Hsa-miR-34b/c rs4938723 T>C and hsa-miR-423 rs6505162 C>A Polymorphisms Are Associated with the Risk of Esophageal Cancer in a Chinese Population

Esophageal cancer is the eighth most common cancer and sixth leading cause of cancer associated death worldwide. Besides environmental risk factors, genetic factors might play an important role in the esophageal cancer carcinogenesis. We conducted a hospital based case–control study to evaluate the genetic susceptibility of functional single nucleotide polymorphisms (SNPs) in the microRNAs on the development of esophageal cancer. A total of 629 esophageal squamous cell carcinoma (ESCC) cases and 686 controls were recruited for this study. The hsa-miR-34b/c rs4938723 T>C, pri-miR-124-1 rs531564 C>G, pre-miR-125a rs12975333 G>T and hsa-miR-423 rs6505162 C>A genotypes were determined using Ligation Detection Reaction (LDR) method. Our results demonstrated that hsa-miR-34b/c rs4938723 CC genotype had a decreased risk of ESCC. The association was evident among patients who never drinking. Hsa-miR-423 rs6505162 C>A might associated with a significantly increased risk of ESCC in patients who smoking. These findings indicated that functional polymorphisms hsa-miR-34b/c rs4938723 T>C and hsa-miR-423 rs6505162 C>A might alter individual susceptibility to ESCC. However, our results were obtained with a limited sample size. Future larger studies with other ethnic populations are required to confirm current findings.     

Genome-Scale Screening of Drug-Target Associations Relevant to Ki Using a Chemogenomics Approach

The identification of interactions between drugs and target proteins plays a key role in genomic drug discovery. In the present study, the quantitative binding affinities of drug-target pairs are differentiated as a measurement to define whether a drug interacts with a protein or not, and then a chemogenomics framework using an unbiased set of general integrated features and random forest (RF) is employed to construct a predictive model which can accurately classify drug-target pairs. The predictability of the model is further investigated and validated by several independent validation sets. The built model is used to predict drug-target associations, some of which were confirmed by comparing experimental data from public biological resources. A drug-target interaction network with high confidence drug-target pairs was also reconstructed. This network provides further insight for the action of drugs and targets. Finally, a web-based server called PreDPI-K_i was developed to predict drug-target interactions for drug discovery. In addition to providing a high-confidence list of drug-target associations for subsequent experimental investigation guidance, these results also contribute to the understanding of drug-target interactions. We can also see that quantitative information of drug-target associations could greatly promote the development of more accurate models. The PreDPI-K_i server is freely available via: http://sdd.whu.edu.cn/dpiki.     

The Embedding Problem for Markov Models of Nucleotide Substitution

Continuous-time Markov processes are often used to model the complex natural phenomenon of sequence evolution. To make the process of sequence evolution tractable, simplifying assumptions are often made about the sequence properties and the underlying process. The validity of one such assumption, time-homogeneity, has never been explored. Violations of this assumption can be found by identifying non-embeddability. A process is non-embeddable if it can not be embedded in a continuous time-homogeneous Markov process. In this study, non-embeddability was demonstrated to exist when modelling sequence evolution with Markov models. Evidence of non-embeddability was found primarily at the third codon position, possibly resulting from changes in mutation rate over time. Outgroup edges and those with a deeper time depth were found to have an increased probability of the underlying process being non-embeddable. Overall, low levels of non-embeddability were detected when examining individual edges of triads across a diverse set of alignments. Subsequent phylogenetic reconstruction analyses demonstrated that non-embeddability could impact on the correct prediction of phylogenies, but at extremely low levels. Despite the existence of non-embeddability, there is minimal evidence of violations of the local time homogeneity assumption and consequently the impact is likely to be minor.     

GPR50 Distribution in the Mouse Cortex and Hippocampus

Neurochemical Research - G protein-coupled receptor 50 (GPR50) belongs to the G protein-coupled receptor which is highly homologous with the sequence of melatonin receptor MT1 and MT2. GPR50...     

Survival analysis for long noncoding RNAs identifies TP53TG1 as an antioncogenic target for the breast cancer

Breast carcinoma is one of the most commonly diagnosed tumors and also one of the deadliest cancers in the female. Long noncoding RNAs (lncRNAs) are emerging as novel targets and biomarkers for breast cancer diagnosis and treatment. In this study, we aimed to study the lncRNAs associated with the outcomes in patients using the breast invasive carcinoma datasets from The Cancer Genome Atlas. The Cox proportional hazards regression model was fitted to each lncRNA. Hierarchy clustering was carried out using these survival-related lncRNAs and the log-rank test was carried out for the clustered groups. DNA methylation status was utilized to identify the lncRNAs regulated by epigenetics. Finally, the coexpressed messenger RNA with the potential lncRNAs were utilized to study the possible functions and mechanisms of lncRNAs. In total, 182 lncRNAs had an impact on the survival time of the patients with a cutoff <0.01. The patients were clustered into three groups using these survival-related genes, which performed significantly different prognosis. Two lncRNAs, which were significantly correlated with the outcomes of breast cancer and were regulated by methylation status, were obtained. These two lncRNAs were TP53TG1 and RP5-1061H20.4. We proposed that TP53TG1 was activated by the wild-type TP53 and performed an impact on the PI3Ks family by binding YBX2 in breast cancer.     

全反式维甲酸协同DAPT抑制胶质瘤干细胞的自我更新

前期研究脑表明,脑胶质瘤干细胞（glioma stem cells,GSCs）是胶质瘤发生和发展的重要因素,探索靶向干预GSCs生长有可能成为脑胶质瘤治疗的有效途径之一。该研究旨在阐明两种药物ATRA和Y-分泌酶抑制剂DAPT协同抑制GSCs自我更新的生物学效应。通过用台盼蓝排染法、克隆球形成试验和免疫印迹分析了两种药物的单独使用或联用对GSC样细胞PGCl和PGC2生长、成球能力和自我更新以及干细胞标志物表达的影响。结果发现,单独使用ATRA对PGCl生长有一定的抑制作用,而对PGC2生长几乎没有影响;DAPT对PGCs的生长抑制作用明显强于ATRA。高浓度ATRA（80μmol/L）能诱导PGCs的分化,降低PGCs成球大小,且成球效率降至5％～8％,而正常对照组为32％～35％;同样,DAPT（40μmol／L）也能降低PGCs成球大小,且成球效率降至2％～3％;低浓度ATRA（20μmol／L）和DAPT（5gmol／L）对PGCs自我更新能力和干性没有明显影响,而联合使用后其明显降低PGCs的成球大小,且成球效率降至3％～5％,促进细胞凋亡,并且明显抑制了干细胞标志物Nestin、CDl33、Sox2、Oct4的表达,提高了分化标志物GFAP的表达。该研究证明了低浓度的ATRA和DAPT能协同抑制脑胶质瘤干细胞PGCs的自我更新。研究结果将为脑胶质瘤的临床研究提供实验依据。     

Capsaicin induces apoptosis in human osteosarcoma cells through AMPK-dependent and AMPK-independent signaling pathways

Recent studies have focused on the anti-tumor activity of capsaicin. However, the potential effects of capsaicin in osteosarcoma cells and the underlying mechanisms are not fully understood. In the current study, we observed that capsaicin-induced growth inhibition and apoptosis in cultured osteosarcoma cells (U2OS and MG63), which were associated with a significant AMP-activated protein kinase (AMPK) activation. AMPK inhibition by compound C or RNA interference suppressed capsaicin-induced cytotoxicity, while AMPK activators (AICAR and A769662) promoted osteosarcoma cell death. For the mechanism study, we found that AMPK activation was required for capsaicin-induced mTORC1 (mTOR complex 1) inhibition, B cell lymphoma 2 (Bcl-2) downregulation and Bax upregulation in MG63 cells. Capsaicin administration induced p53 activation, mitochondrial translocation and Bcl-2 killer association, such effects were dependent on AMPK activation. Interestingly, we observed a significant pro-apoptotic c-Jun NH2-terminal kinases activation by capsaicin in MG63 cells, which appeared to be AMPK independent. In conclusion, capsaicin possessed strong efficacy against human osteosarcoma cells. Molecular studies revealed that capsaicin activated AMPK-dependent and AMPK-independent signalings to mediate cell apoptosis. The results of this study should have significant translational relevance in managing this deadly malignancy.