Tumor Biol. DOI 10.1007/s13277-015-3111-1

RESEARCH ARTICLE

SYF2 is upregulated in human epithelial ovarian cancer and promotes cell proliferation Sujuan Yan & Yan Deng & Yong Qiang & Qinghua Xi & Rong Liu & Shuyun Yang & Jian Liu & Chunhui Tang & Jianxin Zhong & Yingying Wang

Received: 29 October 2014 / Accepted: 14 January 2015 # International Society of Oncology and BioMarkers (ISOBM) 2015

Abstract SYF2 is reported to be as a cell cycle regulator at the G1/S transition and encodes a nuclear protein that interacts with cyclin-D-type binding protein 1. In our study, we investigated the role of SYF2 in human epithelial ovarian cancer (EOC) progression. Western blot and immunohistochemistry analysis displayed that SYF2 was overexpressed in EOC tissues and EOC cell lines. In addition, the immunoreactivity of SYF2 was positively correlated with tumor grade and Ki-67

expression. In vitro, serum starvation-refeeding experiment and SYF2-siRNA transfection assay demonstrated that the expression of SYF2 was promoted in the proliferative progression of EOC cells, while knockdown of SYF2 expression decreased and inhibited cell growth rate of EOC cells. With all the results, we support that SYF2 might contribute to EOC progression via modulation of proliferation in EOC cells and would provide a novel therapeutic target of human EOC.

Sujuan Yan and Yan Deng contributed equally to this work.

Keywords Epithelial ovarian cancer (EOC) . SYF2 . Proliferation . Prognosis

S. Yan : Y. Wang (*) Department of Pathogen Biology, Medical College, Jiangsu Provice Key Laboratory for Information and Molecular Drug Target, Nantong University, Nantong 226001, Jiangsu Province, People’s Republic of China e-mail: [email protected] Y. Deng : Q. Xi : J. Liu : C. Tang : J. Zhong (*) Department of Obstetrics and Gynecology, Affiliated Hospital of Nantong University, Nantong University, Nantong 226001, Jiangsu Province, People’s Republic of China e-mail: [email protected] S. Yan Department of Obstetrics and Gynecology, The First People’s Hospital of Jingmen, 67 Xiangshan Avenue, Dongbao District, Jingmen 448000, Hubei, China Y. Qiang Department of General Surgery, The First People’s Hospital of Jingmen, 67 Xiangshan Avenue, Dongbao District, Jingmen 448000, Hubei Province, People’s Republic of China R. Liu Department of Oncology, Nantong University Cancer Hospital, Nantong University, Nantong 226001, Jiangsu Province, People’s Republic of China S. Yang Department of Pathology, Nantong University Cancer Hospital, Nantong University, Nantong 226001, Jiangsu Province, People’s Republic of China

Introduction Ovarian cancer is the fifth leading cause of cancer-related mortalities in female [1, 2] and accounts for the highest tumor-associated mortality of gynecological malignancies [3]. Epithelial ovarian cancer (EOC) accounts for 80–90 % of all ovarian cancers and is the leading killer among all gynecological malignancies [4]. Although substantial advances in surgical techniques and chemotherapeutic treatments have been made in ovarian cancer, the rate of patients with ovarian cancer who can survive 5 years after the initial diagnosis is only approximately 30 % [5]. Because of lack of early symptoms, late diagnosis, and ineffective chemotherapy, mortality of ovarian cancer has exceeded all that of other cancers of the female reproductive system [6]. Therefore, the identification of the molecular markers for prognosis is important in improving therapeutic methods and raising survival rate of ovarian cancer patients. SYF2, also known as p29 CCNDBP1 interactor, is a chromosome-associated protein [7], primarily found as Grap2 and cyclin D interacting protein (GCIP) [8]. Currently, previous studies show that SYF2 is mainly involved in cell cycling by modulating transcriptional and posttranscriptional controls

Tumor Biol.

of α-tubulin [9, 10], pre-mRNA splicing [11], and DNA damaging and repairing [7, 12]. One report has shown that GCIP, interplayed with cyclin D1 which acts as a SYF2 interacting protein [13], dysregulated in tumor: colon cancer, prostatic cancer, breast cancer, etc. But, the studies of SYF2 during ovarian tumor genesis were seldom reported. In our study, we investigated a possible role of SYF2 in EOC progression and found that SYF2 expression was upregulated in EOC specimens and EOC cell lines. We also confirmed the correlation of SYF2 expression with clinicopathological variables and prognostic implications. In addition, we transfected EOC cell line with siRNA and found that knockdown of SYF2 gene could inhibit EOC cell proliferation.

Materials and methods Patients and tissue samples For Western analysis, fresh samples were frozen in liquid nitrogen immediately after surgical removal and maintained at −80 °C until use, including one normal tissue from a woman who underwent hysterectomy for benign disease. For immunohistochemical analysis, 119 cases of EOC specimens (including 45 serous papillary adenocarcinoma, 16 mucinous papillary carcinoma, 14 endometrioid adenocarcinoma, 14 clear cell carcinoma, and 30 specimens classified as Bothers^) and the clinicopathologic data were collected from patients who underwent surgery from 2004 to 2009 at the Department of Pathology, Affiliated Hospital of Nantong University. None of these patients had received any chemotherapy or radiotherapy before surgery. All patients were followed up for 1– 60 months. The specimens were fixed in 10 % formalin and embedded in paraffin. EOC tissues were reviewed regarding histopathologic type based on the WHO classification (grade 1, G1; n=15), moderately (grade 2, G2; n=33), and poorly differentiated (grade 3, G3; n=71). The average age of 119 patients was 50 years (range 32–78). The Ethics Committee of Affiliated Hospital of Nantong University had authorized us to use the tissue sections for research. The main clinical and pathologic variables are shown in Table 1.

Table 1

Expression of SYF2 in 119 human ovarian cancer specimens

Clinicopathological parameters

Age (years) ≤50 >50 FIGO stage, n (%) I II III IV

SYF2 expression Low

High

35 84

15 33

20 51

0.717

38 31 33 17

21 9 12 6

17 22 21 11

0.135

11 14 23

4 19 48

0.013*

14 9 8 8 9

31 7 6 6 21

0.096

19 29

24 47

0.520

37 11

50 21

0.421

31 17

35 36

0.100

38 10

52 19

0.460

31 17

35 36

0.100

37 11

13 58

<0.001*

Histologic grade, n (%) 1 15 2 33 3 71 Histologic subtype, n (%) Serous 45 Mucinous 16 Endometrioid 14 Clear cell 14 Others 30 Menopause Absent 43 Present 76 Lymph node status, n (%) Negative 87 Positive 32 Ascite, n (%) Absent 66 Present 53 Malignant tumor cells in peritoneal fluid, n (%) Absent 90 Present 29 Other organ metastasis, n (%) Absent 66 Present 53 Ki67 Low expression 50 High expression 69 a

P valuea

No. of cases

Statistical analyses were performed by the Pearson’s χ2 test

*P<0.05 was considered significant

Antibodies Western blot The antibodies used for Western blot analysis and immunohistochemistry were as follows: (1) mouse anti-SYF2 monoclonal antibody (Santa Cruz Biotechnology, USA), (2) mouse anti-human Ki-67 monoclonal antibody (Santa Cruz Biotechnology, USA), (3) mouse anti-human PCNA monoclonal antibody (Santa Cruz Biotechnology, USA), (4) rabbit antihuman cyclin D1 polyclonal antibody (Santa Cruz Biotechnology, USA), and (5) rabbit anti-human GAPDH polyclonal antibody (Santa Cruz Biotechnology, USA).

Western blot analysis was done as previously detailed [14]. Tissue and cell protein were promptly homogenized in a homogenization buffer containing 1 M Tris HCl pH 7.5, 1 % Triton X-100, 1 % Nonidet p-40 (NP-40), 10 % sodium dodecyl sulfate (SDS), 0.5 % sodium deoxycholate, 0.5 M EDTA, leupeptin 10 μg/mL, aprotinin 10 μg/mL, and 1 mM PMSF, and then centrifuged at 10,000×g for 30 min to collect the supernatant liquid. Protein concentrations were

Tumor Biol.

determined with a Bio-Rad protein assay (Bio-Rad, Hercules, CA, USA). The total cellular protein extracts were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and transferred to polyvinylidene difluoride filter (PVDF) membranes (Millipore, Bedford, MA). After the membranes were blocked in 5 % nonfat milk in TBST (150 mM NaCl, 20 mM Tris, 0.05 % Tween 20) for 2 h, they were incubated with the primary antibodies overnight at 4 °C. Then, the membranes were washed with TBST for three times, 5 min each, and then horseradish-peroxidase-linked IgG as the secondary antibodies for 2 h at room temperature. The membrane was developed using the ECL detection systems. The experiments were carried out in three separate occasions. Immunohistochemical staining Tissues were formalin-fixed and paraffin-embedded for immunohistochemical study. The sections were dewaxed in xylene and rehydrated in graded ethanols. Then, endogenous peroxidase activity was blocked by soaking in 3 % hydrogen peroxide for 15 min. Thereafter, the sections were processed in 10 mmol/L citrate buffer (pH 6.0) and heated to 105 °C in an autoclave for three cycles of 5 min each to retrieve antigen. After rinsing in phosphate-buffered saline (PBS, pH=7.2), 10 % goat serum was applied to block any nonspecific reactions for 1.5 h. Then, the sections were incubated with antihuman SYF2 antibody (diluted 1:200) and anti-human Ki-67 antibody (diluted 1:600) for 2 h at room temperature. The sections were then incubated with horseradish-peroxidaseconjugated anti-mouse or anti-rabbit Ig polymer as a second antibody (Envision kit, Dako) for 20 min at room temperature, according to the manufacturer’s instructions. After rinsing in water, the sections were counterstained with hematoxylin, dehydrated, and coverslipped. Immunohistochemical analysis All of the stained sections were evaluated in a blinded manner without acknowledging the clinical and pathological features of the patients. For assessment, five high-power fields in each specimen were selected randomly; at least 500 cells were counted to determine the labeling index (LI), representing the percentage of immunostained cells that is related to the total number of cells. In half of the samples, staining was repeated two times to avoid possible technical errors, but the similar results were obtained in these samples. For assessment of SYF2, intensity was estimated in comparison with the control and scored as follows: 0, negative staining; 1, weak staining; 2, moderate staining; and 3, strong staining. Scores which represent the percentage of tumor cells stained positive were as follows: 0, <1 % positive tumor cells; 1, 1–10 %; 2, 10– 50 %; 3, 50–75 %; and 4, >75 %. Then, we multiplied the two

scores, and a score of 0 was considered negative, 2–3 was considered weak, 4–5 was considered moderate, and 6–7 was considered strong. For statistical analysis, 0–3 were counted as low expression, and 4–7 were counted as overexpression [15]. As for statistical analysis of Ki- 67, a cutoff value was used to distinguish tumors with a low (<50.7 %) or high (≥50.7 %) level of Ki-67 expression. Cell culture and cell cycle analysis Human ovarian carcinoma cell lines HO-8910 and SKOV3 were purchased from the Shanghai Institute of Cell Biology. The cells were maintained in RPMI 1640 (GibCo BRL, Grand Island, NY, USA) supplemented with 10 % heat-inactivated fetal calf serum, and 100 U/mL penicillin-streptomycin mixture (GibCo BRL, Grand Island, NY, USA) at 37 °C and 5 % CO2. For cell cycle analysis, the cells were fixed in 70 % ethanol overnight at 4 °C and then incubated with 1 mg/mL RNase A for 30 min at 37 °C. Subsequently, the cells were stained with propidium iodide (PI, 50 mg/mL, Becton–Dickinson, San Jose, CA) in PBS, and 0.5 % Tween 20, and analyzed by using a Becton Dickinson flow cytometer BD FACScan (San Jose, CA) and Cell Quest acquisition and analysis programs. Gating was set to exclude cell debris, cell doublets, and cell clumps. With regard to cell synchronization, serum deprivation was used for cell cycle G1-S phase arrest. siRNAs and transfection There are three siRNAs targeting on SYF2 (Gene ID: 25949 NM_015484.4) gene and negative control (NC) siRNA were designed and provided by Nantong Biomics Biotechnologies Co., Ltd. (China). The target sequences were as follows: 5′GUGGUUUCUUAAACGUAUAdTdT-3′, 5′-GAGACGUC CUUAUAAUGAUdTdT-3′, and 5′-GAAUGAAGCUCG UAAAUUdTdT-3′. HO-8910 or SKVO3 cells were plated the day before transfection at 50–70 % confluency. The cells were then transfected with siRNAs at final concentrations of 50 nM with Lipofectamine 2000. The cells were collected after 48 h for the following assays. Cell proliferation assay Cell proliferation was determined by Cell Counting Kit-8 (CCK-8, Dojindo, Kumamoto, Japan) assay following the manufacturer’s instructions. In brief, the cells were seeded at a density of 2×104 cells/well into a 96-well cell culture cluster (Corning, Corning, NY, USA) in 100 μL culture medium and incubated overnight. CCK-8 reagents were added with 10 μL to a subset of wells, and the cells were incubated for 2 h at 37 °C. The absorbance was recorded with an automated plate reader. Each experiment was repeated at least three times.

Tumor Biol.

Statistical analysis Statistical analysis was performed using the SPSS 17.0 statistical software. The association between SYF2 and Ki-67 expression and clinicopathological features was analyzed using the Pearson χ2 test. SYF2 and Ki-67 expression was studied using the Spearman rank correlation test, because the data were not normally distributed. For analyzing the survival data, Kaplan-Meier curves were constructed, and the log-rank test was performed. Multivariate analysis was performed using Cox’s proportional hazards model, with P<0.05 considered statistically significant. The results are expressed as the mean±SD.

Results SYF2 was over-expressed in EOC tissues and ovarian cell lines To verify the role of SYF2 in EOC, Western blot analysis of SYF2 was performed using surgical specimens and two EOC cell lines including HO-8910 and SKOV3 (Fig. 1). There are ten surgical samples, including one normal ovarian tissue, Fig. 1 The expression of SYF2 in EOC tissues and EOC cells. a Western blot analysis showing the SYF2 expression in nine ovarian cancer tissues from G1 (grade 1) to G3 (grade 3) each three cases compared with one normal ovarian tissue. b Bar chart demonstrating the ratio of SYF2 to GAPDH by densitometry. The data are mean±SD. P<0.05, compared with normal tissue. c Western blot performed to detect the expression of SYF2 in two human EOC cell lines: HO-8910 and SKOV3. GAPDH was used as a loading control and each experiment repeated at least three times

three low-grade EOC tissues (grade 1), three medium-grade EOC tissues (grade 2), and three high-grade EOC tissues (grade 3). Higher expression of SYF2 was found in highgrade EOC tissues and lower expression in low ones. In normal ovarian tissue, SYF2 almost did not express (Fig. 1a, b). As expected, SYF2 also highly expressed in EOC cell lines (Fig. 1c). Since SYF2 is reported to be participated in the proliferation of some disease [16, 17], we also examined the intracellular expression of SYF2 and Ki-67 (a cell proliferation index) in 119 specimens of EOC by immunohistochemical analysis. As shown in Fig. 2, we found that SYF2 and Ki-67 were mainly located in the nucleus of EOC cells. The high expression of SYF2 was along with the high expression of nuclear localized Ki-67. Furthermore, the higher the grade of EOC, the higher the level of these two markers will be revealed. Thus, the expression of SYF2 was high in EOC tissues and EOC cell lines and is positively correlated with grade. Correlation of SYF2 expression with clinicopathologic parameters in EOC To clarify the clinicopathological significance of SYF2, the correlation of SYF2 expression with clinicopathologic

Tumor Biol.

Fig. 2 Immunohistochemical stain of SYF2 and Ki-67 in EOC tissues. Paraffin-embedded tissue sections were stained with antibodies for SYF2 and Ki-67 and counterstained with hematoxylin. a–d SYF2 and Ki-67 immunoreactivity in cancer tissue of G1. e–h SYF2 and Ki-67 staining in

cancer tissue of G2. i–l SYF2 and Ki-67 staining in cancer tissue of G3. The experiment details were described in the BMaterials and methods^ section. a, b, e, f, i, j Images in magnification of×200. c, d, g, h, k, l Images in magnification of×400

variables was evaluated by Pearson χ2 test (Table 1). We divided the expression of SYF2 and Ki-67 in the tumor specimens into high group and low group according to the cutoff value mentioned in the BMaterials and methods^ section. SYF2 expression was significantly associated with the histologic grade (P=0.013) and Ki-67 (P<0.001), and there was no correlation with age (P=0.717), FIGO stage (P=0.135), histologic subtype (P=0.096), menopause (P=0.520), lymph node status (P=0.421), ascite (P=0.100), malignant tumor cells in peritoneal fluid (P=0.460), and other organ metastases (P=0.100). In addition, Spearman’s correlation test showed

that there was a positive correlation between the expression of SYF2 and Ki-67 (r=0.708, P<0.001, Fig. 3).

Fig. 3 Relationship between SYF2 expression and Ki-67 proliferation index in EOC. Scatter plot of SYF2 against Ki-67 with regression line showing a correlation of them using the Spearman’s correlation coefficient

SYF2 expression with clinical prognostic of EOC Kaplan-Meier analysis was used to calculate the impact of SYF2 expression level on patients’ survival time (Fig. 4). The survival curves indicated that patients with high expression of SYF2 had poorer overall survival than others in 119

Fig. 4 Kaplan-Meier survival curves for low SYF2 expression versus high SYF2 expression in 119 EOC patients. Patients with lower expression of SYF2 had a longer survival than those with higher expression

Tumor Biol.

clinical cases (P<0.001, Fig. 4). Univariate survival analysis indicated that histologic grade (P=0.047), SYF2 (P<0.001), and Ki-67 (P<0.001) were independent prognostic indicators with EOC (Table 2). Moreover, multivariate analysis using the Cox’s proportional hazards model showed that histologic grade (P<0.001), SYF2 (P=0.005), and Ki-67 (P<0.001) Table 2 Survival status and clinicopathological parameters in 119 human ovarian cancer specimens Clinicopathological parameters

Survival status Total

Alive

Age (years) ≤50 35 15 >50 84 23 FIGO stage, n (%) I 38 15 II 31 8 III 33 10 IV 17 5 Histologic grade, n (%) 1 15 5 2 33 5 3 71 28 Histologic subtype, n (%) Serous 45 19 Mucinous 16 3 Endometrioid 14 5 Clear cell 14 5 Others 30 6 Menopause Absent 43 18 Present 76 20 Lymph node status, n (%) Negative 87 25 Positive 32 13 Ascite, n (%) Absent 66 26 Present 53 12 Malignant tumor cells in peritoneal fluid, n (%) Absent 90 32 Present 29 6 Other organ metastasis, n (%) Absent 66 26 Present 53 12 SYF2 Low expression 48 30 High expression 71 8 Ki67 Low expression 50 34 High expression 69 4 a

Dead

20 61

0.099

23 23 23 12

0.655

10 28 43

0.047*

26 13 9 9 24

0.229

25 56

0.081

62 19

0.217

40 41

0.051

58 23

0.135

40 41

0.051

18 63

<0.001*

Expression of SYF2 participates in the cell cycle progress of EOC cells Since SYF2 is reported to be involved in cell cycle progression by modulating transcriptional and posttranscriptional control of α-tubulin and cyclin D1 [9, 18, 19], we believe that SYF2 expression would participate in the cell cycle progress of EOC cells. We made a cell serum starvation and releasing models in HO-8910 cells and SKOV3 cells. Flow cytometry analysis showed that HO-8910 cells and SKOV3 cells with serum deprivation for 48 h were arrested in G0/G1 phase. After serum readdition, the HO-8910 cells were released from the G1 phase (Fig. 5a; from 79.57 to 40.82 %) and reentered the S phase (Fig. 5a; from 15.61 to 38.87 %), and the SKOV3 cells were released from the G1 phase (Fig. 5b; from 79.64 to 49.42 %) and reentered the S phase (Fig. 5b; from 17.51 to 41.87 %). Next, Western blot was used to analyze the expression of SYF2 during cell progression, as well as the proliferation markers such as PCNA and cyclin D1 [20]. We collected the HO-8910 cell and SKOV3 cell protein at different time points in two EOC cells, and as expected, we found that SYF2 was significantly increased 4 h after serum re-addition. Meanwhile the cell proliferation markers PCNA and cyclin D1 had a similar tendency with the protein level (Fig. 5c, d). These results affirmed that SYF2 may be involved in the proliferation of EOC in a cell-cycle-dependent pathway. Knockdown of the expression of SYF2 inhibited the proliferation of EOC Cells To further investigate the effect of SYF2 on cell proliferation of EOC, HO-8910 and SKOV3 cells were transfected with SYF2 siRNAs and negative control. We found that the protein levels of SYF2 were decreased both in HO-8910 and SKOV3 cells and SYF2-siRNA2 could obviously knock them down by Western blot analysis (Fig. 6a, b). During the experiments as followed, SYF2-siRNA2 was used to knock down the expression of the SYF2 in both HO-8910 and SKOV3 cells. We also found that, compared with negative control, knocking Table 3 Contribution of various potential prognostic factors to survival by Cox regression analysis on 119 human ovarian cancer specimens Hazard ratio P valuea 95.0 % Confidence interval Histologic grade

16 65

Statistical analyses were performed by the Pearson’s χ2 test

*P<0.05 was considered significant

P valuea

were independent prognostic indicators for patients’ overall survival (Table 3).

<0.001*

0.521

<0.001* 0.374–0.725

SYF2 expression 0.399 Ki-67 expression 5.068

0.005* 0.210–0.760 <0.001* 2.595–9.899

a

Statistical analyses were performed by the Cox regression analysis

*P<0.05 was considered significant

Tumor Biol.

Fig. 5 SYF2 expression promoted proliferation of EOC cells. a, b Flow cytometry quantitation of cell cycle progress in HO-8910 and SKOV3 cells. The cells after serum starvation for 48 h and then addition of medium containing 10 % FBS for the indicated time points (0, 4, 8, 12, 24 h). c, d HO-8910 and SKOV3 cells harvested and analyzed for SYF2, and cell-cycle-related molecules including PCNA and cyclin D1 expression

by Western blot assay following the serum starvation and refeeding experiment. GAPDH was used as loading control. e, f The histograms below demonstrated the ratio of SYF2, PCNA, and cyclin D1 protein to GAPDH for each time point by densitometry. Mean±SEM of three independent experiments. (n=3, *,#,^P<0.05, compared with control cells serum-starved for 48 h)

down SYF2 expression by siRNA caused failing to accumulate cyclin D1 and PCNA (Fig. 6e, f). Additionally, we also found that HO-8910 and SKOV3 cells treated with siRNA

exhibited a declining cell proliferation rate compared with the negative control siRNA by CCK-8 assay (Fig. 6g, h). Next step, we detected the cell cycle distribution of EOC cells

Tumor Biol.

Fig. 6 Knockdown of the expression of SYF2 inhibited proliferation of EOC cell lines. a, b SYF2 protein level detected by Western blot 48 h after siRNA transfection of HO-8910 and SKOV3 cells. The results showed that si-SYF2#2 had the highest knockdown efficiency of the three siRNAs tested. c, d The bar chart below demonstrates the ratio of SYF2 protein to GAPDH by densitometry. The data are mean±SD (P<0.05 compared with the control). e, f Western blot analysis showed the levels

of cyclin D1 and PCNA in SYF2 knockdown by si-SYF2#2 HO-8910 and SKOV3 cells. Data are presented as means±SD. *,^P<0.05, compared with the control group. g, h The comparison in growth curves between the cells treated with SYF2 si-SYF2#2 and negative control siRNA by using CCK-8 assay. i, j Flow cytometric analysis of cell cycle distribution 48 h later following control siRNA and si-SYF2#2 transfection. The data are mean±SD (P<0.05 compared with the control)

transfected with SYF2-siRNA2 and the negative control by fluorescence-activated cell sorting (FACS). Compared with

the negative control, we can see that the cell (treated with SYF2-siRNA2) quantity was increased in the G0/G1 phase,

Tumor Biol.

while that in the S phase was decreased (Fig. 6i, j). These results suggested that SYF2 may impact the G0/G1-S transition and thus the cell growth. With all these, knocking down the expression of SYF2 would inhibit proliferation of EOC.

Discussion Ovarian cancer (OC) is the leading cause of death among gynecologic malignancies in the world [3]. Yet, due to population expansion and the increasing proportion of the aged ones, a rise of OC incidence has been observed in Asian countries such as China and Japan [21, 22]. Epithelial ovarian cancer (EOC) accounts for approximately 70 % of all ovarian malignancy diseases. To date, the underlying molecular mechanisms that determine the biologic behavior of EOC remain poorly understood. Apprehension of the molecular basis of EOC will significantly refine the diagnosis and managements of these tumors and will eventually lead to the progress of more specific, effective treatment modalities [23]. In the present study, we demonstrate the functional role and clinical significance of SYF2 expression in EOC. As a yeast homolog of p29, SYF2 was reported in that the depletion of ISYL1 and SYF2 will lead to tubulin decrease under conditions of temperature restrictiveness and will cause inhibition of cell cycle in G2/M phase [24]. Nevertheless, in another article, it was shown that, under the circumstances of SYF2 deficit, cell cycle will be inhibited in G1 stage and synthesis of DNA will decrease [7]. Abnormal embryologic development and embryonic lethal change can be found in transgenic mice with depletion of SYF2, and lower znp29 in zebra fish is lethal to the embryo [10]. Cyclin D1, which is a member of the D-type cyclins, promotes cell cycle progression through G1 phase by combining with cyclin-dependent kinase (CDK)-4 and -6. It reported that SYF2 was overexpressed in glioma samples, and a significantly positive correlation between SYF2 level and glioma malignancy also plays a role in regulating glioma cell proliferation in a cell-cycle-dependent pathway [17]. Recently, it has been found that the expression level of SYF2 is unregulated in esophageal squamous cell carcinoma (ESCC), serum starvation-refeeding experiment, and SYF2-siRNA transfection assay, demonstrating that SYF2 expression promoted proliferation of ESCC cells, while SYF2 knockdown led to decreased cell growth rate and colony formation resulted from growth arrest of cell cycle at G0/G1 phase [16]. And in our paper, we found that SYF2 was overexpressed in EOC tissues and EOC cells and was involved in proliferation of EOC cells through cell cycle pathway. In our research, we demonstrated that SYF2 might be an important prognosis factor in EOC. At first, Western blot and immunohistochemistry analysis revealed that SYF2 was overexpressed in EOC tissues and EOC cells and found that

there was a significantly positive correlation between SYF2 level and EOC. Both SYF2 and Ki-67 were predominant in the nucleus, and SYF2 expression was positively correlated with Ki-67 expression. Accordingly, Kaplan–Meier survival analysis showed that high expression of SYF2 trended poor prognosis of all EOC patients. Furthermore, we demonstrated that SYF2 promoted the proliferation of EOC by serum starvation and release experiments and CCK-8 assay. Knockdown of SYF2 expression by siRNA could downregulate the expression of PCNA and cyclin D1 in HO-8910 cells and SKOV3 cells. Besides, flow cytometry analysis demonstrated that SYF2 participated in cell cycle of EOC cells, and knockdown of the expression of SYF2 resulted in the arrest of cell cycle at G0/G1 phase. In summary, we proved that SYF2 was upregulated in EOC tissues and EOC cells, and its expression was positively correlated with proliferation of EOC. Knocking down SYF2 could inhibit the cell proliferation of EOC. From these experimental data, we can believe that SYF2 may potentially be a novel target for pharmaceutical treatment of EOC. Acknowledgments This work was supported by the National Natural Science Foundation of China (No. 81302285). Conflict of interest None.

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