ABSTRACT
Aim To explore the inhibitory effect of lenvatinib plus fluvastatin on liver transplantation tumor in mice and the mechanism.Methods Mouse model of subcutaneous liver cancer was used.Single agent of lenvatinib, single agent of fluvastatin, a combination of lenvatinib and fluvastatin and control solvent were given to four groups of mice.Tumor volume was measured.Immunohistochemistry was used to examine proliferation of tumor cells.Tunel was employed to detect the cell apoptosis.qRT-PCR and immunohistochemistry were used to measure the expression of TLR4.Western blot was employed to determine β-catenin expression.Rescue experiment was done using human hepatoma cells cultured in vitro.Results Treatment with both lenvatinib and fluvastatin significantly suppressed tumor growth in nude mice.Combined treatment significantly decreased the expressions of PNCA and increased apoptosis in tumor cells.Mechanically combined treatment synergistically suppressed the mRNA and protein expression of TLR4 which further inhibited the expression of β-catenin in hepatoma cells.Conclusions A combination of lenvatinib and fluvastatin synergistically inhibits tumor growth and promotes tumor cell apoptosis.The combination treatment significantly inhibits TLR4/β-catenin signaling pathway.
ABSTRACT
OBJECTIVE@#To establish a compact and efficient hypergraph representation and a graph-similarity-based retrieval method of molecules to achieve effective and efficient medicine information retrieval.@*METHODS@#Chemical structural formula (CSF) was a primary search target as a unique and precise identifier for each compound at the molecular level in the research field of medicine information retrieval. To retrieve medicine information effectively and efficiently, a complete workflow of the graph-based CSF retrieval system was introduced. This system accepted the photos taken from smartphones and the sketches drawn on tablet personal computers as CSF inputs, and formalized the CSFs with the corresponding graphs. Then this paper proposed a compact and efficient hypergraph representation for molecules on the basis of analyzing factors that directly affected the efficiency of graph matching. According to the characteristics of CSFs, a hierarchical collapsing method combining graph isomorphism and frequent subgraph mining was adopted. There was yet a fundamental challenge, subgraph overlapping during the collapsing procedure, which hindered the method from establishing the correct compact hypergraph of an original CSF graph. Therefore, a graph-isomorphism-based algorithm was proposed to select dominant acyclic subgraphs on the basis of overlapping analysis. Finally, the spatial similarity among graphical CSFs was evaluated by multi-dimensional measures of similarity.@*RESULTS@#To evaluate the performance of the proposed method, the proposed system was firstly compared with Wikipedia Chemical Structure Explorer (WCSE), the state-of-the-art system that allowed CSF similarity searching within Wikipedia molecules dataset, on retrieval accuracy. The system achieved higher values on mean average precision, discounted cumulative gain, rank-biased precision, and expected reciprocal rank than WCSE from the top-2 to the top-10 retrieved results. Specifically, the system achieved 10%, 1.41, 6.42%, and 1.32% higher than WCSE on these metrics for top-10 retrieval results, respectively. Moreover, several retrieval cases were presented to intuitively compare with WCSE. The results of the above comparative study demonstrated that the proposed method outperformed the existing method with regard to accuracy and effectiveness.@*CONCLUSION@#This paper proposes a graph-similarity-based retrieval approach for medicine information. To obtain satisfactory retrieval results, an isomorphism-based algorithm is proposed for dominant subgraph selection based on the subgraph overlapping analysis, as well as an effective and efficient hypergraph representation of molecules. Experiment results demonstrate the effectiveness of the proposed approach.
Subject(s)
Algorithms , Databases, Chemical , Information Storage and Retrieval , Molecular StructureABSTRACT
<p><b>OBJECTIVE</b>This study aimed to investigate the effects of gene polymorphism of heat shock protein 70-2 (HSP 70-2) 1267A/G on the mRNA level HSP 70-2 mRNA and the protein level HSP 70 in human lung cancer.</p><p><b>METHODS</b>Forty six lung cancer patients diagnosed histopathologically between February and August 2008 from a hospital in zhengzhou were enrolled as the subjects in this study. Gene polymorphism of HSP 70-2 1276A/G in 46 patients with lung cancer was detected by PCR-RFLP. The mRNA levels of HSP 70-2 mRNA and the protein levels of HSP 70 in lung tissue and para-cancerous tissues of these subjects were determined by RT-PCR and Western blotting respectively.</p><p><b>RESULTS</b>The expression levels of HSP 70-2 mRNA (1.02 ± 0.30) and HSP 70 protein (0.44 ± 0.12) in the lung cancer tissues was significantly higher than that in para-cancerous tissues (0.19 ± 0.04, 0.12 ± 0.02). The relative levels of HSP 70-2 mRNA in the subjects with AA genotype (1.32 ± 0.22) were significantly higher than the patients with AG genotype or GG genotype (0.95 ± 0.17, 0.70 ± 0.16) at the site of 1267 (A/G) (P < 0.01); however, the relative protein levels of HSP 70 were 0.47 ± 0.13 (AA genotype), 0.42 ± 0.11 (AG genotype), 0.45 ± 0.11 (GG genotype), respectively, which showed no statistically significant difference (P > 0.05).</p><p><b>CONCLUSION</b>The polymorphism of HSP 70-2 1267 (A/G) is highly associated with the transcription level of HSP 70-2 mRNA, but not with the expression level of HSP 70 protein.</p>