Data integration of LCGene and how to use LCGene:
1. Data integration of LCGene database Four steps for collecting lung cancer genes Curating lung cancer genes from the literature 2. Information for lung cancer genes General information Literature-based evidence Gene expression profile Mutation information Gene interaction network 3. Query and search database Text search for lung cancer-related genes Quick access information in database 4. Browse database By chromosome By cancer type By literature number By marked KEGG pathway 5. Data download
Data integration of LCGene database
The primary aim of the database is to support lung cancer (LC) research by maintaining a high-quality database of lung cancer genes that serves as a comprehensive, fully classified, and accurately annotated lung cancer gene resource, with extensive cross-references and querying interfaces freely accessible to the scientific community.
Four steps for collecting lung cancer genes
Construction of this lung cancer gene database for human genes involved four key steps: querying lung cancer-related literature; identification of the description related to lung cancer; mapping the description of lung cancer genes from the literature to Entrez gene database IDs; including extensive annotations of cellular function, gene expression, mutation, methylation, transcription factor, post-translational modification, and protein-protein interaction. In detail, five steps were involved in the curation of lung cancer genes from the literature before final inclusion in the LCGene database: exhaustive searching for relevant abstracts from the PubMed databases using the keywords "lung cancer gene;" extracting the description for the lung cancer gene from text; grouping the descriptions extracted from PubMed abstract records by their topics using Entrez related topic function; extraction of gene name from the grouped descriptions of lung cancer genes; and finally, mapping the gene name to the Entrez geneID.
Exhaustive search: On January 22, 2021, to assemble a comprehensive list of LC-related genes and associated literature, we performed an extensive literature query of the Gene Reference Into Function (GeneRIF) database using Perl regular expression to identify sentences with both lung and cancer keywords: [(lung OR pulmonary) AND (cancer OR tumor OR carcinoma)]. We retrieved 15,964 records of genes associated with lung cancer. In GeneRIF, each record contains a sentence to describe the function of the gene in the Entrez Gene database. Normally, GeneRIF records provide a link to full abstracts with PubMed IDs. To provide accurate information, we further downloaded all 15,964 unique PubMed abstracts for manual curation.
Curation of lung cancer genes from the literature
Extracting gene description: To evaluate the information about lung cancer gene, the sentences containing keywords "cancer", "lung", "pulmonary", or "tumor" were extracted from all the PubMed abstracts. Group abstracts: All of the downloaded abstracts are categorized according to topic and related articles provided by Entrez. This enables us to quickly and easily determine whether and how certain gene names are highly related to lung cancer genes. It also enables us to determine whether and how certain references are related to other highly confirmed references concerning lung cancer gene descriptions. Curation: In this step, we manually review the abstracts, evaluate the context given, and add relevant comments and features to the entry. We can, often from reading the abstract, judge whether the described gene is a lung cancer gene. In these cases, care is taken to analyze other references about the same gene. The description of each lung cancer gene is added to the new entry. Mapping the gene symbols: A major step in the article curating process is mapping the gene name in the text to an Entrez gene ID. This serves as the starting point for cross-referencing the gene in other public databases. The synonyms of the gene symbol are carefully considered, and some synonyms are deleted or transferred to the Entrez gene ID.
Information for lung cancer genes [ top ]
Information is presented on five different pages, including general information view, literature highlight view, gene expression view, gene mutation view, and gene interaction view. The general information page is the following: On this page, users can find the data source and our curated descriptions of lung cancer genes from the literature. Clicking the hyperlink at the top of the page makes it easy to switch to other annotations. Curated literature information appears as follows: The word cloud chart was generated based on all the curated sentences from the literature, and provides an overview of the gene functions found the literature. On the literature highlight page, the user can find literature details with the keywords highlighted . The keyword "lung" 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 below. The gene expression page is as follows: Information regarding transcription factor regulation and post-transcriptional modifications were integrated from the transcription factor database TRANSFAC. Users can find gene expression profiles from 184 human tumor samples and 84 normal tissue samples from BioGPS. By clicking the hyperlink in the profile images, it is easy to view all the sample information. Some genes have multiple probes; to provide an unbiased view for users, we have presented gene expression data from all probes with no modifications. Users can obtain all the sample information by clicking on the images. The gene mutation page appears as follows: All the cancer related mutations were collected from the COSMIC database. The gene interaction page appears as follows: All of the related protein-protein interactions were collected from the Pathway Commons database; we further divided the interactions into three main types, including "Physical Interaction," "Metabolic Interaction," and "Signaling Interaction." Based on all the data, we furthermore plotted the top 100 interactors, which presents a quick overview of potential interactions.
Query and sequence search against the database [ top ]
All the lung cancer genes and their annotations in our database are searchable. The text-based search function is provided at (Query). Text search of various annotation in our database Users can search in the LCGene database by typing gene name, accession IDs and its characteristics, including genomic location, interaction partner, mutation, biological pathway, and genetic disease. We provided four different forms of searching for users, including "Gene General Information Search", "Literature Search", and "Other Annotation Search"; this allows users to access general information, literature-based information, 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. Text search information includes three steps. Step 1: select a specific annotation or field from the dropdown menu in basic gene information and mutation query forms. Step 2: input keywords of interest. Step 3: the basic gene information and mutation query forms support the logical 'And,' 'Or,' and 'Not' operators to combine multiple keywords. To quickly access the information in the database, a quick search form is provided at the top of each page. The search result shows the list of matched lung cancer genes linked to the detailed gene information page below.
Browse database [ top ]
The LCGene database supports browsing lung cancer genes using curated cancer types. In the cancer type page, users can explore the top 17 cancer types associated with over 100 genes. LCGene supports annotation-based browsing including chromosomes.
Using different chromosomes From the Browser page, users can browse the genes in LCGene by their chromosome location. Lung cancer sub-type in the subtype section, users can browse the genes in LCGene by the curated sub-type information. The literature number From the literature section, users can browse the genes in the LCGene database according to the numbers of literature-based evidences. Tumor suppressor, oncogene, and KEGG pathway From the Browser page, users can obtain lung cancer gene lists with known tumor suppressive and oncogenic roles based on the TSGene and ONGene database. All the lung cancer genes are also further highlighted in KEGG pathways.
Data analysis and download [ top ]
Users can freely download all the lung cancer genes in the LCGene database for academic researchers, but it is not to be used for profit purposes. Please access the Download page. If users have any suggestion to add new comment to records in current LCGene or to revise wrong information in current LCGene,please send us email directly.

Data integration of LCGene and how to use LCGene:

1. Data integration of LCGene database

Four steps for collecting lung cancer genes

Curating lung cancer genes from the literature

2. Information for lung cancer genes

General information

Literature-based evidence

Gene expression profile

Mutation information

Gene interaction network

3. Query and search database

Text search for lung cancer-related genes

Quick access information in database

By marked KEGG pathway

5. Data download

Data integration of LCGene database

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

Four steps for collecting lung cancer genes

Construction of this lung cancer gene database for human genes involved four key steps: querying lung cancer-related literature; identification of the description related to lung cancer; mapping the description of lung cancer genes from the literature to Entrez gene database IDs; including extensive annotations of cellular function, gene expression, mutation, methylation, transcription factor, post-translational modification, and protein-protein interaction.

In detail, five steps were involved in the curation of lung cancer genes from the literature before final inclusion in the LCGene database: exhaustive searching for relevant abstracts from the PubMed databases using the keywords "lung cancer gene;" extracting the description for the lung cancer gene from text; grouping the descriptions extracted from PubMed abstract records by their topics using Entrez related topic function; extraction of gene name from the grouped descriptions of lung cancer genes; and finally, mapping the gene name to the Entrez geneID.

Exhaustive search:
On January 22, 2021, to assemble a comprehensive list of LC-related genes and associated literature, we performed an extensive literature query of the Gene Reference Into Function (GeneRIF) database using Perl regular expression to identify sentences with both lung and cancer keywords: [(lung OR pulmonary) AND (cancer OR tumor OR carcinoma)]. We retrieved 15,964 records of genes associated with lung cancer. In GeneRIF, each record contains a sentence to describe the function of the gene in the Entrez Gene database. Normally, GeneRIF records provide a link to full abstracts with PubMed IDs. To provide accurate information, we further downloaded all 15,964 unique PubMed abstracts for manual curation.

Curation of lung cancer genes from the literature

Extracting gene description:
To evaluate the information about lung cancer gene, the sentences containing keywords "cancer", "lung", "pulmonary", or "tumor" were extracted from all the PubMed abstracts.

Group abstracts:
All of the downloaded abstracts are categorized according to topic and related articles provided by Entrez. This enables us to quickly and easily determine whether and how certain gene names are highly related to lung cancer genes. It also enables us to determine whether and how certain references are related to other highly confirmed references concerning lung cancer gene descriptions.

Curation:
In this step, we manually review the abstracts, evaluate the context given, and add relevant comments and features to the entry. We can, often from reading the abstract, judge whether the described gene is a lung cancer gene. In these cases, care is taken to analyze other references about the same gene. The description of each lung cancer gene is added to the new entry.

Mapping the gene symbols:
A major step in the article curating process is mapping the gene name in the text to an Entrez gene ID. This serves as the starting point for cross-referencing the gene in other public databases. The synonyms of the gene symbol are carefully considered, and some synonyms are deleted or transferred to the Entrez gene ID.

Information for lung cancer genes [ top ]

Information is presented on five different pages, including general information view, literature highlight view, gene expression view, gene mutation view, and gene interaction view.

The general information page is the following:

On this page, users can find the data source and our curated descriptions of lung cancer genes from the literature. Clicking the hyperlink at the top of the page makes it easy to switch to other annotations.

Curated literature information appears as follows:

The word cloud chart was generated based on all the curated sentences from the literature, and provides an overview of the gene functions found the literature. On the literature highlight page, the user can find literature details with the keywords highlighted . The keyword "lung" 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 below.

The gene expression page is as follows:

Information regarding transcription factor regulation and post-transcriptional modifications were integrated from the transcription factor database TRANSFAC.

Users can find gene expression profiles from 184 human tumor samples and 84 normal tissue samples from BioGPS. By clicking the hyperlink in the profile images, it is easy to view all the sample information. Some genes have multiple probes; to provide an unbiased view for users, we have presented gene expression data from all probes with no modifications.

Users can obtain all the sample information by clicking on the images.

The gene mutation page appears as follows:

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

The gene interaction page appears as follows:

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

Based on all the data, we furthermore plotted the top 100 interactors, which presents a quick overview of potential interactions.

Query and sequence search against the database [ top ]

All the lung cancer genes and their annotations in our database are searchable. The text-based search function is provided at (Query).

Text search of various annotation in our database

Users can search in the LCGene database by typing gene name, accession IDs and its characteristics, including genomic location, interaction partner, mutation, biological pathway, and genetic disease. We provided four different forms of searching for users, including "Gene General Information Search", "Literature Search", and "Other Annotation Search"; this allows users to access general information, literature-based information, 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. Text search information includes three steps.

Step 1: select a specific annotation or field from the dropdown menu in basic gene information and mutation query forms.

Step 2: input keywords of interest.

Step 3: the basic gene information and mutation query forms support the logical 'And,' 'Or,' and 'Not' operators to combine multiple keywords.

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

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

Browse database [ top ]

The LCGene database supports browsing lung cancer genes using curated cancer types. In the cancer type page, users can explore the top 17 cancer types associated with over 100 genes.

LCGene supports annotation-based browsing including chromosomes.

Using different chromosomes

From the Browser page, users can browse the genes in LCGene by their chromosome location.

Lung cancer sub-type

in the subtype section, users can browse the genes in LCGene by the curated sub-type information.

The literature number

From the literature section, users can browse the genes in the LCGene database according to the numbers of literature-based evidences.

Tumor suppressor, oncogene, and KEGG pathway

From the Browser page, users can obtain lung cancer gene lists with known tumor suppressive and oncogenic roles based on the TSGene and ONGene database. All the lung cancer genes are also further highlighted in KEGG pathways.

Data analysis and download [ top ]

Users can freely download all the lung cancer genes in the LCGene database for academic researchers, but it is not to be used for profit purposes. Please access the Download page.

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