Gastric cancer is one of the most common carcinomas in China. microRNAs, a type of non-coding RNA, are important specific regulators and are involved in numerous bioprocesses of an organism. microRNA-21 (miR-21) has been identified as the most suitable choice for further investigation because it is overexpressed in nearly all solid tumors; furthermore, it has been demonstrated that miR-21 is involved in the genesis and progression of human cancer. It has been reported that PTEN, an important tumour suppressor, is regulated by multiple miRNAs. Thus, in this study we focused on the expression and significance of miR-21 in gastric cancer tissues, and the role of miR-21 in the biological behaviour and the expression of PTEN in gastric cancer cells. Real-time PCR was used to detect miR-21 expression in gastric cancer tissues, the adjacent normal tissues, and the gastric cell lines. The gastric cancer cell line BGC-823 was transfected with pre-miR-21/miR-21 inhibitor to overexpress/downregulate miR-21. The influence of miR-21 on the biological behaviour of gastric cancer cells was evaluated using the CCK-8 kit, FCMs, the scratch healing assay and the transwell test. Western blotting and the Luciferase Reporter Assay were used to evaluate the change of PTEN expression after lowered expression of miR-21 in gastric cancer cell lines. Real-time PCR analysis indicated that miR-21 exhibited higher expression in gastric cancer tissues compared to the adjacent non-tumor tissues. miR-21 expression was significantly associated with the degree of differentiation of the tumour tissues (P=0.004), as well as local invasion and lymph node metastasis (P<0.01). After transfection, pre-miR21 BGC-823 cells grew faster than the negative and control groups (P<0.01). The reduction in miR-21 expression demonstrated a remarkable effect on the biological behaviour of gastric cancer cells (P<0.05); the pre-miR-21-transfected cells healed more quickly compared to the control cells in the scratch healing assay, whereas the transwell test indicated that cell migration in vitro was notably inhibited with the downregulation of miR-21 (P<0.05). The western blot results and Luciferase Reporter Assay demonstrated that PTEN expression was remarkably increased after miR-21 inhibition (P<0.05). microRNA-21 expression was upregulated in gastric carcinoma tissues and was significantly associated with the degree of differentiation of tumour tissues, local invasion and lymph node metastasis. Overexpression of miR-21 promoted BGC-823 cell growth, invasion and cell migration in vitro, whereas downregulation of miR-21 exhibited a stronger inhibitory effect on the biological behaviour of gastric cancer cells; additionally, miR-21 inhibition may upregulate the PTEN expression level, which indicates that PTEN may be a target gene for gastric cancer initiation and development.
In this paper, we define and study a novel text mining problem, which we refer to as comparative text mining. Given a set of comparable text collections, the task of comparative text mining is to discover any latent common themes across all collections as well as summarize the similarity and differences of these collections along each common theme. This general problem subsumes many interesting applications, including business intelligence, summarizing reviews of similar products, and comparing different opinions about a common topic. We propose a generative probabilistic mixture model for comparative text mining. The model simultaneously performs cross-collection clustering and within-collection clustering, and can be applied to an arbitrary set of comparable text collections. The model can be estimated efficiently using the Expectation-Maximization (EM) algorithm. We evaluate the model on two different text data sets (i.e., a news article data set and a laptop review data set), and compare it with a baseline clustering method also based on a mixture model. Experiment results show that the model is quite effective in discovering the latent common themes across collections and performs significantly better than our baseline mixture model.
Conditional functional dependencies (CFDs) have recently been proposed as a useful integrity constraint to summarize data semantics and identify data inconsistencies. A CFD augments a functional dependency (FD) with a pattern tableau that defines the context (i.e., the subset of tuples) in which the underlying FD holds. While many aspects of CFDs have been studied, including static analysis and detecting and repairing violations, there has not been prior work on generating pattern tableaux, which is critical to realize the full potential of CFDs.This paper is the first to formally characterize a "good" pattern tableau, based on naturally desirable properties of support, confidence and parsimony. We show that the problem of generating an optimal tableau for a given FD is NP-complete but can be approximated in polynomial time via a greedy algorithm. For large data sets, we propose an "on-demand" algorithm providing the same approximation bound, that outperforms the basic greedy algorithm in running time by an order of magnitude. For ordered attributes, we propose the range tableau as a generalization of a pattern tableau, which can achieve even more parsimony. The effectiveness and efficiency of our techniques are experimentally demonstrated on real data.
Tumor initiation and growth depend on its microenvironment in which cancer-associated fibroblasts (CAFs) in tumor stroma play an important role. Prostaglandin E2 (PGE2) and interleukin (IL)-6 signal pathways are involved in the crosstalk between tumor and stromal cells. However, how PGE2-mediated signaling modulates this crosstalk remains unclear. Here, we show that microRNA (miR)-149 links PGE2 and IL-6 signaling in mediating the crosstalk between tumor cells and CAFs in gastric cancer (GC). miR-149 inhibited fibroblast activation by targeting IL-6 and miR-149 expression was substantially suppressed in the CAFs of GC. miR-149 negatively regulated CAFs and their effect on GC development both in vitro and in vivo. CAFs enhanced epithelial-to-mesenchymal transition (EMT) and the stem-like properties of GC cells in a miR-149-IL-6-dependent manner. In addition to IL-6, PGE2 receptor 2 (PTGER2/EP2) was revealed as another potential target of miR-149 in fibroblasts. Furthermore, H. pylori infection, a leading cause of human GC, was able to induce cyclooxygenase-2 (COX-2)/PGE2 signaling and to enhance PGE2 production, resulting in the hypermethylation of miR-149 in CAFs and increased IL-6 secretion. Our findings indicate that miR-149 mediates the crosstalk between tumor cells and CAFs in GC and highlight the potential of interfering miRNAs in stromal cells to improve cancer therapy.
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