Diagnostic and prognostic role of BTA, NMP22, survivin and cytology in urothelial carcinoma.

BACKGROUND: Cytology is a recommended noninvasive urine test for the detection and surveillance of bladder cancer and upper-tract urothelial carcinoma. It is however characterized by poor sensitivity in low-grade tumors. This study aims to determine the diagnostic and prognostic role of BTA, BTA-stat, NMP22, and Survivin. METHODS: Urine samples were collected from a total of 105 patients (bladder cancer (n=61), upper-tract urothelial carcinoma (n=44), and controls (n=52). The samples were directly assessed using cytology, BTA-stat (Qualitative test), BTA (chemiluminescence test), NMP22 (Qualitative test), and Survivin (enzyme-linked immunosorbent assay). Cancer progression and recurrence were assessed after a median follow-up of 32 months (4-47 months). Univariate and multivariate analyses were performed using Kaplan-Meier survival analysis and Cox proportional hazards regression. RESULTS: The triple combination of Survivin + BTA + Cytology was the most promising model for discriminating bladder cancer or upper-tract urothelial carcinoma from controls (UTUC group: the area under the curve value 0.97, sensitivity 86%, specificity 96%; BC group: the area under the curve value 0.86 sensitivity 67%, specificity 96%). Univariate survival analysis, showed Cytology (P=0.02; HR=5.35) and Survivin (HR=3.24; P=0.03) to have a significant association with the progression-free survival, while Survivin (HR=4.15; P=0.04) was statistically associated with cancer-specific survival in the bladder cancer group. The multivariable analysis did not show any of these markers as independent prognostic factors. CONCLUSIONS: These biomarkers showed a higher sensitivity than cytology, but a poorer specificity. All biomarkers exhibited good diagnostic performance in both bladder cancer and upper-tract urothelial carcinoma. Combining Survivin + BTA + Cytology was superior to the use of a single marker or combining other biomarkers.

Pan-cancer analysis of iron metabolic landscape across the Cancer Genome Atlas.

Iron is an essential metal ion in the human body and usually dysregulated in cancers. However, a comprehensive overview of the iron-related genes and their clinical relevance in cancer is lacking. In this study, we utilized the expression profiling, proteomics, and epigenetics from the Cancer Genome Atlas database to systematically characterized the alterations of iron-related genes. There were multiple iron-related genes with dysregulation across 14 cancers and some of these ectopic changes may be associated with aberrant DNA methylation. Meanwhile, a variety of genes were significantly associated with patient survival, especially in kidney renal clear cell carcinoma. Then differentially expressed genes were validated in clinical samples. Finally, we found deferoxamine and erastin could inhibit proliferation in various tumor cells and influence the expression of several iron-related genes. Overall, our study provides a comprehensive analysis of iron metabolism across cancers and highlights the potential treatment of iron targeted therapies for cancers.

Comprehensive analysis of microRNA-messenger RNA regulatory network in gemcitabine-resistant bladder cancer cells.

Chemotherapy is still a standard treatment of unresectable bladder cancer or distant metastases. The chemotherapy resistance always occurs after a period of treatment indicating poor prognosis. The current study aimed to explore the molecular mechanism of chemoresistance in bladder cancer cells. The gene expression profiles of GSE77883, including three untreated T24 cells samples and three gemcitabine-resistant T24 cells samples, was downloaded from Gene Expression Omnibus database. The screening of differentially expressed genes (DEGs), gene function analysis, and interaction prediction between microRNAs (miRNAs) and DEGs were performed by R software. The protein-protein interaction (PPI) and miRNA-DEGs networks were constructed and visualized by Cytoscape software. Then, the small molecules, with potential synergistic or antagonistic effects to gemcitabine resistance, were identified using the Connectivity Map database. Finally, gemcitabine-resistant T24 cell line was established and key genes were validated by quantitative real-time polymerase chain reaction (qRT-PCR). In total, 536 upregulated and 513 downregulated genes were screened and mainly enriched in oxidative stress response and signaling pathways related to extracellular matrix-receptor interaction and focal adhesion. PPI network showed interleukin 6, tumor necrosis factor, kinesin family member 11, and BUB1 mitotic checkpoint serine/threonine kinase B were key genes. The miRNA-DEGs regulatory networks included 18 miRNAs and 185 DEGs, including miR-182-5p, miR-590-3p, miR-320a and serum- and glucocorticoid-regulated kinase 1 (SGK1). Then, the related key genes and miRNAs were confirmed by qRT-PCR. Furthermore, 81 small molecules with antagonistic or synergistic effect to GEM were screened. We have investigated the molecular mechanisms driving GEM-resistance in bladder cancer cells that would contribute to the development of chemotherapy for advanced bladder cancer.