Department of Vascular Surgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China.
Department of Intensive Care Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China.
BMC Med Genomics. 2022 Jun 30;15(1):145. doi: 10.1186/s12920-022-01257-1.
This study identified underlying genetic molecules associated with histologically unstable carotid atherosclerotic plaques through bioinformatics analysis that may be potential biomarkers and therapeutic targets.
Three transcriptome datasets (GSE41571, GSE120521 and E-MTAB-2055) and one non-coding RNA dataset (GSE111794) that met histological grouping criteria of unstable plaque were downloaded. The common differentially expressed genes (co-DEGs) of unstable plaques identified from three mRNA datasets were annotated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomics (KEGG). A protein-protein interaction (PPI) network was constructed to present the interaction between co-DEGs and screen out hub genes. MiRNet database and GSE111794 dataset were used to identify the miRNAs targeting hub genes. Associated transcription factors (TFs) and drugs were also predicted. These predicted results were used to construct miRNA/TFs-hub gene and drug-hub gene regulatory networks.
A total of 105 co-DEGs were identified, including 42 up-regulated genes and 63 down-regulated genes, which were mainly enriched in collagen-containing extracellular matrix, focal adhesion, actin filament bundle, chemokine signaling pathway and regulates of actin cytoskeleton. Ten hub genes (up-regulated: HCK, C1QC, CD14, FCER1G, LCP1 and RAC2; down-regulated: TPM1, MYH10, PLS3 and FMOD) were screened. HCK and RAC2 were involved in chemokine signaling pathway, MYH10 and RAC2 were involved in regulation of actin cytoskeleton. We also predicted 12 miRNAs, top5 TFs and 25 drugs targeting hub genes. In the miRNA/TF-hub gene regulatory network, PLS3 was the most connected hub genes and was targeted by six miRNAs and all five screened TFs. In the drug-hub gene regulatory network, HCK was targeted by 20 drugs including 10 inhibitors.
We screened 10 hub genes and predicted miRNAs and TFs targeting them. These molecules may play a crucial role in the progression of histologically unstable carotid plaques and serve as potential biomarkers and therapeutic targets.
通过生物信息学分析,鉴定与组织学不稳定颈动脉粥样硬化斑块相关的潜在遗传分子标志物和治疗靶点。
下载了 3 个转录组数据集(GSE41571、GSE120521 和 E-MTAB-2055)和 1 个非编码 RNA 数据集(GSE111794),这些数据集符合不稳定斑块的组织学分组标准。从 3 个 mRNA 数据集中鉴定出的不稳定斑块的共同差异表达基因(co-DEGs)通过基因本体论(GO)和京都基因与基因组百科全书(KEGG)进行注释。构建蛋白质-蛋白质相互作用(PPI)网络,以展示 co-DEGs 之间的相互作用,并筛选出枢纽基因。利用 miRNet 数据库和 GSE111794 数据集鉴定靶向枢纽基因的 miRNAs。还预测了相关的转录因子(TFs)和药物。这些预测结果用于构建 miRNA/TFs-枢纽基因和药物-枢纽基因调控网络。
共鉴定出 105 个 co-DEGs,包括 42 个上调基因和 63 个下调基因,主要富集在含有胶原蛋白的细胞外基质、焦点黏附、肌动蛋白丝束、趋化因子信号通路和调节肌动蛋白细胞骨架。筛选出 10 个枢纽基因(上调:HCK、C1QC、CD14、FCER1G、LCP1 和 RAC2;下调:TPM1、MYH10、PLS3 和 FMOD)。HCK 和 RAC2 参与趋化因子信号通路,MYH10 和 RAC2 参与肌动蛋白细胞骨架调节。我们还预测了 12 个 miRNAs、前 5 个 TFs 和 25 种针对枢纽基因的药物。在 miRNA/TF-枢纽基因调控网络中,PLS3 是最相关的枢纽基因,被 6 个 miRNAs 和所有 5 个筛选出的 TFs 靶向。在药物-枢纽基因调控网络中,HCK 被包括 10 种抑制剂在内的 20 种药物靶向。
我们筛选出 10 个枢纽基因,并预测了针对它们的 miRNAs 和 TFs。这些分子可能在组织学不稳定颈动脉斑块的进展中发挥关键作用,可作为潜在的生物标志物和治疗靶点。