Sage Journals: Discover world-class research

Abstract

Oral submucous fibrosis (OSF) is a chronic insidious disease which predisposes to oral cancer. Understanding the molecular markers for OSF is critical for diagnosis and treatment of oral cancer. In this study, the proteins expression profile of OSF tissues was compared to normal mucous tissues by 2 dimensional electrophoresis (2-DE). The 2-DE images were analyzed through cut, spot detection and match analysis using mass spectrometry (MS). Differentially expressed genes were identified as candidates. RT-PCR, Western Blot and immunohistochemistry were performed to validate the difference in expression of the candidates between OSF and normal mucous tissues. The shRNA targeted to the candidates were then transfected by Lipofectamine2000 to the 3T3 cells to study gene function. Cell proliferation and apoptosis were measured by MTT, clonogenic formation, PI and TUNEL staining. From the proteomic analysis, 94 of the 182 selected spots with differential expression were identified by MS analysis and Cyclophilin A (CYPA) was determined to be the OSF-associated protein candidate. The significant differences in expression between OSF and normal tissues were verified and confirmed by RT-PCR, Western blot and Immunohistochemical analysis. Inhibition of CYPA expression by RNA interference suggested its potential activities involved in cell proliferation and apoptosis process. In conclusion, these results indicated a novel molecular mechanism of OSF pathogenesis and demonstrated CYPA as a potential biomarker and gene intervention targets of OSF. These data may help the development for therapeutics of oral cancer.

Keywords

Oral submucous fibrosis proteomics 2-D electrophoresis mass spectrum Cyclophilin A small hairpin RNA

1. Introduction

Oral submucous fibrosis (OSF) is a chronic pathological condition which is predisposes to oral cancer [1]. Histologically, OSF is characterized by epithelial atrophy and progressive accumulation of collagen fibers in the lamina propria and submucous of the oral mucosa with a progressive loss of vascularity [2]. As the condition continues, the jaws eventually become so rigid that the patients may not be able to open their mouth [3]. The condition is linked to areca nut chewing, a habit similar to tobacco chewing, which is practiced predominantly in Southeast Asia and India [4]. Regarded as a precancerous condition by WHO, OSF has become one of the major oral premalignant lesions. Despite many years’ research, the pathogenesis for the malignant transformation of OSF, especially from a molecular perspective, is still not very clear. Meanwhile, molecular markers that specifically marks OSF condition and its transitioning process to oral cancer is still missing in clinical practice [5]. It’s believed that the main problem is traditional single gene or multiple genes studies were not able to uncover the overall changes of gene expression in the OSF conditions [6].

Since molecular marker plays such a crucial role in diagnosis, monitoring, and treatment of OSF, screening the gene expression profile by high through-put technology to identify specific markers for OSF tissue sounds like an attractive strategy. Proteomics, as a study of the complete protein complement of the cell, is a promising approach in the identification of protein biomarkers with changed levels which may be useful as invaluable new targets for therapeutic intervention and markers for early detection [7]. In the past decade, proteomic approach has been successfully used to study many types of cancer, such as brain, lung, liver, stomach and colon cancers [8, 9, 10]. It was considered to be one of the best technology to identify important marker proteins for the elucidation of the molecular mechanisms of cancerogenous pathogenesis [11]. Two-dimensional gel electrophoresis (2-DE), mass spectrometry (MS) and bioinformatics are three major techniques used in proteomic studies. With combination of these techniques, novel biomarkers have been reported on oral cancers in recent years [12, 13]. However, as far as we understand, very few proteomic studies on OSF have been reported.

In this study, total proteins in OSF and normal mucous tissues were analyzed by 2-DE and the differentially expressed proteins were identified with MS. Cyclophilin A was selected as a potential marker for OSF pathogenesis. The expression of Cyclophinli A was validated by RT-PCR, Western Blot. Its activity in cell proliferation and apoptosis was valued with RNA interference. Our data could be used for diagnosis and treatment OSF related oral cancer.

2. Materials and methods

2.1 Patient samples

Twenty five samples of OSF tissue were obtained from Department of stomotolgy of Xiangya Hospital, Changsha, China, between August 2006 and December 2007. Normal mucous tissues were collected at the West China School of Stomatology, Sichuan University in the same time period. Fresh tissue were separated in two halves. One half of the sample was snap frozen and stored in $-$ 80 ${}^{\circ}$ C freezer for total protein isolation. The other half was fixed with 10% formalin followed by paraffin embedding for histological examination. Twenty five samples of normal mucous tissue were collected from healthy volunteers. The Institutional Ethics Committee of Sichuan University approved this study and informed consents were obtained from all patients or volunteers prior to sample collection.

2.2 Two-dimensional electrophoresis and image analysis

Tissue were minced in liquid nitrogen and lysed in lysis buffer (7 M urea, 2 M thiourea, 4% CHAPS, 2 mM TBP, 2 mM PMSF, 1 mg/ml DNase I and 0.2 mg/ml RNase A) [14]. After centrifugation followed by vortex and incubation, the supernatant was precipitated with cold actone/trichloroacetic acid. The pellet was resolved in rehydration buffer (7 M urea, 2 M thiourea, 4% CHAPS, 2 mM TBP, 0.2% carrier ampholytes). Total protein concentration was determined with Pierce ${}^{\text{TM}}$ BCA Protein Assay Kit (Thermo Scientific, Rockford, IL). Then, 200 $\mu$ g of protein were loaded into one IPG strip for analysis. Isoelectric focusing (IEF) was performed using Ready Strip TM IPG strips (17 cm, PH 3–10 NL, Bio-Rad, Hercules, CA) on PROTEAN IEF system (Bio-Rad, Hercules, CA) until a total of 80,000 Vh reached, after passive rehydration for 16 h. The focused strips were then equilibrated twice for reduction and alkylation, and transferred onto 12% SDS-polyacrylamide gels using PROTEAN II xi Cell system (Bio-Rad, Hercules, CA). The protein spots in gels were visualized by G250 Coomassie brilliant blue staining. Image analysis was performed using a PDQuest software 7.1 (Bio-Rad, Hercules, CA). Spot intensity was quantified automatically by calculation of spot volume after normalization of the image by taking the ratio of intensity of one spot to the total spots, and expressed as a fractional intensity. Those spots with 2.5-fold or more changes in expression and frequencies higher than 25% were selected for identification.

2.3 In-gel digestion

Spots of interest were excised and in-gel digested according to the manufacturer’s instruction (Promega, Madison, WI) with some modifications. Briefly, the gel spots were destained twice with 0.2 ml of 100 mM NH ${}_{4}$ HCO ${}_{3}$ /50% acetonitrile (ACN) for 45 min at 37 ${{}^{\circ}}$ C, and dehydrated in 100% ACN for 5 min. Then the spots were incubated with 10 $\mu$ l of 10 $\mu$ g/ml Trypsin Gold (Promega, Madison, WI) at room temperature for 1 hr and then at 37 ${{}^{\circ}}$ C overnight with 20 $\mu$ l digestion buffer (40 mM NH4HCO3/10% ACN) covered. The liquid was then removed and saved, and tryptic peptides were extracted twice with 50 $\mu$ l of 50% ACN/5% trifluoroacetic acid (TFA) by sonication for 15 min. Then all extracts were pooled and dried in Speed Vac at room temperature. Peptides were desalted using C18 ZipTip (Millipore, Bedford, MA) and reconstituted in 5 $\mu$ l 70% ACN/0.1% TFA.

2.4 Mass spectrometry analysis

1.5 $\mu$ l of the peptide elute was mixed with $\alpha$ -cyano-4-hydroxycinnamic acid matrix in identical volume on the stainless MALDI target until air-dried. MALDI-Q-TOF (matrix-assisted laser desorption/ionization quadrupole time-of-flight) MS/MS was performed on a Waters Micromass Q-Tof Premier mass spectrometer (Waters, Manchester, UK). The automatic scan rate was 1 second with an inter-scan delay of 0.02 second. Spectra were accumulated until a satisfactory signal/noise ratio had been obtained from a range of 900 mz to 3500 mz. After MS acquisition, 10 ions of maximum intensity were selected automatically for MS/MS analysis. Trypsin autolysis products and keratinderived precursor ions were automatically excluded. The collision voltage of CID was varied between 34 and 161 eV depending on the mass of the precursor. Data from the tandem mass spectrometry (MS/MS), as PKL (peaklist) files acquired by the ProteinLynx software (Version 2.2.5; Waters, Manchester, UK), were processed with the search algorithm MASCOT (Version 2.2; Matrix Science, London, U.K.) against the NCBInr protein sequence database (Release date: 18th Mar 2007). The MS/MS data were retrieved against the Homo sapiens subset of the sequences with the parameters set as follows: enzyme, trypsin; allowance of up to one missed cleavage peptide; mass tolerance, $\pm$ 0.1 Da; and MS/MS tolerance, $\pm$ 0.05 Da. Fixed modifications of cysteine carboamidomethylation, and variable modifications of methionine oxidation were allowed. The justification of the threshold employed was $P<$ 0.05, indicating the identification at the 95% confidence interval for those matched peptides, and MASCOT scores (based on combined MS and MS/MS spectra) over 66 were considered statistically significant. Only those individual MS/MS spectra with statistically significant ions scores exceeding the threshold (based on MS/MS data) were considered acceptable. To eliminate the redundancy of proteins appearing in the database under different names or accession numbers, the one-protein member belonging to the species Homo sapiens with the highest MASCOT score was further selected out from a multiple-member protein family.

2.5 Semi-quantitative RT-PCR

The primer sequences and the expected sizes of PCR products were as follows: Cyclophilin A: (Forward) 5’-CATGGTCAACCCCA CGTGTTCTT-3’ and (Reverse) 5’-TAG ATG GAC TTG CCA CCA GTG CCA T-3’ (236 bp); GAPDH: (Forward) 5’-AGCTTCGGCA CATATTTCATCTG-3’ and (Revserse) 5’-CGTTCAC TCCCATGACAAACA-3’ (311 bp). Total RNA was extracted using Trizol reagent (Invitrogen, Carlsbad, CA) and RT-PCR was performed with conditions as follows: reverse transcription at 48 ${{}^{\circ}}$ C for 30 min and denaturation at 94 ${{}^{\circ}}$ C for 2 min; then amplification for 30 cycles at 94 ${{}^{\circ}}$ C for 0.5 min, annealing at 60 ${{}^{\circ}}$ C for 0.5 min, and extension at 72 ${{}^{\circ}}$ C for 0.5 min; then terminal elongation step at 72 ${{}^{\circ}}$ C for 10 min and a final holding stage at 4 ${{}^{\circ}}$ C. PCR products were resolved on 2% agarose gel. Mean Value Intensity (MVI) were collected for both CYPA and GAPDH. The expression level of CYPA was the ratio of MVI between CYPA and GAPDH.

2.6 Western blotting

Tissue samples were ground in liquid nitrogen and lysed in RIPA lysis buffer (50 mM Tris-HCl (pH 7.4), 0.25 % sodium deoxycholate, 150 mM NaCl, 1% NP-40, 1 mM EDTA, 1 mM NaF, 1 mM Na3V4, 1 mM PMSF). Lysates were subjected to 12% SDS-PAGE, transferred to polyvinylidene difluoride (PVDF) membranes (Millipore, Bedford, MA), and immunoblotted with rabbit anti-human Cyclophilin A antibody (Upstate Biotechnology, Charlottesville, VA). The blots were labeled with horseradish peroxidaseconjugated secondary antibody, visualized by chemiluminescent detection.

2.7 Immunohistochemistry

The sections were stained by the Envision System-HRP method (DakoCytomation Inc, Carpinteria, CA), according. Specific antibodies performed included rabbit anti-human Cyclophilin A, and goat anti-human PCNA (Santa Cruz Biotechnology, Santa Cruz, CA). Immunostaining intensity (A) was classified as lack of staining (0), mild staining (1), moderate staining (2), and strong staining (3). The proportion of staining-positive cells (B) was semi-quantitatively divided into 4 grades, as $<$ 5% (0), 6–25% (1), 26–50% (2), 51–75% (3), and $>$ 75% (4). The score was measured as A $\times$ B, and the result was defined as negative ( $--$ , 0), weakly positive ( $+$ , 1–3), positive ( $++$ , 4–7), and strongly positive ( $+++$ , 8–12). The immunostaining was also quantified using Imagepro-plus 5.0 software, as integral optical density (IOD) scores. Results were assessed and confirmed separately by two experienced pathologists.

2.8 siRNA synthesis and shRNA plasmid vector construction

A double strand siRNA oligonucleotide targeting Cyclophilin A (sense: 5’-AAGAUGAGAACUUCAUC CUdTdT-3’; antisense: 5’-AGGAUGAAGUUCUCAU CUUdTdT-3’) with dTdT-overhangs at 3’ end was designed according to the published sequence of human Cyclophilin A (NM_021130). This sequence, corresponding to the nucleotides 265–283 bp, had been used in a previous study [14], and proved to be specific and effective. The HK sequence, with no homology to any human gene, was used as negative control. The plasmid Pgenesil-2 containing kanamycin resistance gene was linearized with BamHI and HindIII, and the annealed oligonucleotide templates were ligated into a plasmid vector using T4 DNA ligase. Chemically competent DH5 $\alpha$ E. coli were transformed and positive transformants were isolated by kanamycin selection and amplified using standard methods. Identification of the insert-containing plasmids was confirmed by digestion with SaII, and plasmid DNA from positive clones was extracted and sequenced for additional verification. Once the requirement had been met, a large-scale preparation of plasmid DNA was extracted and named CYPA-shRNA or HK-shRNA.

2.9 Cell culture and transfection

The murine fetal 3T3 fibroblast cell line (ATCC, VA) was maintained in Roswell Park Memorial Institute (RPMI) $-$ 1640 medium. The lipofectamine2000 (Invitrogen, Carlsbad, CA) and siRNA were diluted in antibiotics-free media, respectively, and then combined at a ratio of 2.5:1. The combinations were transfected to the cells in indicated concentrations according to the manufacturer’s recommendation.

2.10 Cell proliferation and apoptosis assays

Cells seeded on 96-well plates in triplicate were transfected with shRNA at various concentrations. After incubation at 37 ${{}^{\circ}}$ C for indicated durations, 20 $\mu$ l MTT (2 mg/ml, Sigma, St. Louis, MO) was added for another 4-h incubation. The MTT formazan precipitate was then dissolved in 200 $\mu$ l DMSO, and the absorbance was measured at a 595 nm wavelength.

For clonogenic formation assay, 100 counted cells transfected with siRNA were seeded in triplicate in a 6-well plate, and cultured continuously for 14 days. Clones were stained with Gimsa, and counted under a microscope. A cluster with more than 50 cells was considered as a clone.

Propidium Iodide (PI, Invitrogen, Carlsbad, CA) staining was carried out 72 hrs after transfection. TUNEL staining was performed according to the manufacturer direction (Promega, Madison, WI). The cells were then observed under a fluorescence microscope (Olympus, Tokyo, Japan).

2.11 Data analysis and Statistics

All quantitative data were recorded as mean $\pm$ SD. Comparisons between two groups were performed by Student’s t test; comparisons among multiple groups were performed by analysis of variance, LSD-t test or Dunnet-t test; comparisons of ordinal data between two groups were performed by rank sum test; relevance analysis of ordinal data was performed by Crosstabs $\chi$ 2 test. Statistical significance was defined as $P<$ 0.05.

Table 1
Proteins up-regulated in OSF

#	Acc#	Protein ID	Gene name	MW/PI	No.of pep	Score
Structural proteins
	P02768	Serum albumin	ALB	69367/5.67	40	685
	P08865	40S ribosomal protein SA	RPSA	32,854/4.79	8	82
	P51884	Lumican	LUM	38,429/6.17	3	69
	P02533	Keratin, type I cytoskeletal 14	KRT14	51,622/5.09	5	104
	P04264	Keratin, type II cytoskeletal 1	KRT1	66,018/8.16	2	63
	P35527	Keratin, type I cytoskeletal 9	KRT9	62,129/5.19	2	79
	P19013	Keratin, type II cytoskeletal 4	KRT4	57,285/6.25	2	73
	P13647	Keratin, type II cytoskeletal 5	KRT5	62,378/7.58	3	75
	P05787	Keratin, type II cytoskeletal 8	KRT8	53,704/5.52	2	65
	P05976	MLC1F	MYL1	21,145/4.97	2	78
	P08590	Myosin light chain 3	MYL3	21,932/5.03	4	116
	P14649	Myosin light chain 6B	MYL6B	22,764/5.56	4	254
	P60660	Myosin light polypeptide 6	MYL6	16,930/4.56	2	81
	P10916	MLC-2	MYL2	18,789/4.92	3	74
	P12883	Myosin-7	MYH7	223,097/5.63	3	65
	P68871	Hemoglobin subunit beta	HBB	15,998/6.81	30	469
	O93349	Hemoglobin subunit beta	HBB2_TRENE	16,326/6.03	5	124
Metabolism
	P23542	Aspartate aminotransferase, cytoplasmic	AAT2	46,058/8.45	3	93
	P62937	PPIase A	PPIA	18,012/7.82	16	307
	P30049	F-ATPase delta subunit	ATP5D	17,490/4.53	2	69
	P00915	Carbonic anhydrase 1	CA1	28,870/6.63	2	120
	P07451	Carbonic anhydrase 3	CA3	29,557/6.94	6	185
		muscle creatine kinase			28	592
		ATP synthase subunit delta, mitochondrial precursor	ATPD		11	168
Signal transduction and cancer related
	P08670	Vimentin	VIM	53,652/5.06	4	120
	P13929	Beta-enolase	ENO3	46,987/7.73	2	78
	P09211	Glutathione S-transferase P	GSTP1	23,356/5.44	3	69
	P55786	PSA	NPEPPS	103,276/5.49	2	64
	P55083	Microfibril-associated glycoprotein 4	MFAP4	28,648/5.21	7	178
	Q9Y566	Shank1	SHANK1	225,021/8.27	3	69
Heat-shock and Redox related
		NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 5			2	129
	A7MCR1	Ubiquinol-cytochrome c reductase, Rieske iron-sulfur polypeptide 1	uqcrfs1	29,714/273	4	221
				amino acids
Others
	P69905	Hemoglobin subunit alpha	HBA1	15126/8.73	15	471
		smooth muscle and non-muscle myosin alkali light chain 6B			19	377
	P20774	Mimecan	OGN	33,922/5.22	3	92
	P07737	Profilin-1	PFN1	15,054/8.47	2	83
	gi $\|$ 34069	unnamed protein product			6	316

Table 2

Proteins down-regulated in OSF

#	Acc#	Protein ID	Gene name	MW/PI	No.of pep	Score
Structural proteins
	P14136	Glial fibrillary acidic protein	GFAP	49,880/5.42	5	89
	Q6RHW0	CK-9	Krt9	72,527/5.55	2	84
	Q86Y46	Keratin, type II cytoskeletal 73	KRT73	58,923/6.93	2	63
	Q7RTS7	Keratin, type II cytoskeletal 74	KRT74	57,865/7.59	3	75
	O95678	Keratin, type II cytoskeletal 75	KRT75	59,504/7.60	8	91
Calcium binding
	P62158	Calmodulin	CALM1	16,838/4.09	2	87
	P06703	Protein S100-A6	S100A6	10,180/5.32	13	526
	P06702	Protein S100-A9	S100A9	13,242/5.71	24	295
	P31949	Protein S100-A11	S100A11	11,740/6.56	6	87
	P04083	Annexin A1	ANXA1	38,714/6.64	9	258
	P07355	Annexin A2	ANXA2	38,604/7.56	10	104
	P09525	Annexin A4	ANXA4	35,883/5.85	5	112
		Annexin A5	ANXA5		53	1414
	P50995	Annexin A11	ANXA11	54,390/7.53	2	63
Metabolism
	P07237	PDI	P4HB	57,116/4.69	19	573
	P55084	TP-beta	HADHB	51,294/9.24	3	79
	P00915	Carbonic anhydrase 1	CA1	28,870/6.63	18	254
	P50440	Glycine amidinotransferase, mitochondrial	GATM	48,455/6.43	2	76
	Q71U36	Tubulin alpha-1A chain	TUBA1A	50,136/4.94	3	87
	P68363	Tubulin alpha-1B chain	TUBA1B	50,152/4.94	2	88
	P60174	TIM	TPI1	26,669/6.51	4	132
	P02787	Serotransferrin	TF	77,050/6.70	13	172
	Q01469	Fatty acid-binding protein, epidermal	FABP5	15,164/6.82	3	98
	P31150	Rab GDI alpha	GDI1	50,583/5.00	2	72
	P60709	Actin, cytoplasmic 1	ACTB	41,737/5.29	11	309
	Q6S8J3	ANKRD26-like family C member 1A	A26C1A	121,363/5.83	3	69
Signal transduction and cancer related
	P51888	Prolargin	PRELP	43,810/9.45	2	83
	P02763	AGP 1	ORM1	23,512/5.00	5	94
	Q92665	S31mt	MRPS31	45,318/8.31	2	86
	P02792	Ferritin light chain	FTL	20,020/5.51	2	54
	P14618	CTHBP	PKM2	57,937/7.95	4	76
	P15927	RP-A p32	RPA2	29,247/5.75	3	87
	A9V9A7	Predicted protein	ORF Names: 34069	38,351/	2	73
	Q8WWQ8	Stabilin-2	STAB2	276,988/5.99	3	65
	P10599	Thioredoxin	TXN	11,737/4.82	4	82
	Q9BXL6	Carma 2	CARD14	113,300/5.62	2	67
	P12111	Collagen alpha-3(VI) chain	COL6A3	343,665/6.15	2	84
	Q6S8J3	ANKRD26-like family C member 1A	A26C1A	121,363/5.83	3	97
	P09382	Galectin-1	LGALS1	14,716/5.34	6	205
Protein degradation
	Q9UL46	Proteasome activator complex subunit 2	PSME2	27,362/5.44	4	113
	P01009	Alpha-1-antitrypsin	SERPINA1	46,737/5.37	3	152
Heat-shock and redox related
	P00441	Superoxide dismutase [Cu-Zn]	SOD1	15,936/5.70	3	79
	P04179	Superoxide dismutase [Mn], mitochondrial	SOD2	24,722/6.86	21	759
	P21266	Glutathione S-transferase Mu 3	GSTM3	26,560/5.37	2	86
	P00387	B5R	CYB5R3	34,235/6.87	2	63
	P29474	Nitric oxide synthase, endothelial	NOS3	133,289/6.98	3	125
	Q9H299	SH3BP-1	SH3BGRL3	10,438/4.82	2	78
	Q9H299	SH3BP-1	SH3BGRL3	10,438/4.82	5	157
Others
	P01861	Ig gamma-4 chain C region	IGHG4	35,941/8.92	3	94
	P02675	Fibrinogen beta chain	FGB	55,928/4.14	2	87
	P02679	Fibrinogen gamma chain	FGG	51,512/5.24	5	112
	Q5VZL5	Zinc finger MYM-type protein 4	ZMYM4	172,788/6.46	3	85
	Q9UJY1	Heat shock protein beta-8	HSPB8	21,604/	3	69
	P01837	Ig kappa chain C region		11,778/5.56	2	76
	P02766	Transthyretin	TTR	15,887/5.35	5	188

Figure 1.

Protein profile differences between oral submucous fibrotic tissue and normal mucous tissue. (A) H&E staining of OSF tissue and normal mucous tissue. Bar $=$ 100 $\mu$ m. (B) Comparison of protein profiles by two-dimensional gel electrophoresis between OSF tissue and normal mucous tissues. Roughly 1000 spots were visualized for both tissues. The spot represent CYPA were indicated in boxes. (C) CLUSTER heat map shows differential protein expression levels. Red shows up-regulation in OSF tissue while green shows down-regulation. (D) Cropped 2-DE gel images of cyclophilin A (CYPA) spot and 3D image generated by PDQuest software. Arrow indicates the spot/peak for CYPA. (E) Ninety-four Proteins with differential expressions were identified by MS, of which 38 up-regulated in OSF tissue, and 56 down-regulated. Among 94 differentially expressed proteins, 35% were involved in cytoskeleton, 20% in metabolism, 20% in signal transduction, 10% in Redox, 2% in protein degradation, and 14% in other functions.

Figure 2.

Identification of Cyclophinlin A in croppted 2-DE gel. MS/MS analysis revealed 1 matched-peptides for Cyclophilin A, with 8% sequence coverage and a MOWSE score of 114.

Figure 3.

Confirmation of Cyclophilin A up-regulation in SOF tissue. (A) RT-PCR indicated 2.1-fold (t test, $P<$ 0.05); (B) Western blot indicated 2.26-fold (t test, $P<$ 0.05) unregulation of Cyclophilin A in OSF tissue comparing to normal mucous tissue. N represents normal tissue, while O represents OSF tissue. Numbers indicate samples from different donors. (C) Immunohistochemical analysis showed the expression pattern of Cyclophilin A in OSF and normal tissues. Bar $=$ 50 $\mu$ m.

Figure 4.

Suppression of Cyclophilin A by shRNA inhibits the proliferation of fibroblasts. (A) Seventy-two hours after transfection, total proteins were collected for western blot. (B) Quantification of western blots indicated that CYPA-shRNA transfected 3T3 fibroblasts had significantly less expression of CYPA (Dunnett-t test, $p<$ 0.05) than control cells. (C) MTT data showed the suppression of cell growth by cyclophilin A-siRNA in duration-dependent manners, and the decrease of proliferation ratio reached to 50% at 72 hr after transfection. (D–E) Clonogenic formation assay showed that the clone numbers decreased significantly in CYPA-shRNA transfected cells when comparing to control cells (Dunnett-t test, $P<$ 0.01). Untreated means 3T3 cells without transfection. Lipo means 3T3 cells transfected with empty transfection reagent Lipofectamine2000. HK-shRNA means 3T3 cells transfected with mock sequence. CYPA-shRNA means 3T3 cells transfected with shRNA sequence specifically targeted to knockdown CYPA gene.

Figure 5.

Suppression of Cyclophilin A by shRNA increases the apoptosis of fibroblasts. (A) Propidium iodide (PI) staining was performed 72 hr after transfection. Bar $=$ 50 $\mu$ m. White arrows indicate the apoptotic cells. (B) TUNEL assay was performed 72 hrs after transfection. Bar $=$ 100 $\mu$ m. (C) Quantification of PI staining images showed that the apoptotic rate of CYPA-shRNA transfected cells was much higher than other groups (Dunnett-t test, $P<$ 0.01). (D) Quantification showed that the TUNEL-positive nuclei significantly increase in the CYPA-shRNA transfected cellscompared with untreated, lipofectamine or negative control (Dunnett-t test, $P<$ 0.01).

3. Results

3.1 Comparison of global expression profile of proteins between SOF and normal mucous tissue

Before proteomic analysis, H&E staining was carried out to confirm the pathological conditions of tissue samples. Normal submucous tissue contained regular epithelial spikes and clear basement membrane, while OSF tissue had edema between collagen fibers, invasion of lymphocyte, and irregular epithelial spikes (Fig. 1A). Two-dimensional electrophoresis was then performed on 25 normal mucous tissue samples and 25 OSF tissue samples. Image analysis was performed using PDQuest 7.0 software. 2D gels displayed well-resolved and reproducible protein profiles for both tissues. Comassie staining visualized on averages of 1000 spots (Fig. 1B) in samples both tissues. Spots at different expression levels (182 spots in total) were analyzed using MALDI-Q-TOF (matrix-assisted laser desorption/ionization quadrupole time-of-flight) tandem mass spectrometry. A total of 94 proteins were identified, among which 38 were up-regulated in OSF tissue while 56 were down-regulated in OSF tissue (Fig. 1C). Among these proteins, most of them were involved in cellular functions, including cytoskeleton, metabolism, signaling transduction, Redox, and protein degradation (Fig. 1E). Full lists of proteins that differentially expressed in two types of tissues were in Tables 1 and 2.

Among the 94 differentially expressed proteins, we chose Cyclophinlin A for detailed analysis due to several reasons. Firstly, the expression of Cyclophilin A was found to be reliably different between normal and OSF tissues in all detected samples (Fig. 1D). Then, the mass spectrum results revealed that the peptide had8% sequence coverage and a MOWSE score of 114 (Fig. 2), which is an indication of accuracy for protein matching. At last, Cyclophinlin A had been reported in literature as an important marker in many carcinomas [15].

3.2 Up-regulation of Cyclophilin A in OSF tissue was confirmed at both mRNA and protein levels

To confirm the difference in expressions of Cyclophilin A in OSF and normal mucous tissue, RT-PCR was carried out to measure the gene expression at mRNA level. As shown in Fig. 3A, the mRNA level of Cyclophilin A was observed between the two tissues (OSF tissues: 70.35 $\pm$ 15.13; normal mucous tissues: 32.2 $\pm$ 6.46; Student’s t test, $P<$ 0.05). Furthermore, results from western blotting showed that Cyclophilin A was up-regulated in all OSF tissues examined (OSF tissues: 59.55 $\pm$ 3.25; normal tissues: 26.35 $\pm$ 2.00; Student’s t test, $P<$ 0.01) (Fig. 3B). Immunohistochemistry showed that Cyclophin A was weakly stained in normal muscous tissue, while strongly expressed in OSF tissue (Fig. 3C). Using a semi-quantification method, 12% of normal muscous tissue were identified as negative, and 88% as weakly positive, none as positive or strongly positive. However, OSF tissue got 0 as negative, 16% as weakly positive, 44% as positive and 40% as strongly positive. These data demonstrate that Cyclophilin A is up-regulated in OSF tissues at both mRNA and protein levels and this is consistent with the results in the 2-DE analysis.

3.3 Suppression of Cyclophilin A by shRNA inhibit proliferation of fibroblasts

To investigate the function of Cyclophilin A in fibroblasts, shRNA sequences were used to transfect fibroblasts 3T3 cells. As shown by western blot, the expression of Cyclophilin A was significantly suppressed 72 hr after transfection (Fig. 4A). Quantification of blots showed its expression was reduced by more than 70%. Scrambled shRNA did not inhibit the expression of Cyclophilin A in a side by side experiment (Fig. 4B). The proliferation of transfected cells was studied by MTT assay and clonogenic formation. Data from MTT assay showed that the proliferation was significantly suppressed by transfection of Cyclophilin A shRNA in a duration-dependent manner (Fig. 4C). After 14 days culture in the clonogenic formation experiment, the clone numbers in untreated control, lipo and HK-shRNA groups, were all significantly larger than the clone number in Cyclophilin A-shRNA group (Dunnett-t test, $P<$ 0.01; Fig. 4D–E ).

3.4 Suppression of Cyclophilin A by shRNA induced apoptosis of fibroblasts

At last, we examined the effects of Cyclophilin A on the apoptosis of fibroblasts by PI and TUNEL staining. Upon PI staining, apoptotic cells represented smaller cell size and lower forward scattered light than normal cells (Fig. 5A). TUNEL staining visualized a large amount of apoptotic cells in CYPA-shRNA transfected group comparing to control groups (Fig. 5B). There were only minimal numbers of cells in untreated and negative control groups showed apoptotic features upon PI staining, however, the CYPA-shRNA transfected group had almost 40% of apoptotic cells (Dunnett-t test, $P<$ 0.01, Fig. 5C). Quantification of TUNEL positive cells also showed that the difference between CYPA-shRNA transfected group and other groups was statistically significant (Dunnett-t test, $P<$ 0.01, Fig. 5D).

4. Discussion

In this study, high-resolution and reproducible protein expression patterns were obtained from 25 samples of OSF tissue and 25 samples of normal mucous tissue by 2D electrophoresis. Approximately 182 protein spots were successfully identified including 94 different proteins. 38 proteins were up-regulated while 56 proteins were down-regulated in OSF tissue comparing to normal tissue. By analysis and classification of those proteins, Cyclophilin A was identified as OSF-associated candidate protein. RT-PCR, western blot and Immunohistochemical analysis of tissues exhibited an increased pattern of Cyclophilin A expression in OSF than in normal mucous tissues. Transfection of CYPA-shRNA into 3T3 cells resulted significant inhibition of Cyclophilin A expression. The MTT assay and clonogenic formation test showed that proliferation and cloning efficiency were inhibited by knocking down Cyclophilinin in 3T3 cells. Apoptosis was also induced by the shRNA transfection.

The peptidylprolyl cis-trans-isomerase (PPIse) family includes Cyclophilin (CyP), FK506 binding protein (FKBP) and parvulin [16]. The common feature of this family of protein is the enzymatic active group consist of 120 amino acid residuals which regulate the activity and stability of the target protein. PPIse was believed to regulate the functions of proteins involved in cell cycles [17]. This family of proteins was also shown to play important roles in autoimmune diseases with its regulatory effects on immunological response [15]. It’s been reported to be up-regulated in the serum of patients with systemic lupus erythematosus, rheumatoid arthritis and psoriasis [18, 19, 20]. As a member of the peptidylprolyl cis-trans-isomerase (PPIse) family, Cyclophilin A is an 18 kDa protein with a broad range of functions in cell proliferation and apoptosis. Initial studies mainly focused on its role in protein folding, immune response and HIV-1 infection [21, 22, 23]. It was generally regarded as the intracellular receptor for cyclosporin A [24]. But it’s later been found in the secretomes of tumor cells as a response to inflammatory stimulation [25]. The Cyclophilin-Acyclosporin A complex was reported to suppress the activity of calcineurin and nuclear transportation of nuclear factor of activated T-cells (NFAT) in T lymphocytes and other immune cells [26, 27].

Recent studies had identified Cyclophilin A as a candidate marker gene in many carcinomas. Up-regulation of Cyclophilin A had been observed in lung cancer [28], cholangiocarcinoma [29], pancreatic cancer [30], myeloma [31] and gastric carcinoma [32]. Our study was the first one to report the up-regulation of Cyclophilin A in oral submuscous fibrotic tissue. This broadened our understanding of the roles of Cyclophilin A in carcinogenesis. These results demonstrated that overexpression of Cyclophilin A was important for the pathogenic process of fibroblasts predispose to cancer cells. Regarding the mechanism how Cyclophilin A involved in carcinogenesis, it’s generally believed to promote cells proliferation and inhibit apoptosis through caspase deactivation [33]. In support of this, our data showed that knockdown of Cyclophilin A in fibroblasts by shRNA inhibit cell proliferation and increase apoptosis.

In conclusion, the present study demonstrated that CYPA is a potential biomarker and gene intervention targets of OSF. These results may uncover novel mechanisms for OSF pathogenic process. These data improve our understanding of the molecules in the initiation and development of OSF, and help the development for therapeutics of oral cancer.

References

Saravanan

Kodanda Ram

and Ganesh

, Molecular biology of oral sub mucous fibrosis, J Cancer Res Ther 9 (2013), 179–180.

and Jian

, The role of epithelial-mesenchymal transition in oral squamous cell carcinoma and oral submucous fibrosis, Clin Chim Acta 383 (2007), 51–56.

Angadi

P.V.

and Rao

, Management of oral submucous fibrosis: an overview, Oral Maxillofac Surg 14 (2010), 133–142.

Trivedy

C.R.

Craig

and Warnakulasuriya

, The oral health consequences of chewing areca nut, Addict Biol 7 (2002), 115–125.

van der Waal

, Potentially malignant disorders of the oral and oropharyngeal mucosa; terminology, classification and present concepts of management, Oral Oncol 45 (2009), 317–323.

Wilkins

M.R.

Sanchez

J.C.

Gooley

A.A.

Appel

R.D.

Humphery-Smith

Hochstrasser

D.F.

and Williams

K.L.

, Progress with proteome projects: why all proteins expressed by a genome should be identified and how to do it, Biotechnol Genet Eng Rev 13 (1996), 19–50.

Verma

Kagan

Sidransky

and Srivastava

, Proteomic analysis of cancer-cell mitochondria, Nat Rev Cancer 3 (2003), 789–795.

Mustafa

G.M.

Larry

Petersen

J.R.

and Elferink

C.J.

, Targeted proteomics for biomarker discovery and validation of hepatocellular carcinoma in hepatitis C infected patients, World J Hepatol 7 (2015), 1312–1324.

Luo

Dong

L.Y.

Yan

Q.G.

Cao

S.J.

Wen

X.T.

Huang

X.B.

and Ma

X.P.

, Research progress in applying proteomics technology to explore early diagnosis biomarkers of breast cancer, lung cancer and ovarian cancer, Asian Pac J Cancer Prev 15 (2014), 8529–8538.

10.

Anagnostopoulos

A.K.

and Tsangaris

G.T.

, The proteomics of pediatric brain tumors, Expert Rev Proteomics 11 (2014), 641–648.

11.

Jayaram

Gupta

M.K.

Polisetty

R.V.

Cho

W.C.

and Sirdeshmukh

, Towards developing biomarkers for glioblastoma multiforme: a proteomics view, Expert Rev Proteomics 11 (2014), 621–639.

12.

Seema

Krishnan

Harith

A.K.

Sahai

Iyer

S.R.

Arora

and Tripathi

R.P.

, Laser ionization mass spectrometry in oral squamous cell carcinoma, J Oral Pathol Med 43 (2014), 471–483.

13.

Al-Tarawneh

S.K.

Border

M.B.

Dibble

C.F.

and Bencharit

, Defining salivary biomarkers using mass spectrometry-based proteomics: a systematic review, OMICS 15 (2011), 353–361.

14.

Zhao

Bai

Wang

Chen

Wei

and Huang

, Proteomics identification of cyclophilin a as a potential prognostic factor and therapeutic target in endometrial carcinoma, Mol Cell Proteomics 7 (2008), 1810–1823.

15.

Nigro

Pompilio

and Capogrossi

M.C.

, Cyclophilin A: a key player for human disease, Cell Death Dis 4 (2013), e888.

16.

Takahashi

Shimizu

Kosaka

Hidaka

Uchida

and Uchida

, Role of prolyl isomerase pin1 in pathogenesis of diseases and remedy for the diseases from natural products, Curr Drug Targets 15 (2014), 973–981.

17.

Galat

, Peptidylprolyl cis/trans isomerases (immuno- philins): biological diversity – targets – functions, Curr Top Med Chem 3 (2003), 1315–1347.

18.

Harigai

Hara

Takahashi

Kitani

Hirose

Suzuki

Kawakami

Hidaka

Kawaguchi

Ishizuka

et al., Presence of autoantibodies to peptidyl-prolyl cis-trans isomerase (cyclosporin A-binding protein) in systemic lupus erythematosus, Clin Immunol Immunopathol 63 (1992), 58–65.

19.

Konttinen

Y.T.

T.F.

Mandelin

Liljestrom

Sorsa

Santavirta

and Virtanen

, Increased expression of extracellular matrix metalloproteinase inducer in rheumatoid synovium, Arthritis Rheum 43 (2000), 275–280.

20.

Al-Daraji

W.I.

Grant

K.R.

Ryan

Saxton

and Reynolds

N.J.

, Localization of calcineurin/NFAT in human skin and psoriasis and inhibition of calcineurin/NFAT activation in human keratinocytes by cyclosporin A, J Invest Dermatol 118 (2002), 779–788.

21.

Gamble

T.R.

Vajdos

F.F.

Yoo

Worthylake

D.K.

Houseweart

Sundquist

W.I.

and Hill

C.P.

, Crystal structure of human cyclophilin A bound to the amino-terminal domain of HIV-1 capsid, Cell 87 (1996), 1285–1294.

22.

Abdurahman

Hoglund

and Vahlne

, Mutation in the loop C-terminal to the cyclophilin A binding site of HIV-1 capsid protein disrupts proper virus assembly and infectivity, Retrovirology 4 (2007), 19.

23.

Damsker

J.M.

Bukrinsky

M.I.

and Constant

S.L.

, Preferential chemotaxis of activated human CD4+ T cells by extracellular cyclophilin A, J Leukoc Biol 82 (2007), 613–618.

24.

Schaller

Ylinen

L.M.

Webb

B.L.

Singh

and Towers

G.J.

, Fusion of cyclophilin A to Fv1 enables cyclosporine-sensitive restriction of human and feline immunodeficiency viruses, J Virol 81 (2007), 10055–10063.

25.

Huang

C.M.

Ananthaswamy

H.N.

Barnes

Kawai

and Elmets

C.A.

, Mass spectrometric proteomics profiles of in vivo tumor secretomes: capillary ultrafiltration sampling of regressive tumor masses, Proteomics 6 (2006), 6107–6116.

26.

Huai

Kim

H.Y.

Liu

Zhao

Mondragon

Liu

J.O.

and Ke

, Crystal structure of calcineurin-cyclophilin-cyclosporin shows common but distinct recognition of immunophilin-drug complexes, Proc Natl Acad Sci U S A 99 (2002), 12037–12042.

27.

Kockx

Jessup

and Kritharides

, Cyclosporin A and atherosclerosis – cellular pathways in atherogenesis, Pharmacol Ther 128 (2010), 106–118.

28.

Yang

Chen

Yang

Qiao

Zhao

and Yu

, Cyclophilin A is upregulated in small cell lung cancer and activates ERK1/2 signal, Biochem Biophys Res Commun 361 (2007), 763–767.

29.

Obchoei

Sawanyawisuth

Wongkham

Kasinrerk

Yao

Chen

and Wongkham

, Secreted cyclophilin A mediates G1/S phase transition of cholangiocarcinoma cells via CD147/ERK1/2 pathway, Tumour Biol 36 (2015), 849–859.

30.

Mikuriya

Kuramitsu

Ryozawa

Fujimoto

Mori

Oka

Hamano

Okita

Sakaida

and Nakamura

, Expression of glycolytic enzymes is increased in pancreatic cancerous tissues as evidenced by proteomic profiling by two-dimensional electrophoresis and liquid chromatography-mass spectrometry/mass spectrometry, Int J Oncol 30 (2007), 849–855.

31.

Zhu

Wang

Zhao

J.J.

Calimeri

Meng

Hideshima

Fulciniti

Kang

Ficarro

S.B.

Tai

Y.T.

Hunter

McMilin

Tong

Mitsiades

C.S.

C.J.

Treon

S.P.

Dorfman

D.M.

Pinkus

Munshi

N.C.

Tassone

Marto

J.A.

Anderson

K.C.

and Carrasco

R.D.

, The Cyclophilin A-CD147 complex promotes the proliferation and homing of multiple myeloma cells, Nat Med 21 (2015), 572–580.

32.

Feng

Xin

Xiao

and Sun

, Cyclophilin A Enhances Cell Proliferation and Xenografted Tumor Growth of Early Gastric Cancer, Dig Dis Sci (2015).

33.

Lee

, Role of cyclophilin a during oncogenesis, Arch Pharm Res 33 (2010), 181–187.

Cyclophilin A was revealed as a candidate marker for human oral submucous fibrosis by proteomic analysis

Abstract

Keywords

1. Introduction

2. Materials and methods

2.1 Patient samples

2.2 Two-dimensional electrophoresis and image analysis

2.3 In-gel digestion

2.4 Mass spectrometry analysis

2.5 Semi-quantitative RT-PCR

2.6 Western blotting

2.7 Immunohistochemistry

2.8 siRNA synthesis and shRNA plasmid vector construction

2.9 Cell culture and transfection

2.10 Cell proliferation and apoptosis assays

2.11 Data analysis and Statistics

Table 1 Proteins up-regulated in OSF

3.1 Comparison of global expression profile of proteins between SOF and normal mucous tissue

3.2 Up-regulation of Cyclophilin A in OSF tissue was confirmed at both mRNA and protein levels

3.3 Suppression of Cyclophilin A by shRNA inhibit proliferation of fibroblasts

3.4 Suppression of Cyclophilin A by shRNA induced apoptosis of fibroblasts

4. Discussion

References

Table 1
Proteins up-regulated in OSF