Project description:Gastric cancers account for the fourth most frequent cancer death worldwide. Although many differential gene expression profiles are reported for gastric cancers, their variation at the post-transcriptional level has not been provided yet. In this study, we compared the gene expressions of normal stomach vs. stomach cancer in an exon-wise manner and compared alternatively spliced transcripts. The RNA from normal and cancer tissues of gastric cancer patients were subjected to Exon 1.0 ST microarrays. Transcriptome analysis of RNAs from normal and cancer tissues of human stomach by exon array. We analyzed 30 pairs of normal-cancer stomach tissues using the Affymetrix Human Exon 1.0 ST platform. Array data was processed by the Affymetrix Exon Array Computational Tool.
Project description:Gastric cancers account for the fourth most frequent cancer death worldwide. Although many differential gene expression profiles are reported for gastric cancers, their variation at the post-transcriptional level has not been provided yet. In this study, we compared the gene expressions of normal stomach vs. stomach cancer in an exon-wise manner and compared alternatively spliced transcripts. The RNA from normal and cancer tissues of gastric cancer patients were subjected to Exon 1.0 ST microarrays.
Project description:MicroRNA (miRNA) expression profiles for gastric cancers were examined to investigate the miRNA involvement in stomach carcinogenesis. miRNA microarray analysis identified statistical unique profiles, which could discriminate stomach cancers from noncancerous stomach tissues.
Project description:Gene expression profiling of apparently normal gastric tissue (obtained from patients undergoing gastric surgery for Non-gastric cancers), paired normals (obtained from the same stomach as the gastric cancer but confirmed by frozen section not to harbour any tumour cells) and gastric cancer, with an intent to identify genes involved in the malignant transformation of normal gastric mucosa and to identify genes which can be used as biomarkers for early diagnosis and potential targets for treatment Identification of novel prognostic markers using microarray gene expression studies. Keywords: Patient tissue samples Two-dye experiments using Universal control RNA (Stratagene) and RNA from tissues. Biological replicates: Apparently Normal = 5; Paired Normal = 20; Gastric cancers = 24. One replicate per array.
Project description:In this dataset, we include the expression data obtained from gastric cancer tissues and gastric normal tissues to determine the differentially expressed genes in gastric cancer tissues.
Project description:In this dataset, we include the expression data obtained from gastric cancer tissues and gastric normal tissues to determine the differentially expressed genes in gastric cancer tissues
Project description:Gene expression profiling of apparently normal gastric tissue (obtained from patients undergoing gastric surgery for Non-gastric cancers), paired normals (obtained from the same stomach as the gastric cancer but confirmed by frozen section not to harbour any tumour cells) and gastric cancer, with an intent to identify genes involved in the malignant transformation of normal gastric mucosa and to identify genes which can be used as biomarkers for early diagnosis and potential targets for treatment Identification of novel prognostic markers using microarray gene expression studies. Keywords: Patient tissue samples
Project description:Small nucleolar RNAs (snoRNAs) are a highly conserved category of non-coding RNAs that play emerging roles in tumorigenesis and aggressiveness. However, the functions and underlying mechanisms of snoRNAs in regulating gastric cancer progression remain elusive. We identify SNORA37 as a driver of alternative splicing and gastric cancer progression. To explore the expression profiles of snoRNAs, we employed the Illumina HiSeq X Ten as a discovery platform to analyze the transcriptome profiling in three pairs of gastric cancer and corresponding normal epithelial specimens. The results showed 15 differentially expressed snoRNAs in gastric cancer tissues, including 9 up-regulated and 6 down-regulated snoRNAs. Meanwhile, 2204 alternative splicing events were also discovered in gastric cancer tissues compared to those in adjacent normal epithelial tissues. Furthermore, we validated the RNA-seq results by real-time RT-PCR with high identity. Overall, our results provided fundamental information about the transcriptomic changes in human gastric cancer tissues, and these findings will help us understand the pathogenesis of cancer progression.