Hindawi Publishing CorporationInternational Journal of ProteomicsVolume 2010, Article ID 726968, 14 pagesdoi:10.1155/2010/726968
Research Article
Comparative Proteomic Analysis of Proteins Involved inthe Tumorigenic Process of Seminal Vesicle Carcinoma inTransgenic Mice
Wei-Chao Chang,1 Chuan-Kai Chou,2 Chih-Chiang Tsou,3 Sheng-Hsiang Li,4
Chein-Hung Chen,1 Yu-Xing Zhuo,2 Wen-Lian Hsu,3 and Chung-Hsuan Chen1, 5, 6
1 Genomics Research Center, Academia Sinica, Taipei, Taiwan2 National Applied Research Laboratories, National Laboratory Animal Center, Taipei, Taiwan3 Institute of Information Science, Academia Sinica, Taipei, Taiwan4 Department of Medical Research, Mackay Memorial Hospital, Tamshui, Taiwan5 Chemistry Department, National Taiwan University, Taipei, Taiwan6 Institute of Atomic and Molecular Sciences, Academia Sinica, Taipei, Taiwan
Correspondence should be addressed to Chung-Hsuan Chen, [email protected]
Received 18 December 2009; Accepted 18 February 2010
Academic Editor: Alexander I. Archakov
Copyright © 2010 Wei-Chao Chang et al. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.
We studied the seminal vesicle secretion (SVS) of transgenic mice by using one-dimensional gel electrophoresis combined withLTQ-FT ICR MS analysis to explore protein expression profiles. Using unique peptide numbers as a cut-off criterion, 79 proteinswere identified with high confidence in the SVS proteome. Label-free quantitative analysis was performed by using the IDEAL Qsoftware program. Furthermore, western blot assays were performed to validate the expression of seminal vesicle proteins.Sulfhydryl oxidase 1, glia-derived nexin, SVS1, SVS3, and SVS6 showed overexpression in SVS during cancer development. Withhigh sequence similarity to human semenogelin, SVS2 is the most abundance protein in SVS and is dramatically decreased duringthe tumorigenic process. Our results indicate that these protein candidates could serve as potential targets for monitoring seminalvesicle carcinoma. Moreover, this information can provide clues for investigating seminal vesicle secretion-containing seminalplasma for related human diseases.
1. Introduction
Primary seminal vesicle carcinoma is an extremely rareneoplasm; only a few cases have been reported [1, 2].Seminal vesicle carcinoma is usually associated with diffusecarcinomas of the bladder, prostate, or upper tracts. Veryfew studies have been published on seminal vesicle invasion[3], and the tumor biology of seminal vesicle carcinomais not well understood. The diagnoses of seminal vesiclecarcinoma are generally based on a combination of morpho-logic, immunohistochemical, and radiological examinations.However, it is difficult to make a definitive diagnosis usinglimited biopsy material.
The seminal vesicle makes up part of the male accessorysexual glands. After puberty, the glands produce a fluid called
seminal vesicle secretion (SVS), which accumulates in thelumen of the seminal vesicles. SVS contains both proteinand nonprotein components and composes the majority ofseminal plasma. The extirpation of seminal vesicles fromadult rodents greatly reduces fertility, indicating that SVSplays an important role in sperm activity and modification[4]. Some SVS proteins have been analyzed to characterizetheir functions and physiological activities [5–9], but theconstituents of the SVS proteome have not been well studied.
Proteomic studies are broadly applied to the diagnostic,prognostic, and therapeutic fields. In terms of diseasediagnosis and prognosis, body fluid analysis proves to bemore attractive than tissue analysis because it providesseveral advantages including low invasiveness, minimumcost, and easy sample collection and processing [10]. The
2 International Journal of Proteomics
linear ion trap-Fourier transform ion cyclotron resonancemass spectrometer (LTQ-FT ICR MS) has been exploitedas a tool for identifying and characterizing isolated proteins[11]. Combining LTQ-FT ICR MS with liquid chromatog-raphy, large-scale and high-quality proteomic analyses ofseveral body fluids are achievable, including tears, urine,and seminal plasma [12–14]. By virtue of its capacity forexhaustive investigation, proteomic research has arousedhigh expectations for the discovery of biomarkers of variousdiseases [15, 16].
In this work, we used the transgenic mouse TAg as ananimal model to study seminal vesicle carcinoma. Transgenicmouse TAg (C57BL/6-TgN (TRAMP) 8247Ng) expresses anSV40 large T antigen that is driven by the probasin promoter[17]. In addition to being models for prostate cancer, TAgmice also develop other tumors, including neuroendocrinetumors in the prostate and neoplasms in the seminal vesicles.We analyzed the SVS proteome by using one-dimensionalPAGE and LC LTQ-FT ICR MS. Accurate masses of trypticpeptides were measured by FT ICR MS, and tandem mass(MS/MS) experiments were performed in LTQ to acquireadequate data for proteomic identification. The resultingmzXML format data and Mascot search results were appliedto perform label-free quantitative analysis. Moreover, weused western blot assays to validate the quantitative results.
2. Materials and Methods
2.1. Animals and Histopathology. TAg mice were purchasedfrom the Jackson Laboratory (Maine, USA), and wild typeC57BL/6JNarl normal control mice were obtained fromthe National Laboratory Animal Center (Taipei, Taiwan).They were housed in a specifically pathogen-free facilityand handled in accordance with the guidelines of Guide forthe Care and Use of Laboratory Animals. All of the micewere given free access to a standard murine chow diet andreverse osmosis water and were maintained on a 14:10hours light-dark cycle at 21–23◦C. In this study, TAg mice(n = 21; n = 7 for each subgroup) of various ages (32–40weeks) and normal control mice (n= 6) were euthanized andthe seminal vesicles and prostate glands were processed forhistopathologic examination.
2.2. Sample Collection and Preparation. The seminal vesicleswere collected by careful dissection to free them from theadjacent coagulating glands, and SVS was squeezed directlyinto 5 mL of 8 M urea solution. Small amounts of coagulatedpellets were removed through centrifugation at 15,000 g for10 minutes. The protein concentration of the supernatantwas determined using the Bio-Rad Protein Assay (Bio-RadLaboratories, Calif, USA) by the measurement of A595. Each20 μg of SVS proteins was applied to 13% PAGE, and thegel was subsequently visualized through coomassie blue-staining. Gel lanes were divided into 10 sections and allslices were cut into small gel pieces (<1 mm3), followed byin-gel digestion. Additionally, five of the observed majorbands were cut for independent assays. Briefly, the procedureof in-gel digestion included the following steps in order:
(a) destaining with 50% acetonitrile (ACN) and 25 mMammonium bicarbonate (ABC); (b) reduction using freshlyprepared 10 mM dithiothreitol for 45 minutes at 58◦C;(c) alkylation using freshly prepared 55 mM iodoacetamidefor 45 min at room temperature in the dark; (d) enzymedigestion with 4 ng/μL sequencing grade trypsin in 25 mMABC solution at 37◦C for 16–18 hours; (e) extraction oftryptic peptides using a 60% ACN/1% trifluoroacetic acidsolution. After drying to remove the solvent, the re-dissolvedtryptic peptides were subjected to LC LTQ-FT ICR MSanalysis.
2.3. LC LTQ-FT ICR MS Analysis. MS/MS experiments wereperformed with an LTQ-FT ICR MS (Thermo Electron,Calif, USA) equipped with a nanoelectrospray ion source(New Objective, Mass, USA), an Agilent 1100 Series binaryHPLC pump (Agilent Technologies, Calif, USA) and aFamos autosampler (LC Packings, Calif, USA). Trypticpeptide mixtures were injected at a 10 μL/min flow rateinto a self packed precolumn in line with a reverse phaseC18 nanocolumn (75 μm I.D. × 200 mm) that used MagicC18AQ resin (particle size, 5 μm; pore size, 200 A; MichromBioresources, Calif, USA). The analytic program was setat a linear gradient from 10% to 50% ACN with a 60minutes running cycle and a split flow rate of 300 nL/min.The full-scan survey MS experiment (m/z 320–2,000) wasexecuted in FT ICR MS with a mass resolution of 100,000at m/z 400. The top ten most abundant multiply chargedions, if they were above a minimum threshold of 1,000counts, were sequentially isolated for MS/MS by LTQ.Singly charged ions were rejected for MS/MS sequenc-ing.
2.4. Mascot Search. The raw files of spectra were convertedto mgf files with Mascot Daemon (data import filter: massrange, 600–5400; grouping tolerance, 1.4) and merged intoa single file for searching by the MASCOT (version 2.1,Matrix Science Ltd., London, UK) software platform basedon the IPI mouse database (v 3.36). The following MASCOTparameter settings were used; the peptide tolerance was15 ppm with 2+ and 3+ peptide charges and the MS/MStolerance was 0.6 Da. Two missed cleavages by trypsinwere allowed, carbamidomethyl (C) was used as a fixedmodification and oxidation (M) and deamidated (NQ) wereused as variable modifications. The significance threshold forthe identification was set to P < .01.
2.5. Label-Free Quantitative Analysis. A software programIDEAL-Q (ID-based Elution time Alignment by Linearregression Quantification) was developed in-house toanalyze LC-MS/MS data for label-free quantitative analysis[18]. The program was used to process the LC-MS dataand the search results obtained from the Mascot searchengine to extract the quantification information. The wholequantitative analysis consisted of the following tasks. (I) Datapreparation and construction of the protein list. The raw datafiles generated from the mass instrument were convertedinto the mzXML data format by the ReAdW program
International Journal of Proteomics 3
(http://tools.proteomecenter.org/wiki/index.php?title=Soft-ware:ReAdW). The data of each fractional LC-MS/MSruns coming from the same sample were merged and thensearched by the Mascot search engine to establish a proteinlist, which contained identified proteins and their relatedpeptide information. The mzXML files coupled with thepeptide and protein identification results were input to theIDEAL-Q program. (II) Extracting quantitative informationfrom each LC-MS run. For quantitative analysis of a peptidein an LC-MS run, we extracted the LC-MS data within therange of ±1.5 minutes of its elution time and ±3.5 Da of theprecursor m/z value. The peak clusters located within theselected elution time and the precursor m/z value from theextracted data underwent a peptide validation process. Forpeptide validation, the following three criteria were applied:signal-to-noise ratio (S/N), charge state (CS), and isotopepattern (IP). The S/N criterion checks whether the precursorpeak has a valid S/N ratio (>2). The CS criterion eliminatedthe peak clusters with an incorrect charge state by examiningwhether the distance between adjacent peaks is equal to 1/z(tolerance ±1/10 1/z). Finally, the IP criterion examined thecorrelation between isotopic distribution of the observedpeak intensities and the theoretical isotopic distributionof the peptide. The correlation was then evaluated by aChi-square goodness of fit test (<0.218). The purpose ofpeptide validation was to filter out false peptide signals; onlythe peptide passing the validation criteria were processedto subsequent quantification. We used the extracted ionchromatogram (XIC) to determine peptide abundance inan LC-MS run. (III) Peptide abundance and peptide ratioprocessing. First we determined the abundances of validpeptides in each LC-MS run. Then we calculated the peptideabundance in a fraction by averaging the peptide abundancesof all repeated runs. We summed the peptide abundances inall fractions to represent the peptide quantity in the sample.Following, the peptide ratio between samples could becalculated. (IV) Protein abundance processing. We selectednondegenerate unique peptides and performed Dixon’stest to eliminate outliers of peptide ratios for each protein.We then used the top three highly abundant peptides ofone protein to represent the quantity of this protein by aweighted average.
2.6. Western Blot. Polyclonal antibodies against SVS1, SVS2,SVS3 [19], SVS5, SVS7 [20], sulfhydryl oxidase 1, glia-derived nexin, carcinoembryonic antigen-related cell adhe-sion molecule 10 (CEACAM 10) [7], Lysozyme C-type M,secreted seminal-vesicle Ly-6 protein 1 (SSLP-1) [21], serineprotease inhibitor kazal-like protein (SPINKL) [22], and ser-ine protease inhibitor Kazal-type 3 (SPINK3) [9] were raisedin New Zealand White rabbits. Antibody against humanalbumin, which also crossreacted with mouse albumin, waspurchased from Calbiochem (Darmstadt, Germany). AfterPAGE separation, proteins were transferred to a PVDFmembrane using a semidry blotter (ATTA, Tokyo, Japan).The electrophoresis program was set with a constant current(1.5 mA/cm2) for 1 hour. The membrane was blocked with5% (w/v) skim milk in phosphate-buffered saline (PBS) at
room temperature for O/N reaction, and then incubatedwith primary antibody (1 : 5000) in PBS with 2% (w/v) skimmilk for 1 hour. After gentle agitation in four changes ofPBST (PBS with 0.05% Tween 20) for 15 minutes each, themembrane was immuno-reacted with secondary antiserum(horseradish peroxidase-conjugated goat antirabbit IgG,Amersham Pharmacia) diluted to 1 : 10000 in PBS with 2%(w/v) skim milk for 1 hour. Immuno-reactive bands wererevealed using an enhanced ECL substrate according to themanufacturer’s instructions (Pierce, Illinois, USA).
3. Results
3.1. Histopathology and Tumor Categories. According to thehistopathologic results, the neoplasm development of theaccessory sex gland was categorized into three stages: (I)hyperplasia of the seminal vesicle (Hp), (II) adenoma ofthe seminal vesicle (Ad), and (III) adenocarcinoma of theseminal vesicle with prostate cancer (Ac) (Figure 1). TheHp stage showed a typical hyperplasia area. These areas,which were characterized by small size and uniformityof cells and nuclei, appeared to have increased glandularenfolding and lack of mitoses. The Ad stage showed thereplacement of most of the normal glandular parenchymawith tumor masses encompassing two main components,epithelial cells and stromal cells. The cuboidal to columnarepithelial cells were arranged in multiple papillary fronds andglandular structures, which were separated and supportedby abundant, immature, and fibrovascular stroma. However,mitotic figures were infrequent. At the Ac stage, the seminalvesicular tumor showed an appearance similar to the Adstage, except that sometimes hemorrhage occurred in theseminal vesicles. Prostatic adenocarcinoma of the Ac stageappeared as intraluminar cribriform to papillary epithelialproliferations that completely or almost completely filled thelumen of several adjacent alveoli. The epithelium that linedthe tumors was composed of bland-appearing, cuboidal totall columnar epithelial cells with maintenance of nuclearpolarity and sometimes with basophilic cytoplasm.
3.2. Protein Pattern and Proteomic Analysis. Three SVS sam-ples of each group were pooled for the proteomic measure-ments. SVS proteins were separated by PAGE and their pro-file was presented by coomassie blue staining (Figure 2). Theprotein profile was dominated by a small number of highlyexpressed proteins. The protein distribution of normal SVSwas different from those coming from the tumorous SVS,which displayed more complex protein contents. Based onprotein pattern comparison, five major bands were chosenas reference indicators. Bands A and E showed upregulatedexpression, while band B showed downregulated expressionin the tumorous SVS. MS/MS was used to analyze the majorproteins in bands A to E, which were identified as albumin,seminal vesicle secretory protein 2 (SVS2), SVS4, SVS5, andhemoglobin beta, respectively. The serum proteins, albumin,and hemoglobin beta, are obviously increased in SVS in theearly stages of tumorigenesis.
4 International Journal of Proteomics
(a) (b)
(c) (d)
Figure 1: Histopathologic section and tumor categories. Tissue slices from seminal vesicles of normal and various tumor stage mice werestained with hematoxylin-eosin. (a) Normal seminal vesicle, (b) Hp stage seminal vesicle, (c) Ad stage seminal vesicle, and (d) Ac stageprostate with carcinoma. Photographs display the images with original magnification ×10. Scale bar, 75 μm.
The proteomic analyses of four groups of SVS, whichwere normal, Hp, Ad, and Ac, were performed by repeatedexperimental runs. As a consequence of these analyses,excluding single peptide or single unique peptide matchedproteins and keratins that were frequent contaminants inproteomic analysis, 179 proteins met the search criterionand were identified in the proteome by combining fourkinds of samples. In order to further improve confidence inthe identified proteins, the reproducibility of the matchedunique peptides found in every SVS sample was consideredas an index to sift through the protein list. The determinationof unique characteristics for a peptide was based on theproteotypic peptide sequence that could only match to oneprotein through the IPI mouse database. The number ofunique peptides for one protein was summed with the resultsof proteomic analyses of the four groups of SVS; therefore,not all peptide signals could be found in the four groups ofSVS. Generally, a smaller number of unique peptides coupledwith a lower detection rate. We defined the undetectable rateas the average percentage that could not find the matchedunique peptides at the designated unique peptide number inthe four groups of SVS. With the unique peptide numbers 2,3, 4, and 5, the undetectable rate was 27.7%, 28.0%, 27.6%,
and 12.5%, respectively. When the unique peptide numberwas more than 5, the undetectable rate decreased to zero(Figure 3). Thus, we chose the unique peptide number 5as a cut-off criterion to finalize the SVS proteome. Basedon this condition, 79 proteins were included in the SVSproteome (Table 1). Among this proteome, 47 proteins weresecreted or serum proteins that were the most abundant inthis proteome and 16 proteins belonged to seminal vesicleproteins that have been identified or characterized at theprevious studies. In addition, a small number of intracellularproteins, including cytoplasm protein, lysosome protein,endoplasmic reticulum protein, and membrane protein werealso found in this proteome.
3.3. Label-Free Quantitative Analysis. To assess the relativeprotein expression levels at normal and various cancer stages,quantitative proteomic analysis was pursued by using a label-free quantitative approach, which adopted the average peak-area of the three most intense peptides for the identifiedproteins to represent the absolute protein abundance [23].The in-house developed program IDEAL-Q [18] was usedto analyze LC-MS data and the corresponding MASCOT
International Journal of Proteomics 5
15
20
25
35
50
70
100
140
240kDa N Hp Ad Ac Major protein
(A) Serum albumin
(B) Seminal vesicle protein 2
(C) Seminal vesicle protein 4(D) Seminal vesicle protein 5
(E) Hemoglobin β
Figure 2: Protein pattern of SVS. SVS proteins were separated by 13% PAGE and visualized by coomassie blue staining. N, normal; Hp, Adand Ac, various tumor stages. Molecular weights of protein markers are shown on the left. Designated bands A–E were identified by MS/MS,and the names of the major proteins are shown on the right.
2 3 4 5 6 > 60
5
10
15
20
25
30
Number of unique peptide
Un
dete
ctab
lera
te(%
)
Figure 3: The relationship of unique peptide number and theundetectable rate. The undetectable rate was defined as thepercentage of proteins without identifiable peak-areas in the sameunique peptide number group.
search results to extract the quantification information.The results obtained from this quantitative calculation areillustrated in Table 1. The stoichiometric distribution ofprotein abundance was from 3.26 × 104 (Dickkopf-likeprotein 1) to 2.77 × 109 (SVS2), which meant that thedynamic range for protein detection reached five orders ofmagnitude by using the described method. To estimate theapplied quantity of SVS proteins for proteomic analysis, thetotal protein abundances were summed and were 3.31 ×109, 9.74 × 108, 1.05 × 109, and 9.85 × 108 for normal, Hp,Ad, and Ac, respectively. The results showed that the quantity
of SVS proteins between various cancer stages was within a10% difference, but the quantity of normal SVS was threetimes more than other samples, which appeared to conflictwith the gel patterns (Figure 2). We further compared thedifference of expression levels of SVS2 and SVS4 (or SVS5)of normal SVS, which displayed almost equal intensity onPAGE gel by dye staining. SVS2 showed a protein abundanceof 2.77 × 109, which was about 200-fold higher than SVS4at 1.29 × 107 (or 150-fold higher than SVS5 at 1.76 × 107).This result implied that quantification errors could occurwith the comparison of various molecular weight proteins.To acquire the protein content distribution for realizingthe effect of using this quantitative analysis method, theabundance of every protein was converted to the percentageof content in every SVS sample. The results illustrated thatSVS2, SVS4, and SVS5 were 83.7%, 0.4% and 0.5% in normalSVS proteins, respectively (Table 1). In the SVS of the Hpstage, the low molecular weight proteins SVS4, SVS5, andhemoglobin beta were 1.4%, 1.2%, and 2.0%, respectively,which were significantly less than SVS2 at 33.0%. Comparedwith the gel pattern, the levels of low molecular weightproteins tended to be underestimated, which lead to errors inmeasuring protein quantity or determining the percentage ofprotein content.
The relative expression levels of tumorous versus nor-mal conditions were achieved by calculating the ratios ofabsolute SVS protein abundances (Table 1). Among sem-inal vesicle proteins, SVS1, SVS3, and glia-derived nexinshowed upregulated expression with ratios greater than 2.With respect to downregulated expression, lysozyme C and
6 International Journal of Proteomics
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International Journal of Proteomics 7
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say
Pro
tein
Mas
s/pI
Hp
Ad
Ac
NH
pA
dA
cN
Hp
/NA
d/N
Ac/
NH
pA
dA
cN
(2)
Seru
mpr
otei
nan
dSe
cret
edpr
otei
n
IPI0
0131
695
Alb
um
in68
648/
5.75
109
8.12
E+
076.
21E
+07
3.52
E+
072.
17E
+07
12.4
4.6
4.6
12.1
3.74
2.86
1.62
8.34
5.94
3.57
0.66
•
IPI0
0129
755
Alp
ha-
1-an
titr
ypsi
n1-
245
946/
5.32
87.
59E
+05
7.53
E+
053.
16E
+05
1.31
E+
066.
66.
35.
527
.50.
580.
570.
240.
080.
070.
030.
04
IPI0
0123
924
Alp
ha-
1-an
titr
ypsi
n1-
445
969/
5.24
248.
49E
+06
1.10
E+
076.
45E
+06
7.10
E+
0614
.96.
77.
116
.41.
201.
540.
910.
871.
050.
650.
21
IPI0
0123
927
Alp
ha-
1-an
titr
ypsi
n1-
545
862/
5.44
98.
01E
+05
2.14
E+
062.
17E
+06
3.01
E+
0625
.54.
727
.110
.60.
270.
710.
720.
080.
200.
220.
09
IPI0
0117
857
Alp
ha-
1-an
titr
ypsi
n1-
645
794/
5.25
101.
45E
+06
1.18
E+
065.
62E
+05
3.36
E+
057.
97.
55.
843
.64.
323.
511.
670.
150.
110.
060.
01
IPI0
0128
249
Alp
ha-
2-H
S-gl
ycop
rote
in37
302/
6.04
97.
34E
+05
7.96
E+
057.
52E
+05
1.20
E+
066.
016
.79.
013
.90.
610.
660.
630.
080.
080.
080.
04
IPI0
0624
663
Alp
ha-
2-m
acro
glob
ulin
1671
77/6
.38
113.
69E
+07
4.63
E+
075.
60E
+07
3.66
E+
0715
.27.
16.
215
.81.
011.
271.
533.
794.
435.
691.
11
IPI0
0169
625
An
tiac
idph
osph
atas
eva
riab
lelig
ht
chai
n18
1695
5/8.
505
ND
ND
ND
6.34
E+
04N
DN
DN
D0.
0N
DN
DN
DN
DN
DN
D0.
00
IPI0
0136
642
An
tith
rom
bin
-III
5197
1/6.
1013
3.27
E+
055.
48E
+05
1.13
E+
062.
61E
+05
32.0
9.2
3.0
12.3
1.26
2.10
4.35
0.03
0.05
0.12
0.01
IPI0
0877
236
Apo
lipop
rote
inA
-I30
569/
5.64
373.
99E
+06
5.29
E+
069.
58E
+06
1.05
E+
0615
.410
.29.
520
.43.
805.
049.
130.
410.
510.
970.
03
IPI0
0377
351
Apo
lipop
rote
inA
-IV
4500
1/5.
4123
2.86
E+
072.
82E
+07
3.54
E+
072.
59E
+07
16.7
17.6
19.8
20.7
1.10
1.09
1.36
2.94
2.69
3.59
0.78
IPI0
0322
463
Bet
a-2-
glyc
opro
tein
138
593/
8.59
95.
68E
+05
2.74
E+
053.
49E
+05
3.87
E+
0429
.55.
68.
236
.414
.67
7.08
9.01
0.06
0.03
0.04
0.00
IPI0
0331
286
Bet
a-2-
mic
rogl
obu
lin13
770/
8.55
158.
61E
+06
1.19
E+
079.
06E
+06
9.84
E+
067.
56.
46.
010
.00.
881.
210.
920.
881.
130.
920.
30
IPI0
0320
420
Clu
ster
in51
623/
5.46
471.
89E
+07
1.06
E+
072.
07E
+07
4.31
E+
0623
.811
.010
.328
.04.
382.
454.
811.
941.
012.
110.
13
IPI0
0323
624
Com
plem
ent
C3,
isof
orm
Lon
g(F
ragm
ent)
1865
38/6
.29
531.
41E
+07
1.62
E+
071.
66E
+07
9.51
E+
0618
.49.
19.
325
.81.
491.
701.
751.
451.
551.
690.
29
IPI0
0130
010
Com
plem
ent
com
pon
ent
fact
orH
1411
79/6
.85
221.
17E
+07
1.43
E+
074.
89E
+06
9.29
E+
0614
.819
.15.
015
.11.
261.
540.
531.
201.
370.
500.
28
IPI0
0114
065
Com
plem
ent
fact
orB
(Fra
gmen
t)84
951/
7.18
91.
54E
+06
1.56
E+
061.
78E
+06
6.84
E+
0514
.46.
44.
814
.22.
252.
272.
600.
160.
150.
180.
02
IPI0
0123
744
Cys
tati
n-C
1552
1/9.
1810
1 .03
E+
061.
10E
+06
8.86
E+
054.
57E
+05
8.7
9.9
6.1
33.9
2.26
2.41
1.94
0.11
0.11
0.09
0.01
IPI0
0331
487
Dic
kkop
f-lik
epr
otei
n1
2662
3/7.
986
2.76
E+
052.
86E
+05
1.36
E+
053.
26E
+04
14.3
8.1
23.7
8.7
8.46
8.77
4.16
0.03
0.03
0.01
0.00
IPI0
0115
522
Fibr
inog
en,a
lph
a61
288/
7.16
132.
69E
+06
3.24
E+
066.
91E
+06
2.55
E+
067.
212
.99.
212
.31.
061.
272.
710.
280.
310.
700.
08
8 International Journal of Proteomics
Ta
ble
1:C
onti
nu
ed.
Acc
essi
onn
um
ber
Un
iqu
ePe
ptid
e(A
)pr
otei
nab
ouda
nce
(B)
aver
age
CV
ofpe
ptid
es(%
)(C
)re
lati
veex
pres
sion
rati
o(D
)p
erce
nta
geof
con
ten
t(E
)W
este
rnbl
otas
say
Pro
tein
Mas
s/pI
Hp
Ad
Ac
NH
pA
dA
cN
Hp
/NA
d/N
Ac/
NH
pA
dA
cN
IPI0
0279
079
Fibr
inog
en,b
eta
5471
8/6.
689
8.79
E+
067.
32E
+06
6.24
E+
063.
98E
+05
22.6
18.5
22.8
13.0
22.0
918
.40
15.6
70.
900.
700.
630.
01
IPI0
0122
312
Fibr
inog
en,g
amm
a50
317/
5.38
166.
52E
+05
5.58
E+
053.
92E
+05
2.45
E+
0514
.25.
09.
46.
92.
672.
281.
600.
070.
050.
040.
01
IPI0
0113
539
Fibr
onec
tin
2723
19/5
.39
114.
53E
+05
8.32
E+
055.
61E
+05
2.85
E+
068.
01.
112
.710
.60.
160.
290.
200.
050.
080.
060.
09
IPI0
0117
167
Gel
solin
,iso
form
185
888/
5.83
51.
58E
+06
1.26
E+
061.
40E
+06
4.13
E+
0533
.622
.822
.417
.93.
843.
053.
390.
160.
120.
140.
01
IPI0
0124
640
Gra
nu
lin64
972/
6.70
171.
93E
+06
2.19
E+
062.
57E
+06
1.14
E+
0610
.53.
615
.618
.61.
701.
922.
250.
200.
210.
260.
03
IPI0
0409
148
Hap
togl
obin
3872
7/5.
887
3.24
E+
053.
78E
+05
3.99
E+
052.
44E
+05
2.8
8.7
10.7
13.5
1.32
1.54
1.63
0.03
0.04
0.04
0.01
IPI0
0469
114
Hem
oglo
bin
,alp
ha
1507
6/7.
967
2.99
E+
073.
87E
+07
9.02
E+
071.
39E
+07
7.4
6.9
6.1
24.0
2.15
2.79
6.49
3.07
3.70
9.15
0.42
IPI0
0110
658
Hem
oglo
bin
,bet
a15
193/
8.96
51.
94E
+07
4.57
E+
076.
68E
+07
1.01
E+
072.
815
.07.
932
.41.
924.
516.
602.
004.
366.
780.
31
IPI0
0128
484
Hem
opex
in51
308/
7.92
272.
18E
+06
8.42
E+
069.
28E
+06
7.59
E+
0519
.511
.53.
07.
82.
8711
.10
12.2
30.
220.
800.
940.
02
IPI0
0322
304
His
tidi
ne-
rich
glyc
opro
tein
HR
G60
401/
7.26
111.
50E
+07
3.43
E+
071.
65E
+07
4.43
E+
076.
44.
45.
216
.70.
340.
770.
371.
543.
281.
671.
34
IPI0
0114
958
Isof
orm
HM
Wof
Kin
inog
en-1
7305
6/6.
0511
2.56
E+
072.
97E
+07
1.68
E+
079.
15E
+06
14.1
16.4
9.7
19.8
2.79
3.25
1.83
2.63
2.84
1.70
0.28
IPI0
0317
340
Lac
totr
ansf
erri
n77
788/
8.86
352.
63E
+07
2.06
E+
071.
52E
+07
1.81
E+
0726
.421
.318
.618
.61.
461.
140.
842.
701.
971.
540.
55
IPI0
0114
403
Met
allo
prot
ein
ase
inh
ibit
or1
2261
3/9.
145
2.37
E+
062.
26E
+06
2.60
E+
063.
27E
+06
13.4
4.4
6.6
26.0
0.72
0.69
0.79
0.24
0.22
0.26
0.10
IPI0
0123
223
Mu
rin
oglo
bulin
-116
5193
/6.0
019
4.28
E+
066.
65E
+06
7.31
E+
064.
64E
+06
5.2
10.5
3.9
18.9
0.92
1.43
1.57
0.44
0.64
0.74
0.14
IPI0
0115
941
Neu
trop
hil
gela
tin
ase-
asso
ciat
edlip
ocal
in22
861/
8.96
162.
22E
+06
4.08
E+
063.
67E
+06
1.35
E+
064.
85.
04.
814
.61.
653.
032.
720.
230.
390.
370.
04
IPI0
0309
704
Nu
cleo
bin
din
-250
273/
5.05
246.
56E
+05
2.82
E+
061.
38E
+06
4.88
E+
059.
614
.16.
816
.21.
345.
782.
830.
070.
270.
140.
01
IPI0
0322
936
Pla
smin
ogen
9072
3/6.
2116
2.89
E+
053.
11E
+05
2.34
E+
052.
07E
+05
6.2
4.5
4.3
14.3
1.39
1.50
1.13
0.03
0.03
0.02
0.01
IPI0
0135
156
Pro
tein
FAM
3B26
135/
8.97
117.
40E
+05
5.28
E+
055.
86E
+05
3.63
E+
0519
.914
.07.
013
.82.
041.
461.
620.
080.
050.
060.
01
IPI0
0311
104
Sem
aph
orin
-3C
8520
6/8.
865
3.16
E+
051.
72E
+05
3.22
E+
056.
56E
+04
41.7
27.1
32.4
50.4
4.82
2.63
4.91
0.03
0.02
0.03
0.00
IPI0
0131
830
Seri
ne
prot
ease
inh
ibit
orA
3K46
850/
5.05
191.
09E
+06
1.12
E+
065.
17E
+05
6.73
E+
0413
.58.
24.
718
.016
.28
16.6
37.
690.
110.
110.
050.
00
IPI0
0139
788
Sero
tran
sfer
rin
7667
4/6.
9490
1.46
E+
071.
28E
+07
1.07
E+
074.
87E
+06
13.6
7.6
13.7
16.3
2.99
2.62
2.20
1.50
1.22
1.09
0.15
IPI0
0309
214
Seru
mam
yloi
dP-
com
pon
ent
2623
0/5.
985
5.96
E+
055.
52E
+05
3.30
E+
055.
09E
+05
47.5
36.3
24.6
6.4
1.17
1.08
0.65
0.06
0.05
0.03
0.02
IPI0
0321
190
Sulf
ated
glyc
opro
tein
161
381/
5.07
85.
36E
+07
5.04
E+
075.
34E
+07
3.39
E+
0728
.018
.05.
335
.81.
581.
491.
585.
504.
825.
421.
02
IPI0
0136
556
Tran
scob
alam
in-2
4755
5/5.
908
9.37
E+
051.
50E
+06
1.85
E+
061.
85E
+06
7.1
4.4
12.7
13.0
0.51
0.81
1.00
0.10
0.14
0.19
0.06
International Journal of Proteomics 9T
abl
e1:
Con
tin
ued
.
Acc
essi
onn
um
ber
Un
iqu
ePe
ptid
e(A
)pr
otei
nab
ouda
nce
(B)
aver
age
CV
ofpe
ptid
es(%
)(C
)re
lati
veex
pres
sion
rati
o(D
)p
erce
nta
geof
con
ten
t(E
)W
este
rnbl
otas
say
Pro
tein
Mas
s/pI
Hp
Ad
Ac
NH
pA
dA
cN
Hp
/NA
d/N
Ac/
NH
pA
dA
cN
IPI0
0127
560
Tran
sthy
reti
n15
766/
5.77
89.
05E
+05
1.29
E+
061.
54E
+06
2.16
E+
0612
.714
.910
.79.
60.
420.
600.
710.
090.
120.
160.
07
IPI0
0129
102
Uro
kin
ase-
typ
epl
asm
inog
enac
tiva
tor
4823
6/8.
5321
3.09
E+
072.
50E
+07
1.70
E+
071.
74E
+07
11.7
15.7
24.2
20.7
1.78
1.44
0.97
3.18
2.39
1.72
0.53
IPI0
0126
184
Vit
amin
D-b
indi
ng
prot
ein
5356
5/5.
3919
1.22
E+
061.
58E
+06
1.37
E+
069.
77E
+05
16.0
20.5
8.9
14.7
1.25
1.62
1.40
0.13
0.15
0.14
0.03
(3)
Cyt
opla
smpr
otei
n
IPI0
0110
850
Act
in,c
ytop
lasm
ic1
4171
0/5.
2911
4.63
E+
055.
79E
+05
3.36
E+
052.
72E
+05
13.0
18.6
5.1
17.1
1.70
2.13
1.23
0.05
0.06
0.03
0.01
IPI0
0223
757
Ald
ose
redu
ctas
e35
709/
6.71
81.
21E
+06
1.41
E+
061.
94E
+06
6.78
E+
0520
.811
.66.
98.
81.
782.
082.
860.
120.
130.
200.
02
IPI0
0462
072
Alp
ha-
enol
ase
4711
1/6.
377
1.81
E+
051.
57E
+05
1.89
E+
051.
44E
+05
47.1
12.2
16.5
6.1
1.26
1.09
1.31
0.02
0.01
0.02
0.00
IPI0
0230
320
Car
bon
ican
hydr
ase
128
303/
6.44
57.
77E
+05
1.14
E+
062.
63E
+05
ND
50.4
1.7
60.3
ND
ND
ND
ND
0.08
0.11
0.03
ND
IPI0
0275
232
Mat
rix
met
allo
prot
ein
ase
730
009/
6.79
69.
13E
+05
1.40
E+
061.
36E
+06
2.44
E+
055.
712
.27.
211
.13.
745.
755.
550.
090.
130.
140.
01
IPI0
0121
788
Pero
xire
doxi
n-1
2216
2/8.
269
1.90
E+
051.
92E
+05
2.86
E+
051.
76E
+05
14.7
8.2
7.0
19.9
1.08
1.09
1.62
0.02
0.02
0.03
0.01
(4)
Lyso
som
epr
otei
n
IPI0
0111
013
Cat
hep
sin
D44
925/
6.71
62.
14E
+05
1.69
E+
053.
55E
+05
2.82
E+
0512
.710
.715
.812
.70.
760.
601.
260.
020.
020.
040.
01
IPI0
0128
154
Cat
hep
sin
L137
523/
6.37
77.
14E
+05
1.80
E+
061.
38E
+06
5.97
E+
058.
67.
815
.817
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10 International Journal of Proteomics
seminal vesicle antigen were decreased two times lower thantheir normal value. SVS2, with a 10-fold decrease, wasthe most differentially expressed protein. Similar differenceswere also observed in the gel patterns. In addition, mostserum proteins (35/46, 76%) had an upregulated expressionin the tumorous SVS. This phenomenon could relate to thephysiological change of seminal vesicles that increases thevascular permeability for serum proteins to enter the lumenof the seminal vesicle.
To evaluate the reproducibility of MS analysis, coefficientof variation (CV) values (%) of the top three highly abundantpeptides in repeated runs were calculated and the average CVvalues are listed in Table 1. In this work, the total averageCV values for normal, Hp, Ad, and Ac samples were 16.4%,15.1%, 10.8%, and 11.5%, respectively.
3.4. Western Blot Validation. The effects of tumorigenesis onthe expression of seminal vesicle secretory proteins were con-firmed by western blot analyses, which were also performedto validate the quantification results of the MS analyses(Table 1). Because no protein has been demonstrated tohave constitutive or consistent expression in SVS, we usedthe same loading quantity as the quantitative control inthis study. Based on MS quantification, more than 75%of serum proteins showed upregulated expression in thetumorous SVS. Using western blot analysis, for example, thehigher levels of albumin were clearly demonstrated in thetumorous SVS, which was consistent with the MS results(Figure 4). Many SVS proteins were also analyzed by theproduced antibodies to verify their expression. The signalintensities of western blot were quantitatively measured bythe software ImageJ (http://rsb.info.nih.gov/ij/) [24], and therelative expression ratios compared with the normal sampleswere calculated (Figure 4(c)). Sulfhydryl oxidase 1, glia-derived nexin, SVS1 and SVS3 showed upregulated expres-sion, but SVS2, CEACAM 10, lysozyme C-type M, SVS5,SSLP-1, SVS7, SPINKL, and SPINK3 showed downregulatedexpression. Regardless of upregulation or downregulation,most SVS proteins changed their secretion depending onthe carcinogenesis progress. The protein expression levelsrevealed a few discrepancies in comparison with the westernblot and MS quantification methods. For example, SSLP-1showed little change during tumorigenic process by using MSanalysis; however, it had a clear decreasing pattern by westernblot. On the whole, the western blot results were in goodagreement with the MS quantification.
4. Discussion
4.1. Tumorigenesis Affects the Composition of the SVS Pro-teome. SVS, one of the major contributors to seminal fluid,is important for semen coagulation and plays an importantrole in promoting sperm motility and suppressing immuneactivity in the female reproductive tract. Only 16 specificseminal vesicle secretory proteins have been identified withhigh confidence in the SVS proteome, which is a relativelysimple system compared to other body fluids. Almost all SVSproteins make changes in their levels during the tumorigenic
process. Compared with increasing protein expression, thesuppression effect produced by tumorigenesis on proteinexpression is more remarkable. The expression of SVS2,SVS5, and lysozyme C-type M decreased 5- to 10-fold atthe Ac stage by MS analysis or western blot assay. Althoughthe functions of most SVS proteins in the reproductivesystem are not fully understood, previous studies havedemonstrated that SVS proteins involved in formation of thecopulatory plug have the abilities to enhance sperm motilityand act as decapacitation factors to modulate the fertilizingability of spermatozoa. They also have activity of serineprotease inhibitors and antimicrobial activity, which maybe involved in fertility (Table 2). According to the currentstudy, the physiological functions of SVS proteins did notshow a definite correlation with the effects of tumorigenesis.For example, SVS1, SVS2, and SVS3 are the componentsof copulatory plug formation; however, SVS1 and SVS3showed upregulated expression, but SVS2 showed downreg-ulated expression. As serine protease inhibitors, glia-derivednexin and SVS6 showed upregulated expression, but SVS5,SPINKL, and SPINK3 showed downregulated expression.Thus, the changes of seminal vesicle proteins during thetumorigenic process need to be explored individually. Basedon our studies, almost all seminal vesicle secretory proteinswere aberrantly expressed by tumor cells. Only a few seminalvesicle proteins have been demonstrated to correlate withthe occurrence of carcinoma (Table 2). The expression ofsulfhydryl oxidase 1, glia-derived nexin, and SVS6 increasedin seminal vesicle carcinoma and other carcinomas. Theresults suggest that the expression of these proteins could beunder similar regulation in various carcinoma systems.
SVS2, the most abundant protein in SVS, decreasedduring seminal vesicle carcinoma. SVS2 shows 55% sequencesimilarity to human semenogelin, which is the major struc-tural component of gelatinous coagulum. Semenogelin isable to protect sperm from protein tyrosine phosphorylationand to prevent induction of the acrosome reaction [38].A member of the gene family that encodes this semen-coagulating protein is commonly found in mammalianspecies [6, 39–41]. As a decapacitation factor, SVS2 can bindsperm to affect fertility in the female reproductive tract.Decreased levels of SVS2 at the tumorigenic stages coulddiminish its inhibition of sperm mobility in a concentration-dependent manner [33]. In addition to varying biologicalactivities, the change of the SVS2 protein level could providea useful target to monitor the progress of seminal vesiclecarcinoma.
4.2. Vascular Permeability Contributes to the Elevated Levels ofSerum Proteins in SVS. Many serum proteins showed upreg-ulation in the tumorous SVS (Table 1). The most strikinglyexpressed proteins, albumin and hemoglobin β, could beobserved on the coomassie blue-stained gel (Figure 2). Theexpression of albumin was also confirmed by western blotassay (Figure 4). Basal levels of serum proteins could beconsidered to come from contamination by surgical leaks.However, elevated levels of serum proteins may originatefrom other sources. First, the mutant secretory cells of
International Journal of Proteomics 11
Upregulated expression
Downregulated expression Relative expression ratio
N Hp Ad Ac
N Hp Ad Ac
N Hp Ad Ac
N Hp Ad Ac
N Hp Ad Ac
N Hp Ad Ac
N Hp Ad Ac
N Hp Ad Ac
N Hp Ad Ac
N Hp Ad Ac
N Hp Ad Ac
N Hp Ad Ac
N Hp Ad Ac
(1) Albumin
(2) Sulfhydryl oxidase
(3) Glia-derived nexin
(4) SVS 1
(5) SVS 3
(1) SVS 2
(2) CEACAM 10
(3) Lysozyme C, type M
(4) SVS 5
(5) SSLP-1
(6) SVS 7
(7) SPINKL
(8) SPINK 3
Hp/N10.69
Ad/N9.72
Ac/N4.45
Hp/N0.87
Ad/N1.41
Ac/N1.82
Hp/N1.9
Ad/N2.29
Ac/N1.66
Hp/N1.26
Ad/N1.26
Ac/N1.08
Hp/N1.03
Ad/N1.11
Ac/N1.22
Hp/N0.21
Ad/N0.19
Ac/N0.16
Hp/N1.08
Ad/N0.86
Ac/N0.9
Hp/N0.65
Ad/N0.48
Ac/N0.45
Hp/N0.3
Ad/N0.34
Ac/N0.21
Hp/N0.76
Ad/N0.66
Ac/N0.29
Hp/N0.81
Ad/N0.59
Ac/N0.68
Hp/N0.7
Ad/N0.64
Ac/N0.55
Hp/N0.46
Ad/N0.44
Ac/N0.32
(a)
(b) (c)
Figure 4: Western blot analysis. The expression of albumin, sulfhydryl oxidase 1, glia-derived nexin, SVS1, SVS3, SVS2, CEACAM 10,Lysozyme C-type M, SVS5, SSLP-1, SVS7, SPINKL, and SPINK3 were examined using polyclonal antibodies. (a) proteins with upregulatedexpression; (b) proteins with downregulated expression; (c) relative expression ratios compared to normal SVS.
the seminal vesicles may produce and secrete them intothe lumen, meaning that they are endogenous proteins.Second, angiogenesis or vascular permeability results in themovement of proteins from the blood into the seminalvesicle lumen. To evaluate this phenomenon, we usedmicroarray gene chips to examine the mRNA expression inthe seminal vesicles from the four stages. The results showedthat the expression of albumin, hemoglobin, apolipoprotein,and α1-antitrypsin remained at background levels (datanot shown). This suggested that these serum proteins areexcluded from being newly synthesized under tumorigenicconditions in seminal vesicles, and that angiogenesis orvascular permeability is responsible for the increase in theirlevels. Vascular permeability is a tightly regulated process that
is often an essential response accompanying angiogenesis,tumor metastasis, or inflammation [42]. Thus, there is areasonable explanation for late (Ac) stage SVS to have a pinkor red appearance.
4.3. Label-Free Quantitative Analysis. Combining one-dimensional PAGE fractionation techniques with LC MS/MSanalysis is a popular approach for proteomic research[43, 44]. Due to simplicity and flexibility, the label-freequantitative strategy is an attractive alternative for thequantification of LC MS/MS-based proteomics. In this study,our experimental data were analyzed by using the self-developed program IDEAL-Q, which was designed to reduce
12 International Journal of Proteomics
Table 2: Summary of seminal vesicle secretory proteins identified in mouse SVS.
Expression
Protein Function Reference Mass Western Cancer-related studies
Upregulated expression
Sulfhydryl oxidase 1Catalyze disulfide bondformation
[25] ⇑ ⇑ [26, 27]
Glia-derived nexin Serine protease inhibitor [8] ⇑ ⇑ [28, 29]
Seminal vesicle secretory protein 1Amine oxidaseactivity/Copulatory plugformation
[5] ⇑ ⇑ —
Seminal vesicle secretory protein 3aCopulatory plugformation
[19] ⇑ ⇑ —
Seminal vesicle secretory protein 3βCopulatory plugformation
[30] ⇑ ⇑ —
Seminal vesicle secretory protein 6Serine proteinaseinhibitor
[31] ⇑ — [32]
Downregulated expression
Seminal vesicle secretory protein 2Semen-coagulatingprotein/Spermdecapacitation factor
[6, 33] ⇓ ⇓ [34]
Carcinoembryonic antigen-related celladhesion molecule 10
Sperm binding andenhancement of spermmotility
[7] ⇓ ⇓ —
Lysozyme C, type M Primary bacteriolysis — ⇓ ⇓ —
Seminal vesicle secretory protein 5Serine proteinaseinhibitor
[35] ⇓ ⇓ —
Secreted seminal-vesicle Ly-6 protein 1Potential cellularadhesion and signaling
[21] ⇔ ⇓ —
Seminal vesicle secretory protein 7Sperm capacitationfactor
[20] ⇓ ⇓ —
Serine protease inhibitor kazal-likeprotein
Serine proteaseinhibitor/Spermdecapacitation factor
[22] ⇓ ⇓ —
Serine protease inhibitor Kazal-type 3Serine proteaseinhibitor/Spermdecapacitation factor
[9] ⇓ ⇓ —
Seminal vesicle antigenSperm decapacitationfactor
[36] ⇓ — —
Seminal vesicle secretory protein 4Anti-inflammatory andimmune-modulatingagent
[37] ⇔ — —
the errors in peak detection and drift of retention time, andto validate the selected peptides by the criteria of signal-to-noise ratio, charge state, and isotope pattern. The averageCV values were in the range of 10–17% for the top threemost abundant peptides, which demonstrated that accuratepeak detection and reproducibility could be acquired byusing the analytical program IDEAL-Q. However, errorswill occur in the analysis of low molecular weight proteinsby using the top three most abundant peptides for quan-titative analysis, as found in a previous study [38]. Theenzymatic reaction produces various peptides with a widerange of ionization efficiency during MS analysis. Smallerproteins will have fewer enzymatic peptides to choose fromthe highest ionization efficiency region to represent their
quantity. Therefore, underestimation is inevitable for thequantification of low molecular weight proteins. For therelative quantification of specific protein abundance changesunder various conditions, such kinds of quantification errormay not affect the comparison of protein ratios. However,to achieve the accurate absolute quantification, modifyingthe original results with parameters regarding molecular sizeneeds to be further pursued.
5. Conclusion
To obtain SVS samples from humans is quite difficult;therefore, SVS samples from a mouse model system were
International Journal of Proteomics 13
chosen as an alternative research target, although the volumeand composition of SVS differs significantly between variousspecies of mammals. Based on proteomic analysis, weidentified 79 proteins, including 16 seminal vesicle secretoryproteins, in the SVS proteome. Label-free quantitative anal-ysis was performed to estimate the quantity of the identifiedproteins. Moreover, most seminal vesicle secretory proteinswere subjected western blot assay to further validate theirexpression. Our data showed that both approaches were ingood agreement with each other. We confirmed that manySVS proteins had differential expression profiles during thetumorigenic process, especially SVS2, with a sequence similarto human semenogelin, which was dramatically decreasedduring the primary stage of seminal vesicle carcinoma. Theinformation obtained from the transgenic mice could behelpful in understanding tumor biology and could be furtherapplied as a reference to study related human diseases.
Acknowledgments
This work was supported by the Genomics Research Center.We express our thanks to Y. C. Chien for the cDNA microar-ray experiments and P. Y. Wang for the ICP MS experiments.Help on manuscript preparation and submission from Ku-Ju Cherry Lin is also acknowledged. W.-C. Chang and C.-K.Chou contributed equally to this work.
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