Gasdermin B (GSDMB) is part of the gasdermin (GSDM) family, and they use varying means of domain interactions in molecules to adjust their pore-forming and lipid-binding actions. The GSDM family has roles in the regulation of cell differentiation and proliferation, particularly in the process of pyroptosis. Nonetheless, the correlation of GSDMB with immune infiltrates and its prognostic values in clear cell renal cell carcinoma (ccRCC) are still undefined. Therefore, we assessed the correlation of GSDMB with immune infiltrates and its prognostic role in ccRCC. The transcriptional expression profiles of GSDMB in ccRCC tissues in addition to normal tissues were retrieved from The Cancer Genome Atlas (TCGA) and additionally verified in a different independent cohort, which was obtained from the Gene Expression Omnibus (GEO) database. The Human Protein Atlas and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) were used to assess the protein expression of GSDMB. To assess the effectiveness of GSDMB in distinguishing ccRCC from normal samples, the receiver operating characteristic (ROC) curve analysis was performed. Relationships between GSDMB expression, clinicopathological variables, and overall survival (OS) were evaluated with multivariate methods as well as Kaplan-Meier survival curves. Protein-protein interaction (PPI) networks were created with STRING. Functional enrichment analyses were conducted by utilizing the “ClusterProfiler” package. The Tumor Immune Estimation Resource (TIMER) and tumor-immune system interaction database (TISIDB) were utilized to determine the association between the mRNA expression of GSDMB and immune infiltrates. GSDMB expression was significantly more upregulated in ccRCC tissues compared to surrounding normal tissues. An increase in the mRNA expression of GSDMB was related to the high pathologic stage and advanced TNM stage. The analysis of the ROC curve indicated that GSDMB had an AUC value of 0.820 to distinguish between ccRCC tissues and adjacent normal controls. Kaplan-Meier survival analysis indicated that ccRCC patients with high GSDMB had a poorer prognosis compared to those with low GSDMB ( P < 0.001 ). Correlation analysis showed that the mRNA expression of GSDMB was associated with immune infiltrates and the purity of the tumor. Upregulation of GSDMB is significantly related to immune infiltrates and poor survival in ccRCC. The results of this study indicate that GSDMB could be regarded as a biomarker for the detection of poor prognosis and potential target of immune treatment in ccRCC.
Purpose. This study aimed to establish a nomogram to predict the overall survival (OS) of patients with bladder cancer (BC) by ferroptosis-related long noncoding RNAs (FRlncRNAs) signature. Methods. We obtained FRlncRNAs expression profiles and clinical data of patients with BC from the Cancer Genome Atlas database. The patients were divided into the training set, testing set, and overall set. Lasso regression and multivariate Cox regression were used to establish the FRlncRNAs signature, the prognosis of each group was compared by Kaplan–Meier (K-M) analysis, and the receiver operating characteristic (ROC) curve evaluated the accuracy of the model. The Gene Set Enrichment Analysis (GSEA) was used for the visualization of the functional enrichment for FRlncRNAs. The databases of GEPIA and K-M Plotter were used for subsequent functional analysis of major FRlncRNAs. Results. Thirteen prognostic FRlncRNAs (LINC00942, MAFG-DT, AL049840.3, AL136084.3, OCIAD1-AS1, AC062017.1, AC008074.2, AC018653.3, AL031775.1, USP30-AS1, LINC01767, AC132807.2, and AL354919.2) were identified to be significantly different, constituting an FRlncRNAs signature. Patients with BC were divided into low-risk group and high-risk group by this signature in the training, testing, and overall sets. K-M analysis showed that the prognosis of patients in the high-risk group was poor and the difference in the subgroup analyses was statistically significant. ROC analysis revealed that the predictive ability of the model was more accurate than traditional assessment methods. A risk score based on FRlncRNAs signature was an independent prognostic factor for the patients with BC (HR = 1.388, 95%CI = 1.228–1.568, P < 0.001 ). Combining the FRlncRNAs signature and clinicopathological factors, a predictive nomogram was constructed. The nomogram can accurately predict the overall survival of patients and had high clinical practicability. The GSEA analysis showed that the primary pathways were WNT, MAPK, and cell-matrix adhesion signaling pathways. The major FRlncRNAs (MAFG-DT) were associated with poor prognosis in the GEPIA and K-M Plotter database. Conclusion. Thirteen prognostic FRlncRNAs and their nomogram were accurate tools for predicting the OS of BC, which might be molecular biomarkers and therapeutic targets.
The meta-analysis was performed to access efficacy of L-carnitine/L-acetyl-carnitine (LC/LAC) and N-acetyl-cysteine (NAC) in men with idiopathic asthenozoospermia. We researched PubMed, EMBASE, and Cochrane Library databases and references to related articles. Finally, seven articles including 621 patients were analyzed. The results indicated that LC/LAC and NAC had a considerable improvement in sperm motility ( p = .03 and p < .0001, respectively) and normal morphology ( p = .006, p = .0002, respectively) compared with the placebo group. Besides, NAC had a significantly greater increase in sperm concentration ( p < .00001) and ejaculate volume ( p = .002) compared with the placebo group, and there was no significant difference in LC/LAC. For the analysis of serum hormones, NAC had no obvious differences in improving the serum testosterone, luteinizing hormone, follicle-stimulating hormone, and prolactin compared with non-treatment group. Conclusively, LC/LAC and NAC showed a greater improvement in sperm motility and normal morphology. Moreover, NAC has a positive effect on sperm concentration and ejaculate volume, whereas no obvious effect was observed in serum hormones.
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