Adenovirus－mediated expression of pig α（1，3）galactosyltransferase reconstructs Gal α（1,3） Gal epitope on the surface of human tumor cells

Gal alpha(1, 3) Gal (gal epitope) is a carbohydrate epitope and synthesized in large amount by alpha(1, 3) galactosyltransferase [alpha(1, 3) GT] enzyme on the cells of lower mammalian animals such as pigs and mice. Human has no gal epitope due to the inactivation of alpha(1, 3) GT gene but produces a large amount of antibodies (anti-Gal) which recognize Gal alpha(1, 3) Gal structures specifically. In this study, a replication-deficient recombinant adenoviral vector Ad5sGT containing pig alpha(1, 3) GT cDNA was constructed and characterized. Adenoviral vector-mediated transfer of pig alpha(1, 3) GT gene into human tumor cells such as malignant melanoma A375, stomach cancer SGC-7901, and lung cancer SPC-A-1 was reported for the first time. Results showed that Gal epitope did not increase the sensitivity of human tumor cells to human complement-mediated lysis, although human complement activation and the binding of human IgG and IgM natural antibodies to human tumor cells were enhanced significantly after Ad5sGT transduction. Appearance of gal epitope on the human tumor cells changed the expression of cell surface carbohydrates reacting with Ulex europaeus I (UEA I) lectins, Vicia villosa agglutinin (VVA), Arachis hypogaea agglutinin (PNA), and Glycine max agglutinin (SBA) to different degrees. In addition, no effect of gal epitope on the growth in vitro of human tumor cells was observed in MTT assay.     

Downregulation of wild-type p53 protein by HER-2／neu mediated PI3K pathway activation in human breast cancer cells： its effect on cell proliferation and implication for therapy

Overexpression and activation of HER-2/neu (also known as c-erbB-2), a proto-oncogene, was found in about 30% of human breast cancers, promoting cancer growth and making cancer cells resistant to chemo- and radio-therapy.Wild-type p53 is crucial in regulating cell growth and apoptosis and is found to be mutated or deleted in 60-70% of human cancers. And some cancers with a wild-type p53 do not have normal p53 function, suggesting that it is implicated in a complex process regulated by many factors. In the present study, we showed that the overexpression of HER-2/neu could decrease the amount of wild-type p53 protein via activating PI3K pathway, as well as inducing MDM2 nuclear translocation in MCF7 human breast cancer cells. Blockage of PI3K pathway with its specific inhibitor LY294002 caused G1-S phase arrest, decreased cell growth rate and increased chemo- and radio-therapeutic sensitivity in MCF7 cells expressing wild-type p53. However, it did not increase the sensitivity to adriamycin in MDA-MB-453 breast cancer cells containing mutant p53. Our study indicates that blocking PI3K pathway activation mediated by HER-2/neu overexpression may be useful in the treatment of breast tumors with HER-2/neu overexpression and wild-type p53.     

microRNA调控网络与肿瘤

microRNA(miRNA)是一类长度约为22nt的小分子非编码RNA,对基因表达进行转录后调控。基因调控网络由各种回路,如前馈和反馈回路组成。它通过将外界刺激整合成合适的输出信号,控制细胞从增殖到死亡几乎所有的生命活动。已知基因调控网络的失调与肿瘤的发生发展密切相关。新近的实验证据表明,miRNA广泛参与基因调控网络中的反馈和前馈回路。该文主要介绍miRNA在基因表达调控网络中的作用及其与肿瘤发生发展的关系。     

基于微阵列数据构建基因调控网络

随着微阵列数据的快速增长, 微阵列基因表达数据日益成为生物信息学研究的重要数据源。利用微阵列基因表达数据构建基因调控网络也成为一个研究热点。通过构建基因调控网络, 可以解读复杂的调控关系, 发现细胞内的调控模式, 并进而在系统尺度上理解生物学进程。近年来, 人们引入了多种算法来利用基因芯片数据构建基因调控网络。文章回顾了这些算法的发展历史, 尤其是其在理论和方法上的改进, 给出了一些相关的软件平台, 并预测了该领域可能的发展趋势。     

肝癌基因调控网络研究进展

肝癌(Hepatocellular carcinoma,HCC)是我国常见的恶性肿瘤之一。肝癌基因调控网络(HCC regulatory network,HCC GRN)是研究肝癌分子机制的重要途径之一,其节点包括肝癌相关的分子,如mi RNA、TF等,网络的边由节点间相互作用关系构成。基于不同类型的数据构建的肝癌基因调控网络其类型及特征各有不同。综合近年来肝癌基因调控网络研究发现,由TF与mi RNA构建的肝癌转录调控网络更能揭露肝癌关键基因,反映关键基因在调控网络中的扰动情况。整合基因变异信息与调控网络成为研究肝癌基因调控网络的趋势,但相应的研究几乎是空白的。本文从HCC GRN的数据来源、分类及特征,及各类型调控网络的近年研究情况等方面进行综述,并结合相关研究工作对肝癌基因调控网络研究现状进行分析与讨论,对前景进行展望,为这一领域研究工作提供参考。     

On the evolution of scale-free topologies with a gene regulatory network model

A novel approach to generating scale-free network topologies is introduced, based on an existing artificial gene regulatory network model. From this model, different interaction networks can be extracted, based on an activation threshold. By using an evolutionary computation approach, the model is allowed to evolve, in order to reach specific network statistical measures. The results obtained show that, when the model uses a duplication and divergence initialisation, such as seen in nature, the resulting regulation networks not only are closer in topology to scale-free networks, but also require only a few evolutionary cycles to achieve a satisfactory error value.     

Synthetic circuits reveal how mechanisms of gene regulatory networks constrain evolution

Phenotypic variation is the raw material of adaptive Darwinian evolution. The phenotypic variation found in organismal development is biased towards certain phenotypes, but the molecular mechanisms behind such biases are still poorly understood. Gene regulatory networks have been proposed as one cause of constrained phenotypic variation. However, most pertinent evidence is theoretical rather than experimental. Here, we study evolutionary biases in two synthetic gene regulatory circuits expressed in Escherichia coli that produce a gene expression stripe—a pivotal pattern in embryonic development. The two parental circuits produce the same phenotype, but create it through different regulatory mechanisms. We show that mutations cause distinct novel phenotypes in the two networks and use a combination of experimental measurements, mathematical modelling and DNA sequencing to understand why mutations bring forth only some but not other novel gene expression phenotypes. Our results reveal that the regulatory mechanisms of networks restrict the possible phenotypic variation upon mutation. Consequently, seemingly equivalent networks can indeed be distinct in how they constrain the outcome of further evolution.     

基于组学数据构建基因调控网络

在生命体内,基因以及其它分子间相互作用形成复杂调控网络,生命过程都是以调控网络的形式存在,如从代谢通路网络到转录调控网络,从信号转导网络到蛋白质相互作用网络等等。因此,网络现象是生命现象的复杂本质和主要特征。本文系统地介绍了基于表达谱数据构建基因调控网络的布尔网络模型,线性模型,微分方程模型和贝叶斯网络模型,并对各种网络构建模型进行了深入的分析和总结。同时,文章从基因组序列信息、蛋白质相互作用信息和生物医学文献信息等方面讨论了基因调控网络方面构建的研究,这对从系统生物学水平揭示生命复杂机制具有重要的参考价值。     

Characterization of the 3'UTR of the BTD gene and identification of regulatory elements and microRNAs

Reduced biotinidase activity is associated with a spectrum of deficiency ranging from total deficiency to heterozygous levels, a finding that is not always explained by the pathogenic variants observed in the BTD gene. The investigation of miRNAs, regulatory elements and variants in the 3’UTR region may present relevance in understanding the genotype-phenotype association. The aims of the study were to characterize the regulatory elements of the 3’UTR of the BTD gene and identify variants and miRNAs which may explain the discrepancies observed between genotype and biochemical phenotype. We evaluated 92 individuals with reduced biotinidase activity (level of heterozygotes = 33, borderline = 35, partial DB = 20 or total DB= 4) with previously determined BTD genotype. The 3’UTR of the BTD gene was Sanger sequenced. In silico analysis was performed to identify miRNAs and regulatory elements. No variants were found in the 3’UTR. We found 97 possible miRNAs associated with the BTD gene, 49 predicted miRNAs involved in the alanine, biotin, citrate and pyruvate metabolic pathways and 5 genes involved in biotin metabolism. Six AU-rich elements were found. Our data suggest variants in the 3''UTR of BTD do not explain the genotype-phenotype discrepancies found in Brazilian individuals with reduced biotinidase.