A Versatile Assay for Detection of Aberrant DNA Methylation in Bladder Cancer

Bioinformatics analysis of the interactions among lncRNA, miRNA and mRNA expression, genetic mutations and epigenetic modifications in hepatocellular carcinoma

The present study aimed to investigate the regulatory networks involving long noncoding RNA (lncRNA), microRNA (miRNA), mRNA, genetic mutations and epigenetic modifications in hepatocellular carcinoma (HCC) by analyzing datasets from The Cancer Genome Atlas (TCGA) database. TCGA was mined, and miRNAs, lncRNAs and mRNAs that were differentially expressed in HCC were identified using R software. A gene regulatory network was constructed using Cytoscape software. Representative genes were selected for functional enrichment analysis using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. The associations among various proteins and protein networks were identified using the online software Search Tool for the Retrieval of Interacting Genes/Proteins. The cBioPortal database was used to analyze the association between genetic mutations and epigenetic modification, and the development of HCC. A total of 35 mRNAs were predicted to be targeted by 77 lncRNAs and 16 miRNAs, establishing a lncRNA‑miRNA‑mRNA regulatory network for HCC. Multivariable Cox regression analysis suggested that long intergenic non‑protein coding RNA 200, miRNA‑137, PDZ binding kinase and DNA polymerase θ were independent prognostic factors. In a regulatory network centered on miRNA‑424, six mRNA target genes were associated with HCC survival rates. Protein‑protein interaction analysis suggested that cell division cycle 25A (CDC25A) interacted with centrosomal protein 55 (CEP55), claspin, E2F transcription factor 7 and cyclin E1 (CCNE1. Mutations in CEP55 affected overall survival and disease‑free survival in HCC, whereas, mutations in CDC25A affected overall survival, and mutations in E2F7 affected disease‑free survival. Decreased methylation levels of CEP55, CDC25A and CCNE1 were associated with vascular invasion. The survival rate of patients with hypermethylation of CCNE1 and CEP55 was significantly associated with the rate of methylation of these loci. The present study provides an integrated bioinformatics analysis of gene expression, genetic mutations and epigenetic modifications that may be associated with the development of HCC.

Urinary Markers in Bladder Cancer: An Update

Bladder cancer (BC) is ones of the most common cancer worldwide. It is classified in muscle invasive (MIBC) and muscle non-invasive (NMIBC) BC. NMIBCs frequently recur and progress to MIBCs with a reduced survival rate and frequent distant metastasis. BC detection require unpleasant and expensive cystoscopy and biopsy, which are often accompanied by several adverse effects. Thus, there is an urgent need to develop novel diagnostic methods for initial detection and surveillance in both MIBCs and NMIBCs. Multiple urine-based tests approved by FDA for BC detection and surveillance are commercially available. However, at present, sensitivity, specificity and diagnostic accuracy of these urine-based assays are still suboptimal and, in the attend to improve them, novel molecular markers as well as multiple-assays must to be translated in clinic. Now there are growing evidence toward the use of minimally invasive “liquid biopsy” to identify biomarkers in urologic malignancy. DNA- and RNA-based markers in body fluids such as blood and urine are promising potential markers in diagnostic, prognostic, predictive and monitoring urological malignancies. Thus, circulating cell-free DNA, DNA methylation and mutations, circulating tumor cells, miRNA, IncRNA and mRNAs, cell-free proteins and peptides, and exosomes have been assessed in urine specimens. However, proteomic and genomic data must to be validated in well-designed multicenter clinical studies, before to be employed in clinic oncology.

Melittin Constrains the Expression of Identified Key Genes Associated with Bladder Cancer

This work is aimed at investigating the effect of melittin on identified key genes in bladder cancer (BC) and further providing a theoretical basis for BC treatment. GSE35014 downloaded from the Gene Expression Omnibus (GEO) database was used to screen differentially expressed genes (DEGs) in BC cells and control. Results showed that a total of 389 upregulated and 169 downregulated genes were identified. Subsequently, GO analysis, KEGG pathway enrichment analysis, and PPI network analysis were employed to disclose the crucial genes and signaling pathways involved in BC. Fifteen module-related DEGs and their associated signaling pathways were obtained according to the PPI network and modular analyses. Based on the analysis of articles retrieved in the PubMed database, we found that melittin could induce apoptosis and constrain the progression of tumor cells as a result of regulating critical cancer-related signaling pathways, such as PI3K-Akt and TNF signaling pathways. Furthermore, PI3K-Akt and TNF signaling pathways were also found to be associated with module-related DEGs according to biological analyses. At last, qRT-PCR analysis demonstrated that melittin could constrain the expression of module-related DEGs (LPAR1, COL5A1, COL6A2, CXCL1, CXCL2, and CXCL3) associated with PI3K-Akt and TNF signaling pathways in BC cells. Functional assays revealed that melittin could constrain the proliferative and migrated abilities of BC cells. Conjointly, these findings provide a theoretical basis for these six genes as drug-sensitive markers of melittin in BC treatment.