Prostate cancer (PCa) stands as a prominent contributor to morbidity and mortality among males on a global scale. Cancer-associated fibroblasts (CAFs) are considered to be closely connected to tumour growth, invasion, and metastasis. We explored the role and characteristics of CAFs in PCa through bioinformatics analysis and built a CAFs-based risk model to predict prognostic treatment and treatment response in PCa patients. First, we downloaded the scRNA-seq data for PCa from the GEO. We extracted bulk RNA-seq data for PCa from the TCGA and GEO and adopted “ComBat” to remove batch effects. Then, we created a Seurat object for the scRNA-seq data using the package “Seurat” in R and identified CAF clusters based on the CAF-related genes (CAFRGs). Based on CAFRGs, a prognostic model was constructed by univariate Cox, LASSO, and multivariate Cox analyses. And the model was validated internally and externally by Kaplan–Meier analysis, respectively. We further performed GO and KEGG analyses of DEGs between risk groups. Besides, we investigated differences in somatic mutations between different risk groups. We explored differences in the immune microenvironment landscape and ICG expression levels in the different groups. Finally, we predicted the response to immunotherapy and the sensitivity of antitumour drugs between the different groups. We screened 4 CAF clusters and identified 463 CAFRGs in PCa scRNA-seq. We constructed a model containing 10 prognostic CAFRGs by univariate Cox, LASSO, and multivariate Cox analysis. Somatic mutation analysis revealed that TTN and TP53 were significantly more mutated in the high-risk group. Finally, we screened 31 chemotherapeutic drugs and targeted therapeutic drugs for PCa. In conclusion, we identified four clusters based on CAFs and constructed a new CAFs-based prognostic signature that could predict PCa patient prognosis and response to immunotherapy and might suggest meaningful clinical options for the treatment of PCa.

The aim of the study was to explore the role and molecular mechanism of dual-specificity phosphatase 8 (DUSP8) in the drug resistance of trastuzumab in breast cancer. Real-time PCR and western blot detected the difference in expression of DUSP8 between breast cancer tissue/cells and trastuzumab-resistant tissues/cells. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value of DUSP8 in breast cancer. si-DUSP8 or dusp8 overexpression vector was transiently transfected, and the effects of si-DUSP8 on apoptosis, cell viability and cell migration of drug-resistant cell lines were investigated by flow cytometry, MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-tetrazolium bromide) and Transwell assays, and its regulation mechanism finally explored. The results showed that the expression of DUSP8 in breast cancer tissues and cells was significantly higher than in matched non-tumor tissues and cells. DUSP8 was significantly upregulated in non-responsive patients compared with patients who responded to trastuzumab. ROC analysis showed that the area under the curve was 0.732, and the diagnostic sensitivity and specificity were 64.86% and 75.76%. DUSP8 knockdown promotes apoptosis and reduces trastuzumab resistance in BT474/TR and SKBR3/TR cells by inhibiting cell migration and cell viability. Knockdown of DUSP8 increased the expression of p-p38 and p-ERK, and the regulation of DUSP8 in chemotherapy resistance of breast cancer cells may be realized by mediating mitogen-activated protein kinase (MAPK)-related signaling pathways. In conclusion, knockdown of DUSP8 expression in trastuzumab-resistant cells can inhibit cell migration and proliferation, and leads to decreased drug resistance by activating MAPK signaling pathway in trastuzumab-resistant cells.

Methylation has a close relationship with immune reactions, metastasis, and cancer cell growth. Additionally, RNA methylation-related proteins have emerged as potential cancer therapeutic targets. The connection between the tumor microenvironment (TME) and methylation-related genes (MRGs) remains unclear. We explored the expression patterns of the MRGs in the genome and transcriptional fields of 796 prostate cancer (PCa) samples using two separate data sets. We identified a relationship between patient clinicopathological characteristics, prognosis, TME cell infiltrating qualities, and different MRG changes, as well as the identification of two distinct molecular groupings. Then, we formed an MRGs model to predict overall survival (OS), and we tested the accuracy of the model in patients with PCa. In addition, we developed a very accurate nomogram to improve the MRG model’s clinical applicability. The low-risk group had fewer tumor mutational burden (TMB), greater tumor immune dysfunction and exclusion (TIDE) ratings, fewer mutant genes, and better OS prospects. We discuss how MGRs may affect the prognosis, clinically important traits, TME, and immunotherapy responsiveness in PCa. In order to get a better understanding of MRGs in PCa, we could further explore the prognosis and create more effective immunotherapy regimens to open new avenues.

We assessed the use of common urodynamics (CUD) combined with contrast-enhanced ultrasound (CEUS) to investigate the efficacy and durability of sigmoid cystoplasty alone in patients with low bladder compliance associated with vesicoureteric reflux (VUR). In this study, we recruited 25 patients with low bladder compliance and VUR who underwent bladder augmentation without antireflux surgery at our institutions between June 2017 and June 2021. The bladder condition and VUR grade were assessed preoperatively and postoperatively via CUD combined with CEUS. The mean follow-up period was 2.6 years. CUD showed significant improvement in bladder capacity and compliance and a decrease in intravesical pressure after sigmoid cystoplasty. CEUS demonstrated resolution of VUR compared with preoperative assessment. Of the 25 patients who had various degrees of reflux, VUR was eliminated in 18 patients and reduced to a lower grade in the remaining seven patients. CUD combined with CEUS is accurate and safe. They are invaluable and reliable tools for morphological and functional evaluations of the entire urinary tract in patients with low bladder compliance and VUR.

Background: RNA methylation modifications, such as N1-methyladenosine/N6-methyladenosine /N5-methylcytosine (m¹A/m⁶A/m⁵C), are the most common RNA modifications and are crucial for a number of biological processes. Nonetheless, the role of RNA methylation modifications of m¹A/m⁶A/m⁵C in the pathogenesis of renal interstitial fibrosis (RIF) remains incompletely understood. Methods: Firstly, we downloaded 2 expression datasets from the GEO database, namely GSE22459 and GSE76882. In a differential analysis of these datasets between patients with and without RIF, we selected 33 methylation-related genes (MRGs). We then applied a PPI network, LASSO analysis, SVM-RFE algorithm, and RF algorithm to identify key MRGs. Results: We eventually obtained five candidate MRGs (WTAP, ALKBH5, YTHDF2, RBMX, and ELAVL1) to forecast the risk of RIF. We created a nomogram model derived from five key MRGs, which revealed that the nomogram model may be advantageous to patients. Based on the selected five significant MRGs, patients with RIF were classified into two MRG patterns using consensus clustering, and the correlation between the five MRGs, the two MRG patterns, and the genetic pattern with immune cell infiltration was shown. Moreover, we conducted GO and KEGG analyses on 768 DEGs between MRG clusters A and B to look into their different involvement in RIF. To measure the MRG patterns, a PCA algorithm was developed to determine MRG scores for each sample. The MRG scores of the patients in cluster B were higher than those in cluster A. Conclusions: Ultimately, we concluded that cluster A in the two MRG patterns identified on these five key m¹A/m⁶A/m⁵C regulators may be associated with RIF.

Circular RNAs (circRNAs) contribute to the malignant phenotype and progression of several types of human cancers, including renal cell carcinoma (RCC). This study probed the molecular mechanism of circPGPEP1 regulating RCC proliferation, Warburg effect, and distant metastasis by targeting the miR-378a-3p/JPT1 axis. Here identified higher circPGPEP1 expression in RCC tissues and cells by RT-qPCR, and high levels of circPGPEP1 were positively correlated with high histological grade and distant metastasis in RCC patients. Furthermore, patients with high levels of circPGPEP1 had a worse survival prognosis. Functional assays presented that knockdown of circPGPEP1 inhibited RCC proliferation, invasion, migration, EMT, and Warburg effect. Dual-luciferase reporter assay, RNA immunoprecipitation, nucleoplasmic RNA isolation, and functional rescue experiments confirmed that circPGPEP1 induced JPT1 expression by sponging miR-378a-3p, thereby promoting RCC malignant phenotype. Xenograft assays and metastasis models further demonstrated that down-regulation of circPGPEP1 effectively inhibited tumor growth and distant metastasis of RCC. Taken together, circPGPEP1, a prognostic circRNA in RCC, acts through the miR-378a-3p/JPT1 axis to regulate RCC progression.