SUMOylation is an important part of post-translational protein modifications and regulates thousands of proteins in a dynamic manner. The dysregulation of SUMOylation is detected in many cancers. However, the comprehensive role of SUMOylation in prostate cancer (PCa) remains unclear. Using 174 SUMOylation-related genes (SRGs) from the MigDSB database and the transcript data of PCa from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), we constructed a SUMOylation-related risk score and correlated it with prognosis, tumor mutation burden (TMB), tumor microenvironment (TME) infiltration, and response to chemotherapy and immunotherapy. Moreover, we validated two vital SRGs by RT-qPCR, western blotting, and immunohistochemistry. Two vital SRGs (DNMT3B and NUP210) were finally selected. The risk score based on these genes exhibited excellent predictive efficacy in predicting the biochemical recurrence (BCR) of PCa. A nomogram involving the risk score and T stage was established to further explore the clinical value of the risk score. We found the high-score group was correlated with worse prognosis, higher TMB, a more suppressive immune microenvironment, and a better response to Docetaxel but worse to PD-1/CTLA-4 blockade. Meanwhile, we validated the significantly higher expression level of NUP210 in PCa at mRNA and protein levels. This study elucidated the comprehensive role of SUMOylation-related genes in PCa. Importantly, we highlighted the role of an important SRG, NUP210, in PCa, which might be a promising target in PCa treatment. A better understanding of SUMOylation and utilizing the SUMOylation risk score could aid in precision medicine and improve the prognosis of PCa.

Background: Kidney stone disease (KSD) is a multifactorial disease involving both environmental and genetic factors, whose pathogenesis remains unclear. This study aims to explore the hub genes related to stone formation that could serve as potential therapeutic targets. Methods: Based on the GSE73680 dataset with 62 samples, differentially expressed genes (DEGs) between Randall’s plaque (RP) tissues and normal tissues were screened and weighted gene co-expression network analysis (WGCNA) was applied to identify key modules associated with KSD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to explore the biological functions. The protein–protein interaction (PPI) network was constructed to identify hub genes. Meanwhile, CIBERSORT and ssGSEA analysis were used to estimate the infiltration level of the immune cells. The correlations between hub genes and immune infiltration levels were also investigated. Finally, the top hub gene was selected for further GSEA analysis. Results: A total of 116 DEGs, including 73 up-regulated and 43 down-regulated genes, were screened in the dataset. The red module was identified as the key module correlated with KSD. 53 genes were obtained for functional enrichment analysis by taking the intersection of DEGs and genes in the red module. GO analysis showed that these genes were mainly involved in extracellular matrix organization (ECM) and extracellular structure organization, and others. KEGG analysis revealed that the pathways of aldosterone-regulated sodium reabsorption, cell adhesion molecules, arachidonic acid (AA) metabolism, and ECM-receptor interaction were enriched. Through PPI network construction, 30 hub genes were identified. CIBERSORT analysis revealed a significantly increased proportion of M0 macrophages, while ssGSEA revealed no significant differences. Among these hub genes, SPP1, LCN2, MMP7, MUC1, SCNN1A, CLU, SLP1, LAMC2, and CYSLTR2 were positively correlated with macrophages infiltration. GSEA analysis found that positive regulation of JNK activity was enriched in RP tissues with high SPP1 expression, while negative regulation of IL-1β production was enriched in the low-SPP1 subgroup. Conclusions: There are 30 hub genes associated with KSD, among which SPP1 is the top hub gene with the most extensive links with other hub genes. SPP1 might play a pivotal role in the pathogenesis of KSD, which is expected to become a potential therapeutic target, while its interaction with macrophages in KSD needs further investigation.

Background: Image-guided surgery (IGS) refers to surgery navigated by medical imaging technology, helping doctors better clarify tumor boundaries, identify metastatic lymph nodes and preserve surrounding healthy tissue function. Recent studies have provided expectable momentum of the application of IGS in prostate cancer (PCa). The authors aim to comprehensively construct a bibliometric analysis of the application of IGS in PCa. Method: The authors searched publications related to application of IGS in PCa from 2013 to 2023 on the web of science core collection (WoSCC) databases. VOSviewer, CiteSpace, and R package ‘bibliometrix’ were used for bibliometric analysis. Results: Two thousand three eighty-nine articles from 75 countries and 2883 institutions led by the United States were included. The number of publications related to the application of IGS in PCa kept high in the last decade. Johns Hopkins University is the top research institutions. Journal of Nuclear Medicine has the highest popularity as the selection of journal and co-cited journal. Pomper Martin G. had published the most paper. Ali Afshar-Oromieh was co-cited most frequently. The clinical efficacy of PSMA-PET/CT in PCa diagnosis and treatment are main topics in this research field, with emerging focuses on the use of fluorescence imaging guidance technology in PCa. ‘PSMA’ and ‘PET/CT’ are the main keywords as long-term research hotspots. Conclusion: This study is the first bibliometric analysis of researches on application of IGS in PCa with three recognized bibliometric software, providing an objective description and comprehensive guidance for the future relevant investigations.

Background. With the growth and aging of population, the incidence of prostate cancer will increase year by year, which is bound to bring greater economic burden to the society. There has been greater interest in the anticancer effects of statin in recent years. It is controversial whether statin use is associated with the risk of prostate cancer (PCa). Thus, we conducted a meta-analysis and systematic review to explore the effects of statin use and their duration and cumulative dose on the overall incidence of PCa. Method. The study was conducted according to the latest guidelines for PRISMA 2020. We searched PubMed and other databases for studies about the association of statin use with the risk of incident prostate cancer between January 1, 1990, and April 11, 2022. Two independent researchers extracted data and evaluated the quality of the studies. R x64 4.1.2 and random-effects model were used for data statistics. Relative risk (RR) and odds ratio (OR) effective values with a 95% confidence interval (95% CI) were used to assess the main results. Results. The results of 6 RCT and 26 cohort studies showed that statins did not significantly associate with the incidence of PCa (RR = 0.94, 95% CI: 0.82–1.08). The similar results were obtained from 9 case-control studies (OR = 1.03, 95% CI: 0.99–1.07). However, statins were associated with a lower risk of Pca (RR = 0.44, 95% CI: 0.28–0.70) when the cumulative defined daily dose (cDDD) was high. Using statins for more than five years could be associated with a reduced incidence of Pca (RR = 0.47, 95% CI: 0.23–0.97). There was a significant heterogeneity in these studies (RCT and cohort study: I² = 98%, < 0.01; case-control study: I² = 72%, < 0.01). Conclusion. We concluded that statins had a neutral association with the overall risk of PCa. High cDDD and long duration were associated with a lower risk of PCa.

Introduction: More and more studies have focused on the associations between human papillomavirus (HPV) infection and pan-cancers. However, current evidence is largely based on retrospective studies, which are susceptible to confounding factors and do not enable the establishment of causal relationships. Methods: A bidirectional two-sample Mendelian randomization (MR) design was employed to thoroughly evaluate the causal relationships between HPV and 12 site-specific cancers except cervical cancer. Single nucleoside polymers (SNPs) with strong evidence from genome-wide association studies (GWAS) were selected from HPV exposure datasets and used as instrumental variables (IVs) in this study. For the MR analysis results, MR-Egger’s intercept P test, MR-PRESSO global test, Cochran’s Q test and a leave-one-out test were applied for sensitivity analysis. Using HPVTIMER, we also performed immune infiltration analyses in head and neck squamous cell carcinoma (HNSCC), oropharyngeal squamous cell carcinoma (OPSCC) and vulval squamous cell carcinoma (VSCC) to evaluate the tumor-immune microenvironment. Results: Based on the evidence of MR analysis, our study conclusively identified HPV16 as a risk factor implicated in the development of bladder cancer, colorectal cancer, and breast cancer, while HPV18 was identified as a risk factor for prostate cancer, ovarian cancer, lung cancer and breast cancer. The MR results also showed that HPV16 may be a protective factor for prostate cancer, anal cancer, lung cancer and oropharyngeal cancer, while HPV18 may be a protective factor for vaginal cancer. Conclusion: An HPV infection may modulate the immune microenvironment and therefore has a potential inhibitory effect on the development of certain cancers. These conclusions provided new insights into the potential mechanisms of carcinogenesis and needed further research for validation.

Background. Bladder cancer is one of the most common malignancies of the urinary system with an unfavorable prognosis. More and more studies have suggested that lipid metabolism could influence the progression and treatment of tumors. However, there are few studies exploring the relationship between lipid metabolism and bladder cancer. This study aimed to explore the roles that lipid metabolism-related genes play in patients with bladder cancer. Methods. TCGA_BLCA cohort and GSE13507 cohort were included in this study, and transcriptional and somatic mutation profiles of 309 lipid metabolism-related genes were analyzed to discover the critical lipid metabolism-related genes in the incurrence and progression of bladder cancer. Furthermore, the TCGA_BLCA cohort was randomly divided into training set and validation set, and the GSE13507 cohort was served as an external independent validation set. We performed the LASSO regression and multivariate Cox regression in training set to develop a prognostic signature and further verified this signature in TCGA_BLCA validation set and GSE13507 external validation set. Finally, we systematically investigated the association between this signature and tumor microenvironment, drug response, and potential functions and then verified the differential expression status of signature genes in the protein level by immunohistochemistry. Results. A novel 6-lipidmetabolism-related gene signature was identified and validated, and this risk score model could predict the prognosis of patients with bladder cancer. In addition, the prognostic model was tightly related to immune cell infiltration and tumor mutation burden. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) showed that mTOR signaling pathway, G2M checkpoint, fatty acid metabolism, and hypoxia were enriched in patients in the high-risk score groups. Furthermore, 3 therapies specific for bladder cancer patients in different risk scores were identified. Conclusions. In conclusion, we investigated the lipid metabolism-related genes in bladder cancer through comprehensive bioinformatic analysis. A novel 6-gene signature associated with lipid metabolism for predicting the outcomes of patients with bladder cancer was conducted and validated. Furthermore, the risk score model could be utilized to indicate the choice of therapy in bladder cancer.