Saad Mohamed N, Hamed Mohamed
Biomedical Engineering Department, Faculty of Engineering, Minia University, Minia 61519, Egypt.
Institute for Biostatistics and Informatics in Medicine and Ageing Research (IBIMA), Rostock University Medical Center, 18057 Rostock, Germany.
Cancers (Basel). 2024 Jul 11;16(14):2517. doi: 10.3390/cancers16142517.
A transcriptome-wide association study (TWAS) was conducted on genome-wide association study (GWAS) summary statistics of malignant melanoma of skin (UK Biobank dataset) and The Cancer Genome Atlas-Skin Cutaneous Melanoma (TCGA-SKCM) gene expression weights to identify melanoma susceptibility genes. The GWAS included 2465 cases and 449,799 controls, while the gene expression testing was conducted on 103 cases. Afterward, a gene enrichment analysis was applied to identify significant TWAS associations. The melanoma's gene-microRNA (miRNA) regulatory network was constructed from the TWAS genes and their corresponding miRNAs. At last, a disease enrichment analysis was conducted on the corresponding miRNAs. The TWAS detected 27 genes associated with melanoma with -values less than 0.05 (the top three genes are (), (), and ). After the joint/conditional test, one gene () was dropped, resulting in 26 significant genes. The Gene Ontology (GO) biological process associated the extended gene set (76 genes) with protein K11-linked ubiquitination and regulation of cell cycle phase transition. K11-linked ubiquitin chains regulate cell division. Interestingly, the extended gene set was related to different skin cancer subtypes. Moreover, the enriched pathways were nsp1 from SARS-CoV-2 that inhibit translation initiation in the host cell, cell cycle, translation factors, and DNA repair pathways full network. The gene-miRNA regulatory network identified 10 hotspot genes with the top three: , , and ; and four hotspot miRNAs: mir-16, mir-15a, mir-125b, and mir-146a. Melanoma was among the top ten diseases associated with the corresponding (106) miRNAs. Our results shed light on melanoma pathogenesis and biologically significant molecular interactions.
对皮肤恶性黑色素瘤的全基因组关联研究（GWAS）汇总统计数据（英国生物银行数据集）和癌症基因组图谱-皮肤黑色素瘤（TCGA-SKCM）基因表达权重进行了全转录组关联研究（TWAS），以确定黑色素瘤易感基因。GWAS包括2465例病例和449,799例对照，而基因表达测试是在103例病例上进行的。之后，应用基因富集分析来确定显著的TWAS关联。从TWAS基因及其相应的微小RNA（miRNA）构建了黑色素瘤的基因- miRNA调控网络。最后，对相应的miRNA进行了疾病富集分析。TWAS检测到27个与黑色素瘤相关的基因，其P值小于0.05（前三个基因是（）、（）和（））。经过联合/条件检验，一个基因（）被剔除，得到26个显著基因。基因本体论（GO）生物学过程将扩展基因集（76个基因）与蛋白质K11连接的泛素化和细胞周期阶段转变的调节联系起来。K11连接的泛素链调节细胞分裂。有趣的是，扩展基因集与不同的皮肤癌亚型有关。此外，富集的途径是来自严重急性呼吸综合征冠状病毒2（SARS-CoV-2）的nsp1，其抑制宿主细胞中的翻译起始、细胞周期、翻译因子和DNA修复途径全网络。基因- miRNA调控网络确定了10个热点基因，前三个是（）、（）和（）；以及四个热点miRNA：mir-16、mir-15a、mir-125b和mir-146a。黑色素瘤是与相应的（106个）miRNA相关的十大疾病之一。我们的结果揭示了黑色素瘤的发病机制和具有生物学意义的分子相互作用。
