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A Database of Lung Cancer-Related Genes for the Identification of Subtype-Specific Prognostic Biomarkers

SIMPLE SUMMARY: We developed a lung cancer-specific database containing genetic and literature data from over 10,000 separate studies. The cancer subtype information was meticulously curated and quality controlled, while the subtype-specific genetics can be explored in a novel manner. In addition, w...

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Detalles Bibliográficos
Autores principales: Liu, Yining, Zhao, Min, Qu, Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10045015/
https://www.ncbi.nlm.nih.gov/pubmed/36979050
http://dx.doi.org/10.3390/biology12030357
Descripción
Sumario:SIMPLE SUMMARY: We developed a lung cancer-specific database containing genetic and literature data from over 10,000 separate studies. The cancer subtype information was meticulously curated and quality controlled, while the subtype-specific genetics can be explored in a novel manner. In addition, we created the Lung Cancer Gene (LCGene) database, an open-access web interface that enables researchers and clinicians to explore these data and conduct large-scale integrative analyses. On LCGene, users can perform gene list-based data integration to gain a quick understanding of the shared and unique characteristics of various subtypes of lung cancer. In summary, data from subtype-based survival analysis, comparative analysis, and CRISPR knockout provide additional novel information for genome-wide gene/biomarker screening in lung cancer subtypes. ABSTRACT: 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.