Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Analysis of gene expression in esophageal squamous cell carcinoma (ESCC)

ABSTRACT: To characterize gene expression in esophageal squamous cell carcinoma, we examined gene expression in tumor and matched normal adjacent tissue from 17 ESCC patients from a high-risk region of China. RNA was extracted from 17 micro-dissected tumor and matched normal tissue pairs using the PureLink Micro-to-Midi Total RNA Purification System (Invitrogen, Carlsbad, CA) Affymetrix HG-U133A 2.0 gene expression arrays were performed according to the manufacturer's directions. The Robust Multiarray Average (RMA) algorithm implemented in Bioconductor in R was used for background correction and normalization across all samples.

ORGANISM(S): Homo sapiens

SUBMITTER: Robert Clifford

PROVIDER: E-GEOD-20347 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Genome wide analysis of DNA copy number neutral loss of heterozygosity (CNNLOH) and its relation to gene expression in esophageal squamous cell carcinoma.

Hu Nan N Clifford Robert J RJ Yang Howard H HH Wang Chaoyu C Goldstein Alisa M AM Ding Ti T Taylor Philip R PR Lee Maxwell P MP

BMC genomics 20101018

<h4>Background</h4>Genomic instability plays an important role in human cancers. We previously characterized genomic instability in esophageal squamous cell carcinomas (ESCC) in terms of loss of heterozygosity (LOH) and copy number (CN) changes in tumors using the Affymetrix GeneChip Human Mapping 500K array in 30 cases from a high-risk region of China. In the current study we focused on copy number neutral (CN = 2) LOH (CNNLOH) and its relation to gene expression in ESCC.<h4>Results</h4>Overall ...[more]

PMID: 20955586

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Project description:MicroRNAs (miRNAs) are an endogenous conserved class of non-coding 20–22 nt small RNAs that regulate gene expression at post-transcriptional level by mostly binding to 3′-UTR of target mRNAs, leading to mRNA degradation or translation inhibition. Recent reports demonstrate a role for miRNA expression in the disease progression and outcome. By now, many researcher focusing on miRNA expression profiles in Barrett's esophagus and esophageal adenocarcinoma have been reported. Nevertheless, there is still a little information available about specific miRNA expression pattern and their roles in ESCC. To develop novel diagnostic and therapeutic targets for esophageal squamous cancer, we first investigated the expression profile of miRNA in three pairs of ESCC clinical samples. Tissues of ESCC and the matched normal counterparts were obtained from surgical specimens immediately after resection from patients undergoing primary surgical treatment of esophageal carcinoma from the Department of Tumor Surgery of Shantou Central Hospital, China. RNA labeling and hybridization were completed by KangChen Bio-tech Inc. (Shanghai, China) according to the manufacturer's instructions. Briefly, total RNA from three pairs of esophageal carcinoma and matched normal tissues were isolated by Trizol (Invitrogen, USA) and purified by RNeasy mini kit (QIAGEN, German). The concentration and quality of total RNA were measured by NanoDrop ND-1000 at 260 and 280 nm (A260/280) and checked by gel electrophoresis. Each RNA sample from three pairs of ESCC was separately labeled either using the miRCURY Hy3/Hy5 labeling kit and hybridized on the six miRCURYTM locked nucleic acid (LNA) array version 11.0 (Exiqon, Denmark), which contains probes for 1700 mature miRNA. Scans were quantified by using GenePix software (Molecular Devices). The data were exported to Microsoft Excel worksheets, log2 transformed, normalized using global Lowess (Locally Weighted Scatter plot Smoothing) regression algorithm (MIDAS, TIGR Microarray Data Analysis System).

Dataset Information

Analysis of gene expression in esophageal squamous cell carcinoma (ESCC)

Publications

Genome wide analysis of DNA copy number neutral loss of heterozygosity (CNNLOH) and its relation to gene expression in esophageal squamous cell carcinoma.

Similar Datasets

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