PSAD In The Diagnosis Of Prostate Cancer And Multi-gene Test Predicts The Biochemical Recurrence Of Prostate Cancer

Part Ⅰ:PSA density in the diagnosis of prostate cancer in the Chinese population:results from the Chinese Prostate Cancer ConsortiumObjective:We performed this study to investigate the diagnostic efficacy of prostate specific antigen density（PSAD）in a large multi-center population in China,and to propose diagnostic reference criteria suitable for the Chinese population based on multi-center data.Methods:We included patients receiving prostate biopsies in 18 large referral hospitals in China（members of the Chinese Prostate Cancer Consortium）.Outpatients with prostate specific antigen（PSA）levels≥4.0 ng ml^-1 regardless of digital rectal examination（DRE）results or PSA levels<4.0 ng ml^-1 and abnormal DRE results were included.All the patients received initial transrectal or transperineal biopsies guided with transrectal ultrasound（TRUS）.The diagnostic performance of PSAD and the sensitivity and specificity for the diagnosis of prostate cancer（PCa）and high-grade prostate cancer（HGPCa,Gleason Score≥7）at different cutoff values were evaluated.Results:A total of 5220 patients were included in the study,and 2014（38.6%）of them were diagnosed with PCa.In patients with PSA levels ranging from 4.0 to 10.0 ng ml^-1,PSAD was significantly associated with PCa and HGPCa in both univariate（odds ratio[OR]=45.15,P<0.0001 and OR=25.38,P<0.0001,respectively）and multivariate analyses（OR=52.55,P<0.0001 and OR=26.05,P<0.0001,respectively）.The areas under the receiver operating characteristic curves（AUCs）of PSAD in predicting PCa and HGPCa were 0.627 and 0.630,respectively.With the PSAD cutoff of 0.10 ng ml^-2,we obtained a sensitivity of 88.7%for PCa,and nearly all（89.9%）HGPCa cases could be detected and biopsies could be avoided in 20.2%of the patients（359/1776 cases）.Among these patients who avoided biopsies,only 30 cases had HGPCa.Conclusion:We recommend 0.10 ng ml^-2 as the proper cutoff value of PSAD,which will obtain a sensitivity of nearly 90%for both PCa and HGPCa in the Chinese population.The results of this study should be validated in prospective,population-based multicenter studies.Part Ⅱ:Screening of genes related to biochemical recurrence of prostate cancer based on Chinese population sequencing data and TCGA databaseBackground:27%-53%of patients face with biochemical recurrence（BCR）after radical prostatectomy（RP）.Predicting BCR has important clinical significance,which can help doctors adjust the treatment plan in time and improve the treatment effect of the patients.Biomarkers can be used as indicators of biological and pathological processes,and the detection of the biomarkers can be completed in a short time.We performed this study to screen out genes related to BCR by bioinformatics methods to predict the possibility of BCR in patients after RP effectively.And these genes will be verified in subsequent studies.Methods:We performed bioinformatics and statistical analysis on the RNA sequencing data of 125 Chinese PCa patients and the TCGA database by Cox regression,Log rank test,and Lasso regression model.The statistical analyses were performed using R Software（R statistical package,version 3.6.0）.All the statistical tests were two-sided,and P<0.05 was considered significantly different.Results:We collected the RNA sequencing data of 125 Chinese PCa patients,and downloaded the RNA sequencing data of 434 patients with valid clinical information related to BCR through the TCGA database.We performed differential screening on the data and a total of 257 differential genes were obtained.Every gene was analyzed by Cox univariate regression analyses and Log rank univariate regression analyses,and 60 genes were screened out for better correlation.The expression values of the 60 genes were extracted from the sequencing data of the 125 patients,and 16 genes were screened out by using stepwise Cox regression model.The 16 genes were fitted with Cox multivariate regression,and the analysis coefficients of them were used to calculate the score of BCR risk of the 125 patients and patients in TCGA database.It was found that the 16 genes above can effectively distinguish the risk of BCR both in the 125 patients and TCGA database（p<0.0001;p=0.0049）.On the other hand,the expression values of the 60 genes were extracted from the RNA sequencing data of the 125 patients,and 20 genes with the highest absolute values of correlation coefficients were screened out by using Lasso regression model.The 20 genes were fitted with Cox multivariate regression,and the analysis coefficients of them were used to calculate the score of BCR risk of the 125patients and patients in TCGA database.It was found that the 20 genes above can effectively distinguish the risk of BCR both in the 125 patients and TCGA database（p=0.0011;p=0.033）.Conclusion:We analyzed the RNA sequencing data of 125 Chinese patients with PCa and the TCGA database through Cox regression analyses and Lasso regression analyses.31genes related to BCR were obtained and the screening of candidate genes was completed.In the next part of the study,we will detect and verify the above-mentioned genes in clinical samples.Part Ⅲ:Validation of genes related to biochemical recurrence of prostate cancer in tissue specimens of Chinese patientsBackground:At present,there are three mature prediction models for predicting the prognosis of PCa through gene combinations in the world,but it is still unclear which model has better predictive effect,or whether there is a better one.In this part of the study,we will detect and validate the expression levels of the genes selected in part II in postoperative specimens of PCa patients.We aim to find a gene combination based on Chinese population that has been validated by the international cohort and is suitable for BCR prediction in Chinese population.Then it is possible to do the functional mechanism research about genes with prognostic effects.Methods:The FFPE（Formalin-Fixed and Parrffin-Embedded）specimen of the patients was sliced,and the tumor tissues were distinguished from the non-tumor tissue by observing the HE stained glass slide.The tumor area was marked.Gene expression in tumor tissues and adjacent tissues were detected by Quanti Gene FFPE Assay technology.Through the release and capture of target RNA,signal amplification and other processes,the expression of the target genes in the samples were detected.Results:A total of 79 samples（including 62 cancer tissue samples and 17 adjacent tissue samples）from 62 patients who received RP in Shanghai Changhai Hospital from2015 to 2018 were included in this study.10 genes（MCM6,NUSAP1,ANLN,FAM111B,CASP3,HPS3,MSRA,TPX2,LMNB1,and FAM83D）with the lowest average expression levels were removed considering the sensitivity of later detection.The expression levels of the genes were analyzed by Cox univariate and mulitivariate regression,and genes with a P value<0.05 were selected to establish a gene combination for predicting BCR in the Chinese population.Conclusion:We verified the expression levels of the genes screened out in Part II in tissue samples of PCa patients.We further screened out the gene combination of 5 genes（CCNB1,CDKN2C,TK1,ABT1 and MCM2）,which has a good predictive efficacy on BCR in Chinese patients.