Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

MRNA expression profiles of newly established 49 gastric cancer cell lines.

ABSTRACT: Establishment and molecular characterization of 49 peritoneally-metastatic gastric cancer cell lines from 18 patients’ ascites. We performed comprehensive transcriptome analyses using microarrays of our established gastric cancer cell lines.

ORGANISM(S): Homo sapiens

PROVIDER: GSE172197 | GEO | 2023/04/01

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

mRNA expression profiles of 223 cancer cell lines including newly established ones

Project description:Establishment and molecular characterization of 239 peritoneally-metastatic cancer cell lines from 170 patients’ ascites in 11 kinds of cancers mainly consisted of gastric, pancreatic, and ovarian cancer. We performed comparative transcriptome analyses using microarrays between our established cancer cell lines and cell-bank derived cancer cell lines

2023-02-21 | GSE172159 | GEO

mRNA expression profiles of 7 gastric cancer cell lines and primary cancer cells.

Project description:Molecular characterization of 7 peritoneally-metastatic gastric cancer cell lines and primary cancer cells established from a patients’ ascites. We performed comprehensive transcriptome analyses using microarrays of our established gastric cancer cell lines and primary cancer cells.

2023-04-01 | GSE172196 | GEO

mRNA expression profiles of newly established 49 gastric cancer cell lines.

Project description:mRNA expression profiles of newly established 49 gastric cancer cell lines.

| PRJNA722410 | ENA

Genomic profiling of 49 gastric cancer cell lines by array-based comparative genomic hybridization

Project description:In this study, we investigated amplifications and deletions of 49 gastric cancer cell lines by 244k oligonucleotide-based array comparative genomic hybridization.

2016-12-01 | GSE74839 | GEO

Gastric cancer ascites proteome

Project description:Gastric cancer is one of the most lethal malignancies with high mortality and gastric cancer-specific biomarker is need due to the lack of specific method for early screening, diagnosis, and prognosis of the patients with gastric cancer. Ascites is known for an important source for conducing biomarker discovery because it contains the secreted proteins from malignant cells, growth factors, and cytokines. In this study, we have conducted a comprehensive proteome study using ascites of patients with inflammatory diseases and gastric cancer. In the discovery stage, we have identified 2761 ascites-specific proteins, where 234 proteins were quantitated using the label free quantitation method, the normalized spectral abundance factor (NSAF); 152 and 82 proteins showed up and down-regulated pattern, respectively. Our ascites proteome can be used as baseline data for the discovery of novel biomarkers of the gastric cancer.

2018-04-16 | PXD002213 | Pride

Single cell RNA sequencing of advanced gastric cancer

Project description:To define the cellular characteristics of malignant ascites of advanced gastric cancer patients and search for therapeutic strategies, we applied single cell RNA sequencing to cancer cells and tumor associated macrophages (TAM), present in large numbers in malignant ascites. We analyzed 180 cells from 4 malignant ascites and 1 cerebrospinal fluid metastasis. The results indicate that the anti-inflammatory characteristics of the tumor associated macrophages are concocted by the tumor cells. By constructing reference transcriptomes for M1 and M2 type macrophages, we found a strong non-inflammatory property of macrophages recovered from the malignant ascites of gastric cancer.

2020-12-10 | GSE140182 | GEO

Ascites-derived circulating microRNAs as potential diagnostic biomarkers of gastric cancer-associated malignant ascites

Project description:Peritoneal carcinomatosis with malignant ascites is associated with dismal prognosis in gastric cancer. Malignant ascites is the most relevant body fluid in which to seek diagnostic biomarkers for peritoneal carcinomatosis. We aimed to identify and validate ascites-derived circulating microRNAs (miRNAs) that are differentially expressed between liver cirrhosis-associated benign ascites (LC-ascites) and gastric cancer-associated malignant ascites (GC-ascites). MiRNA expression levels were investigated in three independent cohorts. Overall, 165 ascites samples (73 LC-ascites and 92 GC-ascites) were obtained from the National Biobank of Korea. Initially, microarrays were used to screen the expression levels of 2,006 miRNAs in the discovery cohort (n = 22). Subsequently, quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR) analyses were used to validate the expression levels of selected miRNAs in the training (n = 70) and validation (n= 73) cohorts. In addition, the levels of carcinoembryonic antigen (CEA), a commonly used tumor marker, were determined in the ascites samples. Expression levels of miR-574-3p, miR-181b-5p, miR-4481, and miR-181d were significantly lower in the GC-ascites samples than in the LC-ascites samples, and miR-181b-5p showed the best diagnostic performance for GC-ascites (area under the curve [AUC] = 0.798 and 0.846 for the training and validation cohorts, respectively). The diagnostic performance of CEA for GC-ascites was improved if CEA and miR-181b-5p were analyzed together (AUC = 0.981 and 0.946 for the training and validation cohorts, respectively). Overall, we identified ascites-derived circulating miRNAs capable of differentiating non-malignant ascites and GC-ascites, and demonstrated that the combined use of miR-181b-5p and CEA produces the optimal diagnostic yield.

2019-02-12 | GSE126399 | GEO

Methylation profiling in gastric cancer with malignant ascites.

Project description:Methylation profiling in gastric cancer with malignant ascites.

| PRJNA714888 | ENA

Roles of membrane-Anchoring ARHGAP fusions in peritoneal metastasis of gastric and pancreatic cancer.

Project description:Diffuse-type gastric cancer (DGC) frequently metastasizes to the peritoneal cavity and causes malignant ascites. Although recent studies revealed that RHOA mutation and CLDN18-ARHGAP6/26 fusions are a hallmark of DGC, their roles are largely unknown. Here, we report the roles of two novel ARHGAP fusions (RP2-ARHGAP6 and OCLN-ARHGAP26) and the above CLDN18-ARHGAP26 fusion in ascites-derived DGC cell lines. A series of experiments revealed that X-ARHGAP6 /26 fusion acts as an inhibitor of RhoA and further suggested that the ARHGAP6 fusion induces cell-adhesion loss and maintains a putative ALDH-high cancer stem cell population, whereas the ARHGAP26 fusion evades apoptosis. Notably, these ARHGAP6/26 fusions were frequently found not only in the ascites of DGC but also in that of pancreatic cancer (12% and 38%, respectively). Together, these data demonstrate that ARHGAP6/26 fusions are useful for developing therapeutics and diagnostics for peritoneal metastasis control of DGC and pancreatic cancer. We used microarrays to identify gene sets regulated by RP2-ARHGAP6-centered signaling in DGC cells.

2020-12-31 | GSE100627 | GEO

Whole exome sequencing of advanced gastric cancer

Project description:To define the cellular characteristics of malignant ascites of advanced gastric cancer patients and search for therapeutic strategies, we obtained 5 malignant ascites and 1 cerebrospinal fluid from five patients with gastric cancer. We analyzed 180 cells from 4 malignant ascites and 1 cerebrospinal fluid metastasis. The results indicate that the anti-inflammatory characteristics of the tumor associated macrophages are concocted by the tumor cells. By constructing reference transcriptomes for M1 and M2 type macrophages, we found a strong non-inflammatory property of macrophages recovered from the malignant ascites of gastric cancer.

| EGAS00001004086 | EGA

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