Expression Of Centromere Protein F Predicts Clinical Progression And Prognosis In Patients With Prostate Cancer

Background and objectives:Prostate cancer (PC a) is one of the most frequently diagnosed cancers among males, and is the second leading cause of cancer-related mortality in Western countries. More than 900,000 new cases of PCa are diagnosed worldwide each year. In 2014, approximately 24% of new cancer cases among American males are PCa. The incidence and mortality of PCa in China also appears to be continuously increasing. As a clinically heterogeneous multifocal disease, its natural history is highly variable and difficult to predict. The mechanisms influencing the progression and prognosis of PCa are multistep processes, including both genetic insults to epithelial cells and alterations in epithelial-stromal interaction. Due to the innovation of surgical techniques and the reduced incidence of surgical complications, many patients with localized PCa have experienced long-term survival through the intervention of radical prostatectomy. However, approximately 20% of patients with PCa suffer from biochemical recurrence (BCR) following radical prostatectomy or radiation and require further interventions. Furthermore, no effective therapeutic treatment is yet available for recurrent or metastatic disease from failed surgery, radiation, chemotherapy or hormonal therapy. Clinical variables, such as serum prostate-specific antigen (PSA) levels, Gleason score (GS), margin status and the response to initial treatment, in various combinations, have been used to predict the disease outcome. However, currently there are no definitive clinical methods for the diagnosis and determination of the disease outcome. Therefore, it is of great importance to identify novel and effective biomarkers involved in the fundamental aspects of tumor biology to provide valuable information for the early diagnosis and tumor progression of PCa.Although there has been limited success in identifying high-risk susceptibility genes analogous to breast cancer 1, early onset (BRCA1) or breast cancer 2, early onset (BRCA2) for breast and ovarian cancer, some candidate susceptibility genes which are associated with the initiation and progression of PCa have been identified, such as the amplified genes on chromosomes 1 and X.The cell cycle progression (CCP) score, a novel RNA expression signature derived from 31 CCP genes, has recently been shown to be a strong predictor of clinical outcome in patients with PCa. Centromere protein F (CENPF), at chromosome 1q41, is one of these 31 genes. It encodes a protein that acts as part of the centromere-kinetochore complex and is a component of the nuclear matrix during the G2 phase of interphase. CENPF is expressed in a cell cycle-dependent manner and is involved in chromosome segregation. CENPF gradually accumulates during the cell cycle until it reaches peak levels in the G2/M phase and is rapidly degraded upon the completion of mitosis. The results of previous studies have demonstrated that CENPF may play a role in the regulation of cell division and may be used as proliferation marker of malignant cell growth in clinical practice due its localization in the cell cycle. Accumulating evidences has demonstrated the involvement of CENPF in various types of human cancer, such as breast cancer, hepatocellular carcinoma, colorectal gastrointestinal stromal tumors, nasopharyngeal carcinoma, non-hodgkin’s lymphoma, salivary gland tumors and neuroblastic tumors. The overexpression of CENPF has also been reported to be associated with a poor prognosis in hepatocellular carcinoma, breast cancer, colorectal gastrointestinal stromal tumors and nasopharyngeal carcinoma. However, the clinical significance of CENPF in PCa has yet not been fully elucidated. Thus, the aim of the present study was to investigate the association of CENPF with tumor progression and prognosis in patients with PCa.Materials and Methods:To reliably identify the candidate genes that are associated with tumor progression and prognosis in patients with PCa, we examined the prognostic value of the 31 CCP genes by statistically analyzing the BCR-free survival in a microarray-based dataset (NCBI GEO accession no:GSE21032), contributed by Taylor et al (herein referred to as the Taylor dataset), which is a relatively large and diverse PCa dataset with microarray expression data for microRNAs (miRNAs or miRs) and protein coding genes (mRNAs). From the 218 prostate tumor samples in this dataset,149 matched normal samples,12 cell lines and xenografts, only 185 samples, including 150 PCa,29 adjacent normal tissue and 6 cell lines, had exon and whole-transcript expression. Thus, we selected these 185 samples for our research. In order to investigate the expression of CENPF at the mRNA level and perform survival analysis, the clinical information from the Taylor dataset, including 150 PCa tissues and 29 adjacent non-cancerous prostate tissues was also collected.For immunohistochemical analysis, a tissue microarray (TMA, n=180) including 99 primary PCa tissues and 81 adjacent non-cancerous prostate tissues was obtained from Shanghai Outdo Biotech Co., Ltd., (Shanghai, China; Cat no: hPro-Ade180PG-01), including detailed clinical information. Patients who had been administered chemotherapy or radiotherapy prior to surgery were excluded from this study.Immunohistochemical was performed as the following steps:The specimens were fixed in 10% neutral-buffered formalin and subsequently embedded in paraffin. The paraffin-embedded tissues were cut at 4μm and then deparaffinized with xylene and rehydrated for further peroxidase [3,3’-diaminobenzidine (DAB)] immunohistochemical staining using the Dako EnVision System (Dako Diagnostics AG, Zug, Switzerland). In brief, the tissueslides were subjected to proteolytic digestion and blocked with peroxidase, and were then incubated overnight with primary antibody against CENPF (rabbit polyclonal antibody, bs-7839R; Beijing Biosynthesis Biotechnology Co., Ltd., Beijing, China) at a dilution of 1:200 at 4℃. After washing with PBS, peroxidase-labeled polymer and substrate-chromogen were then employed to visualize the staining of the protein of interest. In each immunohistochemistry run, negative controls were carried out by omitting the primary antibody. Following counterstaining with hematoxylin, immunostaining was scored by 2 independent experienced pathologists, who were blinded to the clinicopathological data and clinical outcomes of the patients. The scores of the 2 pathologists were compared and any discrepancies in the scores were resolved by the re-examining of the stainings by both pathologists to achieve a consensus score. The immunolabeling of the cancer cells was evaluated. The number of positively stained cells in 10 representative microscopic fields was counted and the percentage of positive cells was also calculated. According to the antibody specification sheet, cytoplasmic staining was regarded as a positive signal. Given the heteogenicity of the staining of the target proteins, tumor specimens were scored in a semi-quantitative manner. Protein levels were determined by the percentage of staining (i.e., from 0 to 100%) and intensity level of staining [i.e.,0 (negative),1 (weak),2 (moderate) and 3 (strong)] in each tumor sample. A final immunoreactivity score (IRS) was obtained by multiplying the percentage of staining and the intensity level for each tumor sample.Statistical analysis.:Statistical analyses were performed by using SPSS version 17.0 software for Windows (SPSS Inc., Chicago, IL, USA). The independent Student’s t-test was used to analyze the results and data are expressed as the means ± SD. The Mann-Whitney test was used for non-normally distributed data. Statistical analysis were performed using Fisher’s exact test for any 2x2 tables, the Pearson χ2test for non-2x2 tables, Kaplan-Meier plots for survival analysis and the Cox proportional hazards regression model for univariate and multivariate survival analyses. Differences were considered statistically significant when the P-value was<0.05.Results:1. Selection of CENPF from the CCP genes.Since the expression of the 31 CCP genes is based on the RNA level, it is likely to represent a fundamental aspect and may prove to be useful in determining the clinical outcome of patients with PCa. Thus, we analyzed the 31 CCP genes in the Taylor dataset using Kaplan-Meier plots. The results revealed that the increased expression of 10 genes may correlate with a shorter BCR-free survival. In these 10 genes, CENPF may be used as a proliferation marker of malignant cell growth. At the same time, it has also been reported to be associated with a poor prognosis in various types of human cancer.2. CENPF protein expression is up-regulated in PCa clinical specimens.We first investigated whether the expression of CENPF is associated with clinical specimens of PCa using a TMA. In this TMA, the expression profile and localization of CENPF in the 99 PCa and 81 adjacent non-cancerous prostate tissues were examined by immunohistochemical analysis. Immunohistochemical staining revealed that CENPF immunostaining occurred mainly in the cytoplasm in the cells from the PCa tissue; however, weak or moderate staining was observed in the adjacent non-cancerous prostate tissues. Furthermore, the expression level of CENPF in the PCa tissues was significantly higher than that in the non-cancerous prostate tissues (IRS:PCa,177.98±94.096 vs. benign,121.30±89.596; P<0.001). Notably, during the assessment of immunostaining, we found that CENPF immunostaining occurred in the stroma between the cancer cells; however, moderate staining was observed in the benign prostate tissue. Furthermore, we analyzed these results from immunostaining with the limited clinical information from the TMA, but failed to find any significant association of CENPF expression with the clinicopathological characteristics of the patients with PCa.3. Association of CENPF mRNA expression with the clinicopathological characteristics of the patients with PCa.Although the increased expression of CENPF in the PCa tissues did not correlate with the clinicopathological characteristics at the protein level in our TMA cohort, we wished to analyze CENPF expression at the mRNA level. Similarly, the mRNA expression level of CENPF in the PCa tissues was significantly higher than that in the adjacent noncancerous prostate tissues at the mRNA level (PCa,5.67±0.47 vs. benign, 5.40±0.11; P<0.001). What is more, the Taylor dataset revealed that the increased expression of CENPF in the patients with PCa correlated with a higher GS (P=0.005), an advanced pathological stage (P=0.008), the presence of metastasis (P<0.001), a shorter overall survival (P=0.003) and PSA failure (P<0.001), giving us a fundamental knowledge of CENPF in clinical outcome of PCa. The expression of CENPF in the high GS group (GS>8) was also higher than that in the intermediate GS group (GS=7) (P=0.02) and the low GS group (GS<6) (P=0.013), although there was no statistically significant difference between the intermediate group and the low group.4. Prognostic implications of CENPF expression in PCa.Using the Taylor dataset, the association of CENPF expression with the overall survival and the BCR-free survival time of the patients with PCa were analyzed using Kaplan-Meier plots. The median CENPF expression in all the PCa tissues of the Taylor dataset was used as the cut-off value to divide all the PCa tissues into high (n=65) and low (n=75) CENPF expression groups. As illustrated in Fig.2, there was no statistically significant difference observed in the overall survival time between the 2 groups (P=0.417); however, the BCR-free survival of the patients with PCa with a high CENPF expression was significantly shorter than that of the patients with a low CENPF expression (P=0.012). In addition, univariate analysis revealed that there was a significant difference in the BCR-free survival [hazard ratio (HR),3.384; 95% confidence interval (CI),2.066-5.541; P<0.001] rates between the patients with a high CENPF expression and those with a low CENPF expression. Furthermore, multivariate analysis revealed that the upregulation of CENPF (HR,4.251; 95% CI, 1.372-13.167; P=0.012), a higher GS (HR,2.624,95% CI 1.671-4.119; P<0.001) and a higher pre-operative PSA level (HR,1.005; 95% CI,1.001-1.01; P=0.02) were independent predictors for a shorter BCR free-survival.Conclusions:1.CENPF can discriminate patients with prostate cancer from patients with benign prostate hyperplasia, suggesting that it may serve as a turmor promoter.2. The increased expression of CENPF in the cancer cells may correlate with clinical progression and may serve as a prognostic factor of the patients with PCa.3. The enhanced expression of CENPF in stromal cells may also a prognostic factor of the patients with PCa.4. CENPF may effect the progression and prognosis of patients with prostate cancer through regulating the chromosomal instability and cell cycle progression protein.5. By analyzing the CENPF expression in patients with prostate cancer, clinical doctors can predict the probability of early biochemical recurrence, and choose the better and effective ndividualized treatment for patients with prostate cancer.