ArticleFrontiers in immunology2024
Exploring potential therapeutic targets for small cell lung cancer based on transcriptomics combined with Mendelian randomization analysis.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: The main objective of this study was to explore and identify new genetic targets in small-cell lung cancer (SCLC) through transcriptomics analysis and Mendelian randomization (MR) analysis, which will help in the subsequent development of new therapeutic interventions. Methods: In this study, we extracted the SCLC dataset from the Gene Expression Omnibus (GEO) database, processed the data, and screened out differentially expressed genes (DEGs) using R software. Based on expression quantitative trait loci data and the genome-wide association study data of SCLC, MR analysis was used to screen the genes closely related to SCLC disease, which intersect with DEGs to obtain co-expressed genes (CEGs), and the biological functions and pathways of CEGs were further explored by enrichment analysis. In addition, the CIBERSORT algorithm was applied to assess the level of immune cell infiltration in SCLC and to analyze the correlation between CEGs and immune cells. Meanwhile, we performed a survival analysis on these five CEGs using an independent cohort of SCLC patients. Finally, the results for the target genes were validated. Results: In this study, 857 DEGs were identified, including 443 up-regulated and 414 down-regulated genes, and 5 CEGs ( Conclusion: The CEGs and their associated functions and pathways screened in this study may be potential targets of therapeutic intervention in SCLC by targeting specific molecular pathways.
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