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A Database of Lung Cancer-Related Genes for the Identification of Subtype-Specific Prognostic Biomarkers2.47 MB
Published VersionCC BY V4.0, Open Access
Journal article
A Database of Lung Cancer-Related Genes for the Identification of Subtype-Specific Prognostic Biomarkers
Biology, Vol.12(3), pp.1-12
2023
PMID: 36979050
Appears in Cancer Research Cluster Research Collection
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.
Details
- Title
- A Database of Lung Cancer-Related Genes for the Identification of Subtype-Specific Prognostic Biomarkers
- Authors
- Yining Liu (Author) - Guangzhou Medical UniversityMin Zhao (Corresponding Author) - University of the Sunshine Coast, Queensland, Centre for BioinnovationHong Qu (Corresponding Author) - Peking University
- Publication details
- Biology, Vol.12(3), pp.1-12
- Publisher
- MDPI AG
- Date published
- 2023
- DOI
- 10.3390/biology12030357
- ISSN
- 2079-7737
- PMID
- 36979050
- Copyright note
- © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/ 4.0/).
- Grant note
- 31671375; 31871339 / National Natural Science Foundation of China 2017YFC1201200 / National Key Research and Development Program of China
- Organisation Unit
- University of the Sunshine Coast, Queensland; GeneCology Research Centre - Legacy; Cancer Research Cluster; School of Science, Technology and Engineering; Centre for Bioinnovation
- Language
- English
- Record Identifier
- 99715098202621
- Output Type
- Journal article
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