联合TCGA和GEO数据库筛选乳腺癌易感基因

本研究是利用公共基因芯片数据库筛选乳腺癌的预后基因,预测和探索这些基因在乳腺癌进展中的可能机制和临床价值.首先,我们筛选了公共基因芯片数据库(gene expression omnibus,GEO)GSE22820和癌症基因组图谱(the cancer genome atlas,TCGA)乳腺癌数据库的重叠差异表达基因,联合R语言分析乳腺癌组织与癌旁正常组织差异表达的基因;其次,基于STRING数据库及Cytoscape软件构建蛋白质相互作用网络图,分析并识别了中枢基因和前3个模块;之后进行了更多的功能分析,包括基因本体(gene ontology,GO)和京都基因与基因组百科全书(kyoto encyclopedia of genes and genomes,KEGG)通路分析以及基因集富集分析(gene set enrichment analysis,GSEA),以研究这些基因的作用以及潜在的潜在机制;最后进行了Kaplan-Meier分析和Cox比例风险分析,以阐明这些基因的诊断和预后效果.相关数据分析表明15个基因的表达水平与生存预后相关,高表达基因患者的总生存时间短于低表达患者(P＜0.05);Cox比例风险分析表明UBE2T、ER-CC6L和RAD51这3个基因是预后生存的独立因素(P＜0.05);GSEA分析表明在UBE2T、ERCC6L和RAD51基因中细胞周期、基础转录因子和卵母细胞减数分裂明显富集.最终,我们得出结论,这3种基因标志物的高表达是乳腺癌预后不良因素,可作为预测乳腺癌患者转移和预后的有效生物标志物.     

Norcantharidin Induced DU145 Cell Apoptosis through ROS-Mediated Mitochondrial Dysfunction and Energy Depletion

Norcantharidin (NCTD), a demethylated analog of cantharidin derived from blister beetles, has attracted considerable attentions in recent years due to their definitely toxic properties and the noteworthy advantages in stimulating bone marrow and increasing the peripheral leukocytes. Hence, it is worth studying the anti-tumor effect of NCTD on human prostate cancer cells DU145. It was found that after the treatment of NCTD with different concentrations (25-100 μM), the cell proliferation was significantly inhibited, which led to the appearance of micronucleus (MN). Moreover, the cells could be killed in a dose-/ time-dependent manner along with the reduction of PCNA (proliferating cell nuclear antigen) expression, destruction of mitochondrial membrane potential (MMP), down-regulation of MnSOD, induction of ROS, depletion of ATP, and activation of AMPK (Adenosine 5‘-monophosphate -activated protein kinase) . In addition, a remarkable release of cytochrome c was found in the cells exposed to 100 μM NCTD and exogenous SOD-PEG could eliminate the generation of NCTD-induced MN. In conclusion, our studies indicated that NCTD could induce the collapse of MMP and mitochondria dysfunction. Accumulation of intercellular ROS could eventually switch on the apoptotic pathway by causing DNA damage and depleting ATP.     

Hsa-miR-34b/c rs4938723 T>C and hsa-miR-423 rs6505162 C>A Polymorphisms Are Associated with the Risk of Esophageal Cancer in a Chinese Population

Esophageal cancer is the eighth most common cancer and sixth leading cause of cancer associated death worldwide. Besides environmental risk factors, genetic factors might play an important role in the esophageal cancer carcinogenesis. We conducted a hospital based case–control study to evaluate the genetic susceptibility of functional single nucleotide polymorphisms (SNPs) in the microRNAs on the development of esophageal cancer. A total of 629 esophageal squamous cell carcinoma (ESCC) cases and 686 controls were recruited for this study. The hsa-miR-34b/c rs4938723 T>C, pri-miR-124-1 rs531564 C>G, pre-miR-125a rs12975333 G>T and hsa-miR-423 rs6505162 C>A genotypes were determined using Ligation Detection Reaction (LDR) method. Our results demonstrated that hsa-miR-34b/c rs4938723 CC genotype had a decreased risk of ESCC. The association was evident among patients who never drinking. Hsa-miR-423 rs6505162 C>A might associated with a significantly increased risk of ESCC in patients who smoking. These findings indicated that functional polymorphisms hsa-miR-34b/c rs4938723 T>C and hsa-miR-423 rs6505162 C>A might alter individual susceptibility to ESCC. However, our results were obtained with a limited sample size. Future larger studies with other ethnic populations are required to confirm current findings.     

Genome-Scale Screening of Drug-Target Associations Relevant to Ki Using a Chemogenomics Approach

The identification of interactions between drugs and target proteins plays a key role in genomic drug discovery. In the present study, the quantitative binding affinities of drug-target pairs are differentiated as a measurement to define whether a drug interacts with a protein or not, and then a chemogenomics framework using an unbiased set of general integrated features and random forest (RF) is employed to construct a predictive model which can accurately classify drug-target pairs. The predictability of the model is further investigated and validated by several independent validation sets. The built model is used to predict drug-target associations, some of which were confirmed by comparing experimental data from public biological resources. A drug-target interaction network with high confidence drug-target pairs was also reconstructed. This network provides further insight for the action of drugs and targets. Finally, a web-based server called PreDPI-K_i was developed to predict drug-target interactions for drug discovery. In addition to providing a high-confidence list of drug-target associations for subsequent experimental investigation guidance, these results also contribute to the understanding of drug-target interactions. We can also see that quantitative information of drug-target associations could greatly promote the development of more accurate models. The PreDPI-K_i server is freely available via: http://sdd.whu.edu.cn/dpiki.     

GPR50 Distribution in the Mouse Cortex and Hippocampus

Neurochemical Research - G protein-coupled receptor 50 (GPR50) belongs to the G protein-coupled receptor which is highly homologous with the sequence of melatonin receptor MT1 and MT2. GPR50...     

Survival analysis for long noncoding RNAs identifies TP53TG1 as an antioncogenic target for the breast cancer

Breast carcinoma is one of the most commonly diagnosed tumors and also one of the deadliest cancers in the female. Long noncoding RNAs (lncRNAs) are emerging as novel targets and biomarkers for breast cancer diagnosis and treatment. In this study, we aimed to study the lncRNAs associated with the outcomes in patients using the breast invasive carcinoma datasets from The Cancer Genome Atlas. The Cox proportional hazards regression model was fitted to each lncRNA. Hierarchy clustering was carried out using these survival-related lncRNAs and the log-rank test was carried out for the clustered groups. DNA methylation status was utilized to identify the lncRNAs regulated by epigenetics. Finally, the coexpressed messenger RNA with the potential lncRNAs were utilized to study the possible functions and mechanisms of lncRNAs. In total, 182 lncRNAs had an impact on the survival time of the patients with a cutoff <0.01. The patients were clustered into three groups using these survival-related genes, which performed significantly different prognosis. Two lncRNAs, which were significantly correlated with the outcomes of breast cancer and were regulated by methylation status, were obtained. These two lncRNAs were TP53TG1 and RP5-1061H20.4. We proposed that TP53TG1 was activated by the wild-type TP53 and performed an impact on the PI3Ks family by binding YBX2 in breast cancer.     

全反式维甲酸协同DAPT抑制胶质瘤干细胞的自我更新

前期研究脑表明,脑胶质瘤干细胞（glioma stem cells,GSCs）是胶质瘤发生和发展的重要因素,探索靶向干预GSCs生长有可能成为脑胶质瘤治疗的有效途径之一。该研究旨在阐明两种药物ATRA和Y-分泌酶抑制剂DAPT协同抑制GSCs自我更新的生物学效应。通过用台盼蓝排染法、克隆球形成试验和免疫印迹分析了两种药物的单独使用或联用对GSC样细胞PGCl和PGC2生长、成球能力和自我更新以及干细胞标志物表达的影响。结果发现,单独使用ATRA对PGCl生长有一定的抑制作用,而对PGC2生长几乎没有影响;DAPT对PGCs的生长抑制作用明显强于ATRA。高浓度ATRA（80μmol/L）能诱导PGCs的分化,降低PGCs成球大小,且成球效率降至5％～8％,而正常对照组为32％～35％;同样,DAPT（40μmol／L）也能降低PGCs成球大小,且成球效率降至2％～3％;低浓度ATRA（20μmol／L）和DAPT（5gmol／L）对PGCs自我更新能力和干性没有明显影响,而联合使用后其明显降低PGCs的成球大小,且成球效率降至3％～5％,促进细胞凋亡,并且明显抑制了干细胞标志物Nestin、CDl33、Sox2、Oct4的表达,提高了分化标志物GFAP的表达。该研究证明了低浓度的ATRA和DAPT能协同抑制脑胶质瘤干细胞PGCs的自我更新。研究结果将为脑胶质瘤的临床研究提供实验依据。