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Data Sheet 1_Identification of druggable targets in melanoma by multi-omics Mendelian randomization integrated with transcriptomic and spatial analysis.pdf

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NIAID Data Ecosystem2026-05-10 收录
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https://figshare.com/articles/dataset/Data_Sheet_1_Identification_of_druggable_targets_in_melanoma_by_multi-omics_Mendelian_randomization_integrated_with_transcriptomic_and_spatial_analysis_pdf/30450521
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BackgroundCutaneous melanoma (CM) is a highly lethal skin tumor. Some patients respond poorly to existing therapies, and developing new targeted therapies remains challenging. MethodsWe combined the results of eQTLs, pQTLs, and genome-wide association study (GWAS) to identify potential causal effects of two target genes on CM, based on multi-omics Mendelian randomization (MR). Sensitivity analysis, co-localization analysis, and inverse MR analysis were also employed to verify the robustness of this causal relationship. Multi-omics data were then applied to explore the expression patterns of immune infiltration of the target genes and construct nomogram models. ResultsThe results showed that the gene prediction levels of EPS15L1 and HGS were associated with an increased risk of CM. Co-localization analysis revealed significant horizontal pleiotropy of the target gene, and reverse MR showed unidirectional causality of the targets. Multi-omics analysis comprehensively demonstrated the expression regulation pattern of the target genes in the CM immune-environment and identified interactions between EPS15L1 (Q9UBC2) and HGS (O14964) and doxorubicin, demonstrating the potential for drug application. The validity of the targets was further verified by molecular biology experiments. ConclusionThis study provides robust genetic and therapeutic evidence for targeting EPS15L1 and HGS in CM treatment.
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