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Expression data of gastric cancer by conventional microarray and by suppressive subtractive hybridization coupled to microarray

ABSTRACT: Transcriptional profiling of gastric tumors compared to paired adjacent non-tumoral gastric tissue by two strategies. The first strategy is a conventional microarray assay, while the second strategy involves a previous Suppression Subtractive Hybridization (SSH) followed by a conventional microarray assay. We applied subtractive hybridization followed by microarray analysis to identify tumor-specific low-abundance transcripts. The goal was to determine differences in gene expression profile in tumor samples by both strategies.

ORGANISM(S): Homo sapiens

PROVIDER: GSE38932 | GEO | 2012/06/27

SECONDARY ACCESSION(S): PRJNA169536

REPOSITORIES: GEO

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Expression data of gastric cancer by conventional microarray and by suppressive subtractive hybridization coupled to microarray

Project description:Transcriptional profiling of gastric tumors compared to paired adjacent non-tumoral gastric tissue by two strategies. The first strategy is a conventional microarray assay, while the second strategy involves a previous Suppression Subtractive Hybridization (SSH) followed by a conventional microarray assay. We applied subtractive hybridization followed by microarray analysis to identify tumor-specific low-abundance transcripts. The goal was to determine differences in gene expression profile in tumor samples by both strategies. Two-condition experiment: tumoral vs. adjacent non-tumoral tissues. Biological replicates: 12 tumoral replicates, 12 non-tumoral replicates. The same replicates were used for both strategies (conventional, SSH). Human Universal Reference RNA (Clontech) was used as the reference.

2012-06-26 | E-GEOD-38932 | biostudies-arrayexpress

Expression data of colon cancer by conventional microarray and by suppressive subtractive hybridization coupled to microarray

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Expression data of colon cancer by conventional microarray and by suppressive subtractive hybridization coupled to microarray

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Gene expression data from advanced gastric and colon cancers: tumoral vs. matched non-tumoral tissues

Project description:This SuperSeries is composed of the following subset Series: GSE38932: Expression data of gastric cancer by conventional microarray and by suppressive subtractive hybridization coupled to microarray GSE38939: Expression data of colon cancer by conventional microarray and by suppressive subtractive hybridization coupled to microarray Refer to individual Series

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Homo sapiens

Project description:Expression data of gastric cancer by conventional microarray and by suppressive subtractive hybridization coupled to microarray

| PRJNA169536 | ENA

Identification of salt stress regulated genes in tomato seedlings by SSH and microarray analysis

Project description:High salinity is one of the most serious threats to crop production. To 1 better understand the molecular basis of plant responses to salt stress, we combined suppression subtractive hybridization (SSH) and microarray approaches to identify the potential important or novel genes involved in salt tolerance. First, SSH libraries were constructed for two cultivated tomato (Solanum lycopersicum) genotypes: LA2711, a salt tolerant cultivar, and ZS-5, a salt sensitive cultivar, to compare salt treatment and non-treatment plants. Then a subset of clones from these SSH libraries were used to construct a tomato cDNA array and microarray analysis was carried out to verify the expression changes of this set of clones upon salt treatment at various time points compared to the corresponding non-treatment controls. A totalof 201 non-redundant genes differentially expressed upon 30 min of salt stress treatment either in LA2711 or ZS-5 were identified from microarray analysis, most of which were not previously associated with salt stress. The diversity of the putative functions of these genes indicated that salt stress resulted in a complex response in tomato plants. Keywords: gene expression, genotype, microarray, salt stress, SSH, tomato

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Stomach ECL cell expression analysis

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