ArticleComputational and structural biotechnology journal2021
Identification of the susceptibility genes for COVID-19 in lung adenocarcinoma with global data and biological computation methods.
Article in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed, 25 citations in OpenAlex.
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- EBNA1BP2 identified as potential prognostic biomarker for multiple tumor types in pan-cancer analysis.Discover oncology · 2024Article
- PPIH acts as a potential predictive biomarker for patients with common solid tumors.BMC cancer · 2024Article
- Unveiling the link between lactate metabolism and rheumatoid arthritis through integration of bioinformatics and machine learning.Scientific reports · 2024Article
- PFDN6 contributes to colorectal cancer progression via transcriptional regulation.eGastroenterology · 2024Article
- MRTO4 acts as an independent prognostic and immunological biomarker and is correlated with tumor microenvironment in hepatocellular carcinoma.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2024Article
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- The m6A methylation profiles of immune cells in type 1 diabetes mellitus.Frontiers in immunology · 2022Article
- Ogt Demonstrated Conspicuous Clinical Significance in Cancers, from Pan-Cancer to Small-Cell Lung Cancer.Journal of oncology · 2022Article
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe risk of infection with COVID-19 is high in lung adenocarcinoma (LUAD) patients, and there is a dearth of studies on the molecular mechanism underlying the high susceptibility of LUAD patients to COVID-19 from the perspective of the global differential expression landscape.
objectivesTo fill the research void on the molecular mechanism underlying the high susceptibility of LUAD patients to COVID-19 from the perspective of the global differential expression landscape.
methodsHerein, we identified genes, specifically the differentially expressed genes (DEGs), correlated with the susceptibility of LUAD patients to COVID-19. These were obtained by calculating standard mean deviation (SMD) values for 49 SARS-CoV-2-infected LUAD samples and 24 non-affected LUAD samples, as well as 3931 LUAD samples and 3027 non-cancer lung samples from 40 pooled RNA-seq and microarray datasets. Hub susceptibility genes significantly related to COVID-19 were further selected by weighted gene co-expression network analysis. Then, the hub genes were further analyzed via an examination of their clinical significance in multiple datasets, a correlation analysis of the immune cell infiltration level, and their interactions with the interactome sets of the A549 cell line.
resultsA total of 257 susceptibility genes were identified, and these genes were associated with RNA splicing, mitochondrial functions, and proteasomes. Ten genes, MEA1, MRPL24, PPIH, EBNA1BP2, MRTO4, RABEPK, TRMT112, PFDN2, PFDN6, and NDUFS3, were confirmed to be the hub susceptibility genes for COVID-19 in LUAD patients, and the hub susceptibility genes were significantly correlated with the infiltration of multiple immune cells.
conclusionIn conclusion, the susceptibility genes for COVID-19 in LUAD patients discovered in this study may increase our understanding of the high risk of COVID-19 in LUAD patients.
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