Searching the Resource Information Network
Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.
Given that most bladder cancers (BCs) are diagnosed in advanced stages with poor prognosis, this study aims to find novel biomarkers associated with the progression and prognosis in patients with BC. 1,779 differentially expressed genes (DEGs) between BC samples and normal bladder tissues were identified in total. Then, 24 DEGs were regarded as candidate hub genes by constructing a protein-protein interaction (PPI) network and a random forest model. Among them, six genes (BUB1B, CCNB1, CDK1, ISG15, KIF15, and RAD54L) were eventually identified by using five analysis methods (one-way Analysis of Variance analysis, spearman correlation analysis, distance correlation analysis, receiver operating characteristic curve, and expression values comparison), which were correlated with the progression and prognosis of BC. Moreover, the validation of hub genes was conducted based on GSE13507, Oncomine, and CBioPortal. Results of univariate Cox regression analysis showed that the expression levels of all the hub genes were influence features of overall survival (OS) and cancer specific survival (CSS) based on GSE13507, and we further established a six-gene signature based on the expression levels of the six genes and their Cox regression coefficients. This signature showed good potential for clinical application suggested by survival analysis (OS: Hazard Ratio = 0.484, 95%CI: 0.298-0.786; P = 0.0034; CSS: Hazard Ratio = 0.244, 95%CI: 0.121-0.493, P < 0.0001) and decision curve analysis. In conclusion, our study indicates that six hub genes have great predictive value for the prognosis and progression of BC and may contribute to the exploration of further basic and clinical research of BC.
Pubmed ID: 31134129
Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.
Software package used for interactive, or batched, statistical analysis in social science, health sciences and marketing. Software platform offers advanced statistical analysis, a library of machine-learning algorithms, text analysis, open-source extensibility, integration with big data and deployment into applications.Versions that were produced by SPSS Inc. before the IBM acquisition (Versions 18 and earlier) would be given origin or publisher of SPSS Inc. in Chicago.
View all literature mentionsSoftware platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.
View all literature mentionsDatabase of known and predicted protein interactions. The interactions include direct (physical) and indirect (functional) associations and are derived from four sources: Genomic Context, High-throughput experiments, (Conserved) Coexpression, and previous knowledge. STRING quantitatively integrates interaction data from these sources for a large number of organisms, and transfers information between these organisms where applicable. The database currently covers 5''214''234 proteins from 1133 organisms. (2013)
View all literature mentionsOncomine Research Platform is a partially-commercial suite of products for online cancer gene expression analysis dedicated to the academic and non-profit research community. Oncomine combines a rapidly growing compendium of 20,000+ cancer transcriptome profiles with a sophisticated analysis engine and a powerful web application for data-mining and visualization. Oncomine facilitates rapid and reliable biomarker and therapeutic target discovery, validation and prioritization. Oncomine was developed by physicians, scientists, and software engineers at the University of Michigan and is now fully supported for the academic and non-profit research community by Compendia Bioscience.
View all literature mentionsA suite of web-based tools to visualize, integrate and analyze cancer genomics and its associated clinical data. It is possible to display your own clinical data within one of their datasets.
View all literature mentionsIntegrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
View all literature mentionsA portal that provides visualization, analysis and download of large-scale cancer genomics data sets.
View all literature mentionsWeb server for cancer and normal gene expression profiling and interactive analyses. Interactive web server for analyzing RNA sequencing expression data of tumors and normal samples from TCGA and GTEx projects, using standard processing pipeline. Provides customizable functions such as tumor or normal differential expression analysis, profiling according to cancer types or pathological stages, patient survival analysis, similar gene detection, correlation analysis and dimensionality reduction analysis.
View all literature mentions