Genetic Polymorphisms of the Telomerase Reverse Transcriptase Gene in Relation to Prostate Tumorigenesis, Aggressiveness and Mortality: A Cross-Ancestry Analysis.

BACKGROUND: Telomerase reverse transcriptase (TERT) has been consistently associated with prostate cancer (PCa) risk. However, few studies have explored the association between TERT variants and PCa aggressiveness. METHODS: Individual and genetic data were obtained from UK Biobank and a Chinese PCa cohort (Chinese Consortium for Prostate Cancer Genetics). RESULTS: A total of 209,694 Europeans (14,550 PCa cases/195,144 controls) and 8873 Chinese (4438 cases/4435 controls) were involved. Nineteen susceptibility loci with five novel ones (rs144704378, rs35311994, rs34194491, rs144020096, and rs7710703) were detected in Europeans, whereas seven loci with two novel ones (rs7710703 and rs11291391) were discovered in the Chinese cohort. The index SNP for the two ancestries was rs2242652 (odds ratio [OR] = 1.16, 95% confidence interval [CI]:1.12-1.20, p = 4.12 × 10-16) and rs11291391 (OR = 1.73, 95%CI:1.34-2.25, p = 3.04 × 10-5), respectively. SNPs rs2736100 (OR = 1.49, 95%CI:1.31-1.71, p = 2.91 × 10-9) and rs2853677 (OR = 1.74, 95%CI:1.52-1.98, p = 3.52 × 10-16) were found significantly associated with aggressive PCa, while rs35812074 was marginally related to PCa death (hazard ratio [HR] = 1.61, 95%CI:1.04-2.49, p = 0.034). Gene-based analysis showed a significant association of TERT with PCa (European: p = 3.66 × 10-15, Chinese: p = 0.043) and PCa severity (p = 0.006) but not with PCa death (p = 0.171). CONCLUSION: TERT polymorphisms were associated with prostate tumorigenesis and severity, and the genetic architectures of PCa susceptibility loci were heterogeneous among distinct ancestries.

Systematic evaluation of narrow-sense validity of polygenic risk score for prostate cancer in a Chinese prostate biopsy cohort.

The aim of this study was to assess the narrow-sense validity of polygenic risk score (PRS) for prostate cancer (PCa) in a Chinese prostate biopsy cohort. We performed an observational prospective study with 2640 men who underwent prostate biopsy. Germline DNA samples were genotyped and PRS was calculated for each subject using 17 PCa risk-associated genetic variants. Additional GWAS data of the ChinaPCa dataset was also used to compliment the evaluation process. The mean PRS was 1.02 in patients with negative biopsy results, which met the baseline benchmark. The mean PRS was significantly higher in the PCa cases (1.32 vs. 1.02, p = 5.56 × 10-17 ). Significant dose-response associations between PRS values and odds ratios for PCa were observed. However, the raw calibration slope was 0.524 and the average bias score between the observed risk and uncorrected PRS value was 0.307 in the entire biopsy cohort. After applying a correction factor derived from a training set, the corrected calibration slope improved to 1.002 in a testing set. Similar and satisfied results were also seen in the ChinaPCa dataset and two datasets combined, while the calibration results were inaccurate when the calibration process were performed mutually between two different study populations. In conclusion, assessing the narrow-sense validity of PRS is necessary prior to its clinical implementation for accurate individual risk assessment.

The Combined Effect of Polygenic Risk Score and Prostate Health Index in Chinese Men Undergoing Prostate Biopsy.

To date, the combined effect of polygenic risk score (PRS) and prostate health index (phi) on PCa diagnosis in men undergoing prostate biopsy has never been investigated. A total of 3166 patients who underwent initial prostate biopsy in three tertiary medical centers from August 2013 to March 2019 were included. PRS was calculated on the basis of the genotype of 102 reported East-Asian-specific risk variants. It was then evaluated in the univariable or multivariable logistic regression models that were internally validated using repeated 10-fold cross-validation. Discriminative performance was assessed by area under the receiver operating curve (AUC) and net reclassification improvement (NRI) index. Compared with men in the first quintile of age and family history adjusted PRS, those in the second, third, fourth, and fifth quintiles were 1.86 (odds ratio, 95% confidence interval (CI): 1.34-2.56), 2.07 (95%CI: 1.50-2.84), 3.26 (95%CI: 2.36-4.48), and 5.06 (95%CI: 3.68-6.97) times as likely to develop PCa (all p < 0.001). Adjustment for other clinical parameters yielded similar results. Among patients with prostate-specific antigen (PSA) at 2-10 ng/mL or 2-20 ng/mL, PRS still had an observable ability to differentiate PCa in the group of prostate health index (phi) at 27-36 (Ptrend < 0.05) or >36 (Ptrend ≤ 0.001). Notably, men with moderate phi (27-36) but highest PRS (top 20% percentile) would have a comparable risk of PCa (positive rate: 26.7% or 31.3%) than men with high phi (>36) but lowest PRS (bottom 20% percentile positive rate: 27.4% or 34.2%). The combined model of PRS, phi, and other clinical risk factors provided significantly better performance (AUC: 0.904, 95%CI: 0.887-0.921) than models without PRS. Adding PRS to clinical risk models could provide significant net benefit (NRI, from 8.6% to 27.6%), especially in those early onset patients (NRI, from 29.2% to 44.9%). PRS may provide additional predictive value over phi for PCa. The combination of PRS and phi that effectively captured both clinical and genetic PCa risk is clinically practical, even in patients with gray-zone PSA.

Machine learning-based prognosis signature for survival prediction of patients with clear cell renal cell carcinoma.

The sole clinicopathological characteristic is not enough for the prediction of survival of patients with clear cell renal cell carcinoma (ccRCC). However, the survival prediction model constructed by machine learning technology for patients with ccRCC using clinicopathological features is rarely reported yet. In this study, a total of 5878 patients diagnosed as ccRCC from four independent patient cohorts were recruited. The least absolute shrinkage and selection operator analysis was implemented to identify optimal clinicopathological characteristics and calculate each coefficient to construct the prognosis model. In addition, weighted gene co-expression network and gene enrichment analysis associated with risk score were also carried out. Three clinicopathologic features were selected for the construction of the prognosis risk score model as the prognostic factors of ccRCC, including tumor size, tumor grade, and tumor stage. In the CPTAC (Clinical Proteomic Tumor Analysis Consortium) cohort, the General cohort, the SEER (Surveillance, Epidemiology, and End Results) cohort, and the Huashan cohort, patients with high-risk score had worse clinical outcomes than patients with low-risk score (hazard ratio 5.15, 4.64, 3.96, and 5.15, respectively). Further functional enrichment analysis demonstrated that our machine learning-based risk score was significantly connected with some cell proliferation-related pathways, consisting of DNA repair, cell division, and cell cycle. In summary, we developed and validated a machine learning-based prognosis prediction model, which might contribute to clinical decision-making for patients with ccRCC.

Genome-Wide 3'-UTR Single Nucleotide Polymorphism Association Study Identifies Significant Prostate Cancer Risk-Associated Functional Loci at 8p21.2 in Chinese Population.

MicroRNAs (miRNAs) are involved in the regulation of gene expression via incomplete base pairing to sequence motifs at the three prime untranslated regions (3'-UTRs) of mRNAs and play critical roles in the etiology of cancers. Single nucleotide polymorphisms (SNPs) in the 3'-UTR miRNA-binding regions may influence the miRNA affinity. However, this biological mechanism in prostate cancer (PCa) remains unclear. Here, a three-stage genome-wide association study of 3'-UTR SNPs (n=33 117) is performed in 5515 Chinese men. Three genome-wide significant variants are discovered at 8p21.2 (rs1567669, rs4872176, and rs4872177), which are all located in a linkage disequilibrium region of the NKX3-1 gene. Phenome-wide association analysis using the FinnGen data reveals a specific association of rs1567669 with PCa over 2,264 disease endpoints. Expression quantitative trait locus analyses based on both Chinese PCa cohort and the GTEx database show that risk alleles of these SNPs are significantly associated with low expression of NKX3-1. Based on the MirSNP database, dual-luciferase reporter assays show that risk alleles of these SNPs downregulate the expression of NKX3-1 via increased miRNA binding. These results indicate that the SNPs at the 3'-UTR of NKX3-1 significantly downregulate NKX3-1 expression by influencing the affinity of miRNA and increase the PCa risk.

Prostate Health Index (phi) and its derivatives predict Gleason score upgrading after radical prostatectomy among patients with low-risk prostate cancer.

To analyze the performance of the Prostate Health Index (phi) and its derivatives for predicting Gleason score (GS) upgrading between prostate biopsy and radical prostatectomy (RP) in the Chinese population, an observational, prospective RP cohort consisting of 351 patients from two medical centers was established from January 2017 to September 2020. Pathological reclassification was determined by the Gleason Grade Group (GG). The area under the receiver operating characteristic curve (AUC) and logistic regression (LR) models were used to evaluate the predictive performance of predictors. In clinically low-risk patients with biopsy GG ≤2, phi (odds ratio [OR] = 1.80, 95% confidence interval [95% CI]: 1.14-2.82, P = 0.01) and its derivative phi density (PHID; OR = 2.34, 95% CI: 1.30-4.20, P = 0.005) were significantly associated with upgrading to GG ≥3 after RP, and the results were confirmed by multivariable analysis. Similar results were observed in patients with biopsy GG of 1 for the prediction of upgrading to RP GG≥2. Compared to the base model (AUC = 0.59), addition of the phi or PHID could provide additional predictive value for GS upgrading in low-risk patients (AUC = 0.69 and 0.71, respectively, both P < 0.05). In conclusion, phi and PHID could predict GS upgrading after RP in clinically low-risk patients.

A Germline Variant at 8q24 Contributes to the Serum p2PSA Level in a Chinese Prostate Biopsy Cohort.

INTRODUCTION: The clinical performance of [-2]proPSA (p2PSA) and its derivatives in predicting the presence and aggressiveness of prostate cancer (PCa) has been well evaluated in prostate biopsy patients. However, no study has been performed to evaluate the common genetic determinants that affect serum level of p2PSA. MATERIALS AND METHODS: Here, we performed a two-stage genome-wide association study (GWAS) on the p2PSA level in Chinese men who underwent a transperineal ultrasound-guided prostate biopsy at Huashan Hospital, Shanghai Cancer Center, and Ruijin Hospital in Shanghai, China. Germline variants significantly associated with the p2PSA level in the first stage (n = 886) were replicated in the second stage (n = 1,128). Multivariate linear regression was used to assess the independent contribution of confirmed single nucleotide polymorphisms (SNPs) and known covariates, such as age, to the level of p2PSA. RESULTS: A novel non-synonymous SNP, rs72725879, in region 8q24.21 of the PRNCR1 gene was significantly associated with the serum level of p2PSA in this two-stage GWAS (p = 2.28 × 10-9). Participants with homozygous "T" alleles at rs72725879 had higher p2PSA levels compared to allele "C" carriers. This variant was also nominally associated with PCa risk (p-combined = 3.44 × 10-18). The association with serum level of p2PSA was still significant after adjusting for PCa risk and age (p = 0.017). CONCLUSIONS: Our study shows that the genetic variants in the 8q24.21 region are associated with the serum level of p2PSA in a large-scale Chinese population. By taking inherited variations between individuals into account, the findings of these genetic variants may help improve the performance of p2PSA in predicting prostate cancer.

The Clinical Implications and Molecular Mechanism of CX3CL1 Expression in Urothelial Bladder Cancer.

BACKGROUND: CX3CL1 is a chemokine that may play important roles in cancer immune regulation. Its mechanism in bladder cancer (BCa) is poorly understood. The objective of the current study was to evaluate the association between CX3CL1 and BCa and the related biological mechanisms. METHODS: A total of 277 patients with BCa were enrolled in the present study. The association between CX3CL1 expression and disease outcome was evaluated. In vitro and in vivo experiments were performed using the TCCSUP cell line to investigate the function of CX3CL1 in BCa. RESULTS: Compared with low expression, high expression of CX3CL1 was significantly associated with poorer progression-free survival (hazard ratio [HR]=2.03, 95% confidence interval [95% CI]: 1.26-3.27, P=0.006), cancer-specific survival (HR=2.16, 95% CI: 1.59-2.93, P<0.001), and overall survival (HR=1.55, 95% CI: 1.08-2.24, P=0.039). Multivariable Cox regression analysis suggested that CX3CL1 was an independent prognostic factor for BCa outcomes. In vitro and in vivo experiments indicated that high expression of CX3CL1 was significantly associated with cell proliferation (P<0.001) and invasion (P<0.001). Gene expression profiling results showed that after CX3CL1 knockdown, CDH1 was significantly upregulated, while ETS1, RAF1, and EIF4E were significantly downregulated. Pathway enrichment analysis suggested that the ERK/MAPK signaling pathway was significantly inhibited (P<0.001). CONCLUSIONS: CX3CL1 is an independent predictor of a poor prognosis in BCa and can promote the proliferation and invasion of BCa cells.

Genetic polymorphisms at 19q13.33 are associated with [-2]proPSA (p2PSA) levels and provide additional predictive value to prostate health index for prostate cancer.

BACKGROUND: Prostate health index (phi), a derivative of [-2]proPSA (p2PSA), has shown better accuracy than prostate-specific antigen (PSA) in prostate cancer (PCa) detection. The present study was to investigate whether previously identified PSA-associated single nucleotide polymorphisms (SNPs) influence p2PSA or phi levels and lead to potential clinical utility. METHODS: We conducted an observational prospective study with 2268 consecutive patients who underwent prostate biopsy in three tertiary medical centers from August 2013 to March 2019. Genotyping data of the 46 candidate genes with a ± 100 kb window were tested for association with p2PSA and phi levels using linear regression. Multivariable logistic regression models were performed and internally validated using repeated tenfold cross-validation. We further calculated personalized phi cutoff values based on the significant genotypes. Discriminative performance was assessed using decision curve analysis and net reclassification improvement (NRI) index. RESULTS: We detected 11 significant variants at 19q13.33 which were p2PSA-associated independent of PCa. The most significant SNP, rs198978 in KLK2 (Pcombined = 5.73 × 10-9 ), was also associated with phi values (Pcombined = 3.20 × 10-6 ). Compared to the two commonly used phi cutoffs of 27.0 and 36.0, the personalized phi cutoffs had a significant NRI for PCa ranged from 5.23% to 9.70% among men carrying variant types (all p < .01). CONCLUSION: Rs198978, is independently associated with p2PSA values, and can improve the diagnostic ability of phi for PCa using personalized cutoff values.

Cost-Effectiveness Analysis of Prostate Health Index in Decision Making for Initial Prostate Biopsy.

BACKGROUND: Clinical studies have suggested that prostate health index (phi) outperforms prostate-specific antigen (PSA) tests in prostate cancer detection. The cost-effectiveness of phi with different cutoffs is poorly understood in the context of decision making for prostate biopsy. METHODS: In a multicenter cohort, 3,348 men with elevated total PSA (tPSA) underwent initial prostate biopsy from August 2013 to May 2019. We constructed a decision model to evaluate the incremental cost-effectiveness ratios of different phi cutoffs. Total costs and reimbursement payments were based on the fee schedule of Shanghai Basic Medical Insurance and converted into United States dollars ($). Two willingness-to-pay thresholds were estimated as one or three times the average gross domestic product per capita of China ($7,760 or $23,279, respectively). RESULTS: The total costs of prostate biopsy and PSA tests were estimated at $315 and $19, respectively. The cost of phi test varied between $72 to $130 in different medical centers. Under different phi cutoffs (from 23 to 35), phi test predicted reductions of 420 (21.7%) to 972 (50.2%) in unnecessary biopsies, with a total gain of 23.77-57.58 quality adjusted life-years compared to PSA tests. All the cutoffs would be cost-effective for patients with tPSA levels of 2-10 ng/ml. Applying 27 as the cutoff was cost-effective for each tPSA range, with missing positive cases ranging from 11 (3.4%) to 33 (11.5%). CONCLUSIONS: Using phi test was cost-effective in the decision-making process for initial prostate biopsy, especially for patients with tPSA values between 2-10 ng/ml. The phi cutoff of 27 was cost-effective regardless of tPSA ranges and should be recommended from a health-economic perspective.

Genetic risk scores based on risk-associated single nucleotide polymorphisms can reveal inherited risk of bladder cancer in Chinese population.

Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) associated with bladder cancer (BCa) risk in Caucasian and East Asian population. The objective of this study was to validate these SNPs in Chinese population and evaluate whether these SNPs could differentiate the individual inherited risk for BCa.A case-control study including 581 BCa cases and 1561 healthy controls was performed. Germline DNA samples from all individuals were genotyped for eight SNPs. Genetic risk score (GRS) was calculated for each individual based on the odds ratios and risk allele frequencies of five risk-associated SNPs.Among eight SNPs evaluated in this study, rs798766 at 4p16.3 [OR = 1.39 (1.15-1.67), P < .001], rs9642880 [OR = 1.17 (1.06-1.30), P < .001] and rs4813953 at 20p12.2 [OR = 1.09 (1.02-1.17), P = .016] were found associated with BCa risk in Chinese population. A genetic risk score was established based on five SNPs (including the above three SNPs and two other SNPs which have the consistent direction with previous reported genome-wide association study). The mean GRS was significantly higher in BCa cases than controls (1.22 vs. 1.01, P < .001). When subjects were categorized into low- (<0.8), average- (0.8-1.2), and high-risk (>1.2) groups, the likelihoods of BCa were 25.2%, 33.7% and 55.0%, respectively (P-trend < 2.2 × 10). In subgroup analyses, no significant difference was observed in mean GRS among BCa patients with different stages or grades.In conclusion, two SNPs derived from East Asian and one SNP from Caucasian were associated with BCa risk in Chinese population. These results provided additional information of genetic risks for BCa in Chinese population. Genetic risk score based on these SNPs can reveal inherited risk of BCa, and may have potential for modifying personalized cancer screening strategy.

Rare Germline Pathogenic Mutations of DNA Repair Genes Are Most Strongly Associated with Grade Group 5 Prostate Cancer.

BACKGROUND: Rare germline mutations in several genes, primarily DNA repair genes, have been proposed to predict worse prognosis of prostate cancer (PCa). OBJECTIVE: To compare the frequency of germline pathogenic mutations in commonly assayed PCa genes between high- and low-grade PCa in patients initially presenting with clinically localized disease. DESIGN, SETTING, AND PARTICIPANTS: A retrospective case-case study of 1694 PCa patients who underwent radical prostatectomy at Johns Hopkins Hospital, including 706 patients with high-grade (grade group [GG] 4 and GG5) and 988 patients with low-grade (GG1) disease. Germline DNA was sequenced for 13 candidate PCa genes using a targeted next-generation sequencing assay by Ambry Genetics. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Carrier rates of pathogenic mutations were compared between high- and low-grade PCa patients using the Fisher's exact test. RESULTS AND LIMITATIONS: Overall, the carrier rate of germline pathogenic mutations in the 13 genes was significantly higher in high-grade patients (8.64%) than in low-grade patients (3.54%, p = 9.98 × 10-6). Individually, significantly higher carrier rates for patients with high- versus low-grade PCa were found for three genes: ATM (2.12% and 0.20%, respectively, p = 9.35 × 10-5), BRCA2 (2.55% and 0.20%, respectively, p = 8.99 × 10-6), and MSH2 (0.57% and 0%, respectively, p = 0.03). The mutation carrier rate was significantly higher in patients with GG5 than in patients with GG1 disease for the 13 genes overall (13.07% and 3.54%, respectively, p = 1.27 × 10-9); for the three genes ATM, BRCA2, and MSH2 (7.73% and 0.40%, respectively, p = 3.20 × 10-13); and for the remaining nine DNA repair genes (5.07% and 2.43%, respectively, p = 0.02). CONCLUSIONS: In men undergoing treatment for clinically localized disease, pathogenic mutations in 13 commonly assayed genes, especially ATM, BRCA2, and MSH2, are most strongly associated with GG5 PCa. These findings emphasize the importance of genetic testing in men with high-grade PCa, particularly GG5 disease, to inform both treatment decisions and familial risk assessment. PATIENT SUMMARY: Prostate cancer in men with inherited mutations in 13 commonly assayed susceptibility genes is more likely to be high-grade, high-risk disease.

Prostate volume does not provide additional predictive value to prostate health index for prostate cancer or clinically significant prostate cancer: results from a multicenter study in China.

To evaluate whether prostate volume (PV) would provide additional predictive utility to the prostate health index (phi) for predicting prostate cancer (PCa) or clinically significant prostate cancer, we designed a prospective, observational multicenter study in two prostate biopsy cohorts. Cohort 1 included 595 patients from three medical centers from 2012 to 2013, and Cohort 2 included 1025 patients from four medical centers from 2013 to 2014. Area under the receiver operating characteristic curves (AUC) and logistic regression models were used to evaluate the predictive performance of PV-based derivatives and models. Linear regression analysis showed that both total prostate-specific antigen (tPSA) and free PSA (fPSA) were significantly correlated with PV (all P < 0.05). [-2]proPSA (p2PSA) was significantly correlated with PV in Cohort 2 (P< 0.001) but not in Cohort 1 (P= 0.309), while no significant association was observed between phi and PV. When combining phi with PV, phi density (PHID) and another phi derivative (PHIV, calculated as phi/PV0.5) did not outperform phi for predicting PCa or clinically significant PCa in either Cohort 1 or Cohort 2. Logistic regression analysis also showed that phi and PV were independent predictors for both PCa and clinically significant PCa (all P < 0.05); however, PV did not provide additional predictive value to phi when combining these derivatives in a regression model (all models vs phi were not statistically significant, all P > 0.05). In conclusion, PV-based derivatives (both PHIV and PHID) and models incorporating PV did not improve the predictive abilities of phi for either PCa or clinically significant PCa.

The study on copy number alteration of clear cell renal cancer in Chinese population.

Objectives: Copy number alteration (CNA) is one of the important genetic variations. Although there are many studies on renal cancer CNA, few studies are based on the Chinese population. In our study, our objective is to acquire the whole-genome CNA landscape in Chinese population and explore the tumor risk-associated functional genes in the CNA regions, by detecting whole-genome in the clear cell renal cancer (ccRCC) tissues. Methods: We enrolled 35 formalin fixed paraffin embedded samples, which were processed by Oncoscan assay, and then acquired the data of whole-genome CNA. Then genes annotation and enrichment analyzing were processed. Furthermore, the gene burden and the affected bp (base pair) per Mbp (million bp) regions in whole-genome were analyzed by comparison of different T stage affected by CNA. Results: We acquired the whole-genome CNA landscape by Oncoscan detection, and found out the high-frequency CNA regions which were not reported in previous studies, for example, 11P11, 22q11.23, 20q11.3 (PDRG1), and Xp22.33 so on. During the analyzing of genes annotation and enrichment, we found out some ccRCC functional genes in the CNA regions which might play a role in the biological process, for example, the copy number loss of DNA repair genes (TTC5、PARP2, etc.) and tumor suppressor genes (TADA3, VHL, BAP1, ERC2-IT1, etc.), the copy number gain of oncogenes (ABL2, MET, HUWE1, etc.) and Notch signal pathway genes (MDK, etc.). Besides, gene fusion (GSTTP and GSTTP2) was noticed at 22q11.23 which copy number loss occurred, and the frequency is 46%. And between the different T stage patients affected by CNA, the T2+T3 group carried more high-frequency CNA regions (P-value was 0.012). Conclusions: In this study, the whole-genome ccRCC CNA landscape in Chinese population was acquired, a few functional genes and fusion genes were found out. However, a larger scale of samples is still needed to validate our results.

HOXA9, PCDH17, POU4F2, and ONECUT2 as a Urinary Biomarker Combination for the Detection of Bladder Cancer in Chinese Patients with Hematuria.

BACKGROUND: DNA methylation biomarkers for bladder cancer (BCa) have not been evaluated extensively in the Chinese population. OBJECTIVE: To develop and validate a urinary biomarker combination of methylation assays in a group of Chinese patients with hematuria. DESIGN, SETTING, AND PARTICIPANTS: A total of 192 urine samples were collected and evaluated from patients with microscopic or gross hematuria, including 97 BCa patients and 95 controls with benign diseases. A two-stage study was conducted: the first stage being assay construction and the second stage being assay validation. Eighty-one urine samples were analyzed for the hypermethylation of eight selected genes in stage 1 and then a four-gene panel was constructed. An additional 111 urine samples were analyzed using the four-gene panel (including HOXA9, PCDH17, POU4F2, and ONECUT2) for independent validation. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The positive predictive value (PPV) and negative predictive value (NPV) were calculated for the combination methylation assay. Uni- and multivariate binary logistic regression analyses (backward elimination, conditional) were performed to calculate the association between BCa and each predictor variable. RESULTS AND LIMITATIONS: The combination assay of HOXA9, PCDH17, POU4F2, and ONECUT2 was selected based on the results of multivariate logistic regression analysis in stage 1. Using a strategy of three-level risk stratification, the assay yielded a consistent PPV of 100%. With an estimated BCa prevalence of 10% in a general hematuria population, the assay would result in an overall NPV of 98%. This combined methylation biomarker would yield an overall area under the receiver operating characteristic curve of 0.871 (with a sensitivity of 90.5% and a specificity of 73.2%) if using the prediction model from multivariate regression analysis. In addition, over half of BCa cases would be predicted accurately and ∼60% of unnecessary cystoscopies could be spared. This study had several limitations. First, the sample size was relatively small. Second, it was performed in a case-control population rather than in a natural hematuria cohort. CONCLUSIONS: A combination methylation assay of HOXA9, PCDH17, POU4F2, and ONECUT2 resulted in high PPV and NPV in Chinese patients with hematuria. With accurate risk prediction, the urinary biomarker combination could spare a sizeable proportion of low-risk patients from extensive and invasive examination. PATIENT SUMMARY: In the present study, we looked at the predictive performance of a urinary biomarker combination of HOXA9, PCDH17, POU4F2, and ONECUT2. We found that this urinary biomarker combination may help discriminate bladder cancer from other benign diseases in patients with hematuria, resulting in a reduction of unnecessary invasive examination in patients at low risk.

Identification of Cancer-Specific Methylation of Gene Combination for the Diagnosis of Bladder Cancer.

Here we conducted an evidence-based study in developing and validating a urinary biomarker combination of gene methylation assays in patients with hematuria. A number of 99 urine samples were obtained and detected from Chinese patients with hematuria. The Cancer Genome Atlas cohort with methylation (HM450) beta-values and clinical data of 412 bladder cancer and 21 matching normal tissue was included as a validation series. A risk score formula was then developed and calculated by the targeted genes, weighted by their estimated regression coefficients from the multivariable binary logistic regression analyses, and evaluated by receiver operating characteristic (ROC) curves analysis. The combination assay of HOXA9, ONECUT2, PCDH17, PENK, TWIST1, VIM and ZNF154 was singled out according to the results of multivariate logistic regression analysis. The higher probability of DNA methylation of all the selected 7 genes was found in bladder cancer group than the control group. Remarkable higher DNA methylation beta-values of all the selected 7 genes were also displayed in bladder cancer tissues compared with their matching normal bladder tissues. And the AUC value of our risk score model were 0.894 and 0.851 in respective cohort, revealing highlighted predictive value of our risk score model on bladder cancer diagnosis. In conclusions, a urinary combined methylation assay of HOXA9, ONECUT2, PCDH17, PENK, TWIST1, VIM and ZNF154 displayed accurate prediction of bladder cancer in hematuria patients, which provided the guidance for the patients at early stage tumor and during the follow-up after operation. Of course, prospective study based on a hematuria cohort with a large sample size should be conducted to validate these findings in the future.

Family history is significantly associated with prostate cancer and its early onset in Chinese population.

BACKGROUND: Family history (FH) of prostate cancer (PCa) in Chinese population is poorly understood. The objective of this study is to evaluate the association between FH and PCa in a Chinese biopsy cohort. METHODS: Consecutive patients who received 10 to 12 core systematic prostate biopsies from April 2013 to October 2018 in three medical centers were enrolled in this study. Demographic information and clinical information were obtained through prebiopsy questionnaire, including cancer FH, age, and total prostate-specific antigen (tPSA). RESULTS: Of 2321 patients, 83 (3.6%) were reported a FH of PCa. The positive biopsy rate in these patients was 54.2%, significantly higher than the patients without the family history of PCa (42.6%; relative risk [RR] = 1.27; P = .024). In patients with positive FH of breast cancer gene (BRCA)-related cancers (breast, ovarian, and prostate cancer, n = 154), 74 (48.1%) were diagnosed as PCa, higher than those without FH (42.7%; RR = 1.13; P = .112). Multivariate logistic regression analysis (after adjusting for age and tPSA values) showed that there was 2.1-fold increased risk of PCa in patients with positive FH of PCa (P = .005), and 1.6-fold increased risk in patients with positive FH of BRCA-related cancers (P = .019). However, there was no significant association between FH of PCa or BRCA-related cancer and high-grade PCa after adjusting age and tPSA level (P = .404 for PCa, P = 0.991 for BRCA-related cancers). CONCLUSIONS: Patients with positive FH of PCa had 2.1-fold higher risk of PCa, and patients with positive FH of BRCA-related cancers had 1.6-fold higher risk in this biopsy cohort of Chinese population. Patients with positive FH of PCa or BRCA-related cancers would have earlier age at onset of PCa.

Concept and benchmarks for assessing narrow-sense validity of genetic risk score values.

BACKGROUND: While higher genetic risk score (GRS) has been statistically associated with increased disease risk (broad-sense validity), the concept and tools for assessing the validity of reported GRS values from tests (narrow-sense validity) are underdeveloped. METHODS: We propose two benchmarks for assessing the narrow-sense validity of GRS. The baseline benchmark requires that the mean GRS value in a general population approximates 1.0. The calibration benchmark assesses the agreement between observed risks and estimated risks (GRS values). We assessed benchmark performance for three prostate cancer (PCa) GRS tests, derived from three SNP panels with increasing stringency of selection criteria, in a PCa chemoprevention trial where 714 of 3225 men were diagnosed with PCa during the 4-year follow-up. RESULTS: GRS from Panels 1, 2, and 3 were all statistically associated with PCa risk; P = 5.58 × 10-3 , P = 1 × 10-3 , and P = 1.5 × 10-13 , respectively (broad-sense validity). For narrow-sense validity, the mean GRS value among men without PCa was 1.33, 1.09, and 0.98 for Panels 1, 2, and 3, respectively (baseline benchmark). For assessing the calibration benchmark, observed risks were calculated for seven groups of men with GRS values <0.3, 0.3-0.79, 0.8-1.19, 1.2-1.49, 1.5-1.99, 2-2.99, and ≥3. The calibration slope (higher is better) was 0.15, 0.12, and 0.60, and the bias score (lower is better) between the observed risks and GRS values was 0.08, 0.08, and 0.02 for Panels 1, 2, and 3, respectively. CONCLUSION: Performance differed considerably among GRS tests. We recommend that all GRS tests be evaluated using the two benchmarks before clinical implementation for individual risk assessment.

Effects of diabetes mellitus and Metformin administration on prostate cancer detection at biopsy among Chinese men: a case-control study.

PURPOSE: To determine the associations among diabetes status, Metformin administration and prostate cancer (PCa) detection at biopsy in Chinese population. METHODS: A case-control study was conducted among a prospectively enrolled prostate biopsy cohort of 518 patients from Jan 2013 to Dec 2014 at our institute. Diabetes status and Metformin administration were determined through medical records and self-report. Different clinical characteristics were registered and compared among different groups. Univariate and multivariate logistic regression analyses were performed to evaluate the effects of diabetes status and Metformin administration on the detection of overall as well as high-grade PCa at biopsy. RESULTS: PCa was detected in 229 (44.2%) men, and high-grade PCa (Gleason score ≥8) was detected in 65 (12.5%) men. Diabetes was observed in 96 men, and 28 of them were administered with Metformin. Both overall and high-grade cancer detection rates were significantly higher in diabetic patients (p<0.001). In multivariate analysis, diabetes status was a risk factor for high-grade cancer detection (OR 7.699, 95%CI 3.483-17.020, p<0.001), but not for total PCa detection (OR 1.774, 95%CI 0.831-3.787, p=0.138). Meanwhile, Metformin administration was proved to be a protective factor for high-grade disease (OR 0.420, 95%CI 0.201-0.879, p=0.021) in multivariate analysis, while no correlation was detected with overall cancer detection (OR 0.786, 95%CI 0.172-3.593, p=0.756). CONCLUSIONS: Diabetes status was positively associated with biopsy-mediated high-grade PCa detection in Chinese population, while the positive association would be partly compromised by Metformin administration.