Untargeted metabolomics reveals that declined PE and PC in obesity may be associated with prostate hyperplasia.

BACKGROUND: Recent studies have shown that obesity may contribute to the pathogenesis of benign prostatic hyperplasia (BPH). However, the mechanism of this pathogenesis is not fully understood. METHODS: A prospective case-control study was conducted with 30 obese and 30 nonobese patients with BPH. Prostate tissues were collected and analyzed using ultra performance liquid chromatography ion mobility coupled with quadrupole time-of-flight mass spectrometry (UPLC-IMS-Q-TOF). RESULTS: A total of 17 differential metabolites (3 upregulated and 14 downregulated) were identified between the obese and nonobese patients with BPH. Topological pathway analysis indicated that glycerophospholipid (GP) metabolism was the most important metabolic pathway involved in BPH pathogenesis. Seven metabolites were enriched in the GP metabolic pathway. lysoPC (P16:0/0:0), PE (20:0/20:0), PE (24:1(15Z)/18:0), PC (24:1(15Z)/14:0), PC (15:0/24:0), PE (24:0/18:0), and PC (16:0/18:3(9Z,12Z,15Z)) were all significantly downregulated in the obesity group, and the area under the curve (AUC) of LysoPC (P-16:0/0/0:0) was 0.9922. The inclusion of the seven differential metabolites in a joint prediction model had an AUC of 0.9956. Thus, both LysoPC (P-16:0/0/0:0) alone and the joint prediction model demonstrated good predictive ability for obesity-induced BPH mechanisms. CONCLUSIONS: In conclusion, obese patients with BPH had a unique metabolic profile, and alterations in PE and PC in these patients be associated with the development and progression of BPH.

Genes associated with inflammation for prognosis prediction for clear cell renal cell carcinoma: a multi-database analysis.

Background: Clear cell renal cell carcinoma (ccRCC) is the largest subtype of kidney tumour, with inflammatory responses characterising all stages of the tumour. Establishing the relationship between the genes related to inflammatory responses and ccRCC may help the diagnosis and treatment of patients with ccRCC. Methods: First, we obtained the data for this study from a public database. After differential analysis and Cox regression analysis, we obtained the genes for the establishment of a prognostic model for ccRCC. As we used data from multiple databases, we standardized all the data using the surrogate variable analysis (SVA) package to make the data from different sources comparable. Next, we used a least absolute shrinkage and selection operator (LASSO) regression to construct a prognostic model of genes related to inflammation. The data used for modelling and internal validation came from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) series (GSE29609) databases. ccRCC data from the International Cancer Genome Consortium (ICGC) database were used for external validation. Tumour data from the E-MTAB-1980 cohort were used for external validation. The GSE40453 and GSE53757 datasets were used to verify the differential expression of inflammation-related gene model signatures (IRGMS). The immunohistochemistry of IRGMS was queried through the Human Protein Atlas (HPA) database. After the adequate validation of the IRGM, we further explored its application by constructing nomograms, pathway enrichment analysis, immunocorrelation analysis, drug susceptibility analysis, and subtype identification. Results: The IRGM can robustly predict the prognosis of samples from patients with ccRCC from different databases. The verification results show that nomogram can accurately predict the survival rate of patients. Pathway enrichment analysis showed that patients in the high-risk (HR) group were associated with a variety of tumorigenesis biological processes. Immune-related analysis and drug susceptibility analysis suggested that patients with higher IRGM scores had more treatment options. Conclusions: The IRGMS can effectively predict the prognosis of ccRCC. Patients with higher IRGM scores may be better candidates for treatment with immune checkpoint inhibitors and have more chemotherapy options.

Prognosis Prediction of Disulfidptosis-Related Genes in Bladder Cancer and a Comprehensive Analysis of Immunotherapy.

As a newly discovered mechanism of cell death, disulfidptosis is expected to help diagnose and treat bladder cancer patients. First, data obtained from public databases were analyzed using bioinformatics techniques. SVA packages were used to combine data from different databases to remove batch effects. Then, the differential analysis and COX regression analysis of ten disulfidptosis-related genes identified four prognostically relevant differentially expressed genes which were subjected to Lasso regression for further screening to obtain model-related genes and output model formulas. The predictive power of the prognostic model was verified and the immunohistochemistry of model-related genes was verified in the HPA database. Pathway enrichment analysis was performed to identify the mechanism of bladder cancer development and progression. The tumor microenvironment and immune cell infiltration of bladder cancer patients with different risk scores were analyzed to personalize treatment. Then, information from the IMvigor210 database was used to predict the responsiveness of different risk patients to immunotherapy. The oncoPredict package was used to predict the sensitivity of patients at different risk to chemotherapy drugs, and its results have some reference value for guiding clinical use. After confirming that our model could reliably predict the prognosis of bladder cancer patients, the risk scores were combined with clinical information to create a nomogram to accurately calculate the patient survival rate. A prognostic model containing three disulfidptosis-related genes (NDUFA11, RPN1, SLC3A2) was constructed. The functional enrichment analysis and immune-related analysis indicated patients in the high-risk group were candidates for immunotherapy. The results of drug susceptibility analysis can guide more accurate treatment for bladder cancer patients and the nomogram can accurately predict patient survival. NDUFA11, RPN1, and SLC3A2 are potential novel biomarkers for the diagnosis and treatment of bladder cancer. The comprehensive analysis of tumor immune profiles indicated that patients in the high-risk group are expected to benefit from immunotherapy.

Telomere maintenance-related genes are important for survival prediction and subtype identification in bladder cancer.

Background: Bladder cancer ranks among the top three in the urology field for both morbidity and mortality. Telomere maintenance-related genes are closely related to the development and progression of bladder cancer, and approximately 60%-80% of mutated telomere maintenance genes can usually be found in patients with bladder cancer. Methods: Telomere maintenance-related gene expression profiles were obtained through limma R packages. Of the 359 differential genes screened, 17 prognostically relevant ones were obtained by univariate independent prognostic analysis, and then analysed by LASSO regression. The best result was selected to output the model formula, and 11 model-related genes were obtained. The TCGA cohort was used as the internal group and the GEO dataset as the external group, to externally validate the model. Then, the HPA database was used to query the immunohistochemistry of the 11 model genes. Integrating model scoring with clinical information, we drew a nomogram. Concomitantly, we conducted an in-depth analysis of the immune profile and drug sensitivity of the bladder cancer. Referring to the matrix heatmap, delta area plot, consistency cumulative distribution function plot, and tracking plot, we further divided the sample into two subtypes and delved into both. Results: Using bioinformatics, we obtained a prognostic model of telomere maintenance-related genes. Through verification with the internal and the external groups, we believe that the model can steadily predict the survival of patients with bladder cancer. Through the HPA database, we found that three genes, namely ABCC9, AHNAK, and DIP2C, had low expression in patients with tumours, and eight other genes-PLOD1, SLC3A2, RUNX2, RAD9A, CHMP4C, DARS2, CLIC3, and POU5F1-were highly expressed in patients with tumours. The model had accurate predictive power for populations with different clinicopathological features. Through the nomogram, we could easily assess the survival rate of patients. Clinicians can formulate targeted diagnosis and treatment plans for patients based on the prediction results of patient survival, immunoassays, and drug susceptibility analysis. Different subtypes help to further subdivide patients for better treatment purposes. Conclusion: According to the results obtained by the nomogram in this study, combined with the results of patient immune-analysis and drug susceptibility analysis, clinicians can formulate diagnosis and personalized treatment plans for patients. Different subtypes can be used to further subdivide the patient for a more precise treatment plan.

Danshen protects liver grafts from ischemia/reperfusion injury in experimental liver transplantation in rats.

Reperfusion injury remains one of the major problems in transplantation. Free radicals and disturbance of microcirculation are the supposed main contributors. Recent evidence shows that Danshen, a traditional Chinese drug used in vascular diseases, can scavenge radicals and improve microcirculation. This study investigates its effect on liver transplantation (LTx). Before organ recovery, female Sprague-Dawley rats (210-240 g) received intravenous Danshen or the same volume of Ringer solution as control. LTx was performed after 1 h of cold storage. Microperfusion, leukocyte-endothelium interaction and latex-bead phagocytosis were evaluated with in vivo microscopy. Survival, transaminases and histology were assessed. Immunohistology was used for TNF-alpha levels. anova and Fisher's exact test were employed for statistical analyses as appropriate. Survival increased from 60% in controls to 100% (P < 0.05). AST and LDH decreased from 3969 +/- 1255 U/l and 15444 +/- 5148 U/l in controls to 1236 +/- 410 U/l and 5039 +/- 1594 U/l, respectively (P < 0.05). In vivo microscopy revealed decreased leukocyte-adherence and increased blood flow velocity in sinusoidal zones after administration of Danshen (P < 0.05), while latex-bead phagocytosis was found in 60% of controls (P < 0.05). The TNF-alpha index decreased from 2.08 +/- 0.09 in controls to 1.09 +/- 0.09 (P < 0.05). This study clearly demonstrates hepatoprotective effects after experimental LTx, which can be explained via anti-oxidative effects, improved microcirculation and decreased Kupffer cell activation.

Danshen protects kidney grafts from ischemia/reperfusion injury after experimental transplantation.

Danshen (DS) is used for treatment of various ischemic events in the traditional Chinese medicine. Hence, this study was designed to investigate its effect on ischemia/reperfusion injury (IRI) after experimental kidney transplantation (eKTx). Nephrectomized Sprague-Dawley rats underwent eKTx. Some animals were infused with 1.5 ml DS 10 min before surgery. Kidney grafts were transplanted after cold storage for 20 h in Histidine-Tryptophane-Ketoglutarate solution. After reperfusion blood samples were collected for blood urinary nitrogen (BUN), creatinine, lactate dehydrogenase (LDH), and alanine transaminase. Further, tissue was assessed for morphologic and pathophysiologic changes. Donor preconditioning with DS (DS-d) significantly decreased BUN, creatinine, LDH, and aspartate aminotransferase to 65-97% of controls while preconditioning of the recipient (DS-r) decreased values to 58-82% (P < 0.05). Tubular damage and caspase-3 decreased significantly in both DS-d and DS-r (DS-d: 96% and 67%, DS-r: 83% and 75% of controls) while heat shock protein 72 and superoxide dismutase increased significantly (DS-d: 143% and 173%, DS-r: 166% and 194% of controls). Further, inducible nitric oxide synthase and tumor necrosis factor-alpha decreased (DS-d: 84% and 61%, DS-r: 79% and 67% of controls) after DS. Preconditioning of both donors and recipients with DS significantly reduces IRI and thus improves graft function after eKTx.

Donor preconditioning with taurine protects kidney grafts from injury after experimental transplantation.

BACKGROUND: Ischemia/reperfusion injury is a major problem in clinical transplantation (Tx). Taurine has been shown to protect liver grafts from ischemia/reperfusion injury after Tx. Thus, this study was designed to evaluate its effect on kidney grafts after transplantation. MATERIALS AND METHODS: Various concentrations of taurine were infused before donor nephrectomy (1.5 mL; 30, 100, 300 mM). Controls were given the same volume of Ringers' solution. Subsequently, grafts were cold-stored for 19 h in histidine-tryptophan-ketoglutarate solution and transplanted. Six hours after Tx, graft function and injury were assessed with blood urea nitrogen/creatinine and aspartate aminotransferase/lactate dehydrogenase. Graft biopsies were taken to evaluate tubular damage, caspase-3, superoxide dismutase, and heat shock protein 72 (HSP-72) to index necrosis, apoptosis, antioxidative capacity, and regeneration, respectively. RESULTS: Taurine significantly decreased blood urea nitrogen, creatinine, aspartate aminotransferase, and lactate dehydrogenase in a dose-dependent manner to up to 71%, 69%, 51%, and 53% of controls, respectively. Further, tubular damage and caspase-3 expression decreased to 44% and 18% of control values (P < 0.01), while superoxide dismutase and heat shock protein 72 expression increased by 95% and 77% of controls, respectively (P < 0.05). CONCLUSIONS: This study demonstrates that donor preconditioning with taurine protects kidney grafts from injury (apoptosis, necrosis), improves graft function, and increases the regenerative potential most likely via mechanisms including antioxidation.