Combination of prostate volume and apparent diffusion coefficient can stratify patients with a PI-RADS score of 3 to reduce unnecessary prostate biopsies.

BACKGROUND: Nowadays, there are many patients who undergo unnecessary prostate biopsies after receiving a prostate imaging reporting and data system (PI-RADS) score of 3. Our purpose is to identify cutoff values of the prostate volume (PV) and minimum apparent diffusion coefficient (ADCmin) to stratify those patients to reduce unnecessary prostate biopsies. METHODS: Data from 224 qualified patients who received prostate biopsies from January 2019 to June 2023 were collected. The Mann-Whitney U test was used to compare non-normal distributed continuous variables, which were recorded as median (interquartile ranges). The correlation coefficients were calculated using Spearman's rank correlation analysis. Categorical variables are recorded by numbers (percentages) and compared by χ2 test. Both univariate and multivariate logistic regression analysis were used to determine the independent predictors. The receiver-operating characteristic curve and the area under the curve (AUC) were used to evaluate the diagnostic performance of clinical variables. RESULTS: Out of a total of 224 patients, 36 patients (16.07%) were diagnosed with clinically significant prostate cancer (csPCa), whereas 72 patients (32.14%) were diagnosed with any grade prostate cancer. The result of multivariate analysis demonstrated that the PV (p < 0.001, odds ratio [OR]: 0.952, 95% confidence interval [95% CI]: 0.927-0.978) and ADCmin (p < 0.01, OR: 0.993, 95% CI: 0.989-0.998) were the independent factors for predicting csPCa. The AUC values of the PV and ADCmin were 0.779 (95% CI: 0.718-0.831) and 0.799 (95% CI: 0.740-0.849), respectively, for diagnosing csPCa. After stratifying patients by PV and ADCmin, 24 patients (47.06%) with "PV < 55 mL and ADCmin < 685 µm2/s" were diagnosed with csPCa. However, only one patient (1.25%) with PV ≥ 55 mL and ADCmin ≥ 685 µm2/s were diagnosed with csPCa. CONCLUSIONS: In this study, we found the combination of PV and ADCmin can stratify patients with a PI-RADS score of 3 to reduce unnecessary prostate biopsies. These patients with "PV ≥ 55 mL and ADCmin ≥ 685 µm2/s" may safely avoid prostate biopsies.

Updated review on analysis of long non-coding RNAs as emerging diagnostic and therapeutic targets in prostate cancers.

Despite advancements, prostate cancers (PCa) pose a significant global health challenge due to delayed diagnosis and therapeutic resistance. This review delves into the complex landscape of prostate cancer, with a focus on long-noncoding RNAs (lncRNAs). Also explores the influence of aberrant lncRNAs expression in progressive PCa stages, impacting traits like proliferation, invasion, metastasis and therapeutic resistance. The study elucidates how lncRNAs modulate crucial molecular effectors, including transcription factors and microRNAs, affecting signaling pathways such as androgen receptor signaling. Besides, this manuscript sheds light on novel concepts and mechanisms driving PCa progression through lncRNAs, providing a critical analysis of their impact on the disease's diverse characteristics. Besides, it discusses the potential of lncRNAs as diagnostics and therapeutic targets in PCa. Collectively, this work highlights state of art mechanistic comprehension and rigorous scientific approaches to advance our understanding of PCa and depict innovations in this evolving field of research.

Creating a novel multiparametric magnetic resonance imaging-based biopsy strategy for reducing unnecessary prostate biopsies: a retrospective cohort study.

Background: The overdiagnosis of prostate cancer (PCa) caused by unnecessary prostate biopsy has become a worldwide problem that urgently requires a solution. We aimed to reduce the unnecessary prostate biopsies and increase the detection rate of clinically significant PCa (csPCa) by creating a novel multiparametric magnetic resonance imaging (mpMRI)-based strategy. Methods: A total of 1,194 eligible patients who underwent transperineal prostate biopsies from January 2018 to December 2022 were included in this retrospective study. Of these patients, 1,080 who received prostate biopsies from January 2018 to July 2022 were regarded as cohort 1 for primary analysis, and 114 patients who received prostate biopsies from August 2022 to December 2022 were collected in cohort 2 for validation. All the mpMRI images were quantitatively evaluated by the Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v. 2.1). The diagnostic performances were assessed through the receiver operating characteristic (ROC) curve and area under the curve (AUC) and were compared with the DeLong test. Cancer diagnosis-free survival analysis was performed using the Kaplan-Meier method and log-rank test. The primary endpoint of this study was clinically significant PCa with an International Society of Urological Pathology (ISUP) grade ≥2. Results: In cohort 1, the results of ROC curves demonstrated that the PI-RADS score had a higher diagnostic accuracy (AUC =0.898 for any-grade PCa; AUC =0.917 for csPCa) than did the other clinical variables (P<0.001). Under the novel mpMRI-based biopsy strategy, all patients with PI-RADS 1 can safely avoid prostate biopsy. For patients with PI-RADS 2, prostate biopsy should be considered for patients with prostate-specific antigen density (PSAD) ≥0.3 ng/mL2 and prostate volume <65 mL. As for patients with PI-RADS 3, structured surveillance programs can be a viable option if PSAD <0.3 ng/mL2 and prostate volume ≥65 mL. Finally, patients with a PI-RADS score of 4 and 5 should undergo prostate biopsy due to the high probability of clinically significant PCa. In the validation analysis of cohort 2, 48 patients were placed into a biopsy-spared group with no csPCa cases, while 66 patients were placed in a biopsy-needed group, with an csPCa detection rate of 50.0%. Overall, the novel strategy demonstrated a sensitivity, specificity, positive predictive value, and negative predictive value of 98.9%, 57.5%, 50.5%, and 99.2%, respectively, for diagnosing csPCa. Conclusions: An mpMRI-based biopsy strategy can effectively avoid about 40% of prostate biopsies and maintain a high detection rate for clinically significant PCa. It can further provide valuable guidance for patients and physicians in considering the necessity of prostate biopsy.

Development and validation of a novel nomogram predicting clinically significant prostate cancer in biopsy-naive men based on multi-institutional analysis.

BACKGROUND: Prediction of clinically significant prostate cancer (csPCa) is essential to select biopsy-naive patients for prostate biopsy. This study was to develop and validate a nomogram based on clinicodemographic parameters and exclude csPCa using prostate-specific antigen density (PSAD) stratification. METHODS: Independent predictors were determined via univariate and multivariate logistic analysis and adopted for developing a predictive nomogram, which was assessed in terms of discrimination, calibration, and net benefit. Different PSAD thresholds were used for deciding immediate biopsies in patients with Prostate Imaging-Reporting and Data System (PI-RADS) 3 lesions. RESULTS: A total of 932 consecutive patients who underwent ultrasound-guided transperineal cognitive biopsy were enrolled in our study. In the development cohort, age (odds ratio [OR], 1.075; 95% confidence interval [CI], 1.036-1.114), PSAD (OR, 6.003; 95% CI, 2.826-12.751), and PI-RADS (OR, 3.419; 95% CI, 2.453-4.766) were significant predictors for csPCa. On internal and external validation, this nomogram showed high areas under the curve of 0.943, 0.922, and 0.897, and low Brier scores of 0.092, 0.102, and 0.133 and insignificant unreliability tests of 0.713, 0.490, and 0.859, respectively. Decision curve analysis revealed this model could markedly improve clinical net benefit. The probability of excluding csPCa was 98.51% in patients with PI-RADS 3 lesions and PSAD <0.2 ng/ml2 . CONCLUSION: This novel nomogram including age, PSAD, and PI-RADS could be applied to accurately predict csPCa, and 44.08% of patients with equivocal imaging findings plus PSAD <0.2 ng/ml2 could safely forgo biopsy.

Establishment and validation of a prognostic nomogram for patients with renal cell carcinoma based on SEER and TCGA database.

Background: Renal cell carcinoma (RCC) is a lethal urological malignancy. Precise risk-stratification is very important for decision-making in postoperative patient management. This study aimed to establish and validate a prognostic nomogram of overall survival (OS) in patients with RCC based on Surveillance, Epidemiology, and End Results (SEER) and TCGA database. Methods: The retrospective data of 40,154 patients diagnosed with RCC during 2010 to 2015 from SEER database (development cohort) and 1,188 patients from TCGA database (validation cohort) were downloaded for analysis. Independent prognostic factors were identified by univariate and multivariate Cox regression analyses and adopted to set up a predictive nomogram of OS. The discrimination and calibration of the nomogram were evaluated by ROC curves, C-index values, and calibration plots, and survival analyses were conducted using Kaplan-Meier curves and long-rank tests. Results: The results of multivariate Cox regression analysis demonstrated that age, sex, tumor grade, the American Joint Committee on Cancer (AJCC) stage, tumor size, and pathological types were independent predictors of the OS of RCC patients. These variables were integrated to construct the nomogram, and verification was conducted subsequently. The area under the ROC curve values of 3- and 5-year survival were 0.785 and 0.769 in the development cohort and 0.786 and 0.763 in the validation cohort. The C-index was 0.746 (95% CI: 0.740-0.752) in the development cohort and 0.763 (95% CI: 0.738-0.788) in the validation cohort, indicating good performance of the nomogram. Calibration curve analysis also suggested supreme accuracy on prediction. Finally, patients in the development and validation cohorts were stratified into three risk-level groups (high, intermediate, and low) based on the risk scores calculated by the nomogram, and significant differences in OS were observed among these three groups. Conclusions: In this study, a prognostic nomogram was established to provide tool for clinicians to better advise RCC patients, determine the follow-up strategies and to select suitable patients for clinical trials.

Combination of PI-RADS score and PSAD can improve the diagnostic accuracy of prostate cancer and reduce unnecessary prostate biopsies.

Objectives: The purpose of this study is to evaluate the diagnostic accuracy of the clinical variables of patients with prostate cancer (PCa) and to provide a strategy to reduce unnecessary biopsies. Patients and methods: A Chinese cohort that consists of 833 consecutive patients who underwent prostate biopsies from January 2018 to April 2022 was collected in this retrospective study. Diagnostic ability for total PCa and clinically significant PCa (csPCa) was evaluated by prostate imaging-reporting and data system (PI-RADS) score and other clinical variables. Univariate and multivariable logistic regression analyses were performed to figure out the independent predictors. Diagnostic accuracy was estimated by plotting receiver operating characteristic curves. Results: The results of univariate and multivariable analyses demonstrated that the PI-RADS score (P < 0.001, OR: 5.724, 95% CI: 4.517-7.253)/(P < 0.001, OR: 5.199, 95% CI: 4.039-6.488) and prostate-specific antigen density (PSAD) (P < 0.001, OR: 2.756, 95% CI: 1.560-4.870)/(P < 0.001, OR: 4.726, 95% CI: 2.661-8.396) were the independent clinical factors for predicting total PCa/csPCa. The combination of the PI-RADS score and PSAD presented the best diagnostic performance for the detection of PCa and csPCa. For the diagnostic criterion of "PI-RADS score ≥ 3 or PSAD ≥ 0.3", the sensitivity and negative predictive values were 94.0% and 93.1% for the diagnosis of total PCa and 99.2% and 99.3% for the diagnosis of csPCa, respectively. For the diagnostic criterion "PI-RADS score >3 and PSAD ≥ 0.3", the specificity and positive predictive values were 96.8% and 92.6% for the diagnosis of total PCa and 93.5% and 82.4% for the diagnosis of csPCa, respectively. Conclusions: The combination of the PI-RADS score and PSAD can implement the extraordinary diagnostic performance of PCa. Many patients may safely execute active surveillance or take systematic treatment without prostate biopsies by stratification according to the PI-RADS score and the value of PSAD.

Bone marrow mesenchymal stem cells therapy on bilateral pelvic nerve crush-induced voiding dysfunction in rats.

INTRODUCTION AND HYPOTHESIS: Neurogenic voiding dysfunction can be induced after radical pelvic surgery and severely affects patients' quality of life. This study aims to investigate the effects of bone marrow mesenchymal stem cells (BMSCs) on neurogenic voiding dysfunction in male rats and explore the underlying mechanisms. METHODS: Thirty 4-week-old male Sprague-Dawley rats were randomly divided into three groups: (1) sham-operated (sham, n = 10), (2) intrabladder wall injection of phosphate buffer solution (PBS) after bilateral pelvic nerve crush (BPNC+PBS, n = 10), and (3) intrabladder wall injection of BMSCs after bilateral pelvic nerve crush (BPNC+BMSCs, n = 10). Four weeks postoperatively, functional and morphological examinations were performed. RESULTS: Compared to the sham group, BPNC rats manifested significant augmentation in the frequency of non-voiding contractions and postvoid residual and bladder capacity, and they had decreases in intravesical pressure and voiding efficiency. However, they were markedly improved after BMSC injection. Masson's trichrome staining showed that the ratio of collagen area in bladder wall tissue significantly increased in the BPNC+PBS group but was reduced following BMSC injection. BPNC increased the protein expression of TGF-ß1, Smad2/3, and collagen I/III but decreased the expression of α-SMA. BMSC injection stimulated higher expression levels of α-SMA and lower expression levels of the other target proteins. The expression levels of vesicular acetylcholine transporters were reduced at 4 weeks post-BPNC, whereas injection of BMSCs boosted the expression quantity. CONCLUSIONS: BMSC therapy suppressed detrusor fibrosis, improved intravesical pressure and voiding efficiency, and partially restored voiding function in male rats after BPNC.

LncRNA NEAT1-associated aerobic glycolysis blunts tumor immunosurveillance by T cells in prostate cancer.

Long noncoding RNA (lncRNA) nuclear enriched abundant transcript 1 (NEAT1) is nuclear-located and transcribed from chromatin 11. To date, little is known about the cellular functions and regulatory mechanisms of NEAT1 in prostate cancer (PCa). In this study, whole-genome RNA sequencing data were downloaded from TCGA and GEO databases. Biological information was used to analyze the different expressions of NEAT1. In situ hybridization (ISH) was performed to detect the expression of NEAT1 in PCa and paracarcinoma clinical samples. Then, NEAT1 was knocked down in PC3 cells through lentiviral infection with a plasmid construct. Bioinformatics and integrative analytical approaches were utilized to identify the relationships of NEAT1 with specific cancer-related gene sets. Cell proliferation assay and colony formation assay were performed to evaluate the cell proliferative ability. Glycolysis stress test, metabolism assay, and infiltrating T-cell function analysis were implemented to assess the changes in metabolism and immune microenvironment of PCa. We found that the expression of NEAT1 was higher in PCa than in non-neoplastic tissues. The cell proliferative capability of PCa cells was significantly reduced in the NEAT1 knockdown group. PCR array and bioinformatics analysis revealed that the enrichment of acidic substance-related gene sets was associated with NEAT1 expression. NEAT1 depletion inhibited PCa cell aerobic glycolysis accompanied by the reduction of lactate levels in the medium. Further, we found that lactate dehydrogenase A (LDHA) expression was positively regulated by NEAT1. At last, co-culture systems indicated that NEAT1 or LDHA knockdown promoted the secretion of CD8+ T-lymphocyte factors, including TNF-α, IFN-γ, and Granzyme B, and enhanced the antitumor effects.

Prognostic significance of CKAP2L expression in patients with clear cell renal cell carcinoma.

Background: Cytoskeleton-associated protein 2-like protein (CKAP2L) is thought to promote the progression of glioma, breast cancer, and ovarian cancer. However, the role of cytoskeleton-associated protein 2-like protein in clear cell renal cell carcinoma (ccRCC) is still unclear. The study aimed to investigate the roles and mechanisms of cytoskeleton-associated protein 2-like protein in clear cell renal cell carcinoma. Methods: The level of cytoskeleton-associated protein 2-like protein in tumors was explored by using UALCAN and Oncomine databases. Gene expression datasets of clear cell renal cell carcinoma from The Cancer Genome Atlas and Gene Expression Omnibus (GEO) were also used to validate the cytoskeleton-associated protein 2-like protein level in clear cell renal cell carcinoma. Survival analysis was performed to investigate the relationship between cytoskeleton-associated protein 2-like protein level and prognosis of clear cell renal cell carcinoma patients. Cox regression analysis was used for identifying the independent prognostic factors. Gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), protein-protein interaction analysis, co-expression analysis, and immune infiltration analysis were used to explore the potential mechanisms of cytoskeleton-associated protein 2-like protein in clear cell renal cell carcinoma. Moreover, the levels of cytoskeleton-associated protein 2-like protein in clinical clear cell renal cell carcinoma tissues were also measured using RT-PCR, immunohistochemical analysis, and Western blotting. M1 macrophages and CD4+ T cells were also detected by immunohistochemistry between tumor and normal tissues. Results: The level of cytoskeleton-associated protein 2-like protein was upregulated in clear cell renal cell carcinoma according to multiple databases and experimental verification. Upregulated cytoskeleton-associated protein 2-like protein is an independent prognostic factor, which might activate the JAK-STAT signaling pathway, the P53 signaling pathway, the TGF-ß signaling pathway, the WNT signaling pathway, etc., in clear cell renal cell carcinoma. Protein-protein interaction analysis and co-expression analysis suggest that cytoskeleton-associated protein 2-like protein might interact with some proliferation proteins. Immune infiltration analysis indicates that cytoskeleton-associated protein 2-like protein may affect the level of activated CD4+ memory T cells, M1 macrophages, CD8+ T cells, and neutrophils in clear cell renal cell carcinoma. More M1 macrophage infiltrations in tumor tissues with higher cytoskeleton-associated protein 2-like protein were validated by clear cell renal cell carcinoma tumor tissues. Conclusion: Cytoskeleton-associated protein 2-like protein is upregulated in clear cell renal cell carcinoma tissues, which may promote progression of the disease. Cytoskeleton-associated protein 2-like protein is a potential target for prognostic markers and a potential treatment target in clear cell renal cell carcinoma.

[Relationship of prostate volume and inflammatory cell infiltration with the positive rate of prostate biopsy].

OBJECTIVE: To investigate the factors influencing the positive rate of prostate biopsy and its relationship with the prostate volume and inflammatory cell infiltration (ICI). METHODS: We retrospectively analyzed the clinical data on 230 cases of double-plane transrectal ultrasound-guided prostate biopsy in our Department of Urology, including the patients' age, body mass index (BMI), serum total prostate-specific antigen (tPSA), PSA density (PSAD), prostate volume, and ICI in the prostate tissue. We also investigated the relationship of the above factors with the pathological results of prostate biopsy by binary logistic regression analysis. RESULTS: The positive rate of prostate biopsy was 38.7% (89/230) in the total number of cases, 28.57% (n = 56) in the 196 cases with tPSA < 100 µg/L, and 97.06% (n = 33) in the 34 cases with tPSA ≥ 100 µg/L. Binary logistic regression analysis showed that the positive rate of prostate biopsy in those with tPSA < 100 µg/L was correlated positively with age (P < 0.01, OR = 1.09), tPSA (P < 0.01, OR = 1.04) and PSAD (P < 0.01, OR = 10.04), negatively with the prostate volume (P < 0.01, OR = 0.98) and ICI (P < 0.01, OR = 0.22), but not with BMI (P > 0.05). As a predictor of positive prostate biopsy, tPSA > 10 µg/L exhibited a sensitivity of 82.14% and a specificity of 35.71%, while PSAD > 0.26 showed a sensitivity of 78.57% and a specificity of 71.43%. CONCLUSIONS: Non-specific elevation of the tPSA level induced by increased prostate volume and inflammatory cell infiltration may lead to unnecessary biopsies in some patients. As a predictor of positive prostate biopsy, PSAD > 0.26 has a higher clinical application value than tPSA > 10 µg/L.

Establishing a novel prediction model for improving the positive rate of prostate biopsy.

BACKGROUND: At present, prostate-specific antigen (PSA) is the primary evaluation index for judging the necessity of prostate cancer (PCa) biopsy. However, there is a high false-positive rate and a low predictive value due to many interference factors. In this study, we tried to find a novel prediction model that could improve the positive rate of prostate biopsy and reduce unnecessary biopsy. METHODS: We retrospectively studied 237 patients, including their age, body mass index (BMI), PSA, prostate volume (PV), prostate imaging-reporting and data system (PI-RADS) v2 score, neutrophil-lymphocyte ratio (NLR), biopsy Gleason score (BGS), and other information. The univariate and multivariate logistic analyses were used to screen out indicators related to PCa. After establishing a prediction formula model, we used receiver operating characteristic (ROC) curves to assess its prediction performance. RESULTS: Our study found that age, PSA, PI-RADS v2 score, and diabetes significantly correlated with PCa. Based on multivariate logistic regression analysis results, we created the following prediction formula: Y = 2.599 × PI-RADS v2 score + 1.766 × diabetes + 0.052 × age + 1.005 × PSAD - 9.119. ROC curves showed the formula's threshold was 0.3543. The composite formula had an excellent capacity to detect PCa with the area under the curve (AUC) of 0.91. In addition, the composite formula also achieved significantly better sensitivity, specificity, and diagnostic accuracy than PSA, PSA density (PSAD), and PI-RADS v2 score alone. CONCLUSIONS: Our predictive formula predicted performance better than PSA, PSAD, and PI-RADS v2 score. It can thus contribute to the diagnosis of PCa and be used as an indicator for prostate biopsy, thereby reducing unnecessary biopsy.

miR­22­3p enhances multi­chemoresistance by targeting NET1 in bladder cancer cells.

With the discovery of new chemotherapeutic drugs, chemotherapy becomes increasingly valuable. However, the resistance of tumor cells to chemotherapeutic agents significantly limits the effectiveness and causes chemotherapy failure. MicroRNAs have been shown to regulate drug resistance in many types of cancer. In the present study, we measured the chemosensitivity of five bladder cancer (BCa) cell lines to seven commonly used chemotherapeutic drugs by Vita­Blue assay. We then identified the most sensitive (5637) and most tolerant cell lines (H­bc) and conducted a multi­group test. This test included expression group analyses of coding and non­coding genes (miR­omic and RNA­seq). Based on our analyses, we selected miR­22­3p as a target. We then determined its own target gene [neuroepithelial cell transforming 1 (NET1)] by bioinformatic analysis and confirmed this finding by TaqMan­quantitative reverse transcription polymerase chain reaction (qRT­PCR), western blot analysis and luciferase reporter assay. The effect of miR­22­3p on BCa multi­chemoresistance was also determined by transfecting cells with the miR­22­3p­mimic or miR­22­3p­antagomiR. We assessed the involvement of NET1 in BCa chemoresistance by siRNA­mediated NET1 inhibition or pINDUCER21­enhanced green fluorescent protein­NET1­mediated overexpression. Plate colony formation and apoptosis assays were conducted to observe the effects of miR­22­3p and NET1 on BCa chemoresistance. In conclusion, our results suggest that miR­22­3p promotes BCa chemoresistance by targeting NET1 and may serve as a new prognostic biomarker for BCa patients.