Browse
Submit Data
Databases
API
Help

Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

14 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Copy number variation profiling of gastric tissues: Cancer Samples vs. Matched Adjacent Noncancerous Samples

ABSTRACT: Copy number variation profiling of gastric tissues comparing gastric cancer tissues with matched adjacent noncancerous tissues. Goal was to determine the effects of chromosomal imbalances on gene expression and carcinogenesis or progression. 27 pairs of gastric tissues: gastric cancer tissues vs. matched adjacent noncancerous tissues.

ORGANISM(S): Homo sapiens

SUBMITTER: Cheng Lei

PROVIDER: E-GEOD-33428 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Json Xml

Publications

Identification of genes with a correlation between copy number and expression in gastric cancer.

Cheng Lei L Cheng Lei L Wang Ping P Yang Sheng S Yang Yanqing Y Zhang Qing Q Zhang Wen W Xiao Huasheng H Gao Hengjun H Zhang Qinghua Q

BMC medical genomics 20120504

<h4>Background</h4>To elucidate gene expression associated with copy number changes, we performed a genome-wide copy number and expression microarray analysis of 25 pairs of gastric tissues.<h4>Methods</h4>We applied laser capture microdissection (LCM) to obtain samples for microarray experiments and profiled DNA copy number and gene expression using 244K CGH Microarray and Human Exon 1.0 ST Microarray.<h4>Results</h4>Obviously, gain at 8q was detected at the highest frequency (70%) and 20q at t ...[more]

PMID: 22559327

Similar Datasets

Cancer Samples vs. Matched Adjacent Noncancerous Samples

Project description:This SuperSeries is composed of the following subset Series: GSE33335: Expression data from gastric tissues: Cancer Samples vs. Matched Adjacent Noncancerous Samples GSE33428: Copy number variation profiling of gastric tissues: Cancer Samples vs. Matched Adjacent Noncancerous Samples Refer to individual Series

2012-05-22 | E-GEOD-33429 | biostudies-arrayexpress

Expression data from gastric tissues: Cancer Samples vs. Matched Adjacent Noncancerous Samples

Project description:To elucidate gene expression associated with copy number changes, we performed a genome-wide copy number and expression microarray analysis of 25 pairs of gastric tissues. 25 pairs of gastric tissues: gastric cancer tissues vs. matched adjacent noncancerous tissues.

2012-05-22 | E-GEOD-33335 | biostudies-arrayexpress

Proteomic profiling of paired interstitial fluids revealed dysregulated pathways and salivary NID1 as a biomarker of oral cavity squamous cell carcinoma

Project description:Patients with oral cavity squamous cell carcinoma (OSCC) are frequently first diagnosed at an advanced stage, leading to poor prognosis and high mortality rate. Early detection of OSCC using body fluid-accessible biomarkers may help improve the prognosis and survival rate of OSCC patients. As tumor interstitial fluid (TIF) is a proximal fluid enriched with cancer-related proteins, it is therefore a valuable reservoir suitable for the discovery of cancer biomarkers as well as dysregulated biological pathways in tumor microenvironment. Thus, we harvested and analyzed the paired tumor (TIF) and adjacent noncancerous (NIF) interstitial fluids from ten OSCC patients using one-dimensional gel electrophoresis coupled with the nano-liquid chromatography-tandem mass spectrometry (GeLC-MS/MS) approach and label-free spectral counting method. The results showed that 113 proteins were up-regulated in at least six OSCC TIFs compared to their respective NIFs, and that the aminoacyl tRNA biosynthesis was statistically enriched in TIFs by Gene Set Enrichment Analysis (GSEA). The enrichment of aminoacyl tRNA biosynthesis in OSCC was verified that four members (IARS, KARS, WARS, and YARS) were revealed to be elevated in OSCC by IHC (n = 12). Among the 113 up-regulated proteins, two candidates (NID1 and SERPINH1) were selected based on an integrated bioinformatics analysis and verified that the salivary NID1 levels were significantly higher in OSCC patients (n = 48) compared to health (n = 51) and OPMD individuals (n = 53). Moreover, the IHC results (n = 222) showed that the expression of NID1 was higher in OSCC compared to adjacent noncancerous epithelium and correlated with pathological T, N, and overall stage as well as survivals of OSCC patients. These results collectively indicate that the analysis of TIF is help to understand the tumor microenvironment, and that salivary NID1 is a potentially useful biomarker for the OSCC.

2019-08-15 | PXD008654 | Pride

Characterization of differentially expressed genes involved in pathways associated with gastric cancer

Project description:To explore the patterns of gene expression in gastric cancer, a total of 32 paired gastric cancer and noncancerous tissues from patients were collected for gene expression microarray analyses. Limma methods were applied to analyze the data, and genes were considered to be significantly differentially expressed if the False Discovery Rate (FDR) values < 0.01, P-value < 0.01 and the fold change >2. Subsequently, Gene Ontology (GO) analysis was used to analyze the main functions of the differentially expressed genes. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we found pathways significantly associated with the differential genes. Gene-Act network and Co-Expression networks were built respectively based on the relationships among the genes, proteins and compounds in the database. There were 2371 differential mRNAs and 350 differential lncRNAs in our microarray data. The GO categories, pathway analyses and the Gene-Act network showed a consistent result that up-regulated genes were involved in tumorigenesis, migration, angiogenesis and microenvironment formation, while down-regulated genes were involved in metabolism. The results of this study provide some novel findings on genes, pathways and the co-expression network in gastric cancer which will be useful to guide further investigation and target therapy for this disease. 32 gastric cancer tissues and 32 paired noncancerous tissues were collected for this microarray analysis.

2015-02-11 | E-GEOD-65801 | biostudies-arrayexpress

Protein profiling reveals the characteristic changes of complement cascade pathway in the tissues of gastric signet ring cell carcinoma

Project description:Signet ring cell carcinoma (SRCC) is a histological subtype of gastric cancer with distinct features in multiple aspects compared to adenocarcinomas (ACs). Lacking of systematically molecular overview to this disease made a slow progress in its clinical practice. In the present proteomics study, gastric tissues were collected from tumor and adjacency including 14 SRCCs and 34 ACs, and laser capture microdissection (LCM) was employed to eradicate cellular heterogeneity of the tissues. Proteome of tissues were profiled by data independent acquisition (DIA) mass spectrometry (MS). Based on the over 6 000 proteins quantified. Univariate analysis and pathway enrichment revealed that some proteins and pathways bared the differences between SRCC and ACs. Importantly, the up regulation for a majority of complement-related proteins were iconic for SRCC but not for AC. A hypothesis, based on the proteomics evidence, was proposed that the complement cascade was evoked in the SRCC microenvironment upon infiltration, while the SRCC cells survived the complement cytotoxicity by secreting endogenous negative regulators. Moreover, an attempt was made to seek appropriate cell models for gastric SRCC, through proteomic comparison of the 15 gastric cell lines and the gastric tumors. The prediction of supervised classifier suggested none of these gastric cell lines qualified in mimicking SRCC. This study discovered that complement cascade is activated at a higher level in gastric SRCC than AC.

2021-02-25 | PXD022405 | Pride

Protein profiling reveals the characteristic changes of complement cascade pathway in the tissues of gastric signet ring cell carcinoma

2021-02-25 | PXD022952 | Pride

Protein profiling reveals the characteristic changes of complement cascade pathway in the tissues of gastric signet ring cell carcinoma

2021-02-25 | PXD022627 | Pride

Gene expression changes in initiation and progression of oral squamous cell carcinomas revealed by laser microdissection and oligonucleotide microarray analysis

Project description:Background. Oral carcinogenesis is a complex process involving multiple genes. However, the genetic changes involved in this process are not demonstrated in the identical oral squamous carcinomas (OSCCs). Methods. According to the pathological characteristics, parts of normal tissues, oral dysplastic lesions (ODLs), and invasive cancers were procured from the identical OSCCs using laser microdissection (LMD), and large scale gene expression profiling was carried out on 33 samples derived from 11 OSCCs. Results. We analyzed genes differentially expressed in normal tissues vs. ODLs and ODLs vs. invasive tumors and identified the 15 candidate genes that continuously increasing or decreasing in its expression during oral carcinogenesis. One of these, ISG15 was chosen for further characterization. Real-time quantitative reverse transcriptase-polymerase chain reaction and immunohistochmistry analysis confirmed that ISG15 expression was consistently increasing during oral tumorigenesis. ISG15 high expression was significantly associated with poor prognosis (P=0.027). In addition, patients whose tumor had high ISG15 expression had worse 5-year survival rate than patients whose tumors had a low expression level (P=0.019). Conclusions. We identified the 15 genes that are continuously increasing or decreasing in its expression during oral carcinogenesis. One of these, ISG15 is likely to be associated with both dysgenesis and tumorigenesis, and may be a potential prognostic marker in these malignancies. Microarray samples of invasive tumor, adjacent dysplastic lesions and noncancerous normal tissues were collected from 11 patients with primary OSCCs. We analyzed genes differentially expressed in (i) normal vs. dysplastic tissues and (ii) dysplastic vs. tumor tissues.

2012-09-11 | E-GEOD-35261 | biostudies-arrayexpress

Global gene expression analysis of gastric cancer by oligonucleotide microarrays

Project description:To gain molecular understanding of carcinogenesis, progression, and diversity of gastric cancer, 22 primary human advanced gastric cancer tissues and 8 noncancerous gastric tissues were analyzed by high-density oligonucleotide microarray in this study. Based on expression analysis of approximately 6800 genes, a two-way clustering algorithm successfully distinguished cancer tissues from noncancerous tissues. Subsequently, genes that were differentially expressed in cancer and noncancerous tissues were identified; 162 and 129 genes were highly expressed (P < 0.05) >2.5-fold in cancer tissues and noncancerous tissues, respectively. In cancer tissues, genes related to cell cycle, growth factor, cell motility, cell adhesion, and matrix remodeling were highly expressed. In noncancerous tissues, genes related to gastrointestinal-specific function and immune response were highly expressed. Furthermore, we identified several genes associated with lymph node metastasis including Oct-2 or histological types including Liver-Intestine Cadherin. These results provide not only a new molecular basis for understanding biological properties of gastric cancer, but also useful resources for future development of therapeutic targets and diagnostic markers for gastric cancer. Keywords: other

2005-05-22 | GSE2685 | GEO

Global gene expression analysis of gastric cancer by oligonucleotide microarrays

2005-05-22 | E-GEOD-2685 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

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