lung cancer , one of the most common causes of cancer - related death in both men and women , is responsible for 1.3 million deaths worldwide every year . lung cancer can be roughly divided into two groups according to pathology : non - small cell lung cancer ( nsclc ) ( 80.4% ) and small cell lung cancer ( 16.8% ) ( 1 ) . many factors potentially contribute to lung cancer formation , e.g. tobacco smoke , ionizing radiation and viral infection . however , the mechanisms involved in lung carcinogenesis remain largely unknown . similar to many other cancers , lung cancer is initiated by activation of oncogenes or inactivation of tumor suppressor genes ( 2 ) . mutations in the k - ras proto - oncogene are responsible for 1030% of lung adenocarcinomas ( 3,4 ) . the epidermal growth factor receptor ( egfr ) regulates cell proliferation , apoptosis , angiogenesis and tumor invasion ( 3 ) . oncogenic mutations and amplification of egfr are common in non - small cell lung cancer and thus provide the basis for treatment with egfr inhibitors . other oncogenes involved include c - met , nkx2 - 1 , pik3ca and braf ( 3 ) . the p53 tumor suppressor gene , located on chromosome 17p , is affected in 6075% of lung cancer including both nsclc and sclc while rb is more likely inactivated in sclc ( 5 ) . p16 is also frequently inactivated through the methylation of its promoter region at genomic dna level . another important tumor suppressor gene is lkb1 , whose loss - of - function mutation / deletion is observed in 30% lung adenocarcinomas and 20% of squamous cell carcinomas ( 6,7 ) . genetic polymorphisms are also indicated to be involved in lung carcinogenesis , e.g. interleukin-1 ( 8) , cytochrome p450 ( 9 ) , apoptosis promoters such as caspase-8 ( 10 ) and dna repair molecules such as xrcc1 ( 11 ) . people with these polymorphisms are susceptible to lung cancer development after exposure to carcinogens . studies also suggest that the mdm2 309 g allele is a low - penetrant risk factor for lung cancer development in asian population ( 12 ) . although lung cancer research data have accumulated dramatically during the past several years , to our knowledge , there is no database specifically focusing on lung cancer molecular biology yet available . omim contains information on all known mendelian disorders and focuses on the relationship between phenotype and genotype ( 13 ) . methycancer is developed to study the interplay of dna methylation , gene expression and cancer . it contains both highly integrated data of dna methylation , cancer - related genes , mutation and cancer information from public resources , and the cpg island ( cgi ) clones derived from the large - scale sequencing projects ( 14 ) . mir2disease aims at providing a comprehensive resource of microrna misregulation in various human diseases ( 15 ) . egfr mutation database has a convenient compilation of somatic egfr mutations in nsclc and associated epidemiological and methodological data , including response to the tyrosine kinase inhibitors gefitinib and erlotinib ( 16 ) . these databases focus on cancer pathogenesis from different angles with a little touch of lung cancer . thus , it is beneficial to establish a lung cancer - related database or platform involving genes / proteins / mirnas . high - throughput techniques applied in the lung cancer research have generated a mass of data and provided important resources for us to potentially explore the molecular mechanisms and identify lung cancer - related molecules . the integration of information generated by small - scale studies and using high - throughput technology could provide a unique resource to facilitate the systematic study of the lung carcinogenesis process . to this end , we collected lung cancer - related molecules and other detailed information for database construction through text mining in combination with bioinformatics analysis . this repository and maintenance system specially designed for lung cancer information can no doubt facilitate future lung cancer investigations . overall , hlungdb enables the exploration of relevant information for human lung cancer - related molecules from multiple angles , making it a unique resource for human lung cancer and will serve as a useful platform for those interested in lung cancer biology . as aforementioned , initial entries describing the relationship between genes and human lung cancer are collected manually . the gene  lung cancer relationship documented in the current release were collected through searching the pubmed database with a list of keywords , such as  lung cancer gene ,  pulmonary cancer gene ,  pulmonary adenocarcinoma gene , etc . after we obtained the literature with the keywords above , we read through and interpreted each paper by collecting the important information , including the type of gene alteration , the clinical correlation and/or significance of the gene alternation with lung cancer , the lung cancer subtype , the potential mechanism of gene regulation and the experimental methods involved . each entry in the database contains detailed information on a lung cancer  gene relationship , including a basic description of the gene , the expression pattern of gene ( up- or down - regulated ) in the lung cancer patient , the experimentally validated regulatory information ( transcription factors , their binding motif and the promoter ) and protein  protein interaction ( ppi ) network etc . gene expression profiling data for lung cancer patient samples the differentially expressed genes were selected if the change between lung cancer samples and normal control is larger than 2-fold . to make the results more reliable , we only selected those genes differentially expressed from at least three patients in a dataset and displayed them on our web site . in the current release of hlungdb , 2585 genes were selected for their relationships with lung carcinogenesis . a total of 271 lung cancer samples from six expression profiling datasets were analyzed to get the gene expression pattern ( 1722 ) . for the lung cancer - related snps , we searched pubmed with key words , namely  snp and lung cancer. then , we collected the snps proven to be correlated with lung cancer from those returned papers . in total , 424 snps , no matter whether they could be mapped to a gene or not , were added into the database . additionally , 360 transcription factors with 1160 binding motifs and 253 lung cancer - related genes with detailed epigenetic information were also placed into the database . previous experiments , both with high - throughput and small - scale methods , have identified many mirnas differentially expressed in lung cancer and/or confirmed to be related to lung cancer . therefore , we selected lung cancer - related mirnas with experimental information from the literature . for those mirnas with identified targets , . currently , there are 212 lung cancer - related mirnas included in the hlungdb . next , we built the hlungdb database by integrating the data we collected with information from other resources ( figure 1 ) , which makes our database a one - stop and knowledgeable platform for the lung cancer research community . hlungdb provides a search engine to query detailed information on each gene  lung cancer relationship documented in the database . query keywords , including gene / protein symbol or its synonym , are all allowed . after submission of the symbol or the alias of a gene , gene centered information will be displayed in a new page , including symbol , alias , description , protein  protein interactions , expression alterations based on the microarray data and regulatory information if the gene has been confirmed to be related to lung cancer in our database . to see more details about how the gene is related to lung cancer , the user can click on the gene symbol link and a new page will appear to display evidence of the genes relationship to lung cancer . clinical significance indicates the effect of the gene alteration on the lung cancer in the point of clinical view that is collected from the literature ;  function describes the gene s role in lung cancer extracted from the published papers ;  gene regulation presents the regulatory relationship of the gene with other genes , while expression alteration shows the analysis results of lung cancer related microarray datasets , in which the user can see how many patients show gene upregulation and/or downregulation . the ppi link leads to a new page that shows the proteins interacting with the query protein , the  show ppi network link will display the selected protein protein interaction network based on experimental evidence mostly from the hprd system ( 23 ) . in the ppi network section , user - friendly interfaces have made all the features of hlungdb ppi easily accessible and also provide direct view for the user to explore the relationship among the proteins . the  regulatory information links the user to the names of the transcription factors confirmed to regulate the gene . see details links the user to a new page that displays the binding site motifs of those transcription factors with the supporting pubmed i d . the  show promoter of gene link will display the promoter sequence(s ) of the selected gene . alternatively , the user can query our system with the protein symbol , and a new summary page will provide a brief description of the protein , the ppi , the links to other related resources and the ppi network . users can also check whether a mirna is related to lung cancer with the mirna symbol . the results page will display the manually collected details for the related mirna , including the disease type the mirna is related to , the alterations in expression of the mirna , the mechanism of the mirna in lung cancer , the experiment methods used to confirm the mechanism , the targets of the mirna if any with pubmed i d and the description of the mirna involved in lung cancer . chromosome on the top of this page , and a chromosome map will return . in the chromosome page , the user can view lung cancer - related genes by chromosome i d . with the second approach , browse on the first page of hlungdb allows users to see all the genes confirmed to be related to lung cancer . , users can easily retrieve all genes that are related to lung cancer . another way to view lung cancer - related genes , users can check those lung cancer genes by clicking on the pathway name and view the network about this pathway through the  pathway network entrance . user can also click on the marginal node on the network to expand the network . for more detailed usage of the network , users can read the annotation on the pathway network page . users can view lung cancer - related information in our database through browsing snp , transcription factor and methylation lists . snp view provides the user with lung cancer - related snp obtained from pubmed by searching  snp and  lung cancer. the it includes the national center for biotechnology information , a repository for published gene information , and pubmed , us national library of medicine , that includes over 18 million citations from medline and other life science journals . in order to provide a central resource for biologists in the lung cancer research community , we developed hlungdb , a database system aimed at providing a comprehensive resource of gene information and their relationships to lung cancer . the goal of the lung cancer database project was to construct a large - scale platform for lung cancer that would contribute to basic research and clinical research in the future . in the past 2 years genes , mirnas , gene promoters , transcription factors , transcription factor - binding sites and the snps related to lung cancer have been collected and integrated into this system . clinical information related to gene expression profile data they have been integrated in such a way that investigators can rapidly query whether a gene or protein is found in human lung cancer , and other detailed lung cancer - related information about this gene . we believe that hlungdb will be particularly interesting to the life science community and will greatly facilitate cancer biologists mission of unraveling the pathogenesis of lung cancer . we are working to increase the quality and quantity of data and to supply additional database function . we will use text - mining tools to help us prescreen pubmed abstracts regularly that potentially describe the lung cancer  gene relationships . second , since many proteins in the signaling transduction pathways are involved in the lung cancer development and progression , our next step is to identify those signal transduction pathways that have significant changes and display their components with identified alteration in lung cancer in a network view . at the same time , we will also collect the downstream genes for each altered signaling pathway in lung cancer and further characterize the relationship between them to ultimately fulfill the goal of identifying new potentially relevant lung cancer genes and new mechanisms . state key program of basic research of china ( grant 2007cb108800 , 2009cb918402 , 2010cb912102 ) ; national high technology research and development program of china ( 863 project ) ( grant no . 2006aa02z313 ) ; national natural science foundation of china ( grant 30870575 , 30740084 and 30871284 ) ; chinese academy of sciences ( 2008kip101 ) ; science and technology commission of shanghai municipality ( 06dz22923 , 08pj14105 ) . h.j . funding for open access charge : national natural science foundation of china and the state key program of basic research of china .
the human lung cancer database ( hlungdb ) is a database with the integration of the lung cancer - related genes , proteins and mirnas together with the corresponding clinical information . 
 the main purpose of this platform is to establish a network of lung cancer - related molecules and to facilitate the mechanistic study of lung carcinogenesis . 
 the entries describing the relationships between molecules and human lung cancer in the current release were extracted manually from literatures . 
 currently , we have collected 2585 genes and 212 mirna with the experimental evidences involved in the different stages of lung carcinogenesis through text mining . 
 furthermore , we have incorporated the results from analysis of transcription factor - binding motifs , the promoters and the snp sites for each gene . 
 since epigenetic alterations also play an important role in lung carcinogenesis , genes with epigenetic regulation were also included . 
 we hope hlungdb will enrich our knowledge about lung cancer biology and eventually lead to the development of novel therapeutic strategies . 
 hlungdb can be freely accessed at http://www.megabionet.org/bio/hlung .