Using Prognosis-Related Gene Expression Signature and Connectivity Map for Personalized Drug Repositioning in Multiple Myeloma.

BACKGROUND Multiple myeloma (MM) is the second most common hematologic cancer with poor prognosis. Novel therapeutic strategies are needed to decrease the high mortality rate. The aim of this study was to identify prospective agents for MM. MATERIAL AND METHODS A microarray dataset was mined, which contains the transcriptome profiles of 588 MM patients. Univariate Cox analysis was performed to analyze the relationships between genes and clinical outcome. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were determined. Protective and risky genes were uploaded to Connectivity Map (CMAP) database to identify the potentially unknown effects of existing drugs. An example was selected to be docked on the known molecules. RESULTS A total of 1445 genes significantly correlated with the event free survival (EFS) of MM patients were identified and included 676 protective and 769 risky indicators. KEGG pathway analysis revealed that these prognosis-associated genes were enriched in the "cell cycle," "DNA replication," and "P53 signaling pathway". The top t3 most significant potential molecules were vorinostat, trifluoperazine, and thioridazine. CDK1 (cyclin-dependent kinase-1) ranked as the core in the class of prognosis-related genes in MM based on protein-protein interaction (PPI) network analysis. With Sybyl-X 2.0, the majority of the top 10 molecules aforementioned displayed high binding forces with CDK1. Among these molecules, trichostatin A had the greatest ability in combining with CDK1. CONCLUSIONS Genes that mainly accumulate in the cell cycle pathway play an essential role in the prognosis of MM, and these prognosis-related genes also have great value in drug development.

[The Use of FTIR Coupled with Partial Least Square for Quantitative Analysis of the Main Composition of Bamboo/Polypropylene Composites].

The biomass to plastic ratio in wood plastic composites (WPCs) greatly affects the physical and mechanical properties and price. Fast and accurate evaluation of the biomass to plastic ratio is important for the further development of WPCs. Quantitative analysis of the WPC main composition currently relies primarily on thermo-analytical methods. However, these methods have some inherent disadvantages, including time-consuming, high analytical errors and sophisticated, which severely limits the applications of these techniques. Therefore, in this study, Fourier Transform Infrared (FTIR) spectroscopy in combination with partial least square (PLS) has been used for rapid prediction of bamboo and polypropylene (PP) content in bamboo/PP composites. The bamboo powders were used as filler after being dried at 105 degrees C for 24 h. PP was used as matrix materials, and some chemical regents were used as additives. Then 42 WPC samples with different ratios of bamboo and PP were prepared by the methods of extrusion. FTIR spectral data of 42 WPC samples were collected by means of KBr pellets technique. The model for bamboo and PP content prediction was developed by PLS-2 and full cross validation. Results of internal cross validation showed that the first derivative spectra in the range of 1 800-800 cm(-1) corrected by standard normal variate (SNV) yielded the optimal model. For both bamboo and PP calibration, the coefficients of determination (R2) were 0.955. The standard errors of calibration (SEC) were 1.872 for bamboo content and 1.848 for PP content, respectively. For both bamboo and PP validation, the R2 values were 0.950. The standard errors of cross validation (SECV) were 1.927 for bamboo content and 1.950 for PP content, respectively. And the ratios of performance to deviation (RPD) were 4.45 for both biomass and PP examinations. The results of external validation showed that the relative prediction deviations for both biomass and PP contents were lower than ± 6%. FTIR combined with PLS can be used for rapid and accurate determination of bamboo and PP content in bamboo/PP composites.

Bone marrow plasma macrophage inflammatory protein protein-1 alpha(MIP-1 alpha) and sclerostin in multiple myeloma: relationship with bone disease and clinical characteristics.

The aim of the study was to investigate the expression of MIP-1 alpha and sclerostin in bone marrow of patients with multiple myeloma (MM), the possible association of the sclerostin and MIP-1 alpha with MBD and the clinical characteristics. 53 patients (29 M, 24 F), median age 64 years was studied. MIP-1 alpha, sclerostin and bone-specific alkaline phosphatase (bALP) levels were quantified using an enzyme-linked immunosorbent assay (ELISA). Sclerostin and MIP-1 alpha mRNA expression was determined by RT-PCR. PTH and 1,25(OH) 2D3 levels were measured with an electrochemiluminescence immunoassay. The sclerostin and MIP-1 alpha concentrations in patients with MM were higher than those in the controls. RT-PCR analysis verified that the bone marrow mononuclear cells (BMMNCs) of most patients showed sclerostin and MIP-1 alpha mRNA expression. The sclerostin and MIP-1 alpha levels in patients with ISS stage III disease were significantly higher than those in patients with ISS stage II disease (p=0.01 and 0.06). The sclerostin and MIP-1 alpha levels in patients with BMD in group C were significantly higher than those in group A+B. There was positive correlation between sclerostin levels and MIP-1 alpha, beta2-microglobulin and aCa levels. A negative association was seen between sclerostin levels and bALP, HB and ALB levels. The MM patients with high sclerostin levels (>0.72 ng/ml) had significantly shorter median survival than those with low sclerostin levels (≤0.72 ng/ml) (χ(2)=7.574, p=0.006). Our findings support the positive relationship between sclerostin levels and MIP-1alpha levels deserve further detailed research.