Identification of key pathways and genes in Barrett's esophagus using integrated bioinformatics methods
MOLECULAR MEDICINE REPORTS
Authors: Zhang, Cong; Shen, Yujie; Wang, Jiazheng; Zhou, Mingxia; Chen, Yingwei
Abstract
Barrett's esophagus (BE) is a premalignant lesion of esophageal adenocarcinoma. The aim of the present study was to investigate the possible mechanisms and biomarkers of BE. To identify the differentially expressed microRNAs (DEmiRNAs) and genes (DEGs) in BE, the miRNA expression profile GSE20099 and the gene expression profiles GSE26886, GSE13083 and GSE34619 were obtained from the Gene Expression Omnibus (GEO) database. DEGs and DEmiRNAs were screened for using the GEO2R tool. Using DAVID, functional and pathway enrichment analysis was performed to explore the biological function of identified DEGs. The protein-protein interaction (PPI) network was detected using STRING and constructed by Cytoscape software. Furthermore, targets of identified DEmiRNAs were predicted by the miRecords database, then integrated with the identified DEGs to obtain key genes involved in BE. In total, 311 DEGs were identified. These genes were significantly enriched in the pancreatic secretion, metabolic pathways and cytochrome P450 drug metabolism pathways. In the PPI network, 16 hub genes, including keratin 16, cystic fibrosis transmembrane conductance regulator, involucrin, protein kinase C and cadherin 17 were identified. Following integration of the predicted target genes of DEmiRNAs with DEGs, three key BE genes were identified: PRKCA, CDH17 and epiregulin. In conclusion, a comprehensive bioinformatics analysis of identified DEGs and DEmiRNAs was performed to elucidate potential pathways and biomarkers involved in the development of BE.
Search for new biomarkers of gastric cancer through serial analysis of gene expression and its clinical implications
CANCER SCIENCE
Authors: Yasui, W; Oue, N; Ito, R; Kuraoka, K; Nakayama, H
Abstract
Gastric cancer is one of the most common human cancers and is the second most frequent cause of cancer-related death in the world. Serial analysis of gene expression (SAGE) is a powerful technique to allow genome-wide analysis of gene expression in a quantitative manner without prior knowledge of the gene sequences. SAGE on 5 samples of gastric cancer with different histology and clinical stages have created large SAGE libraries of gastric cancer that enable us to identify new cancer biomarkers. Commonly up-regulated genes in gastric cancer in comparison with normal gastric epithelia included CEACAM6, APOC1 and YF13H12. By comparing gene expression profiles of gastric cancers at early and advanced stages, several genes differentially expressed by tumor stage were also identified, including FUS, CDH17, COL1A1 and COL(1)A(2), which should be novel genetic markers for high-grade malignancy. Regenerating gene type IV (REGIV) is one of the most up-regulated genes in a SAGE library of a scirrhous-type gastric cancer. In vitro studies using RegIV-transfected cells revealed that RegIV is secreted by cancer cells and inhibits apoptosis, suggesting that RegIV may serve as a novel biomarker and therapeutic target for gastric cancer. Production of RNA aptamers could be a useful approach to establish a detection system in blood. A custom-made array, named Ex-STO-MACHIP, consisting of 395 genes, including highly differentially expressed genes identified by our SAGE and other known genes related to carcinogenesis and chemosensitivity, is useful to study the molecular pathogenesis of gastric cancer and to obtain information about biological behavior and sensitivity to therapy in the clinical setting. Combined analyses of gene expression profile, genetic polymorphism and genetic instability will aid not only cancer detection, but also characterization of individual cancers and patients, leading to personalized medicine and cancer prevention.