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ORIGINAL ARTICLE
Year : 2017  |  Volume : 13  |  Issue : 3  |  Page : 487-490

Respiratory cancer database: An open access database of respiratory cancer gene and miRNA


Department of Sub-DIC Bioinformatics, National Institute of Technology, Raipur, Chhattisgarh, India

Date of Web Publication31-Aug-2017

Correspondence Address:
Jyotsna Choubey
Sub DIC Bioinformatics, National Institute of Technology, Raipur, Chhattisgarh
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0973-1482.168978

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 > Abstract 

Aims: Respiratory cancer database (RespCanDB) is a genomic and proteomic database of cancer of respiratory organ. It also includes the information of medicinal plants used for the treatment of various respiratory cancers with structure of its active constituents as well as pharmacological and chemical information of drug associated with various respiratory cancers.
Materials and Methods: Data in RespCanDB has been manually collected from published research article and from other databases. Data has been integrated using MySQL an object-relational database management system. MySQL manages all data in the back-end and provides commands to retrieve and store the data into the database. The web interface of database has been built in ASP.
Results and Conclusions: RespCanDB is expected to contribute to the understanding of scientific community regarding respiratory cancer biology as well as developments of new way of diagnosing and treating respiratory cancer. Currently, the database consist the oncogenomic information of lung cancer, laryngeal cancer, and nasopharyngeal cancer. Data for other cancers, such as oral and tracheal cancers, will be added in the near future. The URL of RespCanDB is http://ridb.subdic-bioinformatics-nitrr.in/.

Keywords: Laryngeal cancer, lung cancer, miRNA, nasopharyngeal cancer


How to cite this article:
Choubey J, Choudhari JK, Patel A, Verma MK. Respiratory cancer database: An open access database of respiratory cancer gene and miRNA. J Can Res Ther 2017;13:487-90

How to cite this URL:
Choubey J, Choudhari JK, Patel A, Verma MK. Respiratory cancer database: An open access database of respiratory cancer gene and miRNA. J Can Res Ther [serial online] 2017 [cited 2020 Jun 4];13:487-90. Available from: http://www.cancerjournal.net/text.asp?2017/13/3/487/168978


 > Introduction Top


Respiratory system cancer refers to any condition that is characterized by a malignant cells anatomically located in the respiratory system. The respiratory system includes all the organs involved in the breathing process such as the nose, pharynx, larynx, lungs, bronchi, and throat. A total of 242,550 new respiratory cancer cases and 163,660 respiratory cancer deaths are projected to occur in the United States in 2014.[1]

Currently available cancer database is organ wise such as renal cancer database,[2] pancreatic cancer database,[3] liver cancer database,[4] lung cancer database,[5] yet today none of the database available which focuses on system wise cancer gene database. With such type of database scientist and clinician can examine the molecular profiles of tumors of organ in a system and can find striking similarities and peculiarities between tumors originating in different organs of a particular organ system.

The wealth of information is scattered in the literature and hence it is difficult to access. Developed respiratory cancer database (RespCanDB) is a compilation of all scattered information related to respiratory cancer gene and miRNA. The aim of this database is to develop, distribute, support, and coordinates access to a variety of databases for the scientific and medical communities engaged in respiratory cancer research. User friendly query interface of RespCanDB have made all the features of database easily accessible.


 > Materials and Methods Top


Data collection and content

RespCanDB contains the information of respiratory cancer associated gene which is collected from research article published in PubMed database. PubMed database is queried with different keyword such as laryngeals cancer, nasopharyngeal cancer, and lung cancer. Then the gene related information is retrieved from other databases such as Entrez gene,[6] GeneCards,[7] and Online Mendelian Inheritance in Man, 2007.[8]

For respiratory cancer related miRNA, PubMed database has been searched with keyword miRNA and laryngeals cancer, miRNA, nasopharyngeal cancer, miRNA, and lung cancer.

Drug related information has also been integrated in RespCanDB via DrugBank.[9] It encompasses information such as absorption distribution metabolism, excretion, and toxicity (ADMET) properties of drug, chemical properties, drug targets, coordinate files for proteins, and small drug molecules and hyperlink to other drug-related databases. This drug-related information might assist in the discovery of new cancer drug receptors and potential drugs for various respiratory cancers.

Database architecture and web interface development

After collection and compilation of all the scientific information related to respiratory cancer, the data has been integrated using MySQL an object-relational database management system.[10] MySQL manages all data in the back-end and provides commands to retrieve and store the data into the database. The web interface of database has been built in ASP. The architecture of RespCanDB is shown in [Figure 1].
Figure 1: Screenshot of respiratory cancer database

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Database statistics

Currently, RespCanDB contains information of 227 genes, 131 miRNA, 22 medicinal plants and 29 drugs related to various respiratory system organ cancers. While analyzing the database, it has been found that some of the gene, miRNA and medicinal plants are common among the lung cancer, nasopharyngeal cancer and laryngeal cancer. Summary of the statistics of the database are provided in [Figure 2].
Figure 2: Statistics of respiratory cancer database (a) statistics of genes (b) statistics of miRNA (c) statistics of medicinal plants

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Data access

User can access the database via web interface. Protein coding gene can be queried from database by selecting cancer type and using keyword gene symbol. This retrieves a list of genes of selected cancer. In the gene-list, genes are arranged in alphabetical order where each gene again link to new page. The gene list page consist the gene related information and hyperlink to other database gives complete information. The main page for each gene provides the following information: (i) General information including the gene symbol, gene id, gene name, gene aliases contig, chromosome location, (ii) link to other public databases, HGNC id, GeneBank id, UniGene id, HPRD id, Ensembl id, (iii) clicking on gene product leads to mRNA/CDS/Protein sequence, UniProt id, and PDB id details, (iv) link to associated disease, (v) link to homologous gene entries, and (vi) link to references that validate the presence of this gene in particular gynecological cancers or breast cancer. The miRNAs, drug and medicinal plants information can also be browsed in a similar way. The miRNA entries medicinal plant entries are linked to miRBase[11] and PubChem database,[12] respectively, wherever available. Drug information page provides chemical properties, pharmacological properties of drugs, drug targets, and hyperlink to other database such as PubChem compound (http://www.ncbi.nlm.nih.gov/pccompound),[12] PubChem substance (http://www.ncbi.nlm.nih.gov/pcsubstance)[12] RxList (http://www.rxlist.com/script/main/hp.asp),[13] KEGG drug (http://www.genome.jp/kegg/drug/),[14] KEGG compound (http://www.genome.jp/kegg/compound/),[14] and PharmGKB (http://www.pharmgkb.org/).[15] [Figure 3] gives the details of database structure of developed RespCanDB.
Figure 3: Database structure

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 > Discussion Top


As currently available database is organ wise, however developed RespCanDB is a respiratory system cancer database. This allows the researchers to make thorough comparison of genes that are common as well as unique in respiratory cancer and helps in analyzing their abnormal behavior in particular cancer. The database integrates the information of protein coding genes, miRNA genes, drug data related to respiratory cancer, and information of medicinal plant data with structure of its active constituents. The database provides detailed information on gene ontology, homologs, associated disease, nucleotide sequence, protein sequence, and protein structure. Information of drug may lead to the discovery of new drug target as well as it may help scientist to in silico prediction of ADMET properties of analogs of these drugs.[16]


 > Conclusion Top


RespCanDB is a comprehensive and integrated database which helps the researchers and clinicians engaged in the field of respiratory cancer. Unlike currently developed drug which is single tumor type, the information of RespCanDB draws the attention of researcher and clinician to focus the development of drugs that can target larger group of cancer with genomic similarity in a respiratory system cancer. In future, RespCanDB would be updated and additional data incorporated.

Acknowledgment

Developers of RespCanDB and authors of this paper, acknowledge the databases NCBI, HPRD, Ensemble, UniProt, RCSB, miRBase and their permission to link information in RespCanDB.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 
 > References Top

1.
Siegel R, Ma J, Zou Z, Jemal A. Cancer statistics, 2014. CA Cancer J Clin 2014;64:9-29.  Back to cited text no. 1
    
2.
Lee L, Wang K, Li G, Xie Z, Wang Y, Xu J, et al. Liverome: A curated database of liver cancer-related gene signatures with self-contained context information. BMC Genomics 2011;12 Suppl 3:S3.  Back to cited text no. 2
    
3.
Chelala C, Hahn SA, Whiteman HJ, Barry S, Hariharan D, Radon TP, et al. Pancreatic expression database: A generic model for the organization, integration and mining of complex cancer datasets. BMC Genomics 2007;8:439.  Back to cited text no. 3
    
4.
Ramana J. RCDB: Renal cancer gene database. BMC Res Notes 2012;5:246.  Back to cited text no. 4
    
5.
Wang L, Xiong Y, Sun Y, Fang Z, Li L, Ji H, et al. HLung DB: An integrated database of human lung cancer research. Nucleic Acids Res 2010;38:D665-9.  Back to cited text no. 5
    
6.
Maglott D, Ostell J, Pruitt KD, Tatusova T. Entrez Gene: Gene-centered information at NCBI. Nucleic Acids Res 2007;35:D26-31.  Back to cited text no. 6
    
7.
Safran M, Solomon I, Shmueli O, Lapidot M, Shen-Orr S, Adato A, et al. GeneCards 2002: Towards a complete, object-oriented, human gene compendium. Bioinformatics 2002;18:1542-3.  Back to cited text no. 7
    
8.
Baxevanis AD. Searching online mendelian inheritance in man (OMIM) for information for genetic loci involved in human disease. Curr Protoc in Hum Genet 2003: Chapter 9: Unit 9.13. p. 1-15.  Back to cited text no. 8
    
9.
Wishart DS, Knox C, Guo AC, Cheng D, Shrivastava S, Tzur D, et al. DrugBank: A knowledgebase for drugs, drug actions and drug targets. Nucleic Acids Res 2008;36:D901-6.  Back to cited text no. 9
    
10.
MySQL 5.5.0 Reference Manual. Oracle Corporation. 12h July 2009.  Back to cited text no. 10
    
11.
Griffiths-Jones S, Grocock RJ, van Dongen S, Bateman A, Enright AJ. miRBase: MicroRNA sequences, targets and gene nomenclature. Nucleic Acids Res 2006;34:D140-4.  Back to cited text no. 11
    
12.
Sayers EW, Barrett T, Benson DA, Bolton E, Bryant SH, Canese K, et al. Database resources of the national center for biotechnology information. Nucleic Acids Res 2010;38:D5-16.  Back to cited text no. 12
    
13.
Hatfield CL, May SK, Markoff JS. Quality of consumer drug information provided by four web sites. Am J Health Syst Pharm 1999;56:2308-11.  Back to cited text no. 13
    
14.
Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M. KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res 2010;38:D355-60.  Back to cited text no. 14
    
15.
Hodge AE, Altman RB, Klein TE. The PharmGKB: Integration, aggregation, and annotation of pharmacogenomic data and knowledge. Clin Pharmacol Ther 2007;81:21-4.  Back to cited text no. 15
    
16.
Maqungo M, Kaur M, Kwofie SK, Radovanovic A, Schaefer U, Schmeier S, et al. DDPC: Dragon database of genes associated with prostate cancer. Nucleic Acids Research 2011; 39:D980-85.  Back to cited text no. 16
    


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  [Figure 1], [Figure 2], [Figure 3]



 

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