ABSTRACT
@#[摘 要] 目的：通过生物信息学方法探索并实验验证胃癌相关标志物miR-1-3p对胃癌细胞增殖的作用及其分子机制。方法：收集TCGA数据库中胃癌（n=375）及癌旁组织（n=45）的转录组数据，构建胃癌特异性mRNA-miRNA网络，筛选潜在的miRNA类标志物，利用TargetScan预测标志物的下游靶基因且分析它们的功能。选取人正常胃上皮细胞GES-1及胃癌细胞AGS、MKN45、NCI-N87，用qPCR法检测细胞中miR-1-3p和心肌蛋白（MYOCD）的表达，用lipofectamine 2000将miR-1-3p模拟物转染至胃癌细胞中，CCK-8法测定轨染后细胞的增殖能力，WB法测定MYOCD的表达量，双荧光素酶报告基因实验验证miR-1-3p与MYOCD之间的靶向结合关系。结果：通过数据库数据分析得到差异表达的259个miRNA和7 545个mRNA，构建胃癌特异性mRNA-miRNA调节网络，分析网络中脆弱结构后确定miR-1-3p为潜在的胃癌标志物，ROC曲线和Kaplan-Meier分析显示其对胃癌的诊断和预后评估有重要意义。细胞实验显示miR-1-3p在胃癌细胞中呈低表达（P<0.05），过表达miR-1-3p可抑制胃癌细胞AGS和MKN-45的增殖能力（P<0.05或P<0.01），且可抑制MYOCD的表达（P<0.01）。TargetScan数据库预测到MYOCD的3'UTR区域中有两个与miR-1-3p结合的位点，双荧光素酶报告基因实验证实miR-1-3p与MYOCD靶向结合且负调控MYOCD的表达（P<0.01）。结论: miR-1-3p可能是胃癌诊断和预后相关潜在的标志物，且miR-1-3p可能是通过靶向MYOCD来影响胃癌细胞的增殖。
ABSTRACT
@#[Abstract] Objective: To explore the regulatory relationship between enhancer and miRNA and the characteristics of the enhancers that regulate miRNA in hepatic carcinoma and normal hepatic tissues, and to screen the differentially expressed miRNAs regulated by enhancers as well as their association with the treatment targets in liver cancer. Methods: Based on the TCGA and FANTOM5 databases, Co-expression and 3D genomic analysis were performed on 417 samples of enhancers and miRNAs in liver cancer and normal liver tissues. The difference in signal value of the enhancer that regulates miRNA was analyzed by ChIP-seq data of histone modification and transcription factor in liver cancer and normal liver tissues in ENCODE database. The differentially expressed miRNAs regulated by enhancers were screened out, and the correlation analysis was performed on the patient's survival and treatment targets. Results: 93 and 40 pairs of enhancer-miRNA were identified in liver cancer and normal liver tissues, respectively. ChIP-seqdata comparison analysis found that the signal of H3K27ac, H3K4me1 and sH3K4me3 histone modification in the region of enhancers regulating miRNA was significantly higher than that in the region of enhancers not regulating miRNA (|rho|>0.3, P<0.05). Moreover, the enrichment of multiple transcription factors in liver cancer-related enhancers was significantly lower than that in normal liver tissue-realted enhancers (|rho|>0.3, P<0.05). Differential expression analysis of enhancer-regulated miRNAs identified 6 miRNAs related to the survival of liver cancer patients(hsa-miR-4664, hsa-miR-5003,hsa-miR-1915,hsa-miR-3619,hsa-miR-4745, hsa-miR-6728),and found that these miRNAs were significantly associated with 87 genes for targeted therapy and 8 tumor immune checkpoint genes (|rho|>0.1, FDR<0.05). Conclusion: The enhancer-miRNA regulatory pairs and the characteristics of the enhancer that regulates miRNA were successfully identified in liver cancer. The miRNAs regulated by enhancers and related to the therapeutic targets and survival of patients with liver cancer were also screened out. It provides a valuable preliminary basis for future in-depth basic and clinical research in hepatic carcinoma.
ABSTRACT
@#[Abstract] Objective: To investigate the pathogenesis of prostate cancer by analyzing the associated hub gene modules of prostate cancer and identifying key transcription factors and genes that affect these modules. Methods: WGCNA (weighted gene co-expressed network analysis) was used to identify hub gene modules associated with important clinicopathological features of prostate cancer, such as pathological staging, Gleason grading etc. The OPOSSUM online tool was used to analyze the transcription factors enriching and regulating those genes. Pathway enrichment analysis and protein-protein interaction network analysis were used to identify key genes in prostate cancer. Finally, the effects of these genes on clinical features and disease-free survival (DFS) of prostate cancer patients were analyzed. Results: Three hub modules were identified, and they were highly associated with pathologic T stage, pathologic N stage and Gleason grading of prostate cancer, respectively. Further screening revealed 13 key dysregulated transcription factors that participated in the regulation of these three hub modules. The differentially expressed genes regulated by the 13 key transcription factors were significantly enriched in Calcium signaling pathway, cGMP-PKG signaling pathway and cAMP signaling pathway. 14 key genes (PRKG1, PRKG2, CYSLTR2, GRPR, CHRM3, ADCY5, ADRA1D, EDNRA, EDNRB, CYSLTR2, AGTR1, GRPR, GRIA1 and OXT) were at important nodes in the gene network. Among them, the high expression of ADRA1A, PRKG2, CHRM3, ADRA1D and EDN3 significantly extended the DFS of patients with prostate cancer (all P<0.01). Conclusion: ADRA1A, PRKG2, CHRM3, ADRA1D and EDN3 are regulated by key dysregulated transcription factors and highly associated with clinical features of prostate cancer. Their high expressions will significantly prolong the DFS of prostate cancer patients, which may shed light to the discovery of mechanism in prostate adenocarcinoma.