Background Pyroptosis can not only inhibit the occurrence and development of tumors but also develop a microenvironment conducive to cancer growth. However, pyroptosis research in prostate cancer (PCa) has rarely been reported. Methods The expression profile and corresponding clinical data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Patients were divided into different clusters using consensus clustering analysis, and differential genes were obtained. We developed and validated a prognostic biomarker for biochemical recurrence (BCR) of PCa using univariate Cox analysis, Lasso-Cox analysis, Kaplan–Meier (K–M) survival analysis, and time-dependent receiver operating characteristics (ROC) curves. Results The expression levels of most pyroptosis-related genes (PRGs) are different not only between normal and tumor tissues but also between different clusters. Cluster 2 patients have a better prognosis than cluster 1 patients, and there are significant differences in immune cell content and biological pathway between them. Based on the classification of different clusters, we constructed an eight genes signature that can independently predict the progression-free survival (PFS) rate of a patient, and this signature was validated using a GEO data set (GSE70769). Finally, we established a nomogram model with good accuracy. Conclusions In this study, PRGs were used as the starting point and based on the expression profile and clinical data, a prognostic signature with a high predictive value for biochemical recurrence (BCR) following radical prostatectomy (RP) was finally constructed, and the relationship between pyroptosis, immune microenvironment, and PCa was explored, providing important clues for future research on pyroptosis and immunity.

The association between COMT Val158Met polymorphism and prostate cancer has been evaluated. However, the results of these studies on the association remain conflicting. To derive a more precise estimation of the relationship, a meta-analysis was performed. A comprehensive search was conducted to identify the eligible studies of COMT Val158Met polymorphism and prostate cancer risk. Summary odds ratios (OR) and 95 % confidence interval (CI) for COMT Val158Met polymorphism and prostate cancer were calculated. Statistical analysis was performed with the software program Review Manage (Version 5.0) and Stata (Version 12.0). Six case-control studies, totally 4,118 persons including 2,143 cases and 1,975 controls, met the included criteria and thus were selected. Our analysis suggested that Val158Met polymorphism was associated with prostate cancer risk in overall population. Collectively, the results of the present study suggest that significant associations of COMT Val158Met polymorphisms with prostate cancer were observed (for additive model: OR = 1.068, 95 % CI = 1.002-1.138, P (heterogeneity) = 0.363, P = 0.043; for dominant model: OR = 1.266, 95 % CI = 1.057-1.517, P (heterogeneity) = 0.000, P = 0.011; for recessive model: OR = 1.050, 95 % CI = 0.961-1.146, P (heterogeneity) = 0.558, P = 0.279; and Val allele versus Met allele OR = 0.932, 95 % CI = 0.894-0.971, P (heterogeneity) = 0.272, P = 0.001). In the subgroup analysis, we detected no significant association between the COMT 158 Val/Met genotype and prostate cancer risk in Caucasian and Asian populations, while the contrary result for additive model (OR = 2.43, 95 % CI = 1.08-5.43, P (heterogeneity) = 0.04, P = 0.03) in Asian populations. The result of this meta-analysis suggests that COMT l58Val/Met polymorphism might be contributed to the overall prostate cancer risk.

Departmental sources Background: Orientin is a flavone isolated from medicinal plants used in traditional Chinese medicine (TCM), which suppresses the growth of cancer cells in vitro. The effects of orientin in bladder cancer cells remains unknown. This study aimed to investigate the effect of orientin on proliferation and apoptosis of T24 human transitional cell bladder carcinoma cells in vitro in the presence of an agonist and an inhibitor of nuclear factor-kappaB (NF-kB). Material/Methods: T24 cells were cultured and divided into four study groups: an untreated control group; a group treated with 100 μM orientin; a group treated with 100 μM orientin with NF-kB agonist, phorbol 12-myristate 13-acetate (PMA); and a group treated with 100 μM orientin and the NF-kB inhibitor, IkBa. The MTT assay was performed to assess cell viability, and flow cytometry evaluated the cell cycle. The expression of proteins in the Hedgehog signaling pathway and inflammatory cytokines were determined by Western blot and enzyme-linked immunosorbent assay (ELISA). Results: Orientin inhibited the proliferation of T24 cells, caused cell cycle arrest, reduced cell viability, and inhibited the expression of inflammatory mediators. Treatment of T24 cells with orientin inhibited the expression of NF-kB and components of the Hedgehog signaling pathway, and the NF-kB agonist, PMA, reversed these effects. Conclusions: Treatment of T24 human bladder carcinoma cells in vitro with orientin inhibited cell proliferation and promoted cell apoptosis by suppressing the Hedgehog signaling pathway and NF-kB.

Background: M7G modification is extremely vital for the development of many cancers, especially tumor immunity. M7G modification is a novel functional regulator of miRNA, and the researches on m7G-related miRNAs in kidney renal clear cell carcinoma (KIRC) are still insufficient. This research aims to establish a risk signature on the foundation of m7G-associated miRNAs, which can precisely forecast the prognosis of KIRC patients.Methods: Transcriptome data and clinical data used in this study come from The Cancer Genome Atlas database. Our team utilized univariable Cox, Lasso and multivariable Cox analyses to construct a m7G-associated miRNAs risk signature that can forecast the prognosis of KIRC patients. Kaplan-Meier method, time-dependent receiver operating characteristic (ROC) curve, and the independent analysis of risk signatures were employed to verify the predictability and accuracy of the risk signature. Subsequently, based on CIBERSORT, ESTIMATE and ssGSEA algorithms, we speculated the potential impact of the proposed risk signature on tumor immune microenvironment. Ultimately, by virtue of the risk signature and tumor immunity, the hub genes affecting the prognosis of KIRC patients were screened out.Results: Our team established and verified a prognostic signature comprising 7 m7G-associated miRNAs (miR-342-3p, miR-221-3p, miR-222-3p, miR-1277-3p, miR-6718-5p, miR-1251-5p, and miR-486-5p). The results of the Kaplan-Meier survival analysis revealed that the prognosis of KIRC sufferers in the high-risk group was often unsatisfactory. The accuracy of the prediction ability of the risk signature was verified by calculating the area under the ROC curve. Univariate-multivariate Cox analyses further showed that this risk signature could be utilized as an independent prognosis-related biomarker for KIRC sufferers. The results of the immune analysis revealed that remarkable diversities existed in immune status and tumor microenvironment between high-risk and low-risk groups. On the foundation of the proposed risk signature and other clinical factors, a nomogram was established to quantitatively forecast the survival of KIRC sufferers at 1, 3 and 5 years.Conclusion: Based on m7G-related miRNAs, a risk signature was successfully constructed, which could precisely forecast the prognosis of sufferers and guide personalized immunotherapy for KIRC patients.

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Background: Pyroptosis can not only inhibit the occurrence and development of tumors but also develop a microenvironment conducive to cancer growth. However, pyroptosis research in prostate cancer (PCa) has rarely been reported.Methods: The expression profile and corresponding clinical data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Patients were divided into different clusters using consensus clustering analysis, and differential genes were obtained. We developed and validated a prognostic signature for biochemical recurrence (BCR) of PCa using univariate Cox analysis, LASSO-COX analysis, Kaplan-Meier (K-M) survival analysis, and time-dependent receiver operating characteristics (ROC) curves.Results: The expression levels of most pyroptosis-related genes (PRGs) are different not only between normal and tumor tissues but also between different clusters. Cluster2 patients have a better prognosis than cluster1 patients, and there are significant differences in immune cell content and biological pathway between them. Based on the classification of different clusters, we constructed an eight genes signature that can independently predict the progression-free survival (PFS) rate of a patient, and this signature was validated using a GEO data set (GSE70769). Finally, we established a nomogram model with good usability.Conclusions: In this study, PRGs were used as the starting point and based on the expression profile and clinical data, a prognostic signature with a high predictive value for biochemical recurrence (BCR) following radical prostatectomy (RP) was finally constructed, and the relationship between pyroptosis, immune microenvironment, and PCa was explored, providing important clues for future research on pyroptosis and immunity.

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