Brevilin A Inhibits Prostate Cancer Progression by Decreasing PAX5-Activated SOX4.

Brevilin A possesses inhibitory effects on the development of prostate cancer (PCa); however, the underlying mechanism remains unclear. The present work aims to analyze how Brevilin A regulates PCa cell malignancy. RNA expression of paired box 5 (PAX5) and SRY-box transcription factor 4 (SOX4) was analyzed by quantitative real-time polymerase chain reaction. Protein expression of PAX5, SOX4, and nuclear proliferation marker (Ki67) was detected by western blotting or immunohistochemistry assay. The viability, proliferation, apoptosis, and migratory and invasive abilities of PCa cells were investigated by cell counting kit-8 (CCK-8), 5-Ethynyl-2'-deoxyuridine (EdU), flow cytometry, and transwell assays, respectively. The association between PAX5 and SOX4 was identified by dual-luciferase reporter assay and chromatin immunoprecipitation assay. Xenograft mouse model assay was used to reveal the effect of Brevilin A on tumor tumorigenesis in vivo. PAX5 and SOX4 expression were upregulated in PCa tissues and cells relative to normal prostate tissues and human prostate epithelial cells. Brevilin A treatment inhibited PAX5 protein expression in PCa cells. Additionally, Brevilin A inhibited proliferation, migration and invasion and induced apoptosis of PCa cells, whereas these effects were attenuated after PAX5 overexpression. SOX4 was transcriptionally activated by PAX5, and its introduction partially relieved the inhibitory effects of PAX5 knockdown on PCa cell malignancy. Moreover, Brevilin A delayed tumor formation in vivo. Brevilin A inhibited PCa progression by regulating SOX4 expression in a PAX5-dependent manner, providing a promising anti-tumor drug for PCa.

Invasive Epithelioid Angiomyolipoma with Tumor Thrombus in the Inferior Vena Cava: A Case Report and Literature Review.

Renal angiomyolipoma (AML) is a benign tumor. However, rare cases of renal AML demonstrate aggressive behaviors such as tumor thrombus extension into the inferior vena cava (IVC). We successfully treated a case of epithelioid AML in the right kidney involving the IVC. We also reviewed and analyzed 45 case reports of the common type of AML. Radiologists and clinicians should know that epithelioid AML can be an aggressive tumor.

miR-1301 promotes prostate cancer proliferation through directly targeting PPP2R2C.

Prostate cancer is the leading cause of cancer deaths among men in the worldwide, it's important to find new prognostic factors and therapeutic targets. microRNAs play critical roles in the development and progression of prostate cancer. Here we revealed miR-1301 promoted prostate cancer progression. miR-1301 was upregulated in prostate cancer tissues and cells, overexpression of miR-1301 promoted anchorage-dependent and -independent growth using MTT analysis, colony formation analysis and soft agar growth analysis, whereas knockdown of miR-1301 suppressed anchorage-dependent and -independent growth. We also found overexpression of miR-1301 inhibited p27 expression and promoted Cyclin D1 expression, whereas knockdown of miR-1301 reduced this effect, suggesting miR-1301 promoted the G1/S transition. These results suggested miR-1301 promoted cell proliferation of prostate cancer. microRNAs can inhibit target mRNA translation or/and induce mRNA degradation, we found tumor suppresser PPP2R2C was the target of miR-1301, simultaneous downregualtion of PPP2R2C and miR-1301 promoted anchorage-dependent and -independent growth. These findings suggested miR-1301 promoted prostate cancer proliferation by inhibiting PPP2R2C, and might a therapeutic target for prostate cancer.

Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

OBJECTIVES: To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. METHODS: The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. RESULTS: Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. CONCLUSIONS: Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC.