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Simple Summary: At present, the immunotherapy and immune microenvironment of bladder cancer have attracted more and more attention from clinicians and researchers. In this study, the high expression of SULF2 by RNA sequencing of tissues from 90 bladder cancer patients was associated with poor prognosis in patients. We further found that a high expression of SULF2 can promote the polarization of macrophages to M2. In mechanistic studies, we found that SULF2 can promote the secretion of IL-8 through Wnt/β-catenin. IL-8 promotes the transcription of CD163 and CD206 in the microenvironment, ultimately leading to the polarization of macrophages to M2 macrophages. This study elucidates the effect of SULF2 on the polarization of macrophages in the tumor microenvironment. Sulfatase 2 (SULF2) affects the occurrence and development of cancer by regulating HSPG-binding factors. However, the mechanism of SULF2 in bladder cancer (BCa) is unknown. To determine this, we analyzed the RNA sequencing of 90 patients with BCa. The results showed that the expression of SULF2 was closely related to the prognosis of BCa. Moreover, in vivo and in vitro experiments revealed that SULF2 promotes tumor proliferation and invasion. Furthermore, using a mouse orthotopic BCa model and flow cytometric analysis, we identified that SULF2 affects the polarization of macrophages. Mechanism studies clarified that SULF2 promoted the release of HSPG-binding factors, such as IL-8, in the microenvironment through β-catenin. Meanwhile, IL-8 activated the JAK2/STAT3 pathway of macrophages to promote the expression of CD163 and CD206, thereby regulating the polarization of macrophages to the M2-type. Conclusively, these results indicate that SULF2 plays an important role in regulating the microenvironment of BCa and promotes the polarization of macrophages to the M2-type by secreting IL-8, which further deepens the malignant progression of BCa. [ABSTRACT FROM AUTHOR]

This study aims to investigate the specific predictive role of the preoperative Nutritional Risk Index (NRI) in oligometastatic prostate cancer (OM-PC) patients, who have undergone cytoreductive radical prostatectomy (cRP), and explored its prognostic index values. A total 89 OM-PC patients, who were identified between 2013 and 2019, were included in the present study. The Kaplan-Meier method and Cox regression analysis were used to separately assess the prostate specific antigen (PSA) progression-free survival (PFS). Overall accuracy was determined by analyzing the area under the receiver operating characteristic curve (AUC). The analysis of patients in these three different groups indicated that patients with lower NRI values were significantly associated with a higher Gleason score and more neoadjuvant androgen deprivation therapy (P < 0.05). In addition, the Kaplan-Meier curve analysis revealed that OM-PC patients in the preoperative high-risk group had shorter PSA-PFS (P < 0.001). Furthermore, the multivariate analysis further predicted that the high-risk NRI value is a common independent prognostic factor for shorter PSA-PFS (P < 0.001). Moreover, it was also observed that the AUC value of the NRI score was higher than other conventional nutritional indicators. The present study suggests that NRI can potentially be used as a new prognostic indicator for PSA-PFS for patients with OM-PC after cRP. [ABSTRACT FROM AUTHOR]

Renal clear cell carcinoma (ccRCC) is a highly aggressive and common form of kidney cancer, with limited treatment options for advanced stages. Recent studies have highlighted the importance of the ubiquitin‐proteasome system in tumor progression, particularly the role of ubiquitin‐conjugating enzyme E2 (UBE2) family members. However, the prognostic significance of UBE2‐related genes (UBE2RGs) in ccRCC remains unclear. In this study, bulk RNA‐sequencing and single‐cell RNA‐sequencing data from ccRCC patients were retrieved from the Cancer Genome Atlas and Gene Expression Omnibus databases. Differential expression analysis was performed to identify UBE2RGs associated with ccRCC. A combination of 10 machine learning methods was applied to develop an optimal prognostic model, and its predictive performance was evaluated using area under the curve (AUC) values for 1‐, 3‐, and 5‐year overall survival (OS) in both training and validation cohorts. Functional enrichment analyses of gene ontology and Kyoto Encyclopedia of Genes and Genomes were conducted to explore the biological pathways involved. Correlation analysis was conducted to investigate the association between the risk score and tumor mutational burden (TMB) and immune cell infiltration. Immunotherapy and chemotherapy sensitivity were assessed by immunophenoscore and tumor immune, dysfunction, and exclusion scores to identify potential predictive significance. In vitro, knockdown of the key gene UBE2C in 786‐O cells by specific small interfering RNA to validate its impact on apoptosis, migration, cell cycle, migration, invasion of tumor cells, and induction of regulatory T cells (Tregs). Analysis of sc‐RNA revealed that UBE2 activity was significantly upregulated in malignant cells, suggesting its role in tumor progression. A three‐gene prognostic model comprising UBE2C, UBE2D3, and UBE2T was constructed by Lasoo Cox regression and demonstrated robust predictive accuracy, with AUC values of 0.745, 0.766, and 0.771 for 1‐, 3‐, and 5‐year survival, respectively. The model was validated as an independent prognostic factor in ccRCC. Patients in the high‐risk group had a worse prognosis, higher TMB scores, and low responsiveness to immunotherapy. Additionally, immune infiltration and chemotherapy sensitivity analyses revealed that UBE2RGs are associated with various immune cells and drugs, suggesting that UBE2RGs could be a potential therapeutic target for ccRCC. In vitro experiments confirmed that the reduction of UBE2C led to an increase in apoptosis rate, as well as a decrease in tumor cell invasion and metastasis abilities. Additionally, si‐UBE2C cells reduced the release of the cytokine Transforming Growth Factor‐beta 1 (TGF‐β1), leading to a decreased ratio of Tregs in the co‐culture system. This study presents a novel three‐gene prognostic model based on UBE2RGs that demonstrates significant predictive value for OS, immunotherapy, and chemotherapy in ccRCC patients. The findings underscore the potential of UBE2 family members as biomarkers and therapeutic targets in ccRCC, warranting further investigation in prospective clinical trials. [ABSTRACT FROM AUTHOR]

Renal clear cell carcinoma (ccRCC) is a highly aggressive and common form of kidney cancer, with limited treatment options for advanced stages. Recent studies have highlighted the importance of the ubiquitin-proteasome system in tumor progression, particularly the role of ubiquitin-conjugating enzyme E2 (UBE2) family members. However, the prognostic significance of UBE2-related genes (UBE2RGs) in ccRCC remains unclear. In this study, bulk RNA-sequencing and single-cell RNA-sequencing data from ccRCC patients were retrieved from the Cancer Genome Atlas and Gene Expression Omnibus databases. Differential expression analysis was performed to identify UBE2RGs associated with ccRCC. A combination of 10 machine learning methods was applied to develop an optimal prognostic model, and its predictive performance was evaluated using area under the curve (AUC) values for 1-, 3-, and 5-year overall survival (OS) in both training and validation cohorts. Functional enrichment analyses of gene ontology and Kyoto Encyclopedia of Genes and Genomes were conducted to explore the biological pathways involved. Correlation analysis was conducted to investigate the association between the risk score and tumor mutational burden (TMB) and immune cell infiltration. Immunotherapy and chemotherapy sensitivity were assessed by immunophenoscore and tumor immune, dysfunction, and exclusion scores to identify potential predictive significance. In vitro, knockdown of the key gene UBE2C in 786-O cells by specific small interfering RNA to validate its impact on apoptosis, migration, cell cycle, migration, invasion of tumor cells, and induction of regulatory T cells (Tregs). Analysis of sc-RNA revealed that UBE2 activity was significantly upregulated in malignant cells, suggesting its role in tumor progression. A three-gene prognostic model comprising UBE2C, UBE2D3, and UBE2T was constructed by Lasoo Cox regression and demonstrated robust predictive accuracy, with AUC values of 0.745, 0.766, and 0.771 for 1-, 3-, and 5-year survival, respectively. The model was validated as an independent prognostic factor in ccRCC. Patients in the high-risk group had a worse prognosis, higher TMB scores, and low responsiveness to immunotherapy. Additionally, immune infiltration and chemotherapy sensitivity analyses revealed that UBE2RGs are associated with various immune cells and drugs, suggesting that UBE2RGs could be a potential therapeutic target for ccRCC. In vitro experiments confirmed that the reduction of UBE2C led to an increase in apoptosis rate, as well as a decrease in tumor cell invasion and metastasis abilities. Additionally, si-UBE2C cells reduced the release of the cytokine Transforming Growth Factor-beta 1 (TGF-β1), leading to a decreased ratio of Tregs in the co-culture system. This study presents a novel three-gene prognostic model based on UBE2RGs that demonstrates significant predictive value for OS, immunotherapy, and chemotherapy in ccRCC patients. The findings underscore the potential of UBE2 family members as biomarkers and therapeutic targets in ccRCC, warranting further investigation in prospective clinical trials., (© 2024 International Union of Biochemistry and Molecular Biology.)