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Orthotopic xenograft model of human brain cancer cells is a good preclinical model for evaluation of antitumor compounds. In the present study, an orthotopic xenograft model of U87MG-m Cherry-luc was established in Balb/c nude mice and the tumor growth was monitored via imaging technology including magnetic resonance imaging (MRI), in vivo imaging (IVI) and micro-CT. Furthermore, the model was evaluated with a positive drug temozolomide. Our data suggest that integrated imaging technology including MRI, IVI and micro-CT in orthotopic xenograft model can be used to facilitate monitoring of cancer progression and evaluate antitumor activity of drugs against glioma.

Vectors used to carry foreign genes play an important role in gene therapy, among which, the adeno-associated virus (AAV) has many advantages, such as nonpathogenicity, low immunogenicity, stable and long-term expression and multiple-tissue-type infection, etc. These advantages have made AAV one of the most potential vectors in gene therapy, and widely used in many clinical researches, for example, Parkinson's disease. This paper introduces the biological characteristics of AAV and the latest research progress of AAV carrying neurotrophic factor, dopamine synthesis related enzymes and glutamic acid decarboxylase gene in the gene therapy of Parkinson's disease.

Aptamers are capable of binding a wide range of biomolecular targets with high affinity and specificity. It has been widely developed for diagnostic and therapeutic purposes. Because of unique three dimensional structures and cell-membrane penetration, aptamers inhibit virus infection not only through binding specific target, such as the viral envelope, genomic site, enzyme, or other viral components, but also can be connected to each other or with siRNA jointly achieve antiviral activity. Taking human immunodeficiency virus and hepatitis C virus as examples, this paper reviewed the effects and mechanisms of aptamers on disturbing viral infection and replication steps. It may provide an insight to the development of aptamer-based new antiviral drugs.

High mobility group A2 protein (HMGA2), an architectural factor, is highly expressed in various cancer types including lung cancers. It is a candidate target for cancer therapy. RNAi is an effective gene silencing method with low cost and less time-consuming. It is possible to exploit this technology in therapy. Here, 5 siRNAs targeting Hmga2 gene (HMGA2 siRNA1-5) were designed and synthesized. MTT assay, colony formation assay, transwell assay and flow cytometry were used to evaluate the effects of these siRNAs on lung cancer cell lines (NCI-H446 and A549). Results from cell proliferation, clone formation, migration and apoptosis showed that HMGA2 siRNA1, 3, 5 could affect these aspects for both lung cancer cell lines. Among the five siRNAs, HMGA2 siRNA5 showed the greatest inhibition effects. The inhibition effects of HMGA2 siRNA5 are sequence specific and are not due to the induction of interferon response. Taken together, siRNAs targeting Hmga2 gene are potential candidates for lung cancer gene therapy.

Comparative pharmacokinetic (PK) analysis is often carried out throughout the entire period of drug development, the common approach for the assessment of pharmacokinetics between different treatments requires that the individual PK parameters, which employs estimation of 90% confidence intervals for the ratio of average parameters, such as AUC and Cmax, these 90% confidence intervals then need to be compared with the pre-specified equivalent interval, and last we determine whether the two treatments are equivalent. Unfortunately in many clinical circumstances, some or even all of the individuals can only be sparsely sampled, making the individual evaluation difficult by the conventional non-compartmental analysis. In such cases, nonlinear mixed effect model (NONMEM) could be applied to analyze the sparse data. In this article, we simulated a sparsely sampling design trial based on the dense sampling data from a truly comparative PK study. The sparse data were analyzed with NONMEM method, and the original dense data were analyzed with non-compartment analysis. Although the trial design and analysis methods are different, the 90% confidence intervals for the ratio of PK parameters based on 1000 Bootstrap are very similar, indicated that the analysis based on NONMEM is a reliable method to treat with the sparse data in the comparative pharmacokinetic study.

The paper aimed to find the optimal combination and evaluation of the interactions of antitumor effect of the curcumin (Cur) and adriamycin (ADM) in vitro. According to the factorial design and data characteristics, the parameter method combined with the response surface approach were used to analyze the pharmacodynamic interactions of in vitro antitumor effects of the combination of Cur and ADM at different dosages. The results showed that the dose-effect relationship of the combination with the ratio of ADM-Cur 1:3 showed significant differences in comparison with either used alone. The dose-effect curve was shift left in combination. The combination of adriamycin (ADM, 0.693-2.132 micromol L(-1)) and curcumin (Cur, 2.047-6.304 micromol L(-1)) with a fixed ratio (1:3) showed a synergism. With increasing doses of the combination, there is an additive effect. Computer simulation showed a trend of decreasing difference between the observed and expected effects with the dose increasing in Cur from 6.304 to 16.0 micromol L(-1) and ADM from 2.132 to 5.3 micromol L(-1). The response surface analysis showed the optimal combination to be Cur 18.50 micromol L(-1) and ADM 3.89 micromol L(-1) with a ratio of 5:1. This study suggests that the parameter method combined with the response surface analysis provides richer and more reasonable information, and is helpful for quantitative design of drug combination therapy and to describe the nature and degree of drug interaction.