Introduction: Cuproptosis seems to promote the progression of diverse diseases. Hence, we explored the cuproptosis regulators in human spermatogenic dysfunction (SD), analyzed the condition of immune cell infiltration, and constructed a predictive model.Methods: Two microarray datasets (GSE4797 and GSE45885) related to male infertility (MI) patients with SD were downloaded from the Gene Expression Omnibus (GEO) database. We utilized the GSE4797 dataset to obtain differentially expressed cuproptosis-related genes (deCRGs) between SD and normal controls. The correlation between deCRGs and immune cell infiltration status was analyzed. We also explored the molecular clusters of CRGs and the status of immune cell infiltration. Notably, weighted gene co-expression network analysis (WGCNA) was used to identify the cluster-specific differentially expressed genes (DEGs). Moreso, gene set variation analysis (GSVA) was performed to annotate the enriched genes. Subsequently, we selected an optimal machine-learning model from four models. Finally, nomograms, calibration curves, decision curve analysis (DCA), and the GSE45885 dataset were utilized to verify the predictions’ accuracy.Results: Among SD and normal controls, we confirmed that there are deCRGs and activated immune responses. Through the GSE4797 dataset, we obtained 11 deCRGs. ATP7A, ATP7B, SLC31A1, FDX1, PDHA1, PDHB, GLS, CDKN2A, DBT, and GCSH were highly expressed in testicular tissues with SD, whereas LIAS was lowly expressed. Additionally, two clusters were identified in SD. Immune-infiltration analysis showed the existing heterogeneity of immunity at these two clusters. Cuproptosis-related molecular Cluster2 was marked by enhanced expressions of ATP7A, SLC31A1, PDHA1, PDHB, CDKN2A, DBT, and higher proportions of resting memory CD4+ T cells. Furthermore, an eXtreme Gradient Boosting (XGB) model based on 5-gene was built, which showed superior performance on the external validation dataset GSE45885 (AUC = 0.812). Therefore, the combined nomogram, calibration curve, and DCA results demonstrated the accuracy of predicting SD.Conclusion: Our study preliminarily illustrates the relationship between SD and cuproptosis. Moreover, a bright predictive model was developed.
The largest solid organ of the male genitalia, the prostate gland, is comprised of a variety of cells such as prostate epithelial cells, smooth muscle cells, fibroblasts, and endothelial cells. Prostate diseases, especially prostate cancer and prostatitis, are often accompanied by acute/chronic inflammatory responses or even cell death. Pyroptosis, a cell death distinct from necrosis and apoptosis, which mediate inflammation may be closely associated with the development of prostate disease. Pyroptosis is characterized by inflammasome activation via pattern recognition receptors (PRR) upon recognition of external stimuli, which is manifested downstream by translocation of gasdermin (GSDM) protein to the membrane to form pores and release of inflammatory factors interleukin (IL)-1β and IL-18, a process that is Caspase-dependent. Over the past number of years, many studies have investigated the role of inflammation in prostate disease and have suggested that pyroptosis may be an important driver. Understanding the precise mechanism is of major consequence for the development of targeted therapeutic strategies. This review summarizes the molecular mechanisms, regulation, and cellular effects of pyroptosis briefly and then discuss the current pyroptosis studies in prostate disease research and the inspiration for us.
Objective This study evaluated the quality of randomized controlled trials (RCTs) on chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS). Methods We searched PubMed, Web of Science, and Embase for RCTs (original articles) on CP/CPPS published from database establishment to 2021. The RCT quality assessment was performed using the Consolidated Standards of Reporting of Trials (CONSORT) statement and the improved Jadad scale. Results In total, 77 RCTs were included. According to the evaluation, 26 (33.77%) papers presented the description of the specific random methods, only 6 (7.79%) papers described the allocation concealment methods, and 26 (33.77%) articles referred to the “blind method”. Of the RCTs, 34 (44.16%) papers recorded the number of patients who withdrew from the study, and 67 (87.01%) papers reported adverse reactions. However, few reports mentioned the sample size calculation, clinical trial registration, or information about the relevant research programs and funding. In addition, 19 (24.68%) reports had Jadad scale scores of ≥ 4 points, and 58 (75.32%) reports had Jadad scale scores of ≤ 3 points. Conclusion To date, the quality of RCT reports on CP/CPPS needs to be further improved, and the results of the RCTs should be accepted and utilized cautiously. It is suggested that researchers should follow the CONSORT statement and the improved Jadad scale to standardize the design and implementation of RCTs to improve the quality of RCTs and provide reliable evidence for the treatment of CP/CPPS.
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