A Database of Lung Cancer-Related Genes for the Identification of Subtype-Specific Prognostic Biomarkers
The molecular subtype is critical for accurate treatment and follow-up in patients with lung cancer; however, information regarding subtype-associated genes is dispersed among thousands of published studies. Systematic curation and cross-validation of the scientific literature would provide a solid...
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MDPI AG
2023-02-01
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| Series: | Biology |
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| Online Access: | https://www.mdpi.com/2079-7737/12/3/357 |
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| author | Yining Liu Min Zhao Hong Qu |
| author_facet | Yining Liu Min Zhao Hong Qu |
| author_sort | Yining Liu |
| collection | DOAJ |
| description | The molecular subtype is critical for accurate treatment and follow-up in patients with lung cancer; however, information regarding subtype-associated genes is dispersed among thousands of published studies. Systematic curation and cross-validation of the scientific literature would provide a solid foundation for comparative genetic studies of the major molecular subtypes of lung cancer. Here, we constructed a literature-based lung cancer gene database (LCGene). In the current release, we collected and curated 2507 unique human genes, including 2267 protein-coding and 240 non-coding genes from comprehensive manual examination of 10,960 PubMed article abstracts. Extensive annotations were added to aid identification of differentially expressed genes, potential gene editing sites, and non-coding gene regulation. For instance, we prepared 607 curated genes with CRISPR knockout information in 43 lung cancer cell lines. Further comparison of these implicated genes among different subtypes identified several subtype-specific genes with high mutational frequencies. Common tumor suppressors and oncogenes shared by lung adenocarcinoma and lung squamous cell carcinoma, for example, exhibited different mutational frequencies and prognostic features, suggesting the presence of subtype-specific biomarkers. Our retrospective analysis revealed 43 small cell lung cancer-specific genes. Moreover, 52 tumor suppressors and oncogenes shared by lung adenocarcinoma and squamous cell carcinoma confirmed the different molecular mechanisms of these two cancer subtypes. The subtype-based genetic differences, when combined, may provide insight into subtype-specific biomarkers for genetic testing. |
| first_indexed | 2024-03-11T06:54:28Z |
| format | Article |
| id | doaj.art-5cccc485e9694909bd847cd35fe6a038 |
| institution | Directory Open Access Journal |
| issn | 2079-7737 |
| language | English |
| last_indexed | 2024-03-11T06:54:28Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
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| series | Biology |
| spelling | doaj.art-5cccc485e9694909bd847cd35fe6a0382023-11-17T09:41:02ZengMDPI AGBiology2079-77372023-02-0112335710.3390/biology12030357A Database of Lung Cancer-Related Genes for the Identification of Subtype-Specific Prognostic BiomarkersYining Liu0Min Zhao1Hong Qu2The School of Public Health, Institute for Chemical Carcinogenesis, Guangzhou Medical University, Guangzhou 510180, ChinaSchool of Science, Technology and Engineering, University of the Sunshine Coast, Maroochydore, QLD 4558, AustraliaCenter for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, ChinaThe molecular subtype is critical for accurate treatment and follow-up in patients with lung cancer; however, information regarding subtype-associated genes is dispersed among thousands of published studies. Systematic curation and cross-validation of the scientific literature would provide a solid foundation for comparative genetic studies of the major molecular subtypes of lung cancer. Here, we constructed a literature-based lung cancer gene database (LCGene). In the current release, we collected and curated 2507 unique human genes, including 2267 protein-coding and 240 non-coding genes from comprehensive manual examination of 10,960 PubMed article abstracts. Extensive annotations were added to aid identification of differentially expressed genes, potential gene editing sites, and non-coding gene regulation. For instance, we prepared 607 curated genes with CRISPR knockout information in 43 lung cancer cell lines. Further comparison of these implicated genes among different subtypes identified several subtype-specific genes with high mutational frequencies. Common tumor suppressors and oncogenes shared by lung adenocarcinoma and lung squamous cell carcinoma, for example, exhibited different mutational frequencies and prognostic features, suggesting the presence of subtype-specific biomarkers. Our retrospective analysis revealed 43 small cell lung cancer-specific genes. Moreover, 52 tumor suppressors and oncogenes shared by lung adenocarcinoma and squamous cell carcinoma confirmed the different molecular mechanisms of these two cancer subtypes. The subtype-based genetic differences, when combined, may provide insight into subtype-specific biomarkers for genetic testing.https://www.mdpi.com/2079-7737/12/3/357lung cancerdatabasegeneticsubtypesystems biologybiomarker |
| spellingShingle | Yining Liu Min Zhao Hong Qu A Database of Lung Cancer-Related Genes for the Identification of Subtype-Specific Prognostic Biomarkers Biology lung cancer database genetic subtype systems biology biomarker |
| title | A Database of Lung Cancer-Related Genes for the Identification of Subtype-Specific Prognostic Biomarkers |
| title_full | A Database of Lung Cancer-Related Genes for the Identification of Subtype-Specific Prognostic Biomarkers |
| title_fullStr | A Database of Lung Cancer-Related Genes for the Identification of Subtype-Specific Prognostic Biomarkers |
| title_full_unstemmed | A Database of Lung Cancer-Related Genes for the Identification of Subtype-Specific Prognostic Biomarkers |
| title_short | A Database of Lung Cancer-Related Genes for the Identification of Subtype-Specific Prognostic Biomarkers |
| title_sort | database of lung cancer related genes for the identification of subtype specific prognostic biomarkers |
| topic | lung cancer database genetic subtype systems biology biomarker |
| url | https://www.mdpi.com/2079-7737/12/3/357 |
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