Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Ena-DATASET-GTI-15-06-2018-16:00:24:059-4268 - samples

ABSTRACT: Whole exome and RNA-seq of matched normal gastric mucosa (n=34) and gastric cancer tissues (n=34) from gastric cancer patients (n=34)

PROVIDER: EGAD00001004164 | EGA |

REPOSITORIES: EGA

ACCESS DATA

Json Xml

Similar Datasets

AGS infected with H. pylori for 24 hours

Project description:Helicobacter pylori (H. pylori) is a type of pathogen in humans that has infected nearly half of the population worldwide. Infections with H. pylori are typically associated with chronic gastritis and may even lead to gastric and duodenal ulcers and stomach cancer. While the mechanisms behind persistent colonization by H. pylori and the development of gastritis associated with it remain unclear, it is generally believed that the gastric epithelial cells (GECs) modulated by H. pylori in the gastric mucosa play a crucial role. We extensively studied the global gene expression patterns in H. pylori-infected AGS cells, a line of gastric epithelial cells, and identified genes that show increased expression upon infection with H. pylori.

2024-11-25 | GSE282738 | GEO

DNA methylation analysis in the gastric tissue collected from health check-up cohort.

Project description:Comprehensive DNA methylation analysis using the clinical FFPE samples of the gastric cancer, gastric mucosa surrounding cancer, and biopsy gastric mucosa.

2023-10-31 | GSE199898 | GEO

Transcription profiling by array of human gastric cancer cell lines and normal gastric mucosa

Project description:expression profiles of 9 gastric cancer cell lines and normal gastric mucosa are studied.

2011-04-01 | E-MEXP-2694 | biostudies-arrayexpress

Methylated CpG island amplification (MCA) microarray analysis of human gastric mucosa and cancer

Project description:Aberrant DNA methylation is implicated in the epigenetic field defect seen in gastric cancer (GC). Our aim in this study was to identify predictive biomarkers by screening for DNA methylation in noncancerous background gastric mucosa from GC patients. A total of 46 endoscopically obtained human gastric mucosa, 10 gastric cancer and 5 cell lines were analyzed using MCA microarray. Aberrant DNA methylation was compared with clinicopathological features. Healthy individuals were divided into two groups based on the types of chronic gastritis; A: antrum-predominant gastritis P or C: pangastritis or corpus-predominant gastritis

2012-09-01 | E-GEOD-39175 | biostudies-arrayexpress

Epigenome signatures during gastric carcinogenesis based on next generation sequencing analysis [Bisulfite-Seq]

Project description:Because gastric cancer cells already had genetic and epigenetic alterations which can affect the gastric carcinogenesis, we tried to characterize genetic and epigenetic changes during gastric carcinogenesis. To do this, we performed MBD sequencing and RRBS sequencing. MBD and RRBS sequencing of gastric mucosa, intestinal metaplasia, and gastric cancer cells from one patient were generated by NGS using Illumina GAII.

2015-09-01 | E-GEOD-55159 | biostudies-arrayexpress

Epigenome signatures during gastric carcinogenesis based on next generation sequencing analysis [MBD-Seq]

2015-09-01 | E-GEOD-55157 | biostudies-arrayexpress

Gastric cancer: cancer vs. normal, chemoresistance signature that correlates with time to progression of disease

Project description:microRNA profiling of gastric cancer vs. normal, pre-/-post CF (cisplatin/fluorouracil) chemotherapy. Biopsy samples were collected prior to chemotherapy from 90 gastric cancer patients treated with CF and from 34 healthy volunteers. At the time of disease progression, post-treatment samples were collected from 8 clinical responders. miRNA expression was determined using a custom-designed Agilent microarray. In order to identify an miRNA signature for chemotherapy resistance, we correlated miRNA expression levels with the time to progression (TTP) after CF. 90 pre-treatment gastric cancer samples, 34 healthy volunteers, 8 post-treatment samples.

2011-12-16 | E-GEOD-30070 | biostudies-arrayexpress

Transcription profiling of rat gastric ECL cells during 24 hrs fasting

Project description:Gastric ECL cells and parietal (PC) cells in normal conditions and gastric ECL cells after 24 hrs fasting were purified using a combination of counter-flow elutriation, nycodenz gradient and FACS based on acridine orange labeling of histamine containing vesicles (ECL cells) or autofluorescense (PC cells) to homogeneity. cRNA probes from this purified cell suspensions and from mixed gastric homogenates were hybridized to whole rat genome expression oligonucleotide microarrays. We imported each channel separately (normalized intensity of Cy3 labeled samples = gProcessedSignal and of Cy5 labeled samples = rProcessedSignal) from the original Agilent Feature Extraction data files (submitted as raw data) after slide scanning from all slides into a Genespring 7.3 microarray database warehouse. Genespringâs built in statistical module was used to compare all channels to each other. The normalization used was against specific samples (the 5 channels of Gastric mucosal scrapings). Genespring identifies genes differentially expressed in the ECL cell samples and the parietal samples and also calculates the significance of difference (p-value). Experiment Overall Design: ECL cells: free access to food and water (250 gm Sprague Dawley Rat) Experiment Overall Design: PC cells: free access to food and water (250 gm Sprague Dawley Rat) Experiment Overall Design: ECL cells: 24 hrs fasting, free access to water (250 gm Sprague Dawley Rat) Experiment Overall Design: Gastric mucosa scrapes: free access to food and water (250 gm Sprague Dawley Rat) Experiment Overall Design: Fasting gastric mucosa scrapes: 24 hrs fasting, free access to water (250 gm Sprague Dawley Rat) Experiment Overall Design: Three independent cell purifications, total RNA isolations and at least one dye swap per sample set (3).

2008-06-14 | E-GEOD-6204 | biostudies-arrayexpress

The genes associated with the response to S-1,cisplatin and docetaxel combination chemotherapy (DCS therapy) for metastatic gastric cancer:

Project description:Despite the effort in defining the molecular mechanisms for the drug resistance, predictors of response to chemotherapy have yet to be developed in gastric cancer. With microarray of whole human genes, we determined 29 genes associated with the response to cisplatin and docetaxel combination chemotherapy for metastatic gastric cancer. We obtained Fresh-frozen samples of tumor tissue and background gastric mucosa tissue from 19 patients with gastric cancer by endoscopic biopsy before DCS therapy. Total RNA was extracted from individual microdissected populations of cancer cells and background mucosa cells using RNAeasy mini kits and amplified with a random primer, WT-Ovation FFPE RNA Amplification System V2; NuGEN, Cincinnati, Ohio) according to the manufacturer’s protocols. The amplified fragmented RNA was hybridized on a Whole Human Genome Oligo Microarray Chip (Agilent Technologies) containing 44,000 cDNA clones.

2014-08-31 | E-GEOD-31811 | biostudies-arrayexpress

CricRNA expression profiling in human gastric cancer

Project description:Using the highly sensitive cricRNA array, we screened 13617 circRNAs abundant in the human gastric cancer and Adjacent normal gastric mucosa tissues, and the function of differentially expressed circRANs were analyzed by bioinformatics. The enrichment results indicated that these circRNAs perhaps participated in the occurrence and development process of gastric cancer.

2016-02-20 | GSE78092 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data