Multivariate logistic regression analysis of the clinical factors influencing locally advanced prostate cancer.

Background: Locally advanced prostate cancer (PCa) carries a high risk of recurrence and metastasis after surgery, and the prognosis is poor. We explored the risk factors for locally advanced PCa among clinical factors (neutrophil: lymphocyte ratio, lymphocyte: monocyte ratio) and indicators of systemic inflammation [prostate-specific antigen (PSA) level, Gleason score, body mass index (BMI)] through retrospective evaluation of patients with PCa diagnosed at our center. The pathologic T stage was a key indicator of locally advanced PCa. Methods: Data from patients with pathologically confirmed PCa at our center from 1 January 2015 to 1 May 2020 were collected in strict accordance with inclusion and exclusion criteria. Clinical data were collected and the relationship between the indicators and the pathologic T stage was explored. First, Spearman rank correlation analysis was used to find the correlates of the pathologic T stage. Then, logistic ordered multiple regression analysis was used to identify independent risk factors. Finally, receiver operating characteristic (ROC) curves were used to assess the diagnostic accuracy for the T stage of PCa. Results: After rigorous screening, the data of 177 patients were obtained. Spearman correlation analysis showed that BMI, the PSA level, Gleason score, hypertension, N stage, and M stage were significantly correlated with the T stage (P<0.05), suggesting that these factors may be involved in locally advanced PCa. Analyses of ROC curves showed that the PSA level [area under the ROC curve (AUC) =0.802] had greater value than BMI (0.675) for the diagnosis of the pathologic T stage PCa, and that a combination of BMI and PSA (combined AUC =0.822) could improve locally advanced PCa diagnosis. Conclusions: BMI and PSA are independent risk factors for locally advanced PCa. They may play a key part in locally advanced PCa.

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.

Influence of body mass index and waist-hip ratio on male semen parameters in infertile men in the real world: a retrospective study.

Background: It is suggested that body mass index (BMI) can affect male semen quality; however, the results remain controversial. In addition, most studies have focused on the effect of obesity on semen quality. Evidence on the relationship of underweight or waist-hip ratio (WHR) with semen quality is rare. This study aimed to assess the association of BMI and WHR with semen quality. Methods: Data, including BMI and WHR, was collected from 715.00 men who underwent a fertility evaluation. BMI (kg/m2) was categorized as <18.50 (underweight), 18.50-24.90 (normal), 25.00-27.90 (overweight), and ≥28.00 (obese) kg/m2 for analysis. WHR was categorized as <0.81 (normal) and ≥0.81 (high). Semen volume, sperm concentration, progressive motility, and total motile sperm count were detected by experienced clinical technicians. Results: Spearman's correlation showed that BMI was weakly associated with sperm progressive motility (r = 0.076, P < 0.05), while WHR showed no relationship with semen parameters. The azoospermia rate was significantly higher (33.33% vs. 2.10%, P < 0.001) and the sperm concentration was lower (P < 0.05) in the underweight group. The nonlinear correlation analysis showed that BMI was negatively associated with sperm concentration while BMI was more than 22.40 kg/m2 (P < 0.05), while WHR was negatively related to sperm progressive motility within 0.82 to 0.89 (P < 0.05). Furthermore, the multivariate logistic analysis showed that follicular stimulating hormone (FSH) was an independent risk factor for normal sperm concentration (odds ratio [OR]: 0.791, P = 0.001) and morphology (OR: 0.821, P = 0.002), BMI was an independent risk factor for normal sperm progressive motility, and testosterone was an independent risk factor for sperm morphology (OR: 0.908, P = 0.023). Conclusion: BMI and WHR were significantly associated with semen parameters, while BMI was an independent risk factor for normal sperm progressive motility. Reproductive hormones, including FSH and testosterone, had a significant influence on sperm concentration and sperm morphology.

Management of male erectile dysfunction: From the past to the future.

Erectile dysfunction is a common disease of the male reproductive system, which seriously affects the life quality of patients and their partners. At present, erectile dysfunction is considered as a social-psychological-physiological disease with complex etiology and various treatment methods. Oral PDE5I is the first-line treatment for erectile dysfunction with the advantages of high safety, good effect and non-invasiveness. But intracavernosal injection, hormonal replacement therapy, vacuum erection device, penile prosthesis implantation can also be alternative treatments for patients have organic erectile dysfunction or tolerance to PDE5I. With the rapid development of technologies, some new methods, such as low-intensity extracorporeal shock wave and stem cell injection therapy can even repair the organic damage of the corpora cavernosa. These are important directions for the treatment of male erectile dysfunction in the future. In this mini-review, we will introduce these therapies in detail.

Enhancement of protein translation by CRISPR/dCasRx coupled with SINEB2 repeat of noncoding RNAs.

The use of new long noncoding RNAs (lncRNAs) as biotechnological or therapeutic tools is still in its infancy, despite recent efforts to uncover their involvement in various biological processes including mRNA translation. An important question is whether lncRNA functional elements can be used to target translation of mRNAs of interest by incorporating the RNA-targeting CRISPR tools. The CRISPR/dCasRx-SINEB2 technology was developed in this research by coupling the sgRNA of a catalytically inactive Type VI-D Cas13 enzyme (CasRx) to an integrated SINEB2 domain of uchl1 lncRNA that promotes the translation of targeted mRNA. It has been demonstrated to be effective and adaptable in selectively increasing the expression of a variety of exogenous and endogenous proteins with a variety of functions with minimal off-target effects. dCasRx-SINEB2 is currently the sole CRISPR-related technique for translational control of gene expression, and works just as well or even better than the traditional RNAe tool under comparable conditions. Additionally, human cancer cells can be prevented from proliferating and migrating both in vitro and in vivo by dCasRx-SINEB2-targeted mRNA translation of transcripts encoding for antitumor proteins, including PTEN and P53. The present study provides an innovative protein enhancement method that will have several applications in biopharmaceuticals production and cancer research.

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.