcription of ARs. The observed over regulation of kinases (Table 1, rows 26, 56, 59, 78, 79, 115, 129, 131, 132, 138) is fully in accordance with the data reported [34, 35]. In particular an oncogenic role was indicated for the non-receptor type tyrosine kinase, Protein Tyrosine Kinase 6 (PTK6, Table 1 row 115) [36]. PTK6 promotes cancer cell proliferation, migration and survival through activating oncogenic signalling pathways. Moreover it is involved in the activation of signal transducers and activators of transcription (STATs) that control tumorigenesis [37] and promotes AKT activation and phosphorylation [38]. Zheng et al. have described the increased levels of PTK6 mRNA in prostate cancer with respect to healthy normal prostate tissue and normal tissue adjacent to the tumor [39]. The same authors evidenced an higher expression of PTK6 in metastatic human prostate cancer samples, suggesting an oncogenic role for PTK6 in prostate tumor development and metastasis [40].

Pathway and network analyses

Proteomic data were analyzed using IPA software to select protein involved in cancer development, occurrence or progression and to evidence the biological processes in which these proteins are involved. IPA analysis suggests ve Top Networks (Supporting Information, Table S3), the rst one related to “Cell Death and Survival, Cancer” comprises 70 focus molecules and evidences as the majority of identi ed protein are directly and not mainly involved in three signalling pathways that play a crucial role in cancerogenesis: (i) the extracellular signal-regulated kinase (ERK) signaling pathway, (ii) the Nuclear factor kappa B (NF-ĸB) pathway and (iii) phosphatidylinositol 3-kinase/protein kinase-B/ mammalian target of rapamycin (PI3K/AKT/mTOR) signalling cascade (Figure 3).

The extracellular signal-regulated kinase (ERK) signalling pathway controls a broad range of cellular activities such as proliferation, survival, differentiation and motility. ERK regulates chromatin remodelling through the phosphorylation of cytoplasmic and nuclear targets as transcriptional factors and Cytoskeleton proteins [41]. In addition, activation of ERK 1/2 due to radiation, osmotic stress or tumor necrosis factor (TNF) inhibits apoptosis, while inhibition of the same pathway supports apoptosis. It has been shown that the increased activity of extracellular signal-regulated kinase is implicated in the development and prognosis of PCa [42]. Nuclear factor kappa B (NF-κB) transcription factors regulate several important physiological processes, including in ammation and immune responses, cell growth, apoptosis, and the expression of certain viral genes. The NF-κB pathway is often active and plays a key role in the disease since it involves a sequence of transcription factors that stimulate promotion and progression of tumors as well as chemotherapy and radiotherapy resistance [43] and it is clear that modulators of this pathway can act at several levels [44]. The phosphatidylinositol 3-kinase/protein kinase-B/mammalian target of rapamycin (PI3K/AKT/ mTOR) signalling cascade is a key oncogenic signalling pathway, which has a central role in several cellular processes signi cant for cancer progression [45]. The PI3K–AKT pathway is inappropriately activated in many cancers by receptor tyrosine kinases. PI3K/AKT/mTOR pathway prevents apoptosis, induce cancer cell growth and promotes resistance to anticancer therapies acting on cellular differentiation and metabolism [46, 47]. Recently, several researches have demonstrated that the activation of the PI3K/AKT/mTOR pathway was strongly implicated in the prostate cancer progression [48]. Moreover, Gao et al. suggested that this signalling pathway could serve as a novel target for therapeutic intervention in prostate cancer [49].

PCa differentially expressed proteins vs bodily fluids

Proteomic data were further elaborated by IPA in order to maximize the impact of the information, to get a more comprehensive understanding about the obtained results and suggest the proposal of biomarkers to screening populations at risk for cancer. The device “Biomarker Filter” measures whether a particular protein is detectable in tissue or bodily fluids in an effort to identify a cohort of possible proteins associated with a specific disease. The proteomic data are evaluated by three restriction levels: (i) Urine, (ii) Urine and Prostate Gland, (iii) Urine, Prostate Gland and Plasma/Serum. Eleven up- and down-regulated proteins are sselected and reported in Table 2. These 11 proteins are eligible cancer biomarkers and are also present in a set of bodily fluids. In PCa Catenin Beta 1 (CTNNB1, Table 2) contributes to cadherin-mediated adhesion and acts as coactivator binding androgen receptor suggesting that it has a role in castration-resistant disease [50]. An abnormal activation of WNT/β-catenin signalling has been reported in colon cancer [51], and a typical up-regulation of cytoplasmic β-catenin was detected in thyroid carcinogenesis [52]. The observed down-regulation of Tropomyosin 2 (TPM2, Table 2) is in agreement with several studies that proved the association of its altered expression with carcinogenesis [53]. The expression change of TPM isoforms can be induced by variety of carcinogens including chemical carcinogens, UV radiation, DNA and RNA tumor viruses during cancer cell transformation. Varisli showed that the expression of TPM2 may decrease with growing score of cancer and suggested the level of this protein are useful as a prognostic biomarker tool for prostate cancer [54]. The up regulation of tropomyosin alpha-3-chain (TPM3, Table 2) is supported by the results of Franzen et al. in which they have found higher level of TPM isoform in the primary breast cancer that had metastasised, rather than in the axillary lymph nodes [55]. Up-regulation of the tyrosine 3-monooxygenase/tryptophan 5 monooxygenase activation protein zeta (YWHAZ, Table 2), a 14-3-3 zeta isoform., belonging to the 14-3-3 protein family, was observed. In humans, 7 different 14-3-3 isoforms have been identified ubiquitously expressed and highly conserved in all eukaryotic organisms [56]. This protein family interact with hundreds of binding partners and is involved in the regulation of vital cellular processes [57]. 14-3-3 protein family was associated with proto-oncogene and oncogene products suggesting a direct contribute to cancer development [58]. Murata et al. [59] analyzed the immunoreactivity of YWHAZ in formalin fixed paraffin embedded sections of benign and tumoral prostate tissue evidencing the protein overexpression in PCa tissue. Platelet endothelial cell adhesion molecule-1 (PECAM-1, Table 2) is a 130kDa membrane glycoprotein belonging to the immunoglobulin superfamily that is able to mediate both homophilic and heterophilic adhesions. PECAM-1 appears to be involved in a variety of biological functions. [60] Karagianis et al. found the up-regulation of PECAM-1 of the proteome of endothelial cells, in which PECAM was differentially regulated by an androgen-independent angiogenic response [61]. The down regulation of Transgelin (TAGLN, Table 2), is consistent with several studies which reported significantly lower levels of TAGLN expression in the immortalised human prostate epithelial cell line RWPE-1, in the metastatic LNCaP cells and in the metastatic PC3 [62]. The down regulation of transgelin can be correlated to the prostate cancer progression, it may be used as a marker for cancer in addition to provide a target for novel cancer therapies. Perturbation of PTK signalling by mutations and other genetic alterations results in deregulated kinase activity and malignant transformation. It well know the switch role of the mammalian target of rapamycin, mTOR (Table 2), in regulating life or death signals, between “cell growth - cell cycle” and “damaged microtubules”. mTOR is emerged as a critical effector in cell-signaling pathways commonly deregulated in human cancers suggesting that mTOR inhibitors may be useful in oncology [63]. BRAF is a serine/threonine kinase (Table 2) that is commonly activated by somatic point mutation in human cancer and his activity is also regulated by phosphorylation of residues in the activation segment. Moreover the high frequency of mutations in melanoma and the relative lack of effective therapies suggested that inhibition of BRAF activity may be an important new strategy in the treatment of some cancer types [64]. The upregulation of Dihydropyrimidinase enzyme (DPYS, Table 2) is another important data. DPYS deficiency induces haematological or gastrointestinal toxicity during treatment with 5-fluorouracil for common neoplasms [65]. Pyrimidine pathways are fundamental in human physiology and several studies report their upregulation in malignancy [66] making them ideal targets for pharmacological intervention. Finally, the identification of upregulated insulin-like growth factor binding protein 5 (IGFBP5, Table 2) is in agreement with its role in the IGF system, where is involved in normal growth and development. In particular increased expression of IGFBP5 has been reported in tumors of the gastrointestinal tract [67, 68]. IGFBP5 appears to exert a specific inhibitory effect on melanoma growth and metastasis through inhibition of the ERK1/2 and P38-MAPK pathways, therefore it may qualify as a useful therapeutic target against melanoma and other cancers [67].

The proposed proteomic approach, focused on base-soluble proteins from tissue and present in biological fluids, constitutes a study leading to a deeper understanding of the PCa from a molecular perspective. The selective proteome extraction allows a direct correlation and identification of deregulated pathways providing a panel of candidate diagnostic biomarkers. A limitation of the study might be the relatively small sample number, but the opportunity to transfer this results on other biological matrices, more easily available (as body fluids), opens new chances. The identification of eleven deregulated proteins from prostatic gland, present in body fluids, and some specific for urine, could be an important start point to select new cancer biomarkers. Further studies are needed to confirm the proposed biomarkers and to evaluate the diagnostic potential of the other differentially expressed proteins which might further improve the diagnostics accuracy of the proposed set.


Reagents and chemicals

Ammonium Bicarbonate (NH4 HCO3, 99.5%), trypsin (proteomics grade), α-cyano-4-hydroxy-trans-cynnamic acid (α-CHCA, 99,0%), water (HPLC grade), trifluoracetic acid (TFA, 99,0%), methanol (HPLC grade), acetone, protease inhibitor cocktail and protein standards for protein molecular weight marker were purchased from Fluka-Sigma Aldrich S.r.l. (Milan, Italy). Protein standards and reagent for protein quantification were acquired by Bio-Rad’s Laboratories, Inc. (Monza, Italy). iTRAQ reagents and buffers were obtained from Applied Biosystems (Foster City, CA). Peptide and protein standards, for mass spectrometer external calibration, were prepared from the Sequazime peptide mass standard kit (Applied Biosystems, Framingham, MA, USA).

Protein extraction

The experimental procedure was developed on porcine prostate tissue. The prostate tissue was given by official slaughterhouse after veterinary inspection and transferred in ice in laboratory. Tissues were washed three times in ice-cold phosphate buffered saline, cut in small pieces, weighed and freezed at -80°C until the protein extraction. The tissues obtained from a total of ten patients (A-L) affected by prostate cancer (Gleason score 6, 3+3) with elevated PSA level (between 10 to 19 ng/ml), classified by Tumour Node Metastasis (TNM) as T1c, N0, M0, were selected for the study after informed consent. This study was approved by the ethics committee of Magna Graecia University, patients had signed a written consent to prostate biopsies and clinical data access for research purpose. After radical prostatectomy “Non Tumoral” (NT) and “Tumoral” (T) fragments prostate tissue from the same individual were cut in two sections. One section was formalin fixed paraffin embedded and stained with hematoxylin-eosin for histological evaluation while the second one was immediately frozen at -80°C prior to proteins extraction. The frozen prostate tissue were powdered in liquid nitrogen. The powdered tissues were further homogenized in 1 mL of a cold solution containing 50mM NH4 HCO3 (pH 8), 0,05% SDS (v/v) and protease inhibitor cocktail (1:100, v/v), then submitted to sonication conditions 3 times for 10s/time [17, 18]. Each operation was performed on ice. The resulting homogenates were centrifuged at 50,000 x g for 1h at 4°C. Concentration of protein extracted was determined by Bradford’s assay [69].

Immunodepletion of high-abundant proteins

The porcine proteins extracted were depleted of high abundant proteins using two commercially cartridge: “Multiple affinity removal spin cartridge” (Agilent Technologies, Milan, Italy, 5188-5230) and “ProteoPrep Blu Albumin and IgG depletion Medium” (Sigma Aldrich, PROT-BA). The cartridge were treated three times with 200 μl of 50mM NH4 HCO3, (pH 8), before loading the sample. A volume of 200 μl, containing 500 μg of extracted proteins, were applied on column and incubated for 10 min at room temperature. After centrifugation at 3000 rpm for 1 min, the flow-through fraction (depleted of albumin, IgG, IgA, transferrin, haptoglobin and α1-antitrypsin for Agilent column and of albumin and IgG for Sigma column) were loaded again on column, centrifuged and collected. The cartridges were washed two times with 200 μl of 50mM NH4 HCO3 and the relative flow-through were collected and combined with the previous depleted fractions. To elute the membrane-bound high abundant proteins, two washing with (NH4)2 CO3 (pH 10), were performed. After 10 min of incubation and a subsequent centrifugation at 3000 rpm for 2 min, the eluted fractions were collected. An aliquot of low abundant proteins fraction and of high abundant eluted proteins were analyzed directly by linear MALDI mass spectrometry and the relative protein amount was quantified by Bradford’s assay. Moreover, each fraction eluted was visualized on SDS-PAGE. Depletion of high abundant proteins for human prostate was performed only with Multiple affinity removal spin cartridge.


Depleted flow-through, eluted fraction containing high abundant proteins and an aliquot of whole extracted proteins were analyzed by SDS-PAGE. All fractions were mixed with 5x gel loading buffer, containing 2-mercaptoethanol and bromophenol blue, denaturated at 95°C for 10 min before electrophoresis analysis in 12.5% sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE). Precision Plus Protein kaleidoscope standard (Bio-Rad’s Laboratories, Milan, Italy) was loaded in the molecular weight marker lane for porcine samples, while an homemade protein molecular weight marker (Lactoferrin 87 kDa, L9507; Bovine Serum Albumin 66 kDa, A2153; Albumin from chicken 44 kDa, A5503; Mioglobin from equine skeletal muscle 17 kDa, M0630; Cytocrome C 12 kDa, C2506) was adopted for human proteins. Proteins were stained with Comassie Brillant Blu R-250 for 4 hours and destained overnight with a solution containing 40% MeOH, 10% CH3 COOH and 50% H2 O.

Porcine protein digestion

Fifty micrograms of pig prostatic proteins from the depleted fraction proteins were digested overnight with trypsin, protein to enzyme ratio of 20:1, at 37°C in NH4 HCO3, 50mM (pH 8.0) and dried by Concentrator Plus system (Eppendorf, Hamburg, Germany).

Human proteins digestion and iTRAQ sample labelling

The experimental conditions for i-TRAQ quantitative analysis were modified as follows. The six standard proteins mixture was digested with trypsin (ratio enzyme: substrate, 1:20) in a solution of Tetraethylammonium bromide (TEAB, 0.5M) and labelled without alkylation and reduction steps. The resulting peptides mixture was separated by off line RP-HPLC and analysed by MALDI-TOF MS. Approximately 40-60% of Six-protein Mix peptides were identified and quantified. 20 peptides of Bovine Serum Albumin (P02769), 23 peptides of β-Galactosidase (P00722), 2 peptides of α-Lactalbumin (P00711), 4 peptides of β-Lactoglobulin (P02754), 4 peptides of Lysozyme (P00698) and 18 peptides of Apotransferrin (P02787) were identified by MS/MS analysis (Table S1, Supporting Information). The number of identified peptides was satisfactory for the unique protein identification with suitable sequence coverage.

Two hundred micrograms of proteins from immunodepleted fractions were precipitated overnight at -20°C in six volume of cold acetone. The pellet was re-suspended in 30 μl of 500mM triethyl ammonium bicarbonate buffer (TEAB, supplied by Applied Biosystem and named as “Dissolution Buffer”) and the proteins were quantified by Bradford’s Protein Assay. Ten micrograms of each NT fraction from patients A-L were pooled together and digested with trypsin, protein to enzyme ratio of 20:1, at 37°C overnight. The same procedure was performed for T fractions from patients A-L. Tryptic peptides were labelled with the iTRAQ reagents (m/z 115.1 and 117.1) following the manifacturer’s protocol (Applied Biosystem). Briefly, the iTRAQ reagents were thawed at room temperature and spun to collect the reagent at the bottom of the tube and dissolved in 70μL of ethanol. The iTRAQ labels were added to the digested samples, in particular m/z 115.1 reporter ions was added to NT sample, while m/z 117.1 to T samples. The mixture was vortexed, centrifuged and incubated for 90 min on a rocker at 5rpm (Digital Rocker RK-1D, Witeg, Germany). The labelled samples were combined and dried in Concentrator Plus system prior to reverse phase chromatography [70-72] (RP-HPLC) fractionation as reported.

MALDI-TOF MS and MS/MS analysis

Linear MALDI-TOF spectra were acquired with a 4700 Proteomics Analyzer mass spectrometer from Applied Biosystems (Foster City, CA) equipped with a 200-Hz Nd:YAG laser at 355-nm wavelength. A 1-μL portion of a premixed solution of whole or depleted samples and α-CHCA (0.3% in TFA) was spotted on the matrix target, dried at room temperature, and analyzed in the mass spectrometer. Spectra were acquired averaging 2500 laser shots with a mass accuracy of 500 ppm in default calibration mode that was performed using the following set of standards: insulin (bovine, [M + H]+ average m/z 5734.59), apomyoglobin (horse, [M +H]2+ average m/z 8476.78, [M + H]+ average m/z 16 952.56), and thioredoxin (Escherichia coli, [M + H]+ average m/z 11 674.48). MS and MS/MS analysis of offline spotted peptide samples were performed using the 5800 MALDI-TOF/TOF analyzer (AB SCIEX, Darmstadt, Germany) equipped with a neodymium: yttrium-aluminium-garnet laser (laser wavelength: 349 nm), in reflectron positive-ion mode. All chromatographic fractions were re-suspended in 10 μl of α-CHCA matrix (10 mg/mL, CH3 CN/0,3% TFA in water, 50:50, v:v), 1 μl of peptides matrix mixed solution was spotted on a MALDI plate and dried at room temperature. At least 4,000 laser shots were typically accumulated with a laser pulse rate of 400 Hz in the MS mode, whereas in the MS/MS mode spectra up to 5,000 laser shots were acquired and averaged with a pulse rate of 1,000 Hz. MS/MS experiments were performed at a collision energy of 1kV and ambient air was used as the collision gas with a medium pressure of 10-6 Torr. Protein identification was performed with the Protein Pilot 4.0 software program (AB Sciex) using the Paragon protein database search algorithm (AB Sciex).20 The data analysis parameters for porcine samples were: Sample Type: Identification; Cys Alkylation: None; digestion: Trypsin; Instrument: 5800 AB Sciex; Species: Suis Scrofa; Database: SwissProt; Search Effort: Thorought ID; Detected Protein Threshold [unused Protscore (Conf)]:1.5 (95,0%). For human labelled proteins, the data analysis parameters were as follows: Sample type: iTRAQ 4plex (Peptide Labelled); Cys Alkylation: None; Digestion: Trypsin; Instrument: 5800; Special Factors: Phosphorylation emphasis, Species: Homo Sapiens; Quantitated tab: checked; ID Focus: Biological modification and Amino acid substitutions; Database: SwissProt_UniProt; Search Effort: Thorough ID; Minimum Detected Protein Threshold [Unused ProtScore (Conf)]: 1.3 (95.0%); Run False Discovery Rate Analysis Tab: checked. The relative quantification was based on the ratio of the reporter ions corresponding to the T tryptic peptides (117.1 Da) over the ratio of the NT (115.1 Da) reporter ions. Proteins giving tryptic peptides with an average reporter ion ratio ≥2 were classified as up-regulated, otherwise those with an average reporter ion ratio ≤0.5 were classified as downregulated [8]. All identified proteins were analyzed through the use of QUIAGEN ‘s Ingenuity® Pathway Analysis (IPA®, QUIAGEN Redwood City, www .quiagen.com/ingenuity).


This work was supported by a Post-Doctoral Research Fellowship from the MIUR (BANDO DI CONCORSO DR 2648/2014).


The authors declare that they have no conflicts of interest.

Figure 1
Electrophoresis profile of prostate human tissue.
Lanes: 1. Marker. 2-3: Depleted and whole fractions from human tumoral (T) prostate tissue from patient A. 4-5: Depleted and whole fractions from human tumoral (T) prostate tissue from patient B. 6-7: Depleted and whole fractions from human non tumoral (NT) prostate tissue from patient B.
Figure 1: Electrophoresis profile of prostate human tissue.
Figure 2
Functional distribution of the identified proteins in accordance to their cellular location.
Figure 2:  Functional distribution of the identified proteins in accordance to their cellular location.
Figure 3
“Cell Death and Survival, Cancer, Gastrointestinal disease” network of 70 proteins observed de-regulated in tumoral prostate tissue by the iterative Ingenuity Pathway Analysis software program.
The node and edge represent the proteins and their interactions, respectively, while the intensity of the node color indicates degree of up- (red) or down- (green) regulation.
Figure 3:  “Cell Death and Survival, Cancer, Gastrointestinal disease” network of 70 proteins observed de-regulated  in tumoral prostate tissue by the iterative Ingenuity Pathway Analysis software program.
Table 1
Identified proteins from tumoral and non tumoral prostate tissue by MS/MS data processinga
aThe identication and quantitation of proteins were performed using the Protein Pilot Paragon Method The MS/MS data were processed using a mass tolerance of 10 ppm and 02 Da for the precursor and fragment ions respectively bAccording to “UniProtKB” (http://wwwuniprotorg/) cAccording to “Compute pI/MW” (http://webexpasyorg/compute_pi/) *Proteins involved in epithelial neoplasia (p-value=362E-05).
Table 1:  Identified proteins from tumoral and non tumoral prostate tissue by MS/MS data processinga
Table 1 Continued
Table 1 Continued
Table 1 Continued
Table 1 Continued
Table 1 Continued
Table 1 Continued
Table 1 Continued
Table 1 Continued
Table 1 Continued
Table 1 Continued
Table 2
Proteins from prostatic gland that are also present in bodily fluidsa
Table 2:  Proteins from prostatic gland that are also present in bodily fluidsa
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