Dataset Information

Application of unique sequence index (USI) barcode to gene expression profiling in gastric adenocarcinoma.

ABSTRACT: Accurate expression profiling is imperative for understanding the biological roles of mRNAs. Real-time PCR have been at the forefront of biological innovation in detection and monitoring of gene expression, however, fluorophore-labeled oligonucleotides and double-stranded DNA binding dyes, the two most frequently used dyes in RNA detection, are not very cost effective and have poor specificity, respectively. We have developed a cost effective and specific approach for mRNA expression profiling via added unique sequence index (USI) to cDNAs before amplification. USI is a barcode which enable the detection of each target RNA. Using this method, caudal type homeobox 1 (CDX1) and FAT atypical cadherin 4 (FAT4) expressions were investigated in tumoral and non-tumoral tissues of gastric cancer patients and compared with commercial ABI kit. Both methods indicated that FAT4 and CDX1 expression were significantly reduced in gastric cancer tissues compared with adjacent noncancerous tissues. Moreover, we have shown that this assay is highly sensitive, linear and reproducible. USI barcode not only provides a powerful tool for mRNA detection due to its sensitivity, specificity and cost-effectiveness, but also allows comfortable design for real-time qPCR assays within the least time and empowers the analysis of many transcripts of virtually any organism. Furthermore, USI barcode is highly affordable for large numbers of different samples or small sample sizes without microarray and expensive commercial platforms.

SUBMITTER: Fattahi S

PROVIDER: S-EPMC5362579 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Application of unique sequence index (USI) barcode to gene expression profiling in gastric adenocarcinoma.

Fattahi Sadegh S Pilehchian Langroudi Maryam M Samadani Ali Akbar AA Nikbakhsh Novin N Asouri Mohsen M Akhavan-Niaki Haleh H

Journal of cell communication and signaling 20170124 1

Accurate expression profiling is imperative for understanding the biological roles of mRNAs. Real-time PCR have been at the forefront of biological innovation in detection and monitoring of gene expression, however, fluorophore-labeled oligonucleotides and double-stranded DNA binding dyes, the two most frequently used dyes in RNA detection, are not very cost effective and have poor specificity, respectively. We have developed a cost effective and specific approach for mRNA expression profiling v ...[more]

PMID: 28120184

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Project description:In the present study, gene expression profiles were analyzed to identify the molecular mechanisms underlying gastric cardia adenocarcinoma (GCA) and gastric non-cardia adenocarcinoma (GNCA). A gene expression dataset (accession number GSE29272) was downloaded from Gene Expression Omnibus, and consisted of 62 GCA samples and 62 normal controls, as well as 72 GNCA samples and 72 normal controls. The two groups of differentially-expressed genes (DEGs) were compared to obtain common and unique DEGs. A differential analysis was performed using the Linear Models for Microarray Data package in R. Functional enrichment analysis was conducted for the DEGs using the Database for Annotation, Visualization and Integrated Discovery. Protein-protein interaction (PPI) networks were constructed for the DEGs with information from the Search Tool for the Retrieval of Interacting Genes. Subnetworks were extracted from the whole network with Cytoscape. Compared with the control, 284 and 268 genes were differentially-expressed in GCA and GNCA, respectively, of which 194 DEGs were common between GCA and GNCA. Common DEGs [e.g., claudin (CLDN)7, CLDN4 and CLDN3] were associated with cell adhesion and digestion. GCA-unique DEGs [e.g., MAD1 mitotic arrest deficient like 1, cyclin (CCN)B1, CCNB2 and CCNE1] were associated with the cell cycle and the regulation of cell proliferation, while GNCA-unique DEGs (e.g., GATA binding protein 6 and hyaluronoglucosaminidase 1) were implicated in cell death. A PPI network with 141 nodes and 446 edges were obtained, from which two subnetworks were extracted. Genes [e.g., fibronectin 1, collagen type I ?2 chain (COL1A2) and COL1A1] from the two subnetworks were implicated in extracellular matrix organization. These common DEGs could advance our understanding of the etiology of gastric cancer, while the unique DEGs in GCA and GNCA could better define the properties of specific cancers and provide potential biomarkers for diagnosis, prognosis or therapy.

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Dataset Information

Application of unique sequence index (USI) barcode to gene expression profiling in gastric adenocarcinoma.

Publications

Application of unique sequence index (USI) barcode to gene expression profiling in gastric adenocarcinoma.

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