BcCluster: a bladder cancer database at the molecular level

Bhat, A., Mokou, M., Zoidakis, J., Jankowski, V., Vlahou, A. and Mischak, H. (2016) BcCluster: a bladder cancer database at the molecular level. Bladder Cancer, 2(1), pp. 65-76. (doi:10.3233/BLC-150024) (PMID:27376128) (PMCID:PMC4927921)

[img] Text
article - Published Version
Available under License Creative Commons Attribution Non-commercial.

607kB

Abstract

Background: Bladder Cancer (BC) has two clearly distinct phenotypes. Non-muscle invasive BC has good prognosis and is treated with tumor resection and intravesical therapy whereas muscle invasive BC has poor prognosis and requires usually systemic cisplatin based chemotherapy either prior to or after radical cystectomy. Neoadjuvant chemotherapy is not often used for patients undergoing cystectomy. High-throughput analytical omics techniques are now available that allow the identification of individual molecular signatures to characterize the invasive phenotype. However, a large amount of data produced by omics experiments is not easily accessible since it is often scattered over many publications or stored in supplementary files. Objective: To develop a novel open-source database, BcCluster (http://www.bccluster.org/), dedicated to the comprehensive molecular characterization of muscle invasive bladder carcinoma. Materials: A database was created containing all reported molecular features significant in invasive BC. The query interface was developed in Ruby programming language (version 1.9.3) using the web-framework Rails (version 4.1.5) (http://rubyonrails.org/). Results: BcCluster contains the data from 112 published references, providing 1,559 statistically significant features relative to BC invasion. The database also holds 435 protein-protein interaction data and 92 molecular pathways significant in BC invasion. The database can be used to retrieve binding partners and pathways for any protein of interest. We illustrate this possibility using survivin, a known BC biomarker. Conclusions: BcCluster is an online database for retrieving molecular signatures relative to BC invasion. This application offers a comprehensive view of BC invasiveness at the molecular level and allows formulation of research hypotheses relevant to this phenotype.

Item Type:Articles
Additional Information:The research leading to these results has received funding from the Marie Curie Actions – BCMolMed under grant agreement no. FP7-PEOPLE-2012- ITN-EID and the European Community’s Seventh Framework Programme under grant agreement no. 306157.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Mischak, Professor Harald
Authors: Bhat, A., Mokou, M., Zoidakis, J., Jankowski, V., Vlahou, A., and Mischak, H.
College/School:College of Medical Veterinary and Life Sciences > Institute of Cardiovascular and Medical Sciences
Journal Name:Bladder Cancer
Publisher:I O S Press
ISSN:2352-3727
ISSN (Online):2352-3735
Published Online:07 January 2016
Copyright Holders:Copyright © 2016 IOS Press and the authors
First Published:First published in Bladder Cancer 2(1):65-75
Publisher Policy:Reproduced under a Creative Commons License

University Staff: Request a correction | Enlighten Editors: Update this record