CDKN3 is an independent prognostic factor and promotes ovarian carcinoma cell proliferation in ovarian cancer
- Authors:
- Published online on: February 20, 2014 https://doi.org/10.3892/or.2014.3045
- Pages: 1825-1831
Abstract
Introduction
Ovarian cancer is one of three major female malignant tumors of the reproductive system. Its incidence is ranked third following cervical and uterine cancer (1). Due to its high malignant potential, the mortality rate of ovarian cancer ranks first among all gynecologic cancers in China. To date, the pathogeny of ovarian cancer is unclear. It is believed that the incidence may be related to environment, hormonal, genetic and other factors. According to different clinical pathological types and genetic features, ovarian cancer can be divided into type I and type II (2). The ovarian malignant progression of type I is low, including low grade serous ovarian cancer, mucinous ovarian cancer and clear cell ovarian cancer. The mutated BRAF or PTEN gene mainly exhibits abnormal expression in this type of ovarian cancer (3). Type II ovarian cancer has a high degree of malignancy, in which BRCA1 and BRCA2 gene mutations are common and the main pathological type is malignant serous ovarian cancer (4–6).
At present, the scientific community believes that a tumor is a disease caused by multiple genomic changes, and tumor progression is based on oncogene activation and/or tumor-suppressor gene deactivation with gene function mutation. Continual growth signal stimulation, evasion of growth inhibition, resistance to the replication of programmed cell death, induction of tumor angiogenesis, and activation of invasion and metastasis are necessary physiological changes leading to different types of malignant tumor cell growth (7). During development, most tumors undergo similar changes in cell physiological characteristics, thus oncogenes and tumor-suppressor genes that are closely associated with these acquired cell behaviors have become a ‘hot’ topic in the study of tumor molecular mechanisms and cancer treatment.
Cyclin-dependent kinase 3 (CDKN3), a member of the family of protein phosphatase inhibitors, participates in the management of the cell cycle, where it plays a dual role (8,9). CDKN3 plays the role of a cell cycle protein-dependent kinase inhibitor and selectively combines with CDK2 (10,11), reducing Rb protein (retinal cell tumor protein, a tumor-suppressor gene) phosphorylation (9). Phosphorylation of Rb protein combined with transcriptional factor E2F1 inhibits cell cycle protein, which is required for G1/S transition, thus blocking G1 to S phase shift (12,13). CDKN3, also a type of Mdm2 protein, combines with p53 and Mdm2, reduces the sensitivity of p21 and reduces p53 target gene production, so as to promote the progression of the cell cycle (14). The CDKN3 gene was demonstrated to exhibit abnormal expression in many types of tumors (15–17). However, its relationship with ovarian cancer and its molecular role has not been reported.
Materials and methods
Patient tissue samples
Ninety-seven ovarian cancer (OC) tissues were collected from patients who underwent routine ovarian resection at The First Affiliated Hospital of China Medical University. None of the specimens were pretreated with preoperative chemotherapy, radiation therapy, or other treatment. All specimens were respectively assessed by two pathologists for pathological diagnosis according to the World Health Organization classification system. The clinicopathologic factors are documented in Table I. Total RNAs and protein were collected from the fresh OC tissues after surgical resection. The study protocol was approved by the Institutional Ethics Committee of China Medical University, and all patients provided written informed consent.
 | Table ICorrelation of CDKN3 expression and the clinicopathological characteristics of the EOC patients. |
Immunohistochemistry
CDKN3 expression was evaluated by immunohistochemistry (IHC) on 5-μm paraffin-embedded tissue sections. Rabbit anti-CDKN3 (1:200; Santa Cruz Biotechnology, Santa Cruz, CA, USA) was used. Sections were stained with 3,3′-diaminobenzidine. Normal rabbit serum was used as a negative control. The CDKN3 immunostaining score was analyzed according to a semi-quantitative scale. Cytoplasmic/nuclear immunostaining was considered positive staining. The percentage of positive cells was scored as follows: 0 (0%), 1 (1%–10%), 2 (11%–50%), 3 (51%–80%) or 4 (>80%). The intensity of staining was defined as follows: no, ‘0’; weak, ‘1’; moderate, ‘2’ and strong staining, ‘3’. Each sample was given a final score ranging from 0 to 12. CDKN3 expression was divided into four levels: −, score 0; 1+, score 1–4; moderate expression 2+, score 4–8; and 3+, score 9–12. The immunohistochemical results of CDKN3 were grouped into low expression (0 to 1+) and high expression (2+ to 3+).
Western blot analysis
Total protein was separated from tissues and cells using lysis buffer (Pierce, Rockford, IL, USA) and quantified by the Bradford method. Total protein (50 μg) was subjected to 10% SDS-PAGE and electrotransferred to PVDF membranes (Millipore, Billerica, MA, USA), which were blocked with blocking buffer (Beyotime, China) for 1 h at room temperature. The primary CDKN3 rabbit polyclonal antibody (1:1000; Santa Cruz Biotechnology, USA) and mouse anti-β-actin antibody (1:1000; Santa Cruz Biotechnology) were incubated on the PVDF membranes at 4°C overnight. The membranes were incubated with secondary antibodies for 2 h at room temperature (1:5000; Beyotime). The relative protein levels were visualized using an ECL system (Pierce).
Cell culture and siRNA treatment
OVCAR3 cancer cells were obtained from the Cell Biology China Academy of Science (Shanghai, China) and cultured in RPMI-1640 medium (Invitrogen, Carlsbad, CA, USA) containing 10% fetal calf serum. The cells were cultured in a 24-well plate at a density of 6×104 cells/well and transfected with siRNA-CDKN3 or Neg. siRNA using the Lipofectamine LTX reagent (Invitrogen) according to the manufacturer’s protocol. CDKN3 siRNAs (purchased from GenePharma Co., Ltd., Shanghai, China) were as follow: CCAUCAAGCAAUACAAUUATT (si-CDKN3#1) and CUGCUUGUCUCCUACUAUATT (si-CDKN3#2).
Colony formation and MTT assay
For the colony formation assay, 100 cells were plated into 6-well plate culture dishes and incubated for 10 days. Plates were stained with 0.1% crystal violet, and colonies with more than 50 cells were counted. For the MTT assay, cells were plated at ~2000 cells/well in 96-well plates in medium containing 10% FBS 24 h after transfection. Then, 20 μl of 5 mg/ml MTT (KeyGen Bio., Nanjing, China) solution was added to each well and incubated for 4 h at 37°C. The media were removed from each well, and the resultant MTT formazan product was solubilized in 150 μl of DMSO. The results were quantitated using a test wavelength of 490 nm.
Cell cycle analysis
OVCAR3 cells were plated in a 6-well plate at a density of 1×105 cells/well. Cells were collected after 24 h and washed in cold PBS, and fixed in 75% cold ethanol. Then the cells were centrifuged at 800 rpm and washed with cold PBS. RNase A and propidium iodide solution were added, and the cells were incubated at room temperature for 30 min in the dark. Cell cycle analysis was performed in a flow cytometer (FACSCalibur; BD Biosciences, USA), and ModFit LT software was used to analyze the percentage of cells in each cell cycle phase.
Transwell assay
OVCAR3 cells (5×104), with 200 μl serum- free RMPI-1640, were added to the upper layer which was coated with 20 μl Matrigel (1:4 dilution; Costar, Corning, NY, USA). RMPI-1640 containing 10% FBS was added to the lower layer, and incubation was carried out for 24 h in a cell incubator. The cells that penetrated the membrane of the chamber were stained with 0.1% crystal violet for 20 min. Cells on the upper membrane were wiped off with a cotton tip. The number of invasive cells were analyzed in 5 random fields under a microscope. The experiments were performed in triplicate.
Statistical analysis
The statistical data were analyzed by SPSS 13.0. The correlation between CDKN3 expression and EOC patient clinicopathological features was analyzed using the χ2 test. The t-test was used to compare messenger RNA (mRNA) in various groups. Kaplan-Meier method was used to evaluate the patient overall survival. A Cox regression model was used to demonstrate the univariate and multivariate analyses of prognostic variables. P<0.05 was considered to indicate a statistically significant result.
Results
CDKN3 expression in the EOC tissue samples and cell lines
CDKN3 protein levels in 30 EOC and 30 HOSE tissues were determined and the results showed that CDKN3 was expressed weakly in the HOSE tissues (20/30), while CDKN3 expression was upregulated >2-fold in 76.7% (23/30) of the EOC tissues (EOC/HOSE >2) (Fig. 1A and B). The mean level of CDKN3 expression in the EOC tissues was 3.35-fold that in the HOSE tissues (Fig. 1C). Western blotting analysis revealed that expression of the CDKN3 protein was markedly higher in the EOC tissues and the OVCAR3 cell line when compared with the levels in the HOSE samples (Fig. 1D and E). In addition, CDKN3 protein expression in OVCAR3 cells transfected with the CDKN3 siRNA showed efficient depletion (Fig. 1F). As shown in Fig. 2, the IHC staining intensity and positivity of CDKN3 in the representative tissues were highly expressed (66/97, 68.0%) and weakly expressed (31/97, 32.0%; Fig. 2A and B), while negative expression was noted in the HOSE tissues (Fig. 2C).
Correlation of the clinical characteristics and CDKN3 expression in the EOC cases
CDKN3 expression levels and clinicopathological characteristics of the EOC patients are summarized in Table I. High expression of CDKN3 was detected in 68.0% (66/97) of the patients and low expression of CDKN3 was noted in 32.0% (31/97) of the EOC patients. High levels of CDKN3 expression were significantly associated with FIGO stage, recurrence and residual tumor size, but no significant correlation was noted with patient age, tumor type, serum Ca-125 level and histological type. Overall survival and disease-free survival were significantly reduced in patients with high CDKN3 expression than in patients with low CDKN3 expression (P<0.05, Fig. 3A and B). Furthermore, multivariate analysis demonstrated that a high level of CDKN3 expression was an independent predictor of prognosis of EOC patients, and was associated with increased risk of a poor prognosis (hazard ratio, 1.661; P=0.005) (Table II).
| Table IIUnivariate and multivariate analyses of factors correlated with overall survival of the EOC patients. |
Depletion of CDKN3 expression suppresses OVCAR3 cell proliferation
MTT assay showed that downregulation of CDKN3 expression significantly reduced the viability of the OVCAR3 cell line (Fig. 4A). The depletion of CDKN3 in the OVCAR3 cells (si-CDKN3#1 and si-CDKN3#2 vs. Neg. Cont.: 45±11 and 34±9 vs. 81±13; P<0.05) also led to a significant reduction in the number and size of foci (Fig. 4B). The DNA content using flow cytometry demonstrated that CDKN3 siRNA transfection increased the percentage of cells in the G1 phase and decreased those in the S phase in the OVCAR3 cell line (P<0.05, Fig. 5). As shown in Fig. 6, the depletion of CDKN3 in OVCAR3 cells did not have a measurable blocking effect on cell invasion.
Discussion
The mechanisms of the cell cycle and cancer is one of the ‘hot’ subjects in the field of oncology research in recent years. The cell cycle is the basic process of life activity. Under normal circumstance, cells enter into the physiological state of proliferation, differentiation, aging and death through normal cell cycle phases. If abnormal cell cycle regulation occurs, the cell enters into a cancerous state. Thus, cell cycle regulation is the core event of cell proliferation regulation, which has a close relationship with cellular carcinogenesis. Involved in cell cycle regulation are: cell cycle proteins (cyclins), cell cycle protein-dependent kinases (cyclin-dependent kinases, CDKs) and cell cycle protein kinase inhibitors (cyclin-dependent kinase inhibitors, CKI/CDKN). Cyclins consist of 8 members, respectively named cyclin A to H. CDK consist of 7 members, respectively named CDK1–7.
CKI/CDKN, a newly discovered protein, inhibits CDK kinase activity combined with CDK, cyclin or cyclin-CDK complex. In the present study, 97 EOC samples were analyzed by χ2 test, indicating that CDKN3 expression had a close relationship with EOC proliferation and tumor recurrence, and it may play a significant role in tumor carcinogenesis and EOC progression. Based on Kaplan-Meier analysis, we discovered that high expression of CDKN3 indicates the poor prognosis of EOC patients, suggesting that it can represent a novel prognostic factor for EOC. This was the first time we evaluated the relationship among CDKN3, clinicopathological features and prognosis in EOC. Furthermore, we recognized that CDKN3 may be used as a novel independent prognostic biomarker to predict the overall survival rate of EOC patients based on the univariate and multivariate Cox hazards analysis. This function of CDKN3 corroborated the results of studies concerning renal cancers and hepatocellular carcinomas (18,19). In previous research, several predictors similar to CDKN3, such as p19INK4d (20), CD163 (21), KPNA2 (22) and p21Waf1/Cip1 (23), were recognized as being related to the prognosis of EOC. To date, however, it is still not definitely confirmed whether indices of this type could be a substitute for predicting the prognosis of EOC. Therefore, further research must be carried out to determine whether CDKN3 together with other molecules of this category may be valuable for determining the prognosis of EOC.
To better understand the biological function of CDKN3, we investigated whether depletion of CDKN3 reduces the malignant phenotypes in EOC cell lines. CDKN3 was previously found to be relatively highly expressed in various cancer cell lines (18,23). Antisense KAP (CDKN3) in HeLa and LNCaP cells exhibited S-phase reduction and also suppression of the cell growth rate in vivo and in vitro (24). Accordingly, we reasoned that CDKN3 may play a role in the regulation of cell growth in ovarian cancer cell lines. We examined the colony formation potential and cell growth rate in OVCAR3 cells following siRNA treatment. We found that OVCAR3 knockdown caused a significant reduction in the proliferation rate and colony formation ability. Therefore, CDKN3 overexpression stimulated malignant cell proliferation. Moreover, we analyzed the role of CDKN3 on cell cycle progression, similar to previous studies (16,25,26), CDKN3 inhibited cell cycle progression in OVCAR3 cells. These data together demonstrated that CDKN3 had a measurable effect on ovarian cancer cell proliferation.
Invasion and metastasis are biological characteristics of malignant tumors, and pose the most problems for clinical treatments. Recent studies indicate that CDKN3 is positively correlated with metastasis of neuroendocrine tumors when compared with their non-metastatic counterparts (27). However, in our study, we did not find such an association. Transwell cell migration assays showed that CDKN3 knockdown did not have a measurable effect on OVCAR3 cell invasion. This finding is coincident with the clinical data of Xing et al (16) in liver cancer. A possible explanation is possibly that tumor cells which express CDKN3 are not able to migrate from the primary tumor site, leading to reduction in metastatic potential, yet CDKN3 expression could support tumor cell survival and proliferation. In addition, CDKN3 may have different influence on cancer cells in various cancer types.
Another issue involves the mechanism of how CDKN3 promotes ovarian cancer progression. A previous study reported that p21 interacts with cyclin/CDK complexes and PCNA to inhibit their kinase activities (28), and CDKN3 could promote the proliferation of liver cells through a p53-p21 manner to induce G1/S phase transition (16). Other studies have shown that CDKN3 through its protein product KAP regulates the cell cycle. It regulates retinoblastoma protein (pRb) activation via a phosphorylation mechanism that is responsible for G1 to S transition (29,30). Currently, one hypothesis of this mechanism is the hypomethylation of its promoter region (9). This hypothesis warrants further study.
In conclusion, this study identified CDKN3 as an oncoprotein overexpressed in EOC which is important for the maintenance of the malignant phenotype and recognized CDKN3 as a candidate target protein for future cancer therapeutics.
Acknowledgements
This study was supported by grants from the National Natural Science Foundation of China (no. 81171649 to Yi Guo).
References
|
Jemal A, Siegel R, Xu J and Ward E: Cancer statistics, 2010. CA Cancer J Clin. 60:277–300. 2010. View Article : Google Scholar | |
|
Dundr P: Ovarian carcinoma: current diagnostic principles. Cesk Patol. 46:53–61. 2010.(In Czech). | |
|
Seidman JD, Ronnett BM and Kurman RJ: Pathology of borderline (low malignant potential) ovarian tumours. Best Pract Res Clin Obstet Gynaecol. 16:499–512. 2002. View Article : Google Scholar : PubMed/NCBI | |
|
Seidman JD and Kurman RJ: Pathology of ovarian carcinoma. Hematol Oncol Clin North Am. 17:909–925. vii2003. View Article : Google Scholar : PubMed/NCBI | |
|
Westfall D, Roma AA and Silva EG: High-grade serous carcinoma of the ovary. Ann Diagn Pathol. 13:285–290. 2009. View Article : Google Scholar : PubMed/NCBI | |
|
Vang R, Shih Ie M and Kurman RJ: Ovarian low-grade and high-grade serous carcinoma: pathogenesis, clinicopathologic and molecular biologic features, and diagnostic problems. Adv Anat Pathol. 16:267–282. 2009. View Article : Google Scholar : PubMed/NCBI | |
|
Tarin D: Inappropriate gene expression in human cancer and its far-reaching biological and clinical significance. Cancer Metastasis Rev. 31:21–39. 2012. View Article : Google Scholar : PubMed/NCBI | |
|
Patterson KI, Brummer T, O’Brien PM and Daly RJ: Dual-specificity phosphatases: critical regulators with diverse cellular targets. Biochem J. 418:475–489. 2009.PubMed/NCBI | |
|
Niculescu MD, Yamamuro Y and Zeisel SH: Choline availability modulates human neuroblastoma cell proliferation and alters the methylation of the promoter region of the cyclin-dependent kinase inhibitor 3 gene. J Neurochem. 89:1252–1259. 2004. View Article : Google Scholar : PubMed/NCBI | |
|
Yeh CT, Lu SC, Chen TC, Peng CY and Liaw YF: Aberrant transcripts of the cyclin-dependent kinase-associated protein phosphatase in hepatocellular carcinoma. Cancer Res. 60:4697–4700. 2000.PubMed/NCBI | |
|
Yeh CT, Lu SC, Chao CH and Chao ML: Abolishment of the interaction between cyclin-dependent kinase 2 and Cdk-associated protein phosphatase by a truncated KAP mutant. Biochem Biophys Res Commun. 305:311–314. 2003. View Article : Google Scholar : PubMed/NCBI | |
|
Blum R, Nakdimon I, Goldberg L, et al: E2F1 identified by promoter and biochemical analysis as a central target of glioblastoma cell-cycle arrest in response to Ras inhibition. Int J Cancer. 119:527–538. 2006. View Article : Google Scholar : PubMed/NCBI | |
|
Wu L, Timmers C, Maiti B, et al: The E2F1-3 transcription factors are essential for cellular proliferation. Nature. 414:457–462. 2001. View Article : Google Scholar : PubMed/NCBI | |
|
Demetrick DJ, Matsumoto S, Hannon GJ, et al: Chromosomal mapping of the genes for the human cell cycle proteins cyclin C (CCNC), cyclin E (CCNE), p21 (CDKN1) and KAP (CDKN3). Cytogenet Cell Genet. 69:190–192. 1995. View Article : Google Scholar : PubMed/NCBI | |
|
MacDermed DM, Khodarev NN, Pitroda SP, et al: MUC1-associated proliferation signature predicts outcomes in lung adenocarcinoma patients. BMC Med Genomics. 3:162010. View Article : Google Scholar : PubMed/NCBI | |
|
Xing C, Xie H, Zhou L, et al: Cyclin-dependent kinase inhibitor 3 is overexpressed in hepatocellular carcinoma and promotes tumor cell proliferation. Biochem Biophys Res Commun. 420:29–35. 2012. View Article : Google Scholar : PubMed/NCBI | |
|
Taylor KJ, Sims AH, Liang L, et al: Dynamic changes in gene expression in vivo predict prognosis of tamoxifen-treated patients with breast cancer. Breast Cancer Res. 12:R392010. View Article : Google Scholar : PubMed/NCBI | |
|
Lai MW, Chen TC, Pang ST and Yeh CT: Overexpression of cyclin-dependent kinase-associated protein phosphatase enhances cell proliferation in renal cancer cells. Urol Oncol. 30:871–878. 2012. View Article : Google Scholar : PubMed/NCBI | |
|
Wang L, Sun L, Huang J and Jiang M: Cyclin-dependent kinase inhibitor 3 (CDKN3) novel cell cycle computational network between human non-malignancy associated hepatitis/cirrhosis and hepatocellular carcinoma (HCC) transformation. Cell Prolif. 44:291–299. 2011. View Article : Google Scholar | |
|
Felisiak-Golabek A, Dansonka-Mieszkowska A, Rzepecka I, et al: p19 mRNA and protein expression as new prognostic factor in ovarian cancer patients. Cancer Biol Ther. 14:973–981. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
No JH, Moon JM, Kim K and Kim YB: Prognostic significance of serum soluble CD163 level in patients with epithelial ovarian cancer. Gynecol Obstet Invest. 75:263–267. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Huang L, Wang HY, Li JD, et al: KPNA2 promotes cell proliferation and tumorigenicity in epithelial ovarian carcinoma through upregulation of c-Myc and downregulation of FOXO3a. Cell Death Dis. 4:e7452013. View Article : Google Scholar : PubMed/NCBI | |
|
Bali A, O’Brien PM, Edwards LS, Sutherland RL, Hacker NF and Henshall SM: Cyclin D1, p53, and p21Waf1/Cip1 expression is predictive of poor clinical outcome in serous epithelial ovarian cancer. Clin Cancer Res. 10:5168–5177. 2004. View Article : Google Scholar : PubMed/NCBI | |
|
Lee SW, Reimer CL, Fang L, Iruela-Arispe ML and Aaronson SA: Overexpression of kinase-associated phosphatase (KAP) in breast and prostate cancer and inhibition of the transformed phenotype by antisense KAP expression. Mol Cell Biol. 20:1723–1732. 2000. View Article : Google Scholar : PubMed/NCBI | |
|
Chinami M, Yano Y, Yang X, et al: Binding of HTm4 to cyclin-dependent kinase (Cdk)-associated phosphatase (KAP). Cdk2cyclin A complex enhances the phosphatase activity of KAP, dissociates cyclin A, and facilitates KAP dephosphorylation of Cdk2. J Biol Chem. 280:17235–17242. 2005. View Article : Google Scholar : PubMed/NCBI | |
|
Yu Y, Jiang X, Schoch BS, Carroll RS, Black PM and Johnson MD: Aberrant splicing of cyclin-dependent kinase-associated protein phosphatase KAP increases proliferation and migration in glioblastoma. Cancer Res. 67:130–138. 2007. View Article : Google Scholar : PubMed/NCBI | |
|
Lee J, Sung CO, Lee EJ, et al: Metastasis of neuroendocrine tumors are characterized by increased cell proliferation and reduced expression of the ATM gene. PLoS One. 7:e344562012. View Article : Google Scholar : PubMed/NCBI | |
|
Chen J, Jackson PK, Kirschner MW and Dutta A: Separate domains of p21 involved in the inhibition of Cdk kinase and PCNA. Nature. 374:386–388. 1995. View Article : Google Scholar : PubMed/NCBI | |
|
Barford D: The mechanism of protein kinase regulation by protein phosphatases. Biochem Soc Trans. 29:385–391. 2001. View Article : Google Scholar : PubMed/NCBI | |
|
Johnson LN, De Moliner E, Brown NR, et al: Structural studies with inhibitors of the cell cycle regulatory kinase cyclin-dependent protein kinase 2. Pharmacol Ther. 93:113–124. 2002. View Article : Google Scholar : PubMed/NCBI |
