No abstract

No abstract

Background Pancreatic cancer is one of the most common malignant cancers worldwide. Currently, the pathogenesis of pancreatic cancer remains unclear; thus, it is necessary to explore its precise molecular mechanisms. Methods To identify candidate genes involved in the tumorigenesis and proliferation of pancreatic cancer, the microarray datasets GSE32676, GSE15471 and GSE71989 were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between Pancreatic ductal adenocarcinoma (PDAC) and nonmalignant samples were screened by GEO2R. The Database for Annotation Visualization and Integrated Discovery (DAVID) online tool was used to obtain a synthetic set of functional annotation information for the DEGs. A PPI network of the DEGs was established using the Search Tool for the Retrieval of Interacting Genes (STRING) database, and a combination of more than 0.4 was considered statistically significant for the PPI. Subsequently, we visualized the PPI network using Cytoscape. Functional module analysis was then performed using Molecular Complex Detection (MCODE). Genes with a degree ≥10 were chosen as hub genes, and pathways of the hub genes were visualized using ClueGO and CluePedia. Additionally, GenCLiP 2.0 was used to explore interactions of hub genes. The Literature Mining Gene Networks module was applied to explore the cocitation of hub genes. The Cytoscape plugin iRegulon was employed to analyze transcription factors regulating the hub genes. Furthermore, the expression levels of the 13 hub genes in pancreatic cancer tissues and normal samples were validated using the Gene Expression Profiling Interactive Analysis (GEPIA) platform. Moreover, overall survival and disease-free survival analyses according to the expression of hub genes were performed using Kaplan-Meier curve analysis in the cBioPortal online platform. The relationship between expression level and tumor grade was analyzed using the online database Oncomine. Lastly, the eight snap-frozen tumorous and adjacent noncancerous adjacent tissues of pancreatic cancer patients used to detect the CDK1 and CEP55 protein levels by western blot. Conclusions Altogether, the DEGs and hub genes identified in this work can help uncover the molecular mechanisms underlying the tumorigenesis of pancreatic cancer and provide potential targets for the diagnosis and treatment of this disease.

There were inconsistent results with respect to the correlation between consumption of wine and the development of colorectal cancer (CRC). We carried out a meta-analysis to investigate this issue. We included observational studies on the aforementioned relationship according to a literature search of Embase and Pubmed from inception till 28 February 2017. The summary relative risk (SRR) and 95% confidence intervals (CI) were calculated using a random-effects model. A total of eight case–control and nine cohort studies were identified, involving 12 110 CRC cases. The study showed that wine drinking was not associated with any greater risk for CRC (SRR=0.99, 95% CI: 0.89–1.10; P heterogeneity<0.001) compared with nondrinkers. The subgroup analyses indicated that null associations were observed in men and women for colon and rectal cancer. Neither light to moderate (<2 drinks/day; SRR=0.93, 95% CI: 0.80–1.08, I 2 =69.2%) nor heavy (≥2 drinks/day; SRR=1.00, 95% CI: 0.86–1.16, I 2 =39.9%) consumption of wine was associated statistically with CRC risk. This meta-analysis suggests that any wine consumption was not associated with the risk of CRC. Null associations were shown in men and women for colon and rectal cancer.

No abstract