Skip to main content
Oncoscience logoLink to Oncoscience
. 2016 Jul 8;3(7-8):220–241. doi: 10.18632/oncoscience.313

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

Donatella Aiello 1,#, Francesca Casadonte 2,#, Rosa Terracciano 2, Rocco Damiano 2, Rocco Savino 2, Giovanni Sindona 1, Anna Napoli 1
PMCID: PMC5043072  PMID: 27713912

Abstract

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.

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

INTRODUCTION

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 ab 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.

RESULTS

An alternative and rapid protocol has been developed for selective protein solubilization [1315] 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 MALDITOF MS profiles of the resulting fractions are reported in Figure 1 and Figure SI2, respectively. The major proteins solute 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 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).

Figure 1. Electrophoresis profile of prostate human tissue.

Figure 1

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.

Table 1. Identified proteins from tumoral and non tumoral prostate tissue by MS/MS data processinga.

Accession Numberb Gene Nameb Protein Nameb IPc MW(Da)c Locationb Biological Processes and Molecular Functionb Quantification 117:115a
1. P63104 YWHAZ 14-3-3 protein zeta/delta* 473 27745 cytoplasm adapter protein implicated in the regulation of signaling pathways negative regulation of apoptotic process 380
2. Q9P2A4 ABI3 ABI gene family member 3 499 39035 cytoplasm regulation of cell migration 180
3. P68032 ACTC1 Actin alpha cardiac muscle 1* 523 42019 cytoskeleton cell structure and motility 227
4. P25054 APC Adenomatous polyposis coli protein* 793 311646 cytoplasm signal transduction oncogenesis beta-catenin binding, protein kinase regulator activity 292
5. O95996 APC2 Adenomatous polyposis coli protein 2 908 243949 cytoplasm and cell membrane promotes rapid degradation of CTNNB1 and may function as a tumor suppressor May function in Wnt signaling 358
6. Q08462 ADCY2 Adenylate cyclase* 840 123603 Citoplasm/membrane membrane-bound and Adenylate cyclase activity 320
7. P51825 AFF1 AF4/FMR2 family member 1* 926 131422 nucleus oncogene transcription factor- 237
8. P10696 ALPPL2 Alkaline phosphatase placental-like 590 57377 membrane hydrolase with biological process unclassified 145
9. Q99490 AGAP2 Arf-GAP with GTPase ANK repeat and PH domain-containing protein 2* 991 124674 cytoplasm and nucleus protein transport oncogenic overexpressed in cancer cells prevents apoptosis and promotes cancer cell invasion 302
10. Q8TF01 PNSIR Arginine/serine-rich protein PNISR* 1002 92577 Nucleus cytoplasm transcription system 159
11. O14525 ASTN1 Astrotactin 1 (Fragment) * 509 144913 membrane cell adhesion 255
12. Q4LE39 ARID4B AT-rich interactive domain-containing protein 4B* 504 147809 Nucleus and cytoplasm transcriptional repressor 217
13. O75815 BCAR3 Breast cancer anti estrogen resistance protein 3 819 92566 intracellular guanine nucleotide responsive factor signal trasduction 721
14. Q9UIF8 BAZ2B Bromodomain adjacent to zinc finger domain protein 2B* 613 240459 nucleus transcriptional regulation 164
15. Q9NYQ7 CELSR3 Cadherin EGF LAG seven-pass G-type receptor 3 623 358185 cell membrane cell signaling receptor 295
16. O15484 CAPN5 Calpain-5* 757 73169 cell surface hydrolase involved in protein metabolism and modification 116
17. Q66K79 CPZ Carboxypeptidase Z precursor * 822 73655 Secreted) extracellular space metalloprotease biological process unclassified 389
18. P35222 CTNNB1 Catenin beta-1* 553 85497 cytoplasm nucleus cell membrane cell adhesion transcription regulation and oncogenesis 210
19. Q96P48 ARAP1 Centaurin-delta-2 586 162192 Golgi apparatus membrane cytoplasm GTPase activation 578
20. Q9HC77 CENPJ Centromere protein J* 623 153000 Cytoplasm cytoskeleton plays an important role in cell division and centrosome function 159
21. O14647 CHD2 Chromodomain-helicase-DNA-binding protein 2 (CHD-2) * 822 211344 nucleus transcription regulation DNA-binding helicase 149
22. Q8TD26 CDH6 Chromodomain-helicase-DNA-binding protein 6* 590 305412 nucleus transcription regulator 353
23. Q02388 COL7A1 Collagen alpha 1(VII) * 595 295220 secreted extracellular space extracellular matrix structural constituent 207
24. P08123 COL1A2 Collagen alpha 2(I) chain* *** 908 129314 secreted extracellular space extracellular matrix structural constituent 319
25. P08572 COL4A2 Collagen alpha 2(IV) chain* 885 167553 secreted extracellular space extracellular matrix structural constituent 312
26. P12277 CKB Creatine kinase B-type* 535 42644 cytoplasm central role in energy transduction in tissues 449
27. Q9P0U4 CXXC1 CXXC-type zinc finger protein 1 861 75712 nucleus transcription regulation 110
28. Q9NZJ0 DTL Denticleless protein homolog 911 79468 Nucleus and cytoplasm cell cycle control DNA damage response and translation DNA synthesis 314
29. P17661 DES Desmin * 521 53536 cytoplasm cytoskeletal protein binding muscle protein 378
30. Q08554 DSC1 Desmocollin 1A/1B precursor 525 99987 cell membrane cell adhesion-mediated signaling 255
31. Q14117 DPYS Dihydropyrimidinase * 681 56630 cytoplasm nucleoside nucleotide and nucleic acid metabolism 630
32. Q9Y485 DMXL1 DmX-like 1 protein * 591 337839 extracellular space unknown 614
33. Q9NPF5 DMAP1 DNA methyltransferase 1-associated protein 1 951 52993 Cytoplasm and nucleus transcription repression and activation 227
34. Q92878 RAD50 DNA repair protein RAD50* 647 153892 nucleus hydrolase 401
35. O60870 KIN DNA/RNA-binding protein KIN17 907 45374 nucleus and cytoplasm involved in DNA replication and the cellular response to DNA damage 050
36. Q8TD84 DSCAML1 Down syndrome cell adhesion molecule-like protein 1* 843 224463 cell membrane cell adhesion and neurogenesis 380
37. Q96DT5 DNAH11 Dynein heavy chain 11 axonemal* 603 521043 cytoplasm force generating protein of respiratory cilia produces force towards the minus ends of microtubules and has ATPase activity 492
38. Q8WXX0 DNAH7 Dynein heavy chain 7 axonemal * 570 461159 cytoplasm cytoskeleton microtubule force generating protein of respiratory cilia produces force towards the minus ends of microtubules and has ATPase activity 443
39. Q03001 DST Dystonin* 514 860662 cytoplasm and cytoskeleton integrator of intermediate filaments involved in actin and microtubule cytoskeleton networks 428
40. P14625 HSP90B1 Endoplasmin* 476 92469 endoplasmic reticulum molecular chaperone 391
41. Q96J88 EPSTI1 epithelial stromal interaction protein 1 990 36793 unspecified unknown 265
42. Q8TAM0 GPR62 G protein-coupled receptor 62* 1099 37619 Cell membrane G-protein coupled receptor 301
43. O94808 GFPT2 Glucosamine-fructose-6-phosphate aminotransferase [isomerizing] 2 703 76931 cytosol aminotransferase 224
44. Q6PCE3 PGM2L1 Glucose 16-bisphoshate syntase 681 70442 cytosol glucose metabolism isomerase and transferase 303
45. P30711 GSTT1 Glutathione S-transferase theta 1* 701 27335 cytoplasm glutathione transferase activity 173
46. Q9NU53 GINM1 Glycoprotein integral membrane protein 1 481 36840 membrane unspecified 127
47. Q14789 GOLGB1 Golgin subfamily B member 1* 496 376019 Golgi apparatus and membrane unknown 050
48. Q99062 CSF3R Granulocyte colony stimulating factor receptor* 576 92156 cell membrane receptor 354
49. Q03113 GNA12 Guanine nucleotide- binding protein subunit alpha-12* 984 44279 membrane modulators or transducers in various trans-membrane signaling systems controller of cell migration through the TOR signaling cascade 379
50. Q96LI6 HSFY1 Heat shock transcription factor Y-linked 668 45107 nucleus cytoplasm transcription regulation 110
51. P69905 HBA1 Hemoglobin subunit alpha 872 15258 cytosol oxygen transporter 497
52. P68871 HBB Hemoglobin subunit Beta 674 15998 cytosol oxygen transporter 271
53. P09105 HBQ1 Hemoglobin subunit theta-1 709 15508 cytosol oxygen transporter 288
54. Q8TEK3 DOT1L Histone-lysine N-methyltransferase H3 lysine-79 specific * 939 184853 nucleus chromatin regulator 304
55. P17482 HOXB9 Homeobox protein Hox-B9* 901 28059 nucleus sequence-specific transcription factor 249
56. Q9HAS2 HIPK3 Homeodomain-interacting protein kinase 3* 716 133743 cytoplasm and nucleus serine/threonine-protein kinase involved in transcription regulation apoptosis and steroidogenic 907
57. P42858 HTT Huntingtin 581 347603 cytoplasm and nucleus may play a role in microtubule-mediated transport or vesicle function Protein binding 388
58. Q9Y4L1 HYOU1 Hypoxia up-regulated protein 1* 516 111335 nucleus protein metabolism and modification 229
59. P23677 ITPKA Inositol 145-trisphosphate 3-kinase A 759 51009 cytosol kinase 299
60. O15503 INSIG1 Insulin-induced protein 1* 908 29987 endoplasmic reticulum membrane protein binding may play a role in growth and differentiation of tissues involved in metabolic control and has a regulatory role during G0/G1 transition of cell growth 098
61. P24593 IGFBP5 Insulin-like growth factor binding protein 5 precursor* 858 30570 secreted signal transduction and cellular protein metabolic process 306
62. Q9BR39 JPH2 Junctophilin 2 882 74222 cell membrane contribute to the formation of junctional membrane complexes and to the construction of skeletal muscle triad junctions 477
63. Q01546 KRT76 Keratin type II cytoskeletal 2 oral 838 65841 cytoskeletal cell structure and motility 293
64. Q96L93 KIF16B Kinesin-like protein KIF-16B* 586 152011 cytoplasm motor protein involved in endosome transport and receptor recycling and degradation 456
65. Q8N4N8 KIF2B Kinesin-like protein KIF2B* 889 76254 cytoplasm motor protein required for spindle assembly and chromosome movement 470
66. Q32MZ4 LRRFIP1 Leucine-rich repeat flightless-interacting protein 1* 459 89253 nucleus and cytoplasm transcriptional repressor 381
67. Q9UNZ5 C19orf53 Leydig cell tumor 10 kDa protein homolog 1155 10577 nucleus potential role in hyper-calcemia of malignancy 449
68. Q9H2C1 LHX5 LIM/homeobox protein Lhx5 787 44406 nucleus transcription regulation 412
69. O75334 PPFIA2 Liprin-alpha2* 580 143291 cytoplasm and cell surface protein binding 261
70. Q9NZR2 LRP1B Low-density lipoprotein receptor-related protein 1B* 509 515498 membrane cell surface proteins involved in endocytosis 261
71. Q9H239 MMP28 Matrix metalloproteinase-28 970 58939 Secreted/extracellular space could play a role in tissues homeostasis and repair 282
72. Q9NR99 MXRA5 Matrix-remodeling-associated protein 5* 857 312150 secreted unknown but it is overexpressed in centenarians 332
73. Q96JG8 MAGED4 Melanoma-associated antigen D4 634 81378 unspecified tumor antigen 214
74. Q8NFU7 TET1 Methylcytosine dioxygenase TET1* 853 235309 nucleus transcription regulation activator and regulator 067
75. P11137 MAP2 Microtubule-associated protein 2* 482 199526 cytoplasm may stabilize the microtubules against depolymerization 272
76. Q9NU22 MDN1 Midasin* 546 632820 nucleus nuclear chaperone required for maturation and nuclear export of pre-60S ribosome subunits 449
77. P08235 NR3C2 Mineralocorticoid receptor (MR) * 722 107067 cytoplasm nucleus endoplasmic reticulum membrane nuclear hormone receptor and transcription factor 262
78. O60336 MAPKBP1 Mitogen-activated protein kinase-binding protein 1 631 163818 unknown involved in JNK signaling pathway 500
79. Q8WV50 BUB1B Mitotic checkpoint serine/threonine-protein kinase BUB1 beta* 520 119545 cytoplasm nucleus cytoskeleton essential component of the mitotic checkpoint with kinase activity 237
80. P02686 MBP Myelin basic protein * 979 33117 peripheral membrane protein formation and stabilization of myelin membrane 262
81. P60660 MYL6 Myosin light polypeptide 6 446 16961 cytoskeleton muscle protein 213
82. P35749 MYH11 Myosin-11* 542 227339 Cytoskeleton and cytosol muscle contraction 227
83. Q9UKX3 MYH13 Myosin-13* 553 223605 cytoplasm muscle contraction 693
84. Q8WXH0 SYNE2 Nesprin-2* 526 796442 ubiquitous involved in the maintenance of nuclear organization and structural integrity 191
85. Q8NF91 SYNE1 Nesprin-1* 537 1011086 Nuclear cytoplasm cytoskeleton and membrane involved in the maintenance of nuclear organization and structural integrity 222
86. Q9ULB1 NRXN1 Neurexin-1* 561 161883 cell membrane cell surface protein involved in cell-cell-interactions exocytosis of secretory granules and regulation of signal transmission 416
87. Q8NFP9 NBEA Neurobeachin* 578 327822 cytoplasm and peripheral membrane protein localization anchoring/targeting kinase A to the membrane 359
88. Q6KC79 NIPBL Nipped-B-like protein * 809 316051 nucleus involved in sister chromatid cohesion 236
89. P04198 MYCN N-myc proto-oncogene protein* 545 49561 nucleus transcription factor proto-oncogene 146
90. P23497 SP100 Nuclear autoantigen Sp-100 483 53768 nucleus and cytoplasm transcription regulation and tumor suppressor 168
91. Q15788 NCOA1 Nuclear receptor coactivator 1* 583 156757 nucleus binds nuclear receptors and stimulates the transcriptional activities in a hormone-dependent fashion Involved in the coactivation of different nuclear receptors and mediated by STAT3 STAT5A STAT5B and STAT6 transcription factors 292
92. O00482 NR5A2 Nuclear receptor subfamily 5 group A member 2* 808 61331 nucleus transcription regulation 237
93. Q5VST9 OBSCN Obscurin* 569 868484 cytoplasm involved in miofibrillogenesis 225
94. Q9C0B5 ZDHHC5 Palmithoyltransferase ZDHHC5 917 77545 cell membrane acyltrasferase 202
95. P54317 PNLIPRP2 Pancreatic lipase-related protein 2 527 51947 secreted lipid metabolism and degradation 173
96. Q8NG07 PNMA1 Paraneoplastic antigen Ma1 478 39761 nucleus and cytoplasmic in tumor cells paraneoplastic antigen 408
97. O15018 PDZD2 PDZ domain-containing protein* 818 280092 nucleus cytoplasm and endoplasmic reticulum cell adhesion 381
98. O95613 PCNT Pericentrin* 540 378037 cytoplasm protein binding 447
99. Q5VV67 PPRC1 Peroxisome proliferator-activated receptor gamma coactivator-related protein 1* 611 177544 nucleus acts as a coactivator during transcriptional activation of nuclear genes related to mitochondrial biogenesis and cell growth 176
100. O00541 PES1 Pescadillo homolog 1 693 68003 nucleus ribosome biogenesis and rRNA processing 189
101. P15259 PGAM2 Phosphoglycerate mutase 899 28766 nucleus cytosol involved in glycolysis and gluconeogenesis 316
102. P16284 PECAM1 Platelet endothelial cell adesion molecular 655 82536 cell membrane protein binding 399
103. Q9HAU0 PLEKHA5 Pleckstrin homology domain-containing family A member 5* 720 127464 cytoplasm protein binding 294
104. Q15149 PLEC Plectin* 574 531791 cytoplasm ankyrin binding and apotoptic process 258
105. Q9NS40 KCNH7 Potassium voltage-gated channel subfamily H member 7* 757 135000 membrane pore-forming (alpha) subunit of voltage-gated potassium channel 067
106. Q7L014 DDX46 Probable ATP-dependent RNA helicase DDX46 933 117362 nucleus nucleoside nucleotide and nucleic acid metabolism 178
107. Q7Z7M1 ADGRD2 Probable G-protein coupled receptor 144* 833 104087 cell membrane G-protein coupled receptor transducer 681
108. P35232 PHB Prohibitin 557 29804 Membrane and cytoplasm DNA replication cell proliferation and differentiation proto- oncogene 347
109. P27918 CFP properdin 833 51276 Secreted immunity and defense 497
110. Q13258 PTGDR Prostaglandin D2 receptor* 939 40271 cell membrane receptor for prostaglandin D2 282
111. Q9P2B2 PTGFRN Prostaglandin F2 receptor negative regulator* 616 98556 endoplasmic reticulum membrane protein binding 213
112. P14921 ETS1 Protein C-ets-1* 503 50408 nucleus and cytoplasm transcription factor 352
113. P80511 S100A12 Protein S100-A12* 581 10575 Cytoplasm and cell membrane signal transduction inflammatory processes and immune response 341
114. A3KN83 SBNO1 Protein strawberry notch homolog 1* 796 154312 nucleus regulation of transcription 412
115. Q13882 PTK6 Protein-tyrosine kinase 6* 656 51834 cytoplasm and nucleus involved in protein metabolism and modification implicated in the regulation of a variety of signaling pathways that control the differentiation and maintenance of normal epithelia as well as tumor growth 479
116. Q9Y315 DERA Putative deoxyribose-phosphate aldolase * 908 35231 cytoplasm lyase 189
117. Q15311 RALBP1 RalA-binding protein 1* 568 76063 membrane signal transduction and ATP catabolic process 213
118. Q08999 RBL2 Retinoblastoma-like protein 2* 727 128367 nucleus transcription factor 338
119. Q7Z5J4 RAI1 Retinoid-acid induced protein 1* 903 203352 cytoplasm and nucleus transcriptional regulator 229
120. Q5T5U3 ARHGAP21 Rho GTPase-activating protein 21 785 217331 peripheral membrane protein GTPase-activating protein 248
121. Q9BST9 RTKN Rhotekin 718 62667 nucleoplasm mediates Rho signaling to activate NF-kappa-B and increases resistance to apoptosis 276
122. Q14137 BOP1 Ribosome biogenesis protein BOP1 580 83630 nucleus ribosome biogenesis, rRNA processing 489
123. Q9H7B2 RPF2 Ribosome production factor 2 homolog* 1000 35583 nucleus poly(A) RNA binding 451
124. Q8WV20 RBMS1 RNA binding motif single stranded interacting protein 1 891 44505 nucleus nucleoside nucleotide and nucleic acid metabolism 607
125. P21817 RYR1 Ryanodine receptor 1* 518 565176 sarcoplasmic reticulum membrane calcium transport 484
126. O14641 DVL2 Segment polarity protein dishevelled homolog DVL-2* 567 78948 cell membrane and cytoplasm Wnt signaling pathway 379
127. Q99719 SEPT5 Septin-5 621 42777 cytoplasm GTO and protein binding 249
128. Q9UQ35 SRRM2 Serine/arginine repetitive matrix protein 2* 1205 299615 nucleus pre-mRNA processing and mRNA splicing 237
129. P15056 BRAF Serine/Threonine protein kinase B-raf* 729 84437 nucleus and cytoplasm proto-oncogene 394
130. Q06190 PPP2R3A Serine/threonine-protein phosphatase 2A regulatory subunit B’’ subunit alpha 509 130278 Colocalized with protein phosphatase type 2A complex calcium ion and protein binding and regulator of Wnt signaling pathway 290
131. P42345 MTOR Serine/threonine-protein kinase mTOR* 673 288892 ubiquitous it is a central regulator of cellular metabolism growth and survival in response to hormones growth factors nutrients energy and stress signals 257
132. Q96Q15 SMG1 Serine/threonine-protein kinase SMG1* 603 410501 nucleus and cytoplasm kinase involved in mRNA surveillance and genotoxic stress response pathways 379
133. Q15464 SHB SH2 domain-containig adapter protein B 910 55042 cytoplasm involved in angiogenesis and apoptosis 225
134. Q9H1V8 SLC6A17 Sodium-dependent neutral amino acid transporter SLC6A17 568 81001 cytoplasmic vesicle multi-pass membrane protein neurotransmitter transporter 201
135. Q96BI1 SLC22A18 Solute Carrier Family 22 member 18 662 13354 cell membrane zinc ion binding 236
136. O94956 SLCO2B1 Solute carrier organic anion transporter family member 2B1* 870 76711 cell membrane ion transport 171
137. P11277 SPTB Spectrin beta chain erythrocytic* 515 246468 cytoplasm cell structure and motility 127
138. Q9BPZ7 MAPKAP1 Stress-activated map kinase interacting protein 1 724 59123 cell membrane and nucleus stress response and phosphatidic acid binding 463
139. Q15431 SYCP1 Synaptonemal complex protein 1* 578 114192 Nucleus and chromosome cell cycle and meiosis 342
140. Q9BQ70 TCF25 Transcription factor 25* 595 76667 nucleus transcriptional repressor 406
141. Q01664 TFAP4 Transcription factor AP-4 563 38726 nucleus transcription regulator 348
142. Q8NHW3 MAFA Transcription factor mammalian MafA* 749 36982 nucleus transcriptional factor 941
143. Q8NEM7 SUPT20H Transcription factor SPT20 homolog 877 85789 nucleus required for MAP kinase p38 (MAPK11 MAPK12 MAPK13 and/or MAPK14) 421
144. P29084 GTF2E2 Transcription initiation factor IIE subunit beta 966 33044 nucleus basal transcription factor 227
145. O75410 TACC1 Transforming acidic coiled-coil-containing protein 1* 481 87794 cytoplasm and nucleus cell cycle and division 555
146. Q01995 TAGLN Transgelin* 887 22611 cytoplasm muscle protein 099
147. Q9UJA5 TRTM6 tRNA (adenine(58)-N(1))-methyltransferase non-catalytic subunit TRM6 718 55799 nucleus tRNA processing 205
148. Q9NYL9 TMOD3 Tropomodulin-3 508 39595 cytoplasm blocks the elongation and de-polymerization of the actin filaments 122
149. P06753 TPM3 Tropomyosin alpha-3-chain 468 32950 cytoplasm and cytoskeleton muscle protein 294
150. P07951 TPM2 Tropomyosin beta chain 466 32851 cytoplasm and cytoskeleton muscle protein 067
151. P49815 TSC2 Tuberin* 698 200608 cytoplasm tumor suppressor and intracellular protein traffic 401
152. P07437 TUBB Tubulin beta chain* 478 49671 cytoplasm and cytoskeleton protein binding and structural constituent of cytoskeleton 435
153. P78324 SIRPA Tyrosine-protein phosphatase non-receptor type substrate 1* 651 54967 membrane involved in intracellular signaling during synaptogenesis and in synaptic function 276
154. Q9NPG3 UBN1 Ubinuclein-1* 937 121520 nucleus, cell junction novel regulator of senescence 262
155. Q14139 UBE4A Ubiquitin conjugation factor E4 A* 511 123522 cytoplasm protein metabolism and modification 261
156. Q9Y6A4 CFAP20 Cilia- and flagella-associated protein 20* 978 22774 nucleus transcription factor 093
157. Q15849 SLC14A2 Urea transporter 2* 651 101209 cell membrane transport protein 127
158. Q8N6Y0 USHBP1 Usher syndrome type-1C protein-binding protein 1 558 76068 cytoplasm nucleus plasma membrane signal transduction 169
159. P62955 CACNG7 Voltage-dependent calcium channel gamma 7 subunit 665 31003 membrane calcium transport 346
160. P21281 ATP6V1B2 V-type proton ATPase subunit B brain isoform 557 56501 peripheral membrane protein cation transport 148
161. Q9UJW8 ZNF180 Zinc finger protein 180 (HHZ168)* 804 79111 nucleus involved in transcriptional regulation 193
162. Q7Z3V5 ZNF571 Zinc finger protein 571* 871 70792 nucleus involved in transcriptional regulation 354
163. Q9H582 ZNF644 Zinc finger protein 644 843 149565 nucleus involved in transcriptional regulation 369
164. Q15776 ZKSCANS Zinc finger protein with KRAB and SCAN domains 8 704 65816 nucleus transcription factor 312
a

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).

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).

DISCUSSION

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 basesoluble 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.

Figure 2. Functional distribution of the identified proteins in accordance to their cellular location.

Figure 2

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 androgendependent LNCaP prostate cancer cells, represses the activation of the AR target genes and it reduces the ARdependent 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

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 five Top Networks (Supporting Information, Table S3), the first one related to “Cell Death and Survival, Cancer” comprises 70 focus molecules and evidences as the majority of identified 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).

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.

Figure 3

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.

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 inflammation 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 significant 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 downregulated proteins are selected 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 upregulation 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].

Table 2. Proteins from prostatic gland that are also present in bodily fluidsa.

Gene Name(a) Accession N(b) Entrez Gene Name Location Family Fold Change Blood Plasma/Serum Urine Prostate Gland
BRAF P15056 v-raf murine sarcoma viral oncogene homolog B (e) Cytoplasm kinase 394 x x x
DPYS Q14117 Dihydropyrimidinase (c) Cytoplasm enzyme 6304 x
CTNNB1 P35222 catenin (cadherin-associated protein) beta 1 88kDa (e) Nucleus transcription regulator 2112 x x
IGFBP5 P24593 insulin-like growth factor binding protein 5 (d) Extracellular Space other 3065 x x
MTOR P42345 mechanistic target of rapamycin (serine/threonine kinase) (e) Nucleus kinase 257 x x x
PGAM2 P15259 phosphoglycerate mutase 2 (d) Cytoplasm phosphatase 316 x x
PECAM1 P16284 platelet/endothelial cell adhesion molecule 1 (cde) Plasma Membrane other 399 x x x x
TAGLN Q01995 Transgelin (cde) Cytoplasm other −1002 x x
TPM3 P06753 tropomyosin alpha-3-chain (cd) Cytoplasm other 2940 x x
TPM2 P07951 tropomyosin 2 (beta) (e) Cytoplasm other −1484 x x x
YWHAZ P63104 tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein zeta (cd) Cytoplasm enzyme 3806 x x x
a

According to QUIAGEN ‘s Ingenuity® Pathway Analysis - Biomarker Filter

b

According to “UniProtKB” (http://wwwuniprotorg/) In the table are listed proteins markers suggested by IPA when Biomarker Filter is restricted to

c

Urine

d

Urine and Prostate Gland

e

Urine Prostate Gland Blood and Plasma/Serum.

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 androgenindependent 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.

MATERIALS AND METHODS

Reagents and chemicals

Ammonium Bicarbonate (NH4HCO3, 99.5%), trypsin (proteomics grade), α-cyano-4-hydroxy-transcynnamic 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 NH4HCO3 (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 × 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 NH4HCO3, (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 NH4HCO3 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)2CO3 (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.

SDS-page

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% CH3COOH and 50% H2O.

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 NH4HCO3, 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 [7072] (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 MALDITOF/TOF analyzer (AB SCIEX, Darmstadt, Germany) equipped with a neodymium: yttrium-aluminiumgarnet 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, CH3CN/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).

SUPPLEMENTARY FIGURES AND TABLES

Acknowledgments

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

Footnotes

CONFLICTS OF INTEREST

The authors declare that they have no conflicts of interest.

REFERENCES

  • 1.Jemal A, Siegel R, Xu J, Ward E. Cancer statistic 2010. CA Cancer J Clin. 2010;60:277–300. doi: 10.3322/caac.20073. [DOI] [PubMed] [Google Scholar]
  • 2.Lilja H, Ulmert D, Vickers AJ. Prostate-specific antigen and prostate cancer: Prediction, detection and monitoring. Nat Rev Cancer. 2008;8:268–278. doi: 10.1038/nrc2351. [DOI] [PubMed] [Google Scholar]
  • 3.Daskivich TJ, Chamie K, Kwan L, Labo J, Palvolgyi R, Dash A, Greenfield S, Litwin MS. Overtreatment of men with low-risk prostate cancer and significant comorbidity. Cancer. 2011;117:2058–2066. doi: 10.1002/cncr.25751. [DOI] [PubMed] [Google Scholar]
  • 4.Rhodes DR, Barrette TR, Rubin MA, Ghosh D, Chinnaiyan AM. Meta-analysis of microarrays: Interstudy validation of gene expression profiles reveals pathway dysregulation in prostate cancer. Cancer Res. 2002;62:4427–4433. [PubMed] [Google Scholar]
  • 5.Napoli A, Aiello D, Di Donna L, Prendushi H, Sindona G. Exploitation of endogenous protease activity in raw mastitic milk by MALDI-TOF/TOF. Anal Chem. 2007;79:5941–5948. doi: 10.1021/ac0704863. [DOI] [PubMed] [Google Scholar]
  • 6.Ye B, Cramer DW, Skates SJ, Gygi SP, Pratomo V, Fu L, Horick NK, Licklider LJ, Schorge JO, Berkowitz RS, Mok SC. Haptoglobin-subunit as potential serum biomarker in ovarian cancer: Identification and characterization using proteomic profiling and mass spectrometry. Clin. Cancer Res. 2003;9:2904–2911. [PubMed] [Google Scholar]
  • 7.Ross P L, Huang Y N, Marchese J N, Williamson B, Parker K, Hattan S, Khainovski N, Pillai S, Dey S, Daniels S, Purkayastha S, Juhasz P, Martin S, Bartlet-Jones M, He F, Jacobson A, Pappin D J. Multiplexed Protein Quantitation in Saccharomyces cerevisiae Using Amine-reactive Isobaric Tagging Reagents. Molecular & Cellular Proteomics. 2004;3:1154–1169. doi: 10.1074/mcp.M400129-MCP200. [DOI] [PubMed] [Google Scholar]
  • 8.Garbis SD, Tyritzis SI, Roumeliotis T, Zerefos P, Giannopoulou EG, Vlahou A, Kossida S, Diaz J, Vourekas S, Tamvakopoulos C, Pavlakis K, Sanoudou D, Constantinides CA. Search for potential markers for prostate cancer diagnosis, prognosis and treatment in clinical tissue specimens using amine-specific isobaric tagging (iTRAQ) with two-dimensional liquid chromatography and tandem mass spectrometry. J Proteome Res. 2008;7:3146–3158. doi: 10.1021/pr800060r. [DOI] [PubMed] [Google Scholar]
  • 9.Sun C, Song C, Ma Z, Xu K, Zhang Y, Jin H, Tong S, Ding W, Xia G, Ding Q. Periostin identified as a potential biomarker of prostate cancer by iTRAQ-proteomics analysis of prostate biopsy. Proteome Sci. 2011;19:9–22. doi: 10.1186/1477-5956-9-22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Mueller MM, Fusenig NE. Friends or foes-bipolar effects of the tumor stroma in cancer. Nature Reviews. 2004;4:839–849. doi: 10.1038/nrc1477. [DOI] [PubMed] [Google Scholar]
  • 11.Gleason DF, Mellinger GT. Prediction of prognosis for prostatic adenocarcinoma by combined histological grading and clinical staging. J. Urol. 1974;111:58–64. doi: 10.1016/s0022-5347(17)59889-4. [DOI] [PubMed] [Google Scholar]
  • 12.Humphrey PA. Gleason grading and prognostic factors in carcinoma of the prostate. Modern Pathology. 2004;17:292–306. doi: 10.1038/modpathol.3800054. [DOI] [PubMed] [Google Scholar]
  • 13.Napoli A, Athanassopoulos CM, Moschidis P, Aiello D, Di Donna L, Mazzotti F, Sindona G. Solid Phase Isobaric Mass Tag Reagent for Simultaneous Protein Identification and Assay. Anal. Chem. 2010;82:5552–5560. doi: 10.1021/ac1004212. [DOI] [PubMed] [Google Scholar]
  • 14.Napoli A, Aiello D, Aiello G, Cappello MS, Di Donna L, Mazzotti F, Materazzi S, Fiorillo M, Sindona G. Mass spectrometry- based proteomic approach in Oenococcus oeni enological starter. J Proteome Res. 2014;13:2856–2866. doi: 10.1021/pr4012798. [DOI] [PubMed] [Google Scholar]
  • 15.Aiello D, Materazzi S, Risoluti R, Thangavel H, Di Donna L, Mazzotti F, Casadonte F, Siciliano C, Sindona G, Napoli A. A major allergen in rainbow trout (Oncorhynchus mykiss): complete sequences of parvalbumin by MALDI tandem mass spectrometry. Mol BioSyst. 2015;11:2373–2382. doi: 10.1039/c5mb00148j. [DOI] [PubMed] [Google Scholar]
  • 16.Swindle MM, Makin A, Herron AJ, Clubb FJ, Jr, Frazier KS. Swine as Models in Biomedical Research and Toxicology Testing. Vet Pathol. 2012;49:344–356. doi: 10.1177/0300985811402846. [DOI] [PubMed] [Google Scholar]
  • 17.Napoli A, Aiello D, Di Donna L, Sajjad A, Perri E, Sindona G. Profiling of hydrophilic proteins from Olea europaea olive pollen by MALDI TOF mass spectrometry. Anal Chem. 2006;78:3434–3443. doi: 10.1021/ac0600508. [DOI] [PubMed] [Google Scholar]
  • 18.Jahouh F, Saksena R, Aiello D, Napoli A, Sindona G, Kovàc P, Banoub JH. Glycation sites in neoglycoglycoconjugates from the terminal monosaccharide antigen of the O-PS of Vibrio cholerae O1, serotype Ogawa, and BSA revealed by matrix-assisted laser desorption–ionization tandem mass spectrometry. JMS. 2010;45:1148–1159. doi: 10.1002/jms.1796. [DOI] [PubMed] [Google Scholar]
  • 19.Zhan X, Desiderio DM. Signaling pathway networks mined from human pituitary adenoma proteomics data. BMC Med. Genomics. 2010;3:13. doi: 10.1186/1755-8794-3-13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Terracciano R, Pasqua L, Casadonte F, Frascà S, Preianò M, Falcone D, Savino R. Derivatized mesoporous silica beads for MALDI-TOF MS profiling of human plasma and urine. Bioconjug Chem. 2009;20:913–923. doi: 10.1021/bc800510f. [DOI] [PubMed] [Google Scholar]
  • 21.Blume-Jensen P, Hunter T. Oncogenic kinase signalling. Nature. 2001;411:355–365. doi: 10.1038/35077225. [DOI] [PubMed] [Google Scholar]
  • 22.Agoulnik IU, Vaid A, Bingman WE, Erdeme H, Frolov A, Smith CL, Ayala G, Ittmann MM, Weigel NL. Role of SRC-1 in the promotion of prostate cancer cell growth and tumor progression. Cancer Res. 2005;65:7959–7967. doi: 10.1158/0008-5472.CAN-04-3541. [DOI] [PubMed] [Google Scholar]
  • 23.Rajalingam K, Wunder C, Brinkmann V, Churin Y, Hekman M, Sievers C, Rapp UR, Rudel T. Prohibitin is required for Ras-induced Raf-MEK-ERK activation and epithelial cell migration. Nat. Cell Biol. 2005;7:837–843. doi: 10.1038/ncb1283. [DOI] [PubMed] [Google Scholar]
  • 24.Artal-Sanz M, Tavernarakis N. Prohibitin couples diapause signalling to mitochondrial metabolism during ageing in C. elegans. Nature. 2009;461:793–797. doi: 10.1038/nature08466. [DOI] [PubMed] [Google Scholar]
  • 25.Toska E, Shandilya J, Goodfellow SJ, Medler KF, Roberts SG. Prohibitin is required for transcriptional repression by the WT1-BASP1 complex. Oncogene. 2014;33:5100–5108. doi: 10.1038/onc.2013.447. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Sievers C, Billig G, Gottschalk K, Rudel T. Prohibitin are required for cancer cell proliferation and adhesion. PLoS One. 2010;5:e12735. doi: 10.1371/journal.pone.0012735. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Ummanni R, Junker H, Zimmermann U, Venz S, Teller S, Giebel J, Scharf C, Woenckhaus C, Dombrowski F, Walther R. Prohibitin identified by proteomic analysis of prostate biopsies distinguishes hyperplasia and cancer. Canc. Lett. 2008;266:171–185. doi: 10.1016/j.canlet.2008.02.047. [DOI] [PubMed] [Google Scholar]
  • 28.Hall A. The cytoskeleton and cancer. Cancer Metastasis Rev. 2009;28:5–14. doi: 10.1007/s10555-008-9166-3. [DOI] [PubMed] [Google Scholar]
  • 29.Yamaguchi H, Condeelis J. Regulation of the actin cytoskeleton in cancer cell migration and invasion. Biochim Biophys Acta. 2007;1773:642–652. doi: 10.1016/j.bbamcr.2006.07.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Taniwaki M, Takano A, Ishikawa N, Yasui W, Inai K, Nishimura H, Tsuchiya E, Kohno N, Nakamura Y, Daigo Y. Activation of KIF4A as a prognostic biomarker and therapeutic target for lung cancer. Clin Cancer Res. 2007;13:6624–6631. doi: 10.1158/1078-0432.CCR-07-1328. [DOI] [PubMed] [Google Scholar]
  • 31.Corson TW, Gallie BL. KIF14 mRNA expression is a predictor of grade and outcome in breast cancer. Int J Cancer. 2006;119:1088–1094. doi: 10.1002/ijc.21954. [DOI] [PubMed] [Google Scholar]
  • 32.Dorsam RT, Gutkind JS. G-protein-coupled receptors and cancer. Nat Rev Cancer. 2007;7:79–94. doi: 10.1038/nrc2069. [DOI] [PubMed] [Google Scholar]
  • 33.Marinissen MJ, Gutkind JS. G-protein-coupled receptors and signaling networks: emerging paradigms. Trends Pharmacol Sci. 2001;22:368–376. doi: 10.1016/s0165-6147(00)01678-3. [DOI] [PubMed] [Google Scholar]
  • 34.Blume-Jensen P, Hunter T. Oncogenic kinase signaling. Nature. 2001;411:355–365. doi: 10.1038/35077225. [DOI] [PubMed] [Google Scholar]
  • 35.Reddy E, Albanito L, De Marco P, Aiello D, Napoli A, Musti AM. Multisite phosphorylation of c-Jun at threonine 91/93/95 triggers the onset of c-Jun pro-apoptotic activity in cerebellar granule neurons. Cell Death Dis. 2013;4:e852. doi: 10.1038/cddis.2013.381. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Sato I, Obata Y, Kasahara K, Nakayama Y, Fukumoto Y, Yamasaki T, Yokoyama KK, Saito T, Yamaguchi N. Differential trafficking of Src, Lyn, Yes and Fyn is specified by the state of palmitoylation in the SH4 domain. J Cell Sci. 2009;122:965–975. doi: 10.1242/jcs.034843. [DOI] [PubMed] [Google Scholar]
  • 37.Weaver AM, Silva CM. Signal transducer and activator of transcription 5b: a new target of breast tumor kinase/protein tyrosine kinase 6. Breast Cancer Res. 2007;9:R79. doi: 10.1186/bcr1794. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Zheng Y, Peng M, Wang Z, Asara JM, Tyner AL. Protein tyrosine kinase 6 directly phosphorylates AKT and promotes AKT activation in response to epidermal growth factor. Mol Cell Biol. 2010;30:4280–4292. doi: 10.1128/MCB.00024-10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Zheng Y, Asara JM, Tyner AL. Protein-tyrosine Kinase 6 Promotes Peripheral Adhesion Complex Formation and Cell Migration by Phosphorylating p130 CRK-associated Substrate. J Biol Chem. 2012;287:148–158. doi: 10.1074/jbc.M111.298117. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Zheng Y, Tyner AL. Context-specific protein tyrosine kinase 6 (PTK6) signalling in prostate cancer. Eur J Clin Invest. 2013;43:397–404. doi: 10.1111/eci.12050. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Dhillon AS, Hagan S, Rath O, Kolch W. MAP kinase signalling pathways in cancer. Oncogene. 2007;26:3279–3290. doi: 10.1038/sj.onc.1210421. [DOI] [PubMed] [Google Scholar]
  • 42.Robertson BW, Bonsal L, Chellaiah MA. Regulation of Erk1/2 activation by osteopontin in PC3 human prostate cancer cells. Molecular Cancer. 2010;9:260. doi: 10.1186/1476-4598-9-260. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Erstad DJ, Cusack JC., Jr Targeting the NF-κB pathway in cancer therapy. Surg Oncol Clin N Am. 2013;22:705–746. doi: 10.1016/j.soc.2013.06.011. [DOI] [PubMed] [Google Scholar]
  • 44.Perkins ND. Post translational modification regulating the activity and function of the nuclear factor ĸB pathway. Oncogene. 2006;25:6717–6730. doi: 10.1038/sj.onc.1209937. [DOI] [PubMed] [Google Scholar]
  • 45.Liu P, Cheng H, Roberts TM, Zhao JJ. Targeting the phosphoinositide 3-kinase pathway in cancer. Nat Rev Drug Discov. 2009;8:627–644. doi: 10.1038/nrd2926. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Engelman JA. Targeting PI3K signalling in cancer: opportunities, challenges and limitations. Nat Rev Cancer. 2009;9:550–562. doi: 10.1038/nrc2664. [DOI] [PubMed] [Google Scholar]
  • 47.Burris HA., III Overcoming acquired resistance to anticancer therapy: focus on the PI3K/AKT/mTOR pathway. Cancer Chemother Pharmacol. 2013;71:829–842. doi: 10.1007/s00280-012-2043-3. [DOI] [PubMed] [Google Scholar]
  • 48.Pourmand G, Ziaee AA, Abedi AR, Mehrsai A, Alavi HA, Ahmadi A, Saadati HR. Role of PTEN gene in progression of prostate cancer. Urology Journal. 2007;4:95–100. [PubMed] [Google Scholar]
  • 49.Gao N, Zhang Z, Jiang BH, Shi X. Role of PI3K/AKT/mTOR signaling in the cell cycle progression of human prostate cancer. Biochemical and Biophysical Research Communications. 2003;310:1124–1132. doi: 10.1016/j.bbrc.2003.09.132. [DOI] [PubMed] [Google Scholar]
  • 50.Whitaker HC, Girling J, Warren AY, Leung H, Mills IG, Neal DE. Alterations in beta catenin expression and localization in prostate cancer. Prostate. 2008;68:1196–1205. doi: 10.1002/pros.20780. [DOI] [PubMed] [Google Scholar]
  • 51.Segditsas S, Tomlinson I. Colorectal cancer and genetic alterations in the Wnt pathway. Oncogene. 2006;25:7531–7537. doi: 10.1038/sj.onc.1210059. [DOI] [PubMed] [Google Scholar]
  • 52.Ishigaki K, Namba H, Nakashima M, Nakayama T, Mitsutake N, Hayashi T, Maeda S, Ichinose M, Kanematsu T, Yamashita S. Aberrant localization of beta catenin correlates with overexpression of its target gene in human papillary thyroid cancer. J Clin Endocrinol Metab. 2002;87:3433–3440. doi: 10.1210/jcem.87.7.8648. [DOI] [PubMed] [Google Scholar]
  • 53.Pawlak G, Helfman DM. Cytoskeletal changes in cell transformation and tumorigenesis. Curr Opin Genet Dev. 2001;11:41–47. doi: 10.1016/s0959-437x(00)00154-4. [DOI] [PubMed] [Google Scholar]
  • 54.Varisli L. Identification of new genes downregulated in prostate cancer and investigation of their effects on prognosis. Genet Test Mol Biomarkers. 2013;17:562–566. doi: 10.1089/gtmb.2012.0524. [DOI] [PubMed] [Google Scholar]
  • 55.Franzen B, Linder S, Uryu K, Alaiya AA, Hirano T, Kato H, Auer G. Expression of tropomyosin isoforms in benign and malignant human breast lesions. Br J Cancer. 1996;73:909–913. doi: 10.1038/bjc.1996.162. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56.Aitken A. 14-3-3 proteins: a historic overview. Semin Cancer Biol. 2006;16:162–172. doi: 10.1016/j.semcancer.2006.03.005. [DOI] [PubMed] [Google Scholar]
  • 57.Van Hemert MJ, Steensma HY, van Heusden GP. 14-3-3 proteins: key regulators of cell division, signalling and apoptosis. Bioessays. 2001;23:936–946. doi: 10.1002/bies.1134. [DOI] [PubMed] [Google Scholar]
  • 58.Neal C L, Yao J, Yang W, Zhou X, Nguyen N T, Lu J, Danes C G, Guo H, Lan K H, Ensor J, Hittelman W, Hung M C, Yu D. 14-3-3zeta overexpression defines high risk for breast cancer recurrence and promotes cancer cell survival. Cancer Re. 2009;69:3425–3432. doi: 10.1158/0008-5472.CAN-08-2765. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.Murata T, Takayama K, Urano T, Fujimura T, Ashikari D, Obinata D, Horie-Inoue K, Takahashi S, Ouchi Y, Homma Y, Inoue S. 14-3-3z a Novel Androgen-Responsive Gene Is Upregulated in Prostate Cancer and Promotes Prostate Cancer Cell Proliferation and Survival. Clin Cancer Res. 2012;18:5617–5627. doi: 10.1158/1078-0432.CCR-12-0281. [DOI] [PubMed] [Google Scholar]
  • 60.Jackson D E. The unfolding tale of PECAM-1. FEBS Lett. 2003;540:7–14. doi: 10.1016/s0014-5793(03)00224-2. [DOI] [PubMed] [Google Scholar]
  • 61.Karagiannis G S, Saraon P, Jarvi K A, Diamandis E P. Proteomic Signatures of Angiogenesis in Androgen- Independent Prostate Cancer. The Prostate. 2014;74:260–272. doi: 10.1002/pros.22747. [DOI] [PubMed] [Google Scholar]
  • 62.Priya D, Prasad & Jo-Anne L, Stanton & Stephen J. Assinder Expression of the actin-associated protein transgelin (SM22) is decreased in prostate cancer. Cell Tissue Res. 2010;339:337–347. doi: 10.1007/s00441-009-0902-y. [DOI] [PubMed] [Google Scholar]
  • 63.Guertin D, Sabatini D M. Defining the Role of mTOR in Cancer. Cancer Cell. 2007;12:9–22. doi: 10.1016/j.ccr.2007.05.008. [DOI] [PubMed] [Google Scholar]
  • 64.Davies H, Bignell G R, Cox C, Stephens P, Edkins S, Clegg S, Teague J, et al. Mutations of the BRAF gene in human cancer. Nature. 2002;417:949–954. doi: 10.1038/nature00766. [DOI] [PubMed] [Google Scholar]
  • 65.van Gennip A H, van Kuilenburg A B. Defects of pyrimidine degradation: clinical molecular and diagnostic aspects. Adv. Exp. Med. Biol. 2000;486:233–241. doi: 10.1007/0-306-46843-3_46. [DOI] [PubMed] [Google Scholar]
  • 66.Loffler M, Fairbanks LD, Zameitat E, Marinaki A M, Simmonds H A. Pyrimidine pathways in health and disease. TRENDS in Molecular Medicine. 2005;11:430–437. doi: 10.1016/j.molmed.2005.07.003. [DOI] [PubMed] [Google Scholar]
  • 67.Wang J, Ding N, Li Y, Cheng H, Wang D, Yang Q, Deng Y, Yang Y, Li Y, Ruan X, Xie F, Zhao H, Fang X. Insulinlike growth factor binding protein 5 (IGFBP5) functions as a tumor suppressor in human melanoma cells. Oncotarget. 2015;6:20636–20649. doi: 10.18632/oncotarget.4114. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68.Hemers E, Duval C, McCaig C, Handley M, Dockray GJ, Varro A. Insulin-Like Growth Factor Binding Protein-5 Is a Target of Matrix Metalloproteinase-7: Implications for Epithelial-Mesenchymal Signaling. Cancer Res. 2005;65:7363–7369. doi: 10.1158/0008-5472.CAN-05-0157. [DOI] [PubMed] [Google Scholar]
  • 69.Bradford M M. Rapid and sensitive method for quantitation of microgram quantities of proteins utilizing the principle of protein-dye binding. Anal. Biochem. 1976;72:248–254. doi: 10.1006/abio.1976.9999. [DOI] [PubMed] [Google Scholar]
  • 70.Mazzotti F, Di Donna L, Taverna D, Nardi M, Aiello D, Napoli A, Sindona G. Evaluation of dialdehydic antiinflammatory active principles in extra-virgin olive oil by reactive paper spray mass spectrometry. International Journal of Mass Spectrometry. 2013;352:87–91. [Google Scholar]
  • 71.Furia E, Aiello D, Di Donna L, Mazzotti F, Tagarelli A, Thangavel H, Napoli A, Sindona G. Mass Spectrometry and Potentiometry studies of Pb(II), Cd(II) and Zn(II) cystine complexes. Dalton Transaction. 2014;43:1055–1062. doi: 10.1039/c3dt52255e. [DOI] [PubMed] [Google Scholar]
  • 72.De Nino A, Di Donna L, Mazzotti F, Sajjad A, Sindona G, Perri E, Russo A, De Napoli L, Filice L. Oleuropein expression in olive oils produced from drupes stoned in a spring pitting apparatus (SPIA) Food Chemistry. 2008;106:677–684. [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials


Articles from Oncoscience are provided here courtesy of Impact Journals, LLC

RESOURCES