Construction of a protein-protein interaction network of Wilms' tumor and pathway prediction of molecular complexes.

Wilms' tumor (WT), or nephroblastoma, is the most common malignant renal cancer that affects the pediatric population. Great progress has been achieved in the treatment of WT, but it cannot be cured at present. Nonetheless, a protein-protein interaction network of WT should provide some new ideas and methods. The purpose of this study was to analyze the protein-protein interaction network of WT. We screened the confirmed disease-related genes using the Online Mendelian Inheritance in Man database, created a protein-protein interaction network based on biological function in the Cytoscape software, and detected molecular complexes and relevant pathways that may be included in the network. The results showed that the protein-protein interaction network of WT contains 654 nodes, 1544 edges, and 5 molecular complexes. Among them, complex 1 is predicted to be related to the Jak-STAT signaling pathway, regulation of hematopoiesis by cytokines, cytokine-cytokine receptor interaction, cytokine and inflammatory responses, and hematopoietic cell lineage pathways. Molecular complex 4 shows a correlation of WT with colorectal cancer and the ErbB signaling pathway. The proposed method can provide the bioinformatic foundation for further elucidation of the mechanisms of WT development.

Genetic variation in WDR1 is associated with gout risk and gout-related metabolic indices in the Han Chinese population.

Gout is the most common form of inflammatory arthritis affecting men, and current evidence suggests that genetic factors contribute to its progression. As a previous study identified that WD40 repeat protein 1 (WDR1) is associated with gout in populations of European descent, we sought to investigate its relationship with this disease in the Han Chinese population. We genotyped six WDR1 single nucleotide polymorphisms in 143 gout cases and 310 controls using Sequenom MassARRAY technology. The SPSS 16.0 software was used to perform statistical analyses. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated by unconditional logistic regression, with adjustments for age and gender. In an analysis using an allelic model, we identified that the minor alleles of rs3756230 (OR = 0.64, 95%CI = 0.450-0.911, P = 0.013) and rs12498927 (OR = 1.377, 95%CI = 1.037-1.831, P = 0.027) were associated with gout risk. In addition, we found that the "A/A" genotype of rs12498927 was associated with increased risk of gout under codominant (OR = 2.22, 95%CI = 1.12- 4.40, P = 0.042) and recessive models (OR = 2.24, 95%CI = 1.20-4.17, P = 0.012). We also determined the "A/G" genotype of rs12498927 to be significantly associated with higher urea levels in gout patients (P = 0.017). Our data shed new light on the association between genetic variations in the WDR1 gene and gout susceptibility in the Han Chinese population.

Construction of polycythemia vera protein interaction network and prediction of related biological functions.

Here, polycythemia vera (PV)-related genes were screened by the Online Mendelian Inheritance in Man (OMIM), and literature pertaining to the identified genes was extracted and a protein-protein interaction network was constructed using various Cytoscape plugins. Various molecular complexes were detected using the Clustervize plugin and a gene ontology-enrichment analysis of the biological pathways, molecular functions, and cellular components of the selected molecular complexes were identified using the BiNGo plugin. Fifty-four PV-related genes were identified in OMIM. The protein-protein interaction network contains 5 molecular complexes with correlation integral values >4. These complexes regulated various biological processes (peptide tyrosinase acidification, cell metabolism, and macromolecular biosynthesis), molecular functions (kinase activity, receptor binding, and cytokine activity), and the cellular components were mainly concentrated in the nucleus, intracellular membrane-bounded organelles, and extracellular region. These complexes were associated with the JAK-STAT signal transduction pathway, neurotrophic factor signaling pathway, and Wnt signaling pathway, which were correlated with chronic myeloid leukemia and acute myeloid leukemia.

Patients with brain metastases derived from gastrointestinal cancer: clinical characteristics and prognostic factors.

PURPOSE: This study seeks to evaluate the natural history, outcome, and possible prognostic factors in patients with brain metastases derived from gastrointestinal cancers. METHODS: The clinical features, prognostic factors, and the effects of different treatment modalities on survival were retrospectively investigated in 103 patients with brain metastases derived from gastrointestinal cancers. RESULTS: The median time from diagnosis of primary tumor to brain metastasis was 22.00 months. The interval between diagnosis of primary tumor relapse and brain metastasis was 8.00 months. The median follow-up time was 7.80 months. The median survival time after diagnosis of brain metastases was 4.10 months for all patients and 1.17 months for patients who received only steroids (36.9 %), 3.97 months for patients who only received whole-brain radiation therapy (WBRT 31.1 %), 11.07 months for patients who received gamma-knife surgery alone or/and WBRT (20.4 %), and 13.70 months for patients who underwent surgery and radiotherapy (12 patients, 11.6 %) (P < 0.001). Multivariate analysis revealed that recursive partitioning analysis (RPA) class, extracranial metastasis, and chemotherapy were independent prognostic factors. Brain metastasis derived from gastrointestinal tract cancer is rare, and overall patient survival is poor. CONCLUSION: RPA class, chemotherapy after brain metastases, and treatment regimens were independent prognostic factors for the survival of patients with brain metastases derived from gastrointestinal cancers.

Construction of gene/protein interaction networks for primary myelofibrosis and KEGG pathway-enrichment analysis of molecular compounds.

The objective of this study was the development of a gene/protein interaction network for primary myelofibrosis based on gene expression, and the enrichment analysis of KEGG pathways underlying the molecular complexes in this network. To achieve this, genes involved in primary myelofibrosis were selected from the OMIM database. A gene/protein interaction network for primary myelofibrosis was obtained through Cytoscape with the literature mining performed using the Agilent Literature Search plugin. The molecular complexes in the network were detected by ClusterViz plugin and KEGG pathway enrichment of molecular complexes was performed using DAVID online. We found 75 genes associated with primary myelofibrosis in the OMIM database. The gene/protein interaction network of primary myelofibrosis contained 608 nodes, 2086 edges, and 4 molecular complexes with a correlation integral value greater than 4. Molecular complexes involved in KEGG pathways are related to cytokine regulation, immune function regulation, ECM-receptor interaction, focal adhesion, actin cytoskeleton regulation, cell adhesion molecules, and other biological behavior of tumors, which can provide a reliable direction for the treatment of primary myelofibrosis and the bioinformatic foundation for further understanding the molecular mechanisms of this disease.

SLC2A9 and ZNF518B polymorphisms correlate with gout-related metabolic indices in Chinese Tibetan populations.

Current evidence suggests that heredity and metabolic syndrome contribute to gout progression. SLC2A9 and ZNF518B may play a role in gout progression in different populations, but no studies have focused on the Tibetan Chinese population. In this study, we determined whether variations in these 2 genes were correlated with gout-related indices in Chinese-Tibetan gout patients. We detected 6 single nucleotide polymorphisms in SLC2A9 and ZNF518B in 319 Chinese Tibetan gout patients. One-way analysis of variance was used to evaluate the polymorphisms' effects on gout based on mean serum levels of metabolism indicators. Polymorphisms in SLC2A9 and ZNF518B affected multiple risk factors related to gout development. Significant differences in serum triglyceride levels and high-density lipoprotein-cholesterol level were detected between different genotypic groups with SLC2A9 polymorphisms rs13129697 (P = 0.022), rs4447863 (P = 0.018), and rs1014290 (P = 0.045). Similarly in ZNF518B, rs3217 (P = 0.016) and rs10016022 (P = 0.046) were associated with high creatinine and glucose levels, respectively. This study is the first to investigate and identify positive correlations between SLC2A9 and ZNF518B gene polymorphisms and metabolic indices in Tibetan gout patients. We found significant evidence indicating that genetic polymorphisms affect gout-related factors in Chinese Tibetan populations.