ONGene
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Data integration of ONGene and how to use ONGene:

1. Data integration of ONGene database

    Three data sources for oncogenes

    Four steps to curate oncogenes from literature

    Curation oncogenes from literature

2. Information for oncogenes

    General information and literature evidence

    Gene expression profile

    Gene regulation

    Mutation information

    Protein-protein interaction

3. Query and search database

    Text search of oncogene

    Quick access information in database

    Blast all protein and nucleotide sequences

4. Browse database

    By chromosome and KEGG pathway

5. Data download


Data integration of ONGene database

The primary aim of the database is to support oncogene research by maintaining a high quality oncogene database that serves as a comprehensive, fully classified, richly and accurately annotated oncogene resource, with extensive cross-references and querying interfaces freely accessible to the scientific community.

Three data sources for oncogenes

We collected known oncogenes from Reactome pathway database6, gene ontology database and PubMed/GeneRif literature database (Figure below). To retrieve a comprehensive annotated genes from gene ontology annotation database (GOA), we curated 4 GO terms related to oncogene: cellular senescence (GO:0090398), stress-induced premature senescence (GO:0090400), oncogene-induced oncogene (GO:0090402), oxidative stress-induced premature senescence (GO:0090403). Then we extracted 1093 protein from various organisms in GOA database associated with oncogene GOs on Jan 8, 2015. In addition, we also downloaded 182 human genes related to oncogene from Reactome database. There 182 human genes are annotated as pathways: Cellular Senescence (pathway ID: 905991), Cellular responses to stress (pathway ID: 645258), Oxidative Stress Induced Senescence (pathway ID: 905993), Senescence-Associated Secretory Phenotype (SASP) (pathway ID: 905996), DNA Damage/Telomere Stress Induced Senescence (pathway ID: 905994), Oncogene Induced Senescence (pathway ID: 905992). However, both GOA and Reactome database did not provide original literatures to support oncogene roles and the data curation is slow than the pace of oncogene biology research.

Four steps to collect oncogenes

To provide a detailed and precise oncogene resource with literature evidence, we performed an extensive literature query of GeneRif database on Jan 10, 2015 using the with a return of 878 GeneRif records associated with 573 PubMed abstracts. GeneRIF (Gene Reference Into Function) is a collection of records with short description about gene function in the Entrez Gene database 8. To further curate those matched literatures, we downloaded all the 573 PubMed abstracts in a Medline format for manual review. Curation of oncogenes from literature included three major steps as follows: grouping all 573 PubMed abstracts by topic using Related function in Entrez; extracting descriptions of oncogenes from grouped abstracts; manually collecting gene names from the descriptions of the oncogenes and mapping the gene names to Entrez gene IDs. These three steps allowed us to quickly and easily evaluate if and how the curated abstract was related to oncogenes and provided cross-checking between multiple literatures. Here, we used Entrez gene IDs for oncogenes to serve as the database key to crosslink the same genes from different public databases. To gain precise oncogene information, much care is taken regarding the species information and gene name/alias. For example, in the sentence " the SIRT1-PARP-1 axis plays a critical role in the regulation of cigarette smoke(CS)-induced autophagy and has important implications in understanding the mechanisms of CS-induced cell death and senescence 9" Both gene Sirt1 and Parp1 were collected and mapped to Gene ID of mouse in the current Entrez gene database. After carefully checking manually, we pinpointed 524 Entrez genes from various species from 564 PubMed abstracts. To provide an consistent overview, we mapped all the 524 genes to 342 human genes using homologous relationships from NCBI HomoloGene database as we implemented previously 10, 11, 12. By integrating the oncogenes from GOA and Reactome, we consolidated 503 human genes in Table S1 (480 protein-coding and 23 non-coding genes, Table S1). This literature-based gene list will be regularly updated based on newly published literatures. Using the resulted human genes, we retrieved 5115 homologs from other species using HomoGene database.

Information for oncogenes  [ top ]

Information is represented on six different types of pages, including general information view, literature highlight view, gene expression view, gene regulation view, gene mutation view, and gene interaction view.

The general information page is like the following:

In this page, users can find the data source and our curated descriptions for oncogenes from literature. It is easy to switch to other annotations by clicking the hyperlink at the top of the page.


User can find the details of the literatures with keywords highlighted in the literature highlight page as below. The keyword "senescence" is marked in red; keywords such as "cancer" and "pathway" are marked in brown; and the keywords such as "mutation" and "expression" are marked in black as shown in below.



The gene expression page is as below:

In the page, users can find gene expression profiles from 184 human tumor samples and 84 normal tissue samples from BioGPS. It is easy to view all the sample information by clicking the hyperlink in the profile images. Some genes have multiple probes; to provide an unbiased view for users, we presented all the gene expressions from all probes without any modification.


User can obtain all the sample inforamtion by clicking on the expression images.


The gene regulation page appears as follows:

The transcription factor regulation and post-transcriptional modification information were integrated from the TRANSFAC and dbPTM databases. In addition, the methylation in promoter regions was annotated based on data from the DiseaseMeth database.


The gene mutation page appears as follows:

All the cancer related mutations were collected from the COSMIC database.

The gene homolog page appears as follows:

All the homologs from NCBI HomoloGene were collected from its public website data portal database.

The gene interaction page appears as follows:

All the related protein-protein interactions were collected from the PathwayCommon database; we further divided the interactions into three main types, including "Physical Interaction," "Metabolic Interaction," and "Signaling Interaction."

Query and sequence search against database   [ top ]

All the oncogenes and their annotations in our database are searchable. The text search (Query) and sequence-based blast (Blast) are provided.

Text search of various annotation in our database

Users can search against the ONGene by typing its name, accession IDs and its characteristics, including genomic location, interaction partner, mutation, biological pathway, and genetic disease. In total, we provided four different search forms for users, including "Gene General Information Search", "Literature Search", "Mutation Search", and "Other Annotation Search" allow users to access general information, literature-based information, mutation, and other annotation information respectively.

The search is performed by typing keywords into any field separately or into several fields simultaneously in the query forms. Generally, text search information in the each searching form mainly includes three steps. Take the basic information query as an example below

  • select a specific annotation or field from from the dropdown menu in basic gene information and mutation query forms.

  • Input your interesting keyword.

  • In addition, the basic gene information and mutation query forms support the logical 'And,' 'Or,' and 'Not' operators to combine multiple keywords.

    The search result shows the list of matched oncogenes linked to the detailed gene information page below.

    Quick search a list of genes in database:

    To quickly access the information in the database, a quick search form is provided at the top of each page.

    Blast all sequences of genes in our database

    In the BLAST menu, users can search the ONGene database based on their input sequences. The high similarity oncogenes with input sequences will be listed in the BLAST result page. In the input page, users can choose various sequence alignment options such as E-value and identity. The matched sequence signatures are visualized on the query sequence.

    To do a sequence-based search for all the oncogenes, please access the BLAST pagepage.

    The output of BLAST is as below

    Click on the hyperlink in the Blast result page, users can access the oncogenes in our database.

  • Browse database  [ top ]

    The ONGene database supports browsing oncogenes using cancer types and curated organ and tissue types. In the cancer type page, users can explore the 288 oncogene types. In addition, to help users get a bird's eye view for specific topic of oncogenes, the classified organ and tissue types were provided.

    In addtion, ONGene also supports annotation-based browsing including chromosome.

    Using different chromosomes

    From the Browser page, users can browse the genes in ONGene by their chromosome location. Moreover, users can obtain the oncogene lists from different cancer type and organ tissue information.

    Data analysis and download   [ top ]

    Users can freely download all the oncogenes in ONGene for academic researchers, but not for profit purposes. Please access Download page.

    If users have any suggestion to add new comment to records in current ONGene or to revise wrong information in current ONGene,please send us email directly.