title: RCDB: Renal Cancer Gene Database.
abstract: BACKGROUND
  Renal cell carcinoma or RCC is one of the common and most lethal urological cancers, with 40% of the patients succumbing to death because of metastatic progression of the disease. Treatment of metastatic RCC remains highly challenging because of its resistance to chemotherapy as well as radiotherapy, besides surgical resection. Whereas RCC comprises tumors with differing histological types, clear cell RCC remains the most common. A major problem in the clinical management of patients presenting with localized ccRCC is the inability to determine tumor aggressiveness and accurately predict the risk of metastasis following surgery. As a measure to improve the diagnosis and prognosis of RCC, researchers have identified several molecular markers through a number of techniques. However the wealth of information available is scattered in literature and not easily amenable to data-mining. To reduce this gap, this work describes a comprehensive repository called Renal Cancer Gene Database, as an integrated gateway to study renal cancer related data.
  
  
  RESULTS
  Renal Cancer Gene Database is a manually curated compendium of 240 protein-coding and 269 miRNA genes contributing to the etiology and pathogenesis of various forms of renal cell carcinomas. The protein coding genes have been classified according to the kind of gene alteration observed in RCC. RCDB also includes the miRNAsdysregulated in RCC, along with the corresponding information regarding the type of RCC and/or metastatic or prognostic significance. While some of the miRNA genes showed an association with other types of cancers few were unique to RCC. Users can query the database using keywords, category and chromosomal location of the genes. The knowledgebase can be freely accessed via a user-friendly web interface at http://www.juit.ac.in/attachments/jsr/rcdb/homenew.html.
  
  
  CONCLUSIONS
  It is hoped that this database would serve as a useful complement to the existing public resources and as a good starting point for researchers and physicians interested in RCC genetics.
authors.affiliation: Department of Biotechnology and Bioinformatics, Jaypee University of Information Technology, 173234, Waknaghat, Solan, Himachal Pradesh, India. jayashree_ramana@yahoo.co.in
authors.forename: Jayashree
authors.initials: J
authors.lastname: Ramana
mesh_terms: D022126:Access to Information; D014408:Biomarkers, Tumor / Q000235:genetics*; D002292:Carcinoma, Renal Cell / Q000175:diagnosis / Q000235:genetics* / Q000556:secondary / Q000628:therapy; D030541:Databases, Genetic; D020022:Genetic Predisposition to Disease; D006801:Humans; D020407:Internet; D007680:Kidney Neoplasms / Q000175:diagnosis / Q000235:genetics* / Q000473:pathology / Q000628:therapy; D035683:MicroRNAs / Q000235:genetics; D010641:Phenotype; D011379:Prognosis
chemical_list: D014408:Biomarkers, Tumor; D035683:MicroRNAs