Objective To explore the value of retinoblastoma binding protein 4 ( RBBP4 ) in diagnosing prostate cancer ( PCa).Methods From January 2015 to December 2015, the prostate tissue after prostatectomy were collected and the differentially expressed degree of RBBP4 protein was analyzed in PCa and adjacent tissues by 2D-DIGE technology.The RBBP4 score of prostate tissue chip which contains 3 normal prostate tissues, 7 cancer adjacent normal prostate tissues, 50 adenocarcinoma and 20 hyperplasia tissue was checked by immunohistochemistry( IHC).In 50 patients with PCa, 4 cases were less than 60 years old and 46 cases were more than 60 years.In those patients, the Gleason scores were less than 7 scores in 18 cases, and more than 7 scores in 30 cases.22 cases were confirmed less than Ⅱ stage, and 28 cases were confirmed more than Ⅲ stage.Finally, the RBBP4 IHC score and the clinic-pathological parameters such as age, Gleason score and clinical stage of PCa patients were analyzed together.Results We found that the protein of RBBP4 increased by 2.15 times in PCa tissues compared to adjacent tissues by using 2D-DIGE technology( P=0.008).The expression of RBBP4 was higher than that in benign tissues by IHC ( F=43.972,P=0.000).And the expression of RBBP4 was positive correlation with Gleason score( t=5.589, P=0.000) and clinical stage(t=5.620,P=0.000), but was negative correlation with age(t=1.125,P=0.266).Conclusions The detection of RBBP4 can help to separate PCa from benign tissues.The overexpression of RBBP4 might result in the rapid growth of malignant cells.It may have certain value in determine the clinical staging and pathological grading of PCa.

Objective To explore the role and clinical significance of GSTM 3 ( glutathione S-trans-ferase mu 3) expression in prostate cancer (PCa). Methods We had used the two-dimensional fluores-cence difference gel electrophoresis ( 2D-DIGE) and mass spectral analysis to further verify the microarray data of mRNA expression profiling discovered .GSTM3 mRNA level was detected by Rael-time Quantitative PCR ( RT-QPCR) in 28 pairs of prostate cancer tissue and benign tissue .The relationship of GSTM 3 level with the serum PSA level and the clinical feature of PCa were analyzed . Results In 2D-DIGE study, we found that the expression of GSTM 3 protein in adjacent tissues was significantly higher than that in PCa tis-sues (P<0.05).RT-QPCR results showed that GSTM3 in adjacent tissues (8.12±0.51) was significantly higher than that in PCa tissues (7.18±0.54) (P<0.05).There was no significant difference of GSTM3 ex-pression in different serum PSA packets ( P>0.05) and prostate cancer clinical pathological parameters ( P>0.05). Conclusions GSTM3 expression is down-regulated in PCa tissues, and we may identify PCa by detecting the GSTM 3 expression .

Objective To detecte the expression of Apelin ( APLN) in prostate cancer tissue and to investi-gate its correlation with prognosis of prostate cancer .Methods Collect prostate cancer patients in Department of Urology of Huadu District People's Hospital for 2014 -2016 years in Guangzhou .The expression of APLN was detected by real-time fluorescence quantitative polymerase chain reaction ( qRT-PCR) in 20 prostate cancer tissues and 20 adjacent normal tissues.The difference between the two groups was compared .And 104 samples of primary prostate cancer and 28 samples of benign paracancerous tissues from the Taylor database were selected to analyze its relationship with the clinical features and prognosis of the patients .Results Compared with the benign paracancerous tissue(7.26 ±0.03),APLN was up-regulated in the prostate cancer tissue (7.62 ±0.42)(t=3.824,P<0.001). The up-regulation of APLN was associated with pathological stage (t=2.942,P=0.003),metastasis(t=3.022, P<0.001),Gleason score (t =2.399,P =0.031),the biochemical recurrence -free survival(t =2.533,P =0.001 ) ,and the biochemical recurrence -free survival of the patients with higher expression of APLN was shorter than that of the patients with lower expression of APLN(χ2 =6.268,P=0.012).Conclusion The abnormal expres-sion of APLN may be associated with tumor formation and malignant progression of prostate cancer .High expression of APLN can predict the biochemical recurrence -free survival in patients with prostate cancer .

Objective We used the dataset base on high throughput sequencing data to construct a diagnosis model by ANN and GA.Methods We screened the Taylor_prostate datasets from GEO according to,then we used the GA to screen the datas further. Finally we used the ANN to analyze the datas and construct a diagnosis model. To validate the model,we used 10-folds crossvalidation as the inner validation and the datas from Grasso dataset( GPL6480 and GPL6848) were used as the outter validation.Results We got 5 genes ACADL,ACTG2, CACNA2D1,PCP4 and SPARCL1.And we used spss to get the AUC of the model which is 94.62.The result of validation is good.Conclusion The performance of the model is good because the AUC is larger than 0.5.