DDEC: Dragon database of genes implicated in esophageal cancer

Magbubah Essack, Aleksandar Radovanovic, Ulf Schaefer, Sebastian Schmeier, Sundararajan V Seshadri, Alan Christoffels, Mandeep Kaur, Vladimir B Bajic, Magbubah Essack, Aleksandar Radovanovic, Ulf Schaefer, Sebastian Schmeier, Sundararajan V Seshadri, Alan Christoffels, Mandeep Kaur, Vladimir B Bajic

Abstract

Background: Esophageal cancer ranks eighth in order of cancer occurrence. Its lethality primarily stems from inability to detect the disease during the early organ-confined stage and the lack of effective therapies for advanced-stage disease. Moreover, the understanding of molecular processes involved in esophageal cancer is not complete, hampering the development of efficient diagnostics and therapy. Efforts made by the scientific community to improve the survival rate of esophageal cancer have resulted in a wealth of scattered information that is difficult to find and not easily amendable to data-mining. To reduce this gap and to complement available cancer related bioinformatic resources, we have developed a comprehensive database (Dragon Database of Genes Implicated in Esophageal Cancer) with esophageal cancer related information, as an integrated knowledge database aimed at representing a gateway to esophageal cancer related data.

Description: Manually curated 529 genes differentially expressed in EC are contained in the database. We extracted and analyzed the promoter regions of these genes and complemented gene-related information with transcription factors that potentially control them. We further, precompiled text-mined and data-mined reports about each of these genes to allow for easy exploration of information about associations of EC-implicated genes with other human genes and proteins, metabolites and enzymes, toxins, chemicals with pharmacological effects, disease concepts and human anatomy. The resulting database, DDEC, has a useful feature to display potential associations that are rarely reported and thus difficult to identify. Moreover, DDEC enables inspection of potentially new 'association hypotheses' generated based on the precompiled reports.

Conclusion: We hope that this resource will serve as a useful complement to the existing public resources and as a good starting point for researchers and physicians interested in EC genetics. DDEC is freely accessible to academic and non-profit users at http://apps.sanbi.ac.za/ddec/. DDEC will be updated twice a year.

Figures

Figure 1
Figure 1
The schematic representation of the DDEC structure. The DDEC is based on the three-tier (layer) architecture, namely; data, logic, and presentation.

References

    1. Stoner GD, Rustgi AK. Biology of the esophageal squamous cell carcinoma. Gastrointest Cancers Biol Diagn. 1995;8:141–146.
    1. WHO. The World Health Report 1997 – conquering suffering, enriching humanity. World Health Forum. 1997;18:248–260.
    1. Reed CE. Surgical management of esophageal carcinoma. Oncologist. 1999;4:95–105.
    1. De LL, Curia MC, Aceto GM, Toracchio S, Colucci G, Russo A, Mariani-Constantini R, Cama A. Analysis of extended genomic rearrangements in oncological research. Ann Oncol. 2007;18 Suppl 6:vi173–vi178.
    1. Gilbert N, Gilchrist S, Bickmore WA. Chromatin organization in the mammalian nucleus. Int Rev Cytol. 2005;242:283–336. doi: 10.1016/S0074-7696(04)42007-5.
    1. Cremer T, Cremer C. Chromosome territories, nuclear architecture and gene regulation in mammalian cells. Nat Rev Genet. 2001;2:292–301. doi: 10.1038/35066075.
    1. Kato K, Yamashita R, Matoba R, Monden M, Noguchi S, Takagi T, Nakai K. Cancer gene expression database (CGED): a database for gene expression profiling with accompanying clinical information of human cancer tissues. Nucleic Acids Res. 2005;33:D533–D536. doi: 10.1093/nar/gki117.
    1. Thiemann KM, Frost MH, Thompson RA. A multifaceted educational approach to increasing awareness and use of physician data query (PDQ) J Cancer Educ. 1999;14:78–82.
    1. Rhodes DR, Yu J, Shanker K, Deshpande N, Varambally R, Ghosh D, Barrette T, Pandey A, Chinnaiyan AM. ONCOMINE: a cancer microarray database and integrated data-mining platform. Neoplasia. 2004;6:1–6.
    1. Eyre TA, Ducluzeau F, Sneddon TP, Povey S, Bruford EA, Lush MJ. The HUGO Gene Nomenclature Database, 2006 updates. Nucleic Acids Res. 2006;34:D319–D321. doi: 10.1093/nar/gkj147.
    1. Safran M, Solomon I, Shmueli O, Lapidot M, Shen-Orr S, Adato A, Ben-Dor U, Esterman N, Rosen N, Peter I, Olender T, Chalifa-Caspi V, Lancet D. GeneCards 2002: towards a complete, object-oriented, human gene compendium. Bioinformatics. 2002;18:1542–1543. doi: 10.1093/bioinformatics/18.11.1542.
    1. Kulikova T, Akhtar R, Aldebert P, Althorpe N, Andersson M, Baldwin A, Bates K, Bhattacharyya S, Bower L, Browne P. EMBL Nucleotide Sequence Database in 2006. Nucleic Acids Res. 2007;35:D16–D20. doi: 10.1093/nar/gkl913.
    1. Flicek P, Aken BL, Beal K, Ballester B, Caccamo M, Chen Y, Clarke L, Coates G, Cunningham F, Cutts T. Ensembl 2008. Nucleic Acids Res. 2008;36:D707–D714. doi: 10.1093/nar/gkm988.
    1. Pruitt KD, Tatusova T, Maglott DR. NCBI reference sequences (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res. 2007;35:D61–D65. doi: 10.1093/nar/gkl842.
    1. Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Sayers EW. GenBank. Nucleic Acids Res. 2009;37:D26–D31. doi: 10.1093/nar/gkn723.
    1. Wheeler DL, Barrett T, Benson DA, Bryant SH, Canese K, Chetvernin V, Church DM, Dicuccio M, Edgar R, Federhen S. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 2008;36:D13–D21. doi: 10.1093/nar/gkm1000.
    1. UniProt Consortium. The universal protein resource (UniProt) Nucleic Acids Res. 2008;36:D190–D195. doi: 10.1093/nar/gkm895.
    1. Gasteiger E, Jung E, Bairoch A. SWISS-PROT: connecting biomolecular knowledge via a protein database. Curr Issues Mol Biol. 2001;3:47–55.
    1. Berman H, Henrick K, Nakamura H, Markley JL. The worldwide Protein Data Bank (wwPDB): ensuring a single, uniform archive of PDB data. Nucleic Acids Res. 2007;35:D301–D303. doi: 10.1093/nar/gkl971.
    1. Alibes A, Yankilevich P, Canada A, az-Uriarte R. ID converter and IDClight: conversion and annotation of gene and protein IDs. BMC Bioinformatics. 2007;8:9. doi: 10.1186/1471-2105-8-9.
    1. Khatri P, Desai V, Tarca AL, Sellamuthu S, Wildman DE, Romero R, Draghici S. New Onto-Tools: Promoter-Express, nsSNPCounter and Onto-Translate. Nucleic Acids Res. 2006;34:W626–W631. doi: 10.1093/nar/gkl213.
    1. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000;25:25–29. doi: 10.1038/75556.
    1. Kelso J, Visagie J, Theiler G, Christoffels A, Bardien S, Smedley D, Otgaar D, Greyling G, Jongeneel CV, McCarthy MI. eVOC: a controlled vocabulary for unifying gene expression data. Genome Res. 2003;13:1222–1230. doi: 10.1101/gr.985203.
    1. Vastrik I, D'Eustachio P, Schmidt E, Gopinath G, Croft D, de Bono B, Gillespie M, Jassal B, Lewis S, Matthews L. Reactome: a knowledge base of biologic pathways and processes. Genome Biol. 2007;8:R39. doi: 10.1186/gb-2007-8-3-r39.
    1. Carninci P, Sandelin A, Lenhard B, Katayama S, Shimokawa K, Ponjavic J, Semple CA, Taylor MS, Engstrom PG, Frith MC. Genome-wide analysis of mammalian promoter architecture and evolution. Nat Genet. 2006;38:626–635. doi: 10.1038/ng1789.
    1. Aerts S, Van LP, Thijs G, Mayer H, de MR, Moreau Y, De Moor B. TOUCAN 2: the all-inclusive open source workbench for regulatory sequence analysis. Nucleic Acids Res. 2005;33:W393–W396. doi: 10.1093/nar/gki354.
    1. Wingender E, Chen X, Fricke E, Geffers R, Hehl R, Liebich I, Krull M, Matys V, Michael H, Ohnhauser R. The TRANSFAC system on gene expression regulation. Nucleic Acids Res. 2001;29:281–283. doi: 10.1093/nar/29.1.281.
    1. Matys V, Kel-Margoulis OV, Fricke E, Liebich I, Land S, Barre-Dirrie A, Reuter I, Chekmenev B, Krull M, Hornischer K. TRANSFAC and its module TRANSCompel: transcriptional gene regulation in eukaryotes. Nucleic Acids Res. 2006;34:D108–D110. doi: 10.1093/nar/gkj143.
    1. Kel AE, Gossling E, Reuter I, Cheremushkin E, Kel-Margoulis OV, Wingender E. MATCH: A tool for searching transcription factor binding sites in DNA sequences. Nucleic Acids Res. 2003;31:3576–3579. doi: 10.1093/nar/gkg585.
    1. Sagar S, Kaur M, Dawe A, Seshadri SV, Christoffels A, Schaefer U, Radovanovic A, Bajic VB. DDESC: Dragon database for exploration of sodium channels in human. BMC Genomics. 2008;9:622. doi: 10.1186/1471-2164-9-622.
    1. Pan H, Zuo L, Choudhary V, Zhang Z, Leow SH, Chong FT, Huang Y, Ong VW, Mohanty B, Tan SL. Dragon TF Association Miner: a system for exploring transcription factor associations through text-mining. Nucleic Acids Res. 2004;32:W230–W234. doi: 10.1093/nar/gkh484.
    1. Bajic VB, Veronika M, Veladandi PS, Meka A, Heng MW, Rajaraman K, Pan H, Swarup S. Dragon Plant Biology Explorer. A text-mining tool for integrating associations between genetic and biochemical entities with genome annotation and biochemical terms lists. Plant Physiol. 2005;138:1914–1925. doi: 10.1104/pp.105.060863.
    1. Kaur M, Radovanovic A, Essack M, Schaefer U, Maqungo M, Kibler T, Schmeier S, Christoffels A, Narasimhan K, Choolani M, Bajic VB. Database for exploration of functional context of genes implicated in ovarian cancer. Nucleic Acids Res. 2009;37:D820–D823. doi: 10.1093/nar/gkn593.
    1. Smyth GK, Yang YH, Speed T. Statistical issues in cDNA microarray data analysis. Methods Mol Biol. 2003;224:111–136.
    1. Pritchard CC, Hsu L, Delrow J, Nelson PS. Project normal: defining normal variance in mouse gene expression. Proc Natl Acad Sci USA. 2001;98:13266–13271. doi: 10.1073/pnas.221465998.
    1. Dennis G Jr, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, Lempicki RC. DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol. 2003;4:3. doi: 10.1186/gb-2003-4-5-p3.
    1. Goto S, Bono H, Ogata H, Fujibuchi W, Nishioka T, Sato K, Kanehisa M. Organizing and computing metabolic pathway datain terms of binary relations. Pac Symp Biocomput. 1997. pp. 175–186.

Source: PubMed

Sponsorit ja yhteistyökumppanit

Sairaudet

Huumeiden interventiot

3
Tilaa