Low Expression of DYRK2 (Dual Specificity Tyrosine Phosphorylation Regulated Kinase 2) Correlates with Poor Prognosis in Colorectal Cancer.

Dual-specificity tyrosine-phosphorylation-regulated kinase 2 (DYRK2) is a member of dual-specificity kinase family, which could phosphorylate both Ser/Thr and Tyr substrates. The role of DYRK2 in human cancer remains controversial. For example, overexpression of DYRK2 predicts a better survival in human non-small cell lung cancer. In contrast, amplification of DYRK2 gene occurs in esophageal/lung adenocarcinoma, implying the role of DYRK2 as a potential oncogene. However, its clinical role in colorectal cancer (CRC) has not been explored. In this study, we analyzed the expression of DYRK2 from Oncomine database and found that DYRK2 level is lower in primary or metastatic CRC compared to adjacent normal colon tissue or non-metastatic CRC, respectively, in 6 colorectal carcinoma data sets. The correlation between DYRK2 expression and clinical outcome in 181 CRC patients was also investigated by real-time PCR and IHC. DYRK2 expression was significantly down-regulated in colorectal cancer tissues compared with adjacent non-tumorous tissues. Functional studies confirmed that DYRK2 inhibited cell invasion and migration in both HCT116 and SW480 cells and functioned as a tumor suppressor in CRC cells. Furthermore, the lower DYRK2 levels were correlated with tumor sites (P = 0.023), advanced clinical stages (P = 0.006) and shorter survival in the advanced clinical stages. Univariate and multivariate analyses indicated that DYRK2 expression was an independent prognostic factor (P < 0.001). Taking all, we concluded that DYRK2 a novel prognostic biomarker of human colorectal cancer

Knockdown of a novel lincRNA AATBC suppresses proliferation and induces apoptosis in bladder cancer

Long intergenic noncoding RNAs (lincRNAs) play important roles in regulating various biological processes in cancer, including proliferation and apoptosis. However, the roles of lincRNAs in bladder cancer remain elusive. In this study, we identified a novel lincRNA, which we termed AATBC. We found that AATBC was overexpressed in bladder cancer patient tissues and positively correlated with tumor grade and pT stage. We also found that inhibition of AATBC resulted in cell proliferation arrest through G1 cell cycle mediated by cyclin D1, CDK4, p18 and phosphorylated Rb. In addition, inhibition of AATBC induced cell apoptosis through the intrinsic apoptosis signaling pathway, as evidenced by the activation of caspase-9 and caspase-3. The investigation for the signaling pathway revealed that the apoptosis following AATBC knockdown was mediated by activation of phosphorylated JNK and suppression of NRF2. Furthermore, JNK inhibitor SP600125 could attenuate the apoptotic effect achieved by AATBC knockdown, confirming the involvement of JNK signaling in the induced apoptosis. Moreover, mouse xenograft model revealed that knockdown of AATBC led to suppress tumorigenesis in vivo. Taken together, our study indicated that AATBC might play a critical role in pro-proliferation and anti-apoptosis in bladder cancer by regulating cell cycle, intrinsic apoptosis signaling, JNK signaling and NRF2. AATBC could be a potential therapeutic target and molecular biomarker for bladder cancer

Additional file 1: of Sleeping Beauty transposon integrates into non-TA dinucleotides

Supplementary tables and figures. (ZIP 3928 kb

A Novel Algorithm to Scheduling Optimization of Melting-Casting Process in Copper Alloy Strip Production

Melting-casting is the first process in copper alloy strip production. The schedule scheme on this process affects the subsequent processes greatly. In this paper, we build the multiobjective model of melting-casting scheduling problem, which considers minimizing the makespan and total weighted earliness and tardiness penalties comprehensively. A novel algorithm, which we called Multiobjective Artificial Bee Colony/Decomposition (MOABC/D) algorithm, is proposed to solve this model. The algorithm combines the framework of Multiobjective Evolutionary Algorithm/Decomposition (MOEA/D) and the neighborhood search strategy of Artificial Bee Colony algorithm. The results on instances show that the proposed MOABC/D algorithm outperforms the other two comparison algorithms both on the distributions of the Pareto front and the priority in the optimal selection results

Research on a resource-constrained project scheduling problem in a hazardous environment and its staffing strategies based on PSO algorithm

We study a resource-constrained project scheduling problem in a hazardous environment considering some different strategies of staffing. An overhaul project of a nuclear power plant is chosen as a typical example. The same as the conventional projects scheduling, the problem is constrained by the availability of resources. However, due to the unique working environment in this project, the availability of resources is constrained by the accumulated amount of harm that the workers could withstand. As this extremely increases the complexity of the problem. In order to address the investigated problem, we propose a novel particle swarm optimization algorithm: probable mechanism-based discrete particle swarm optimization algorithm (PMPSO). The PMPSO algorithm is a discretization form of the traditional particle swarm optimization (PSO) algorithm. We use the PMPSO algorithm to solve the problem thinking of nine combinations of staffing strategies respectively. Comparison experiments of the combination of staffing strategies show that strategy of ‘3’ outperforms the other strategies. Numerical experiments indicate the adaptability of the PMPSO algorithm and the validity of the conclusion

Dual targeting of glioblastoma multiforme with a proteasome inhibitor (Velcade) and a phosphatidylinositol 3-kinase inhibitor (ZSTK474).

Proteasome inhibitors have been proven to be effective anticancer compounds in many tumor models, including glioblastoma multiforme (GBM). In this study, we found that the proteasome inhibitor Velcade (PS-341/bortezomib) caused GBM cell death while simultaneously activating the PI3K/Akt pathway. Therefore, we sought to investigate if the PI3K inhibitor ZSTK474 would enhance the effectiveness of Velcade in anticancer therapy. Two GBM cell lines were used to detect the effects of Velcade and ZSTK474 alone or in combination in vitro. The combination of Velcade and ZSTK474 synergistically inhibited the proliferation of GBM cell lines. Cell apoptosis was increased when exposed to Velcade and ZSTK474 in combination as shown by Annexin V analysis. Treatment with both drugs led to downregulation of the p-Akt, p-4EBP1 and p-mTOR proteins as determined by western blot analysis. The anticancer ability of Velcade for glioblastoma multiforme was, therefore, enhanced by combination with the PI3K pathway inhibitor ZSTK474 in glioblastoma multiforme