Evaluation of PSA-age volume score in predicting prostate cancer in Chinese population

LGALS3 cfDNA methylation in seminal fluid as a novel prostate cancer biomarker outperforming PSA

BACKGROUND

The unmet challenge in prostate cancer (PCa) management is to discriminate it from benign prostate hyperplasia (BPH) due to the lack of specific diagnostic biomarkers. Contemporary research on potential PCa biomarkers is directed toward methylated cell-free DNA (cfDNA) from liquid biopsies since epigenetic mechanisms are strongly involved in PCa development.

METHODS

In the present research, cfDNA methylation of the LGALS3 gene in blood and seminal plasma of PCa and BPH patients was assessed using pyrosequencing, as well as LGALS3 DNA methylation in tissue biopsies. Liquid biopsy samples were taken from patients with clinical suspicion of PCa, who were subsequently divided into two groups, that is, 42 with PCa and 55 with BPH, according to the histopathological analysis.

RESULTS

Statistically significant higher cfDNA methylation of LGALS3 in seminal plasma of BPH than in PCa patients was detected by pyrosequencing. ROC curve analysis showed that it could distinguish PCa and BPH patients with 56.4% sensitivity and 70.4% specificity, while PSA did not differ between the two patient groups. In contrast, there was no statistically significant difference in LGALS3 cfDNA methylation in blood plasma between the two patient groups. In prostate tumor tissue, there was a statistically significant DNA hypermethylation of LGALS3 compared to surrounding nontumor tissue and BPH tissue.

CONCLUSIONS

The DNA hypermethylation of the LGALS3 gene represents an event specific to PCa development. In conclusion, LGALS3 cfDNA methylation in seminal fluid discriminates early PCa and BPH presenting itself as a powerful novel PCa biomarker highly outperforming PSA.

Value of serum free prostate-specific antigen density in the diagnosis of prostate cancer

PURPOSE

To investigate the value of serum free prostate-specific antigen density (fPSAD) in the diagnosis of prostate cancer (PCa).

METHODS

The data of 558 patients who underwent transrectal ultrasound-guided prostate biopsy were retrospectively analyzed. According to the pathological results, the patients were divided into a PCa group and a benign prostatic hyperplasia (BPH) group. Receiver operating characteristic curves were plotted, based on which the sensitivity, specificity, Youden index, concordance, and kappa values of free prostate-specific antigen (fPSA), the free-to-total f/tPSA, prostate-specific antigen density (PSAD), the free-to-total (f/t)/PSAD ratio, and fPSAD were compared. The patients were divided into three groups by PSA levels (PSA < 4 ng/mL, PSA = 4-10 ng/mL, and PSA > 10 ng/mL), into three groups by age (age < 60 year, age = 60-80y, and age > 80 years), and into two groups by prostate volume (PV) (PV ≤ 80 mL and PV > 80 mL) to compare the sensitivity, specificity, and concordance of indicators.

RESULTS

tPSA, PSAD, (f/t)/PSAD, and fPSAD had high accuracy in predicting PCa with AUC values of 0.820, 0.900, 0.846, and 0.867. fPSAD showed lower diagnostic sensitivity but significantly higher specificity and concordance for PCa than tPSA, f/tPSA, (f/t)/PSAD, or PSAD. Thus, fPSAD had the highest accuracy in the diagnosis of PCa. In the groups with different PSA, age, and PV stratification, the concordance of fPSAD was significantly higher (88.61%, 90.74%, and 90.38%) than that of other indicators.

CONCLUSION

With the optimal cutoff value of 0.062, fPSAD has a higher diagnostic value for PCa than tPSA, f/tPSA, (f/t)/PSAD, and PSAD, and can well predict the risk of PCa, significantly improve the clinical diagnostic rate of PCa, and reduce unnecessary biopsy.

Potential diagnostic value of multiple indicators combined with total prostate-specific antigen in prostate cancer

OBJECTIVE

We aimed to investigate the diagnostic value of different laboratory indicators in combination with total prostate-specific antigen (TPSA) for prostate cancer (PCa).

METHODS

In this retrospective study, we selected 291 patients who underwent prostate biopsy. Patients were divided into the benign prostatic hyperplasia group and the PCa group. In both groups, patients were again divided into a group with TPSA 4.0-10.0 ng/mL and a group with TPSA >10.0 ng/mL. Clinical data including age, pre-puncture TPSA, free prostate-specific antigen (FPSA), and prostate volume (PV) were collected from all patients. We calculated the metrics PSA/PV (prostate-specific antigen density, PSAD), age/PV (AVR), age × PV/TPSA (PSA-AV), and (FPSA/TPSA)/PSAD [(F/T)/PSAD]). We plotted receiver operating characteristic (ROC) curves and calculated the area under the ROC curve (AUC).

RESULTS

We found statistically significant differences in PV, PSAD, AVR, PSA-AV, and (F/T) PSAD for patients with TPSA 4.0-10.0 ng/mL and TPSA >10 ng/mL. We further plotted the ROC of individual or combined indices in different subgroups and calculated the AUC. We found that the diagnostic efficacy of the combined indices was higher with TPSA >10 ng/mL.

CONCLUSION

The combination of TPSA with multiple indicators may improve diagnostic accuracy for PCa.

LINC01146/F11R facilitates growth and metastasis of prostate cancer under the regulation of TGF-β

The effect of long intergenic non-protein coding RNAs (lncRNAs) was verified in prostate cancer (PCa), but the mechanism of LINC01146 in PCa is unclear. Bioinformatics was applied to analyze LINC01146 expression in PCa and predict target genes of LINC01146, followed by the verification of qRT-PCR, RNA pull-down and co-immunoprecipitation (Co-IP). The correlation between LINC01146 expression and clinicopathological characteristics was investigated. The location of LINC01146 in PCa cells was detected by fluorescence in situ hybridization (FISH). After interference with LINC01146 or/and F11 receptor (F11R) or treated with transforming growth factor beta 1 (TGF-β1), the function of LINC01146 in PCa in vitro or in vivo was determined by CCK-8, colony formation, flow cytometry, scratch test, transwell assay, xenograft experiment and western blot. LINC01146 and F11R were over-expressed in PCa and positively correlated with poor prognosis. LINC01146 located in the cytoplasm and combined with F11R. LINC01146 overexpression impeded apoptosis, facilitated viability, proliferation, migration and invasion in PCa cells in vitro, promoted tumor growth in vivo, downregulated E-cadherin, Bax and Cleaved caspase-3, and upregulated N-cadherin, Vimentin and PCNA, but LINC01146 silencing did the opposite. F11R was positively regulated by LINC01146 and F11R depletion negated the effect of LINC01146 overexpression on malignant phenotypes of PCa cells. The expression of LINC01146 and F11R was regulated by TGF-β1. The promoting role of TGF-β1 in migration, invasion and F11R in PCa cells was reversed by LINC01146 silencing. LINC01146 upregulated F11R to facilitate malignant phenotypes of PCa cells, which was regulated by TGF-β.

The influence of prostate volume on clinical parameters in prostate cancer screening

PURPOSE

The purpose of the study was to evaluate the diagnostic significance of two new and a few clinical markers for prostate cancer (PCa) at various prostate volumes (PV).

METHODS

The study subjects were divided into two groups. Among them, there were 70 cases in the PV ≤30 ml group (benign prostatic hyperplasia [BPH]: 32 cases, PCa: 38 cases) and 372 cases in the PV > 30 ml group (BPH: 277 cases, PCa: 95 cases). SPSS 26.0 and GraphPad Prism 8.0 were used to construct their receiver operating characteristic (ROC) curves for diagnosing PCa and calculating their area under the ROC curve (AUC).

RESULTS

In the PV ≤30 ml group, the diagnostic parameters based on prostate-specific antigen (PSA) had a decreased diagnostic significance for PCa. In the PV > 30 ml group, PSAD (AUC = 0.709), AVR (AVR = Age/PV, AUC = 0.742), and A-PSAD (A-PSAD = Age×PSA/PV, AUC = 0.736) exhibited moderate diagnostic significance for PCa, which was better than PSA-AV (AUC = 0.672), free PSA (FPSA, AUC = 0.509), total PSA (TPSA, AUC = 0.563), (F/T) PSA (AUC = 0.540), and (F/T)/PSAD (AUC = 0.663). Compared with AVR, A-PSAD exhibited similar diagnostic significance for PCa, but higher than PSA density (PSAD).

CONCLUSIONS

Choosing appropriate indicators for different PVs could contribute to the early screening and diagnosis of PCa. The difference in the diagnostic value of two new indicators (A-PSAD and AVR), and PSAD for PCa may require further validation by increasing the sample size.

Clinical research analysis based on prostate cancer screening diagnosis

This study aimed to analyse the clinical characteristics and risk factors of patients with positive prostate biopsy at 4-20 ng/mL of prostate-specific antigen (PSA), construct a new parameter based on this characteristics and assess its diagnostic value for prostate cancer (PCa). Logistic regression analysis was used to clarify the risk factors of PCa, and a new parameter based on the results was constructed. Compare the diagnostic value of various diagnostic parameters for PCa. Logistic multivariate regression analysis revealed that age (OR, 5.269; 95%CI, 2.762-10.050), comorbid diabetes (OR, 2.437; 95%CI, 1.162-5.111), PSA (OR, 2.462; 95%CI, 1.198-5.059) and prostate volume (PV) (OR, 0.227; 95%CI, 0.100-0.516) are risk factors for PCa. The age, PSA and PV of patients were combined to construct a new parameter, that is A-PSAD = (age × total PSA [TPSA])/PV]. The area under the receiver-operating characteristic curve(AUC) of A-PSAD (0.728) for PCa diagnosis was higher than the AUCs of TPSA (0.581), free prostate-specific antigen (0.514), (F/T)PSA (0.535) and PSAD (0.696), with significant differences. Age, history of diabetes, TPSA and PV are risk factors for PCa(PSA:4-20ng/mL); in addition, A-PSAD has a moderate diagnostic value for PCa and may become a new indicator for PCa screening.

Immunohistochemical investigation of cytokine expression levels as biomarkers in transrectal ultrasound-guided needle biopsy specimens of prostate adenocarcinoma

Cytokines influence the biological behaviour of prostate cancer (PC) and may influence patient outcome and serve as useful prognostic biomarkers. The aim of the present study was to evaluate cytokine expression levels in prostatic needle biopsy specimens and the association with clinicopathological characteristics of patients with PC. A total of 18 patients with PC who underwent transrectal ultrasound (TRUS) guided prostate biopsy were included in the clinical study. These patients were naïve to radiotherapy (RT) or androgen deprivation therapy prior to TRUS biopsy and clinical follow up data was collected. Cytokine expression levels were analysed by using immunohistochemistry and Spearman's correlation test was used to determine the correlation between cytokine expression and clinicopathological characteristics. Expression levels of pro-inflammatory TNF-α and IL-6 decreased as Gleason score (GS) increased; however, a statistically significant difference was not detected. A statically significant correlation was observed between needle biopsy specimen and pre-RT plasma sample expression levels of pro-inflammatory TNF-α and IL-6 (P=0.01 and P=0.05, respectively) and anti-inflammatory TGF-β1 (P=0.05). However, further studies are needed to confirm these results using a larger sample size to confirm the prognostic value of pro-inflammatory TNF-α and IL-6 and anti-inflammatory TGF-β1 in patients with PC.

Total thiol can contribute to differentiating prostate cancer from BPH: Prostate Thiol Index as a new player

To assess the distinctiveness of serum native thiol (NT), total thiol (TT) and disulfide (SS) levels in PCa patients, we created a new parameter, prostate thiol index (PTI) [tPSA (TTxPVxAge) ^-1/2 ]. We determined the performance of the PTI on PCa diagnosis. A total of 107 male patients (PCa:65; BPH:42) who were separated according to their Gleason scores, ISUP grades and EAU risk groups and 20 healthy subjects were included. The performances of the tests were determined. The PCa and BPH groups had lower NT and TT levels and higher SS levels than the control group. PCa patients had higher PTI, tPSA, fPSA, PSAD levels, lower fPSA%, PV and PSA-AV levels than BPH patients. TT, PTI, tPSA, fPSA, fPSA%, PSA-AV, PSAD and PV had significant diagnostic performances. PTI had the highest AUC value and accuracy, PSA-AV had the highest specificity, and fPSA had the lowest sensitivity. The performance of the PTI was the best in distinguishing PCa from BPH. PTI, tPSA and PSAD positively and PSA-AV negatively correlated with ISUP grades and EAU groups. TT can contribute to the discrimination of PCa from BPH and PTI may decrease unnecessary biopsies in clinical practice.

PI-RADS version 2.1 scoring system is superior in detecting transition zone prostate cancer: a diagnostic study

PURPOSE

The studies comparing the versions 2 vs. 2.1 of the Prostate Imaging Reporting and Data System (PI-RADS) are rare. This study aimed to evaluate whether PI-RADS version 2.1 is superior in detecting transition zone prostate cancer in comparison with PI-RADS version 2.

METHODS

This was a diagnostic study of patients with prostate diseases who visited the Urology Department of The Second Affiliated Hospital of Soochow University and underwent a magnetic resonance imaging (MRI) examination between 03-01-2016 and 10-31-2018. The images originally analyzed using PI-RADS version 2 were retrospectively re-analyzed and scored in 2019 according to the updated PI-RADS version 2.1. The kappa and receiver operating characteristic (ROC) curves were used.

RESULTS

For Reader 1, compared with PI-RADS version 2, version 2.1 had higher sensitivity (85% vs. 79%, P = 0.03), lower specificity (65% vs. 83%, P < 0.001), and lower area under the curve (AUC) (0.749 vs. 0.809, P < 0.001). For Reader 2 (first attempt), compared with PI-RADS version 2, version 2.1 had lower specificity (67% vs. 91%, P < 0.001) and lower AUC (0.702 vs. 0.844, P < 0.001). For Reader 2 (second attempt), compared with PI-RADS version 2, version 2.1 had higher sensitivity (88% vs. 78%, P < 0.001) and lower specificity (77% vs. 91%, P < 0.001). The kappa between the two attempts for Reader 2 was 0.321.

CONCLUSION

These results suggest that PI-RADS version 2.1 might improve the detection of prostate cancers in the transition zone compared with PI-RADS version 2 but that it might results in higher numbers of biopsies because of lower specificity.

Comparison of diagnostic efficacy between transrectal and transperineal prostate biopsy: A propensity score-matched study

This study compared the diagnostic efficacy of transrectal ultrasound (TRUS)-guided prostate biopsy (TRBx) and transperineal prostate biopsy (TPBx) in patients with suspected prostate cancer (PCa). We enrolled 2962 men who underwent transrectal (n = 1216) or transperineal (n = 1746) systematic 12-core prostate biopsy. Clinical data including age, prostate-specific antigen (PSA) level, and prostate volume (PV) were recorded. To minimize confounding, we performed propensity score-matching analysis. We measured and compared PCa detection rates between TRBx and TPBx, which were stratified by clinical characteristics and Gleason scores. The effects of clinical characteristics on PCa detection rate were assessed by logistic regression. For all patients, TPBx detected a higher proportion of clinically significant PCa (P < 0.001). Logistic regression analyses illustrated that PV had a smaller impact on PCa detection rate of TPBx compared with TRBx. Propensity score-matching analysis showed that the detection rates in TRBx were higher than those in TPBx for patients aged >- 80 years (80.4% vs 56.5%, P = 0.004) and with PSA level 20.1-100.0 ng ml^-1 (80.8% vs 69.1%, P = 0.040). In conclusion, TPBx was associated with a higher detection rate of clinically significant PCa than TRBx was; however, because of the high detection rate at certain ages and PSA levels, biopsy approaches should be optimized according to patents' clinical characteristics.

Epidemiological and Economic Evaluation of a Pilot Prostate Cancer Screening Program

Background. Prostate cancer (PCa) is the second most commonly diagnosed cancer, and the sixth most common killer among men worldwide (Aubry et al., 2013). This research was motivated by the fact that PCa screening continues to be a controversial topic in the Kazakh medical community. This study aimed at description of how newly diagnosed PCa patients are managed in Pavlodar region of the Kazakhstan Republic and at presentation of a budget impact analysis (BIA) for PCa screening program. Also, we aimed to provide a comparative analysis of pricing system on medical services applied in both private and public healthcare sectors of the Kazakhstan Republic. Methods. New cases of PCa have been retrospectively analyzed for the period from January 2013 to December 2017 based on the information obtained from information system "Policlinic" maintained by the Pavlodar regional branch of the Republican Center for Electronic Health and from Cancer Registry of Pavlodar Regional Oncology Center. All data were analyzed with the help of SPSS 20.0 software. Results. The mean age of PCa patients was 68.34 years (SD = 8.559). The government of Kazakhstan invested 20,437,000 KZT (Kazakhstani tenge) in 2017 equivalently 61,188 USD-to fund a pilot study for examination of 9638 men. From 2013 to 2017, out of 49,334 men residing in Pavlodar region of Kazakhstan 1,248 men were diagnosed with prostate diseases, including 130 PCa cases. The PCa detection rate was equal to two cases per month. Only 22.8% of all PCa cases identified in the region within specified time period were revealed as a result of the government-funded PCa screening program. The average prostate cancer detection rate among the target group of Pavlodar region within the period of 5 years was equal to 0.23%. Conclusion. Based on the fact that the PCa screening program failed to enable adequate detection of new PCa cases, we would not recommend to continue this type of screening unless it is undergone careful revision and replanning.

Improving the detection rate of prostate cancer in the gray zone of PI-RADS v2 and serum tPSA by using prostate-specific antigen-age volume

To improve the detection of prostate cancer (PCa) by combining the Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) and prostate-specific antigen-age volume (PSA-AV), especially among those in gray zone with PI-RADS v2 score 3 or serum total prostate-specific antigen (tPSA) 4 to 10 ng/mL.The 357 patients were enrolled in this study. The PI-RADS v2 scoring system was used to represent characteristics on multiparametric magnetic resonance imaging (mpMRI). PI-RADS v2 score 3 or tPSA 4 to 10 ng/mL were defined as the gray zone in detecting PCa. The formula equates to the patient age multiplied by the prostate volume, which is divided by the tPSA level. Univariate and multivariate analyses were done to ascertain significant predictors of prostate cancer.In all, 174 (48.7%) were benign prostatic hyperplasia, 183 (51.3%) had PCa. The results showed that PI-RADS v2, tPSA, and PSA-AV were significant independent predictors of prostate cancer. PI-RADS v2 score ≥4 could detect PCa with rate of 82.1%. Serum tPSA ≥10 ng/mL could detect PCa with rate of 66.2%, PSA density (PSAD) ≥0.15 ng/mL/cc with rate of 62.8%, and PSA-AV ≤250 with rate of 83.5%. Combining with PSA-AV ≤250, patients those with tPSA 4 to 10 ng/mL could improve the detection from 36.0% up to 81%, those with PI-RADS v2 score 3 from 28.6% up to 60.0%.PI-RADS v2 and PSA-AV are faithful variables for detecting PCa. And for patients, those in gray zones of PI-RADS v2 and tPSA, PSA-AV can improve detection rate of PCa.