MicroRNA expression profiling in human Barrett's carcinogenesis
Matteo FassanStefano VoliniaJeff PalatiniMarco PizziRaffaele BaffaMarina de BernardGiorgio BattagliaPaola ParenteCarlo M. CroceGiovanni ZaninottoErmanno AnconaMassimo Rugge
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Abstract:
Abstract Barrett's esophagus (BE) is characterized by the native stratified squamous epithelium (N) lining the esophagus being replaced by a columnar epithelium with intestinal differentiation (Barrett's mucosa; BM). BM is considered as the main risk factor for esophageal adenocarcinoma (Barrett's adenocarcinoma; BAc). MicroRNAs (miRNAs) are a class of small noncoding RNAs that control gene expression by targeting messenger RNAs and they are reportedly dysregulated in BM. To test the hypothesis that a specific miRNA expression signature characterizes BM development and progression, we performed miRNA microarray analysis comparing native esophageal mucosa with all the phenotypic lesions seen in the Barrett's carcinogenic process. Specimens were collected from 14 BE patients who had undergone esophagectomy, including: 14 with N, 14 with BM, 7 with low‐grade intraepithelial neoplasia, 5 with high‐grade intra‐epithelial neoplasia and 11 with BAc. Microarray findings were further validated by quantitive real‐time polymerase chain reaction and in situ hybridization analyses using a different series of consecutive cases (162 biopsy samples and 5 esophagectomies) of histologically proven, long‐segment BE. We identified a miRNA signature of Barrett's carcinogenesis consisting of an increased expression of 6 miRNAs and a reduced expression of 7 miRNAs. To further support these results, we investigated target gene expression using the Oncomine database and/or immunohistochemical analysis. We found that target gene expression correlated significantly with miRNA dysregulation. Specific miRNAs are directly involved in BE progression to cancer. miRNA profiling significantly expands current knowledge on the molecular history of Barrett's carcinogenesis, also identifying molecular markers of cancer progression.Keywords:
Barrett's esophagus
Microarray can parallel quantification of large numbers of genes and promises to provide detailed insight into cellular processes involved in the regulation of gene expression. In plants, microarray for gene expression profiling should provide an important way for understanding of gene functions and signaling networks that operate plants growth and development, respond to biotic and abiotic stresses, important agronomic characters. This review focuses on the application of microarray for gene expression profiling in plants. Moreover, development and application of tobacco microarray is also summarized. This review will provide useful information for better application of plant microarray in studies of gene function and regulation mechanism.
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This study aimed to use gene chips to investigate differential gene expression profiles in the occurrence and development of acute myocardial infarction (AMI). The study included 12 AMI patients and 12 healthy individuals. Total mRNA of peripheral bloodwas extracted and reversed-transcribed to cDNA for microarray analysis. After establishing two pools with three subjects each (3 AMI patients and 3 healthy individuals), the remaining samples were used for RT-qPCR to confirm the microarray data. From the microarray results, seven genes were randomly selected for RT-qPCR. RT-qPCR results were analyzed by the 2-ΔΔCt method. Microarray analysis showed that 228 genes were up- regulated and 271 were down-regulated (p ≤ 0.05, |logFC| > 1). Gene ontology showed that these genes belong to 128 cellular components, 521 biological processes, and 151 molecular functions. KEGG pathway analysis showed that these genes are involved in 107 gene pathways. RT-qPCR results for the seven genes showed expression levels consistent with those obtained by microarray. Thus, microarray data could be used to select the pathogenic genes for AMI. Investigating the abnormal expression of these differentially expressed genes might suggest efficient strategies for the prevention, diagnosis, and treatment of AMI.
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Murine transplantation models are used extensively to research immunological rejection and tolerance. Here we studied both murine heart and liver allograft models using microarray technology. We had difficulty in identifying genes related to acute rejections expressed in both heart and liver transplantation models using two standard methodologies: Student's t test and linear models for microarray data (Limma). Here we describe a new method, standardized fold change (SFC), for differential analysis of microarray data. We estimated the performance of SFC, the t test and Limma by generating simulated microarray data 100 times. SFC performed better than the t test and showed a higher sensitivity than Limma where there is a larger value for fold change of expression. SFC gave better reproducibility than Limma and the t test with real experimental data from the MicroArray Quality Control platform and expression data from a mouse cardiac allograft. Eventually, a group of significant overlapping genes was detected by SFC in the expression data of mouse cardiac and hepatic allografts and further validated with the quantitative RT-PCR assay. The group included genes for important reactions of transplantation rejection and revealed functional changes of the immune system in both heart and liver of the mouse model. We suggest that SFC can be utilized to stably and effectively detect differential gene expression and to explore microarray data in further studies.
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