[Clinical characteristics and prognostic factors of distant metastatic penile cancer].

OBJECTIVE: To investigate the clinical features of distant metastatic penile cancer (DMPC) and the factors influencing its prognosis. METHODS: We searched the Surveillance, Epidemiology and End Results Database for cases of DMPC diagnosed between 2004 and 2019, analyzed their clinical characteristics and the cancer-specific survival (CSS) rates relating to different factors using the Kaplan-Meier method and the differences among the variables by log-rank test. We determined the variables independently associated with CSS by Cox regression analysis. RESULTS: According to the inclusion criteria, 108 cases of DMPC were identified. The patients were mainly married White people, with a median CSS of 9 months, and 1-, 2- and 3-year CSS rates of 36.4%, 17.8% and 13.5%, respectively. Pairwise comparison showed no statistically significant differences in the median overall CSS among the patients in the surgery, chemotherapy and surgery + chemotherapy groups (8 mo vs 9 mo vs 13 mo, P > 0.05). Race was an independent factor affecting the prognosis of CSS. CONCLUSION: Distant metastatic penile cancer is a rare malignancy with poor prognosis, for which there have been no existing ideal treatment options.

[Heavy metal exposure and reproductive toxicity: Advances in studies].

Heavy metals are among the major pollutants affecting the environment, with a higher density of metal element than that of water and an extensive presence in the natural environment. Trace elements such as zinc, copper, nickel and chromium mediate important physiological functions and metabolic regulation at normal levels, and insufficient intake of them will lead to related diseases. Heavy metals such as cadmium, lead and mercury do not participate in the normal metabolism of the human body and will cause damage to the body even at an extremely low dose. Heavy metal pollution mainly comes from industrial wastewater, fossil fuel combustion, wastewater, smelting, mining, vehicle exhaust, hazardous waste dumping, and fertilizer abuse. Unable to be biodegraded, heavy metals have a long biological half-life in nature, which in turn leads to bio-accumulation and -amplification. Eating contaminated vegetables is one way of being exposed to heavy metals. Heavy metals produce adverse effects not only on the human reproductive system, but also on the fetus by penetrating the placental barrier, and on the hypothalamic-pituitary-gonadal axis as well, consequently affecting sexual maturation and reproductive function. With the sharp increase of heavy metals in the environment, researches on their reproductive toxicity and antagonistic drugs have an important clinical significance.

[Clinical study of artificial intelligence-guided image fusion assisted transperineal prostate biopsy].

OBJECTIVE: To compare the diagnostic efficacy of AI-guided mpMRI-TRUS fusion assisted transperineal systematic biopsy, targeted biopsy and combined biopsy in the diagnosis of PCa, and to evaluate the clinical application value of combined biopsy. METHODS: From April 2022, the general personal information and clinical data of patients with suspicious prostate lesions (PI-RADS≥3) detected by 3.0T mpMRI were collected, then underwent AI-guided mpMRI-TRUS fusion-assisted transperineal prostate biopsy. The data included age, PSA level, PV, PSAD, PI-RADS score, Gleason score of biopsy tissue, etc. The mpMRI image data were imported into the real-time fusion imaging system before biopsy. After image fusion, the suspected PCa lesion was taken as the target, 2 to 3 cores of targeted biopsy were first performed, then 12 cores of systematic biopsy were continued. The results of targeted biopsy + systematic biopsy were defined as the results of combined biopsy. The detection rate of PCa, CsPCa and pathological Gleason score were compared among different biopsy methods, and the diagnostic efficacy in different PI-RADS score groups was further evaluated. RESULTS: A total of 118 PCa cases were detected in 220 patients enrolled in this study. The PCa detection rates of systematic biopsy and targeted biopsy were 40.45% and 43.64%, the result reveals no statistical significance (P=0.562). The PCa detection rate of combined biopsy was 53.64%, higher than single biopsy method and the differences were statistically significant (P<0.05). The detection rates of CsPCa in systematic biopsy and targeted biopsy were 28.18% and 37.27% which reveals significant statistical difference (P=0.042). The CsPCa detection rate of combined biopsy was 41.82%, higher than single biopsy method, the difference was statistically significant compared with systematic biopsy (P=0.003), but was not compared with targeted biopsy (P=0.330). In PI-RADS score 3 group, the PCa detection rate of systematic biopsy and targeted biopsy was 39.29% and 21.43%, which reveals no statistical significance (P=0.146). The PCa detection rate of combined biopsy was 50%, higher than single biopsy method, the difference was statistically significant compared with targeted biopsy (P=0.026), but was not compared with systematic biopsy (P=0.420). In PI-RADS 4 ~5 group, the PCa detection rate of systematic biopsy and targeted biopsy was 40.10%, and 46.88% which reveals no statistical significance (P=0.181). The PCa detection rate of combined biopsy was 54.17%, higher than single biopsy method, the difference was statistically significant compared with systematic biopsy (P=0.006), but was not compared with targeted biopsy (P=0.153). Among PCa patients detected by both systematic and targeted biopsy, 39 had concordant pathologic Gleason scores, 13 had escalating pathologic Gleason scores for systematic biopsy, and 18 had escalating pathologic Gleason scores for targeted biopsy. CONCLUSION: Compared with systematic biopsy, AI-guided mpMRI-TRUS image fusion assisted transperineal targeted prostate biopsy has a higher detection rate of CsPCa and is probably closer to the true pathological Gleason score. Compared with single biopsy, combined biopsy has higher diagnostic efficiency for PCa, which can be used as one of the options of prostate biopsy in clinical practice.

[Clinically rare subtypes of prostate cancer: Progress in research].

Prostate cancer has now become the most common urinary tract tumor in men. Some special subtypes of prostate cancer are occasionally found clinically, which are characterized by rapid disease progression, easy recurrence and metastasis, poor effect of single endocrine therapy, and shorter overall survival of the patients than those with common prostate adenocarcinoma. Early diagnosis and early treatment with novel targeting drugs and genetic tests may prolong the survival of the patients. This review presents an overview and a prospect of the epidemiological features, origin, molecular regulation mechanisms, clinical characteristics and treatment of three rare subtypes of prostate cancer.

[Primary testicular mucinous cystadenoma: A case report and literature review].

Objective: To investigate the tissue source, clinical diagnosis, treatment and prognosis of primary testicular mucinous cystadenoma (PTMC). METHODS: We retrospectively analyzed the clinical data on a case of PTMC and reviewed relevant literature. RESULTS: The patient underwent radical resection of the right testis after relevant preoperative examinations. Postoperative pathology indicated mucinous cystadenoma with low-grade intraepithelial neoplasia of the glandular epithelium. No recurrence was observed during an 11-month follow-up. CONCLUSIONS: PTMC is an extremely rare testicular and ovarian surface epithelial tumor, usually benign, rarely malignant. For the treatment of localized PTMC, radical orchiectomy is mostly recommended, while for the cases with invasion, metastasis or recurrence tendency, chemotherapy protocols for ovarian tumors can be considered.

Prognostic Value of a Long Non-coding RNA Signature in Localized Clear Cell Renal Cell Carcinoma.

BACKGROUND: Long non-coding RNAs (lncRNAs) can be used as prognostic biomarkers in many types of cancer. OBJECTIVE: We sought to establish an lncRNA signature to improve postoperative risk stratification for patients with localized clear cell renal cell carcinoma (ccRCC). DESIGN, SETTING, AND PARTICIPANTS: Based on the RNA-seq data of 444 stage I-III ccRCC tumours from The Cancer Genome Atlas project, we built a four-lncRNA-based classifier using the least absolute shrinkage and selection operation (LASSO) Cox regression model in 222 randomly selected samples (training set) and validated the classifier in the remaining 222 samples (internal validation set). We confirmed this classifier in an external validation set of 88 patients with stage I-III ccRCC from a Japan cohort and using quantitative reverse transcription polymerase chain reaction (RT-PCR) in another three independent sets that included 1869 patients from China with stage I-III ccRCC. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Univariable and multivariable Cox regression, Harrell's concordance index (c-index), and time-dependent receiver operating characteristic curves were used to evaluate the association of the classifier with overall survival, disease-specific survival, and disease-free survival. RESULTS AND LIMITATIONS: Using the LASSO Cox regression model, we built a classifier named RCClnc4 based on four lncRNAs: ENSG00000255774, ENSG00000248323, ENSG00000260911, and ENSG00000231666. In the RNA-seq and RT-PCR data sets, the RCClnc4 signature significantly stratified patients into high-risk versus low-risk groups in terms of clinical outcome across and within subpopulations and remained as an independent prognostic factor in multivariate analyses (hazard ratio range, 1.34 [95% confidence interval {CI}: 1.03-1.75; p=0.028] to 1.89 [95% CI, 1.55-2.31; p<0.001]) after adjusting for clinical and pathologic factors. The RCClnc4 signature achieved a higher accuracy (mean c-index, 0.72) than clinical staging systems such as TNM (mean c-index, 0.62) and the stage, size, grade, and necrosis (SSIGN) score (mean c-index, 0.64), currently reported prognostic signatures and biomarkers for the estimation of survival. When integrated with clinical characteristics, the composite clinical and lncRNA signature showed improved prognostic accuracy in all data sets (TNM + RCClnc4 mean c-index, 0.75; SSIGN + RCClnc4 score mean c-index, 0.75). The RCClnc4 classifier was able to identify a clinically significant number of both high-risk stage I and low-risk stage II-III patients. CONCLUSIONS: The RCClnc4 classifier is a promising and potential prognostic tool in predicting the survival of patients with stage I-III ccRCC. Combining the lncRNA classifier with clinical and pathological parameters allows for accurate risk assessment in guiding clinical management. PATIENT SUMMARY: The RCClnc4 classifier could facilitate patient management and treatment decisions.