Oncotarget

Research Papers:

Sorcin induces gastric cancer cell migration and invasion contributing to STAT3 activation

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Oncotarget. 2017; 8:104258-104271. https://doi.org/10.18632/oncotarget.22208

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Huan Tuo, Feng Shu, Sha She, Min Yang, Xiao Qin Zou, Juan Huang, Huai Dong Hu, Peng Hu, Hong Ren, Shi Fang Peng, Yi Xuan Yang _

Abstract

Huan Tuo1,*, Feng Shu1,*, Sha She1, Min Yang1, Xiao Qin Zou1, Juan Huang1, Huai Dong Hu1,2, Peng Hu1,2,3, Hong Ren1,2,3, Shi Fang Peng4,5 and Yi Xuan Yang1,2,3

1Department of Infectious Diseases, The Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China

2Institute for Viral Hepatitis of Chongqing Medical University, Chongqing 400016, China

3Key Laboratory of Molecular Biology for Infectious Diseases, Ministry of Education, Chongqing Medical University, Chongqing 400016, China

4Department of Infectious Diseases, Xiangya Hospital, Central South University, Hunan 410008, China

5Department of Health Management Center, Xiangya Hospital, Central South University, Hunan 410008, China

*These authors have contributed equally to this work

Correspondence to:

Yi Xuan Yang, email: yxyangooo@sohu.com

Shi Fang Peng, email: sfp1988@csu.edu.cn

Keywords: gastric cancer (GC); sorcin; migration; invasion; iTRAQ

Received: July 08, 2017     Accepted: September 21, 2017     Published: October 31, 2017

ABSTRACT

Gastric cancer (GC) is a globally occurring malignancy that is characterized by a high mortality rate due to a high tendency to metastasize and poor prognoses. Sorcin, as known as SRI, a soluble resistance-related calcium-binding protein, plays a significant role in multidrug resistance. Sorcin is related to the migration and invasion of cancer cells. However, the mechanism remains unclear. Here, we used immunohistochemistry to confirm that the expression of sorcin in cancer tissues is higher than that in the adjacent normal tissues. The wound healing and transwell results indicate that sorcin can induce migration and invasion of GC cells. To explore the role of sorcin in GC metastasis, isobaric tags for relative and absolutely quantitation (iTRAQ) were used to examine cells with and without sorcin knockdown to identify the differentially expressed proteins (DEPs). The results were evaluated via RT-PCR and western blot to confirm the ITRAQ data. Inhibition of sorcin expression can down- regulate the expression of CTSZ, MMP2, MMP9 and p-STAT3 followed by suppression of tumor growth and metastasis. Together, we concluded that sorcin has a oncogenic activity via inducing tumor growth and metastasis, leading to development of therapeutic treatments for GC.


Sorcin induces gastric cancer cell migration and invasion contributing to STAT3 activation | Tuo | Oncotarget

INTRODUCTION

Gastric cancer is the second leading cause of cancer-associated death worldwide [1, 2]. Approximately 40% of all GC cases occur in China and these are often diagnosed in the advanced stages [3, 4]. The 5 year survival rate was 28% in 2014 [5]. Many factors result in the occurrence of GC, including genetic and epigenetic alterations. In spite of this, tumor suppression genes and growth factors have been discovered which affect the progression of GC [68], although the molecular mechanism of tumor metastasis is still poorly documented [9].

Sorcin, a soluble resistance-related calcium-binding protein, belongs to the small penta-EF-hand protein family [10, 11]. Sorcin expressed in many human tissues and at high levels in bones, heart, brain, kidneys, breasts and skin. Sorcin has been found to over expressed in many cancers such as leukemia and gastric, ovarian and breast cancers [10, 12, 13]. Although the function of sorcin in tumors is still unclear, a number of studies have shown that sorcin may associate with multidrug resistance (MDR) [12, 1416]. Using a gene co-expressed with P-glycoproteins in multidrug-resistant cells, sorcin was shown to be resistance-related [17]. On the other hand, sorcin is related to epithelial-to-mesenchymal (EMT) transition, which contributes to cancer metastases, as in breast cancer and colorectal cancer [14, 18].

Since sorcin plays a significant role in cancer metastasis and the mechanism for this action remains elusive, the present study utilized isobaric tags for lative and absolute quantitation (iTRAQ) to identify differentially expressed proteins (DEP) in AGS and MKN-28 gastric cancer cell lines in which sorcin had been silenced via Small interfering RNA (siRNA). After verification by PT-PCR and western blot, the DEPs were further investigated in order to identify a pathway to explain the sorcin-modulated metastatic mechanism. Our data demonstrated that sorcin can induce tumor growth and metastasis via STAT3 signaling, leading to development of therapeutic treatments for GC.

RESULTS

Differential expression of sorcin in tissues

IHC was utilized to verify whether the expression of sorcin differed between tumor tissues and adjacent normal tissues. The results showed that sorcin expression was higher in tumor tissues than that in normal adjacent tissues (Figure 1A). The IHC value of sorcin in tumor tissues was significantly higher than that in normal tissues (Figure 1B). Moreover, Pearson correlation analysis showed that IHC scoring was correlated with the Grade and Stage of tumor (Table 1).

Sorcin levels were higher in GC tissue than in adjacent normal tissue.

Figure 1: Sorcin levels were higher in GC tissue than in adjacent normal tissue. (A) Representative images of the immmunohistochemical analysis of Sorcin in GC tissue and matched GC adjacent normal tissue. (B) IHC score values of Sorcin are significantly higher in GC tissue compared to matched GC adjacent normal tissue. * P<0.001.

Table 1: Pearson correlation coefficients between IHC scoring, tumor grade, and tumor stage

1

2

3

1 IHC scoring

1

2 Grade

0.817**

1

3 Stage

0.869**

0.92**

1

* P < 0.05 ** P < 0.01 *** P < 0.001.

Effect of sorcin knockdown on migration and invasion in AGS and MKN28 cell lines

In order to identify the association of sorcin with GC migration and invasion, the control siRNA and SRI siRNA (SRI siRNA1 and SRI siRNA3) were transfected into the AGS and MKN28 cell lines. Cells transfected with the SRI siRNA showed significant suppression of sorcin expression (Figure 2A). Pursuant with these results, the invasion and migration capabilities of AGS and MKN28 cells were significantly decreased after transfection with SRI siRNA (Figure 2B and 2C).

Figure 2:

Figure 2: (A) Western blot analysis showed that three different siRNAs targeting sorcin specific siRNAs significantly reduced SRI protein levels in cell lysates, compared to control siRNA and lipo2000 and band intensity analysis. (B) Migration ability of cells in wound healing assays after sorcin knockdown. * P<0.05., Migration ability of AGS and MKN28 after silencing SRI. (C) Invasion ability of AGS and MKN28 after silencing SRI.

Analysis of iTRAQ data of differentially expressed proteins

The iTRAQ technology was used to explore the mechanism by which sorcin affects cell migration and invasion. The iTRAQ assays were performed on proteins isolated from AGS and MKN28 cells sorcin knockdown vs control cells without sorcin silencing. Specimens were labeled in duplicate to improve the confidence and enhance the range of protein identification. Table 2 shows the flow chart of the iTRAQ proteomics approach. The ratios of 114:113, 116:115, 118:117 and 121:119 identified the differential protein expression. An additional 1.3-fold change cutoff for all iTRAQ ratios (ratio <0.77 or >1.3) was used for classifying proteins as being up- or down-regulated.

Table 2: The iTRAQ-based MS workflow

Table 2: The iTRAQ-based MS workflow

A total of 65 proteins were identified in AGS cells and 57 proteins in MKN28 cells. According to the conventions, 22 proteins were up-regulated and 43 proteins were down-regulated in the AGS line. In the MKN-28 line, 25 proteins were up-regulated and 32 were down-regulated (Table 3). To identify the cellular and molecular characteristics of these proteins, the differentially expressed proteins were classified using the PANTHER (www.pantherdb.org/) Classification System (Figure 3A and 3B). Using STRING analysis, sorcin was identified as the most important node in the DEP network because it had the greatest connectivity (Figure 3C).

Table 3: The proteins observed to be differentially expressed by iTRAQ analysis in supernatant of AGS and MKN28: SRI knockdown vs control

AGS

N

Accession

Name

114:113

PVal 114:113

116:115

PVal 116:115

1

sp|Q9NPD8|UBE2T_HUMAN

Ubiquitin-conjugating enzyme E2 T

1.744066

0.026624629

1.325548983

0.044529971

2

tr|H6VRG1|H6VRG1_HUMAN

Keratin 1

1.523257017

0.001

1.7892345

0.02378564

3

sp|Q14019|COTL1_HUMAN

Coactosin-like protein

1.486366034

0.003839253

1.9871653

0.00457829

4

sp|P02787|TRFE_HUMAN

Serotransferrin

1.47558701

0.001567603

1.79888654

0.00167298

5

sp|P35527|K1C9_HUMAN

Keratin, type I cytoskeletal 9

1.456223011

0.000636358

1.89176432

0.000398717

6

tr|D3DPK5|D3DPK5_HUMAN

SH3 domain binding glutamic protein like 3

1.416821957

0.01751755

1.56279981

0.0192865

7

sp|P60174|TPIS_HUMAN

Triosephosphate isomerase

1.394827962

0.000135839

1.52817629

0.000027817

8

sp|P62195|PRS8_HUMAN

26S protease regulatory subunit 8

1.392753959

0.0281204

1.79875428

0.0367186

9

sp|Q5JS37|NHLC3_HUMAN

NHL repeat-containing protein 3

1.388023019

0.045731839

1.591827113

0.0378192

10

tr|Q53FB6|Q53FB6_HUMAN

Mitochondrial aldehyde dehydrogenase 2 variant

1.377797961

0.000768409

1.398271918

0.00036182

11

sp|P04075|ALDOA_HUMAN

Fructose-bisphosphate aldolase A

1.372123957

0.00147034

1.679281179

0.0017891

12

sp|Q5T4S7|UBR4_HUMAN

E3 ubiquitin-protein ligase UBR4

1.350811958

0.03672374

1.378291179

0.028917123

13

tr|Q6FGB3|Q6FGB3_HUMAN

PCBD protein (Fragment)

1.343956947

0.01979435

1.562919023

0.018273689

14

sp|Q9Y3C6|PPIL1_HUMAN

Peptidyl-prolyl cis-trans isomerase-like 1

1.343673944

0.01674393

1.782993739

0.017289381

15

tr|Q5U000|Q5U000_HUMAN

Cathepsin Z

0.749955177

0.035744209

0.65124789

0.02134678

16

sp|P02647|APOA1_HUMAN

Apolipoprotein A-I

0.746485889

0.01251418

0.635172839

0.013671898

17

tr|B4DVA7|B4DVA7_HUMAN

Beta-hexosaminidase

0.725379229

0.002918514

0.726019284

0.002189322

18

sp|Q0VDF9|HSP7E_HUMAN

Heat shock 70 kDa protein 14

0.725047827

0.037717941

0.6218956

0.031275433

19

sp|P18065|IBP2_HUMAN

Insulin-like growth factor-binding protein 2

0.718883276

0.007395078

0.71452389

0.001789562

20

tr|G3V1C3|G3V1C3_HUMAN

Apoptosis inhibitor 5

0.709504426

0.000174285

0.7219271

0.000342613

21

tr|Q6IBU0|Q6IBU0_HUMAN

EIF5 protein

0.707335413

0.02353386

0.682615293

0.03782919

22

sp|Q14393|GAS6_HUMAN

Growth arrest-specific protein 6

0.705515504

0.037340712

0.67281927

0.000128913

23

sp|Q96JB5|CK5P3_HUMAN

CDK5 regulatory subunit-associated protein 3

0.704363883

0.04963446

0.672918274

0.038291833

24

sp|P31949|S10AB_HUMAN

Protein S100-A11

0.67395997

0.033712041

0.631987527

0.02567891

25

sp|P23396|RS3_HUMAN

40S ribosomal protein S3

0.662013173

0.000471662

0.452719272

0.000261839

26

sp|Q9NZL4|HPBP1_HUMAN

Hsp70-binding protein 1

0.600465178

0.000367309

0.52918762

0.000271836

27

sp|P01037|CYTN_HUMAN

Cystatin-SN

0.576057613

0.001708777

0.342516829

0.001728391

28

sp|Q9H173|SIL1_HUMAN

Nucleotide exchange factor SIL1

0.574737787

0.0174674

0.328910722

0.001729372

29

sp|P21926|CD9_HUMAN

CD9 antigen

0.516185224

0.020510839

0.035617839

0.025618923

30

sp|P04080|CYTB_HUMAN

Cystatin-B

0.473518968

0.003953285

0.49178256

0.000267819

Continued MKN28

N

Accession

Name

118:117

PVal 118:117

121:119

PVal 121:119

1

sp|P02787|TRFE_HUMAN

Serotransferrin

1.794528008

0.000295122

2.189219183

0.00028131

2

sp|Q9UNN8|EPCR_HUMAN

Endothelial protein C receptor

1.662192941

0.025397651

1.927371831

0.023618391

3

sp|Q14558|KPRA_HUMAN

Phosphoribosyl pyrophosphate synthase-associated protein 1

1.648730993

0.02934215

1.789276184

0.037826173

4

sp|Q9HAV7|GRPE1_HUMAN

GrpE protein homolog 1, mitochondrial

1.476071954

0.02040467

1.789261312

0.018927193

5

sp|P28070|PSB4_HUMAN

Proteasome subunit beta type-4

1.468814969

0.003261048

1.567289184

0.004527192

6

sp|P28070|PSB4_HUMAN

Proteasome subunit beta type-4

1.468814969

0.003261048

1.898976558

0.004261839

7

sp|O75153|CLU_HUMAN

Clustered mitochondria protein homolog

1.453933954

0.00138173

1.356183992

0.00017282

8

tr|Q6FHK7|Q6FHK7_HUMAN

PSME3 protein

1.446910977

0.007649424

1.888927368

0.001839104

9

sp|P46926|GNPI1_HUMAN

Glucosamine-6-phosphate isomerase 1

1.442389965

0.0117149

1.666618829

0.000271893

10

tr|I3L504|I3L504_HUMAN

Eukaryotic translation initiation factor 5A-1

1.413321972

0.001034902

1.789379381

0.002781939

11

tr|Q32Q12|Q32Q12_HUMAN

Nucleoside diphosphate kinase

1.385175943

0.02030622

1.89283901

0.018293134

12

tr|Q59FD4|Q59FD4_HUMAN

Hexokinase 1 isoform HKI variant

1.377347946

0.002164863

1.478290002

0.001830019

13

tr|Q6IPT9|Q6IPT9_HUMAN

Elongation factor 1-alpha

1.374544978

0.001090406

1.7829381

0.001782018

14

tr|B7Z6Q5|B7Z6Q5_HUMAN

Beta-galactosidase

0.713971794

0.01131486

0.34152719

0.027816291

15

sp|Q96AY3|FKB10_HUMAN

Peptidyl-prolyl cis-trans isomerase FKBP10

0.642570615

0.036040939

0.582981739

0.028917362

16

sp|Q06828|FMOD_HUMAN

Fibromodulin

0.640408993

0.00128549

0.527819371

0.003281903

17

sp|O00339|MATN2_HUMAN

Matrilin-2

0.633856475

0.003664825

0.608972562

0.00278183

18

sp|P36955|PEDF_HUMAN

Pigment epithelium-derived factor

0.62459141

0.032367039

0.592817293

0.034527189

19

sp|Q92930|RAB8B_HUMAN

Ras-related protein Rab-8B

0.623568416

0.017293719

0.672910381

0.019287301

20

sp|P16035|TIMP2_HUMAN

Metalloproteinase inhibitor 2

0.617994773

0.00642046

0.72341819

0.007189201

21

sp|P05121|PAI1_HUMAN

Plasminogen activator inhibitor 1

0.61286068

0.046489481

0.626152901

0.056289129

22

tr|D3DQH8|D3DQH8_HUMAN

SPARC

0.597940624

0.000163077

0.462791023

0.000179038

23

tr|Q1L857|Q1L857_HUMAN

Ceruloplasmin

0.59214592

0.003437676

0.415272801

0.002619939

24

tr|J3KPA4|J3KPA4_HUMAN

Vascular endothelial growth factor A

0.587758303

0.03545526

0.362891004

0.027810381

25

tr|Q5U000|Q5U000_HUMAN

Cathepsin Z O

0.578644204

0.026196879

0.26783619

0.002819381

26

sp|P22692|IBP4_HUMAN

Insulin-like growth factor-binding protein 4

0.57805872

0.01133533

0.703739491

0.022367192

27

tr|E7EV71|E7EV71_HUMAN

Latent-transforming growth factor beta-binding protein 1

0.531398475

0.006499027

0.462739103

0.006728913

28

sp|P13645|K1C10_HUMAN

Keratin, type I cytoskeletal 10

0.512651515

0.01043807

0.537280182

0.003781928

29

tr|C9J0K6|C9J0K6_HUMAN

Sorcin

0.43533988

0.048046826

0.50781692

0.03681903

30

sp|Q9NZL4|HPBP1_HUMAN

Hsp70-binding protein 1

0.314401984

0.045458108

0.452719301

0.035279103

PANTHER analysis of proteins differentially expressed in GC cells.

Figure 3: PANTHER analysis of proteins differentially expressed in GC cells. (A) AGS Proteins were categorized by protein class, biological process, and molecular function. (B) MKN28 Proteins were categorized by protein class, biological process, and molecular function. (C) STRING analysis.

Validation of iTRAQ identified candidate proteins

PT-PCR and western blot were used to confirm the changes in the selected proteins. mRNA expression of UBE2T, CTSZ, HSPBP1, S100A11, CSTB, MMP1 and RAC1 were in line with the iTRAQ resultsin AGS cells. In the MKN-28 cell line, mRNA expression of UBE2T, CTSZ, HSPBP1, KRT1, TIMP2, VEGFA and IBP4 were similar to the iTRAQ results. After silencing of sorcin, the mRNA expression of UBE2T was significantly up-regulated compared with 18s, while the mRNA expression of the other identified proteins was down-regulated (Figure 4). Western blot analysis was utilized to quantify the expression levels of the selected proteins (Figure 5A and 5B). The results of CTSZ and HSPBP1 are consistent to the iTRAQ data.

Validation of differentially expressed proteins in mRNA level.

Figure 4: Validation of differentially expressed proteins in mRNA level. RT-PCR detected the relative mRNA expression levels of some DEPs in the sorcin knockdown group compared with untreated (no knockdown) group.

Validation of differentially expressed proteins in protein level.

Figure 5: Validation of differentially expressed proteins in protein level. Western blot analysis of CTSZ, HSPBP1, STAT3, p-STAT3, MMP9 and MMP2. (A) Protein levels from AGS cells transfected with SRI-specific or control siRNAs were analyzed by western blot analysis. Band intensity analysis shows significant reduction of p-STAT3, MMP9, and MMP2 after sorcin silencing (* P<0.05). (B) Protein levels from MKN28 cells transfected with SRI-specific or control siRNAs were analyzed by western blot analysis. Band intensity analysis shows significant reduction of p-STAT3, MMP9, and MMP2 after sorcin silencing (* P<0.05).

Knockdown of sorcin suppresses p-STAT3, MMP9 and MMP2 protein expression. Many studies have reported that the overexpression of p-STAT3, MMP2 and MMP9 promotes metastasis. We detected the expression of these proteins in both silenced and untreated cells. The results demonstrated that the down regulation of sorcin inhibits p-STAT3, MMP2, MMP9 expression at the protein level in AGS and MKN28 cells (p<0.05) (Figure 5A and 5B).

Sorcin plays a role in proliferation and cell cycle

AGS and MKN28 cells were transfected with sorcin siRNA sequences. According to the western blot analysis, efficient silencing of sorcin expression was demonstrated by the sorcin-specific siRNA sequences. We also used the MTT assay to examine the proliferation of sorcin-silenced vs control AGS cells and MKN-28 cells. The proliferation of AGS and MKN28 cells was depressed compared to the control cells. We examined the change of the cell cycle and the results showed a difference in the cycles of sorcin-silenced cells compared with untreated cells (Figure 6A and 6B).

GC proliferation after knockdown of SRI.

Figure 6: GC proliferation after knockdown of SRI. (A) Proliferation was significant inhibit in cell transfected with SRI- specific siRNA in AGS (* P<0.05). (B) Proliferation was significant inhibit in cell transfected with SRI- specific siRNA in MKN28 (* P<0.05).

DISCUSSION

Gastric cancer has high mortality and mobility rate and is the third leading cause of cancer deaths [19, 20]. Surgery and chemotherapy are the prime treatment for curing the malignancy [8, 20]. According to official statistics, about 50% of GC cases suffer metastases at diagnosis [21]. The 5-year survival rate is greatly decreased in patients with metastases compared with patients diagnosed early in the progression [20]. Therefore, it is urgent to explore the molecular mechanisms underlying the progression of GC, which could identify biomarkers or treatments for GC.

Sorcin is over expressed in many malignant tumors. In the present study, the iTRAQ method was utilized to compare protein expression in GC tumor tissue and compare them with expression from adjacent tissues. As previously reported, sorcin plays a vital role in invasion and migration of tumors, also has an influence on tumor proliferation.

Some of DEPs identified by the iTRAQ results were attributed to cellular processes. CTSZ, HspBp1, S100A11, CTSB, UBET2E, KRT1, MMP1, Rac1 and VEGFA were selected as candidate proteins, and PT-PCR and western blot analyses were used to validate the iTRAQ results. To identify the major changes after suppressing sorcin, we classified these proteins into different categories according to their biological process and molecular functions.

CTSZ is considered a lysosomal proteolytic enzyme and is a member of the peptide C1 family associated with many biological processes, including immune response, cell adhesion and proliferation [22]. CTSZ is over expressed in many cancers [23, 24]. CTSZ belongs to the cathepsin family of lysosomal hydrolases that contribute to the turnover of intra cellular proteins and the degradation of extracellular matrix [25]. Interestingly, several of the tumor-promoting functions of CTSZ were not dependent on its described catalytic activity [26]. Several proteases have been shown to mediate adhesion and migration of cells through interaction with integrins [27]. CTSZ contains an Arg-Gly-Asp (RGD) motif allows it to interact with integrins [26, 28]. RGD is a protein sequence vital to the binding of proteins to cell surface [29], which mediates cell adhesive properties, and this region interacts with the integrin αvb3 [30]. This interaction influences cellular migration as well as cell adhesion [30, 31]. Many studies have shown that CTSZ is related with the EMT, which could promote invasion and migration in tumor [32]. The extracellular matrix (EMT) plays an important role in modulating cell behavior, including cell survival and metastasis [33].

MMPs, a group of zinc-dependent endopeptidases, are involved in degradation of the ECM. MMP2 and MMP9 contribute to tumor metastasis [3436]. Studies have reported signal transducer and activator of transcription 3 (STAT3) is active in many cancers [3741]. In the present study, we found that silencing sorcin was related to metastatic activity in tumor cells. Therefore, we suspect that sorcin may be associated with the STAT3 pathway. We found that p-STAT3, MMP2, MMP9 were suppressed after silencing sorcin in GC cell lines. Taken together, these findings suggest that sorcin contribute to STAT3 activation.

In conclusion, our findings indicated that silencing sorcin affects the development of GC cells, by reducing the capacity for invasion, migration and proliferation via CTSZ and the STAT3 pathway. Therefore, suppressing the expression of the sorcin may lead to therapeutic treatments for GC.

MATERIALS AND METHODS

Cell lines

The two human gastric cancer lines AGS and MKN28 were obtained from ATCC, and grown in high glucose DMEM with 10% fetal bovine serum (FBS Corning), augmented with 1% penicillin and streptomycin. Cells were maintained in an incubator in an atmosphere of 5% carbon dioxide at 37°C.

Reagents

The eight-plex iTRAQ kits were acquired from Applied Biosystems (Foster City, CA, USA). Bio-Rad (Hercules, CA, USA) provided all electrophoresis reagents. CytoSelect™ 24-well Cell Migration and Invasion assay kits (8 μm, colorimetric format) were purchased from Cell Biolabs (San Diego, CA, USA). Opti-MEM was acquired from Gibco (San Diego, CA, USA). SRI specific siRNA (HSS110179, HSS110180, HS110181) and Lipofectamine 2000 were purchased from Invitrogen (Carlsbad, CA, USA). Sorcin, CTSZ, Hspbp1 and CSTB antibody were obtained from OriGene (Rockville, MD, USA). The S100A11 antibody used in this study was purchased from Abcam (Cambridge, MA, USA).

Sample collection and ITRAQ labeling

Cells were grown to 80% confluence, washed two times with PBS and incubated in DMEM for 24h. The supernatant containing secreted proteins was collected and filtered using a 0.22 mm filter (Millipore, Bedford, MA, USA) and concentrated by centrifugation with an Amican centrifugal filter (Billerica, MA, USA). The protein concentration was measured using a 2D Quant kit. For each sample, 100 ug of protein was precipitated overnight, re-dissolved in lysis buffer, and cysteine-blocked in accordance with the manufacturer’s instructions. Th protein samples were then labeled with the iTRAQ tags. The secretory protein samples from AGS without sorcin knockdown were labeled with tag 113 and tag 115. The secretory proteins from AGS cells with sorcin-silencing were labeled with tag 114 and tag 116. The secretory proteins from MKN-28 cells without sorcin knockdown were labeled with tags 117 and 119 and the secretory proteins from sorcin-silenced MKN-28 cells were labeled with tags 118 and 121.

Fractionation of pepitides

The pooled iTRAQ labeled samples were dissolved in 300uL 1% Pharmalyte (Amersham Biosciences) and 8M urea and evenly coated on pre-hydrated IPG strips (pH 3-8). The peptides were isolectrically focused successively for 1h at 500v, 1h at 1000v, 1h at 3000v, and 8.5h at 8000v to give a total of 68kv in an IPGphor system (Amersham Biosciences). The peptides were extracted using an acetonitrile (ACN) and formic acid solution. Fractions were lyophilized in a vacuum concentrator and purified on an SPE C18 column. The purified fractions were re-lyophilized and stored in -20°C for use in mass spectrometric analysis.

Mass spectrometry

The purified, labeled peptides were reconstituted in Buffer A (2% ACN; 0.1% formic acid) and injected into the nano LC ESI MS/MS system. Mass spectrometry was performed using a Qstar Elite mass spectrometer coupled to a Dionex Ultimate 3000 liquid chromatography system. A gradient series for each analysis was loaded on C-18 pepMap column at a flow rate of 0.3ul/min. The mass spectrometer was set to perform data acquisition in the positive ion mode, with a selected mass range of 300-1800 m/z. The two most abundantly charged ions above 20 counts were selected for MS/MS. Dynamic exclusion criteria was set to 30s with a ± 50 Da mass tolerance.

Protein Pilot software (version 2.0 applied biosystems, MDS Sciex) was used for the identification and qualification of proteins, with the search being carried out against the International Protein Index (IPI) human database (version 3.77).

Immunohistochemistry and tissue Microarray IHC assessment of sorcin was performed using a commercial tissue microarray (Biomax, Rockville, MD, USA) containing 40 GC samples and 40 matched GC adjacent normal tissue. Immunohistochemistry was performed on the tissue microarrays as previously described [42]. The tissue samples were dewaxed with xylene and rehydrated using an alcohol gradient. The samples were washed three times in double distilled H2O (5 min per wash) and subjected to heat-induced antigen retrieval in a 0.1 M citrate solution for 5 minutes. Endogenous peroxidase activity in the samples was quenched by incubation in 3% H2O2. The sections were blocked with BSA for 0.5h and incubated with anti-sorcin antibody overnight at 4°C. Detection was performed on an Envision/horseradish peroxidase system (DakoCytomation, Glostrup, Denmark) and all slides were counterstained with Gill hematoxylin for examination. Protein expression was evaluated by recording staining intensity (scale 0-3) and the percentage of positive cells (0-100%). Multiplying these scores yielded a value of 0-300. All data analyses were performed with SPSS v.16.0 software (SPSS, Chicago, IL, USA) using the student the t-test with 95% confidence levels.

Sorcin siRNA transfection, wound healing, cell migration and invasion assays

AGS and MKN28 cells were transfected with 50nm of sorcin specific Stealth Selected RNAi siRNA (HSS) or a negative control siRNA using Lipofactamin 2000, according to the manufacturers protocol (Life Technologies, Carlsbad, CA, USA). The cells were cultured in serum-free, high-glucose DMEM with free serum for 2 days in 6-well plates. When the cells became confluent, a scratch was made in the monolayer with a sterile P200 pipette tip. The cells were washed twice with PBS to remove debris and the wound channel was photographed under a phase-contrast microscope at 0h and 24h for comparison. Adobe Photoshop 7.0 was used to measure the relative width of the wound, and cell migration was determined by the ability of the cells to close the scratch area. Migration and invasion assays was performed using Cell Invasion Assay kits (Cell Biolabs, Inc., Beijing China). AGS and MKN28 cells were transfected with negative siRNA or sorcin-targeting siRNA and cultured in free serum media. Approximately 3*105/300ul cells were seeded into the upper chambers of the Transwell chambers, and 500ul media was loaded into the lower chamber. The migration assay cells were cultured for 12h, while the invasion assay cells were cultured for 24h. The non-invasive cells were gently removed with cotton and the invading cells were stained, fixed, extracted and quantified with cyQuant GR fluorescent dye at 560 nm. The knockdown of sorcin protein expression was confirmed by western blot.

RNA extraction and quantitative PT-RCR

Total RNA was extracted using TRIZOL Regent (Gibico-BRL, Gaithersburg, MD, USA), according to the manufacturer’s protocol. First-strand cDNA was synthesized from 2ug of total RNA using a Reverse Transcription kit (Thermo Fisher Scientific, Waltham, MA, USA). A Fast PCR kit (KAPA SYBR, MA, USA) was used to perform PT-PCR using primers for UBE2T (Hs00311058_CE), CTSZ (Hs00216567_CE), HSPBP1 (Hs00358592_CE), S100A11 (Hs00273948_CE), CSTB (Hs00220803_CE), MMP1 (Hs00111380_CE), RAC1 (Hs00368991_CE), KRT1 (Hs00444496_CE), TIMP2 (Hs00171270_CE), VEGFA (Hs00275352_CE) and IBP4 (Hs00398644_CE) (Table 4). Quantification of gene expression was calculated using the 2-ΔΔCTmethod. RT-PCR analyses were conducted in triplicate.

Table 4: The sequence of genes specific primers as followed

Gene

Primer sequence

Gene

Primer sequence

UBE2T

F 5-TGCGAGCTCGTAGAAATATT-3

CTSZ

F 5-CGGCCTCATGAGTACCTGTC-3

R 5-TTGAGGGATGGTCTCCAAGC-3

R 5-GCAGTATTGGGGGATGTGCT-3

HSPBP1

F 5-CCTCTTCGCCATCTCCTGTC-3

S100A11

F 5-CTATGGCTTGCCATGACTCCT-3

R 5-TCAACACAGAGAAGCCGTCC-3

R 5-TACAAGAAAGTTGGGCAGGTCC-3

CSTB

F 5-TCCCTGTGTTTAAGGCCGTG-3

MMP1

F 5-GCGAGCCCTCCTTTATCTCC-3

R 5-ACACTCGCAGGTGTACGAAG-3

R 5-AGGGTCTAAAACGCCAGTCG-3

RAC1

F 5-AGGCAAACGCCCATTGGATA-3

KRT1

F 5-GGTGTCAAGTCCTCTGGTGG-3

R 5-ACTGCGGTCACTTACCTTGG-3

R 5-ACAAGAAAGTTGGGTATCTGGT-3

TIMP2

F 5-TCAAGAGAAGTGACGGCTCC-3

VEGFA

F 5-TGCGGATCAAACCTCACCAA-3

R 5-ACAAGAAAGTTGGGTATGGGTCC-3

R 5-CAAGAAAGTATGGGCACCGC-3

IBP4

F 5-CAAGTGCTGGTGTGTGGACC-3

R 5-AAGAAAGTTGGGCACTCTCGAA-3

Western blot analysis

Cells were lysed with lysis buffer and the concentration of the proteins was determined by a 2D Quantification kit (GE Healthcare). The proteins were separated by 12% SDS-PAGE and transfected to PVDF membranes. The membranes were blocked in BSA for 1h at room temperature, and incubated with the primary antibody (1:500 dilution) overnight at 4°C. The membranes were washed three times and incubated with HRP-conjugated secondary antibody (1:10000). The membranes were washed thrice with TBST and visualized with the ChemiDoc MP imaging system (BioRad Laboratories, Hercules, CA, USA).

Cell proliferation assay

AGS and MKN28 cells were seeded in 96-well plates at a density of 1.5x103 cells/well. Cells were cultured in DMEM with 10% FBS and transfected with SRI siRNA or control siRNA for 0, 24, 48, 72 and 96 h at 37°C. The MTT assay was performed as follows: cells were incubated with 20 μl MTT (Sigma-Aldrich, St Louis, USA) at 37°C for 4 h. The MTT substrate was then dissolved in 200 μl of DMSO (Sigma-Aldrich, St Louis, USA) for 5 min. The absorbance was measured at 570 nm.

Statistical analysis

All experiments were performed in triplicate and the data are expresses as the mean ± standard deviation. The Student’s t-test was used to analysis the variables between two groups. Differences were considered significant when p<0.05.

Author contributions

Huan Tuo and Feng Shu: performed all experiments. Sha She, Min Yang, Xiao Qin Zou, Juan Huang performed some experiments. Hong Ren, Huai Dong Hu and Peng Hu gave some critical suggestions to this project. Huan Tuo and Feng Shu analyzed data and wrote the manuscript. Shi Fang Peng Yi Huan Yang did conception and design and final approval of manuscript. Yi Xuan Yang made financial support, and final approval of manuscript.

CONFLICTS OF INTEREST

The authors declare that no conflicts of interest exist.

FUNDING

This study was supported by the National Natural Science Foundation of China (81171560, 30930082, 81171561, 30972584 and 81372399) and the National Science and Technology Major Project of China (2008ZX10002-006, 2012ZX1002007001, 2011ZX09302005, 2012ZX09303001001 and 2012ZX10002003).

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