Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

E-GEOD-66270

ABSTRACT: Genome-wide analysis of gene expression patterns in human kidney cancer [patients without metastasis]

OTHER RELATED OMICS DATASETS IN: GSE66272

PROVIDER: E-GEOD-66270 | ExpressionAtlas | 2020-10-21

REPOSITORIES: ExpressionAtlas

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	E-GEOD-66270-analysis-methods.tsv	Tabular
	E-GEOD-66270-atlasExperimentSummary.Rdata	Rdata
	E-GEOD-66270-configuration.xml	Xml
	E-GEOD-66270-percentile-ranks.tsv	Tabular
	E-GEOD-66270.condensed-sdrf.tsv	Tabular

Items per page:

1 - 5 of 46

Similar Datasets

Homo sapiens

Project description:Genome-wide analysis of gene expression patterns in human kidney cancer [patients without metastasis]

| PRJNA276295 | ENA

Homo sapiens

Project description:Genome-wide analysis of gene expression patterns in human kidney cancer [patients with metastasis]

| PRJNA276296 | ENA

Genome-wide analysis of gene expression patterns in human kidney cancer [patients without metastasis]

Project description:To investigate the mechanisms of ccRCC progression and metastasis, we performed expression profiling of human kidney cancer and benign tissues. mRNA microarray expression analysis was performed by using 28 matched malignant and non-malignant kidney tissue samples from 14 ccRCC patients without diagnosed metastasis. This dataset is part of the TransQST collection.

2016-08-31 | E-GEOD-66270 | biostudies-arrayexpress

Genome-wide analysis of gene expression patterns in human kidney cancer

Project description:Genome-wide analysis of gene expression patterns in human kidney cancer

| PRJNA276293 | ENA

Genome-wide methylation analysis of esophageal squamous cell carcinoma

Project description:Genome-wide methylation analysis was performed by methylated DNA immunoprecipitation-CGI microarray analysis. A pool of four cancer samples without lymph node metastasis, two pools of four cancer samples with lymph node metastasis, and three metastatic lymph nodes were prepared from the patients, and analyzed by MeDIP-CGI microarray.

2010-12-21 | E-GEOD-21238 | biostudies-arrayexpress

TR study of ‘A multi-center proof-of-concept phase2 study of encorafenib + binimetinib + cetuximab in patients with BRAF non-V600E mutated metastatic colorectal cancer (BIGBANG study)&quot

Project description:Primary outcome(s): Cancer related genome analysis, gene expression and molecular characterization analysis

| 2647002 | ecrin-mdr-crc

Proteomic data for tumor pericytes derived from colorectal cancer patients

Project description:This study aims to investigate differentially expressed proteins in tumor pericytes derived from colorectal cancer patients with or without liver metastasis. Tumor pericytes were isolated from tumor of colorectal cancer patients with or without liver metastasis. Then, tumor pericytes were cultured and subjected to proteomic analysis. TCAF2 was significantly increased in tumor pericytes from liver metastasis patients.

2024-01-26 | PXD033011 | Pride

Matched Lung Tumor And Emphysematous Matrix Proteomics, Transcriptomics, and Translatomics

Project description:Chronic obstructive pulmonary disease (COPD) is a known risk factor for developing lung cancer suggesting that the COPD stroma contains factors supporting tumorigenesis. Since cancer initiation is complex we used a multi-omic approach to identify gene expression patterns that distinguish COPD stroma in patients with or without lung cancer. Our overall objective is the identification of gene expression pathways and levels of regulation in lung stroma of patients with COPD that harbor lung cancer. We obtained lung tissue from patients with COPD and lung cancer (tumor and adjacent non-malignant tissue) and those with COPD without lung cancer for proteomic and mRNA (cytoplasmic and polyribosomal) profiling. We used the joint and individual variation explained (JIVE) method to integrate and analysis across the three datasets. JIVE identified eight latent patterns that robustly distinguished and separated the three groups of tissue samples. Predictive variables that associated with the tumor, compared to adjacent stroma, were mainly represented in the transcriptomic data, whereas, predictive variables associated with adjacent tissue compared to controls was represented at the translatomic level. Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analysis revealed extracellular matrix (ECM) and PI3K-Akt signaling pathways as important signals in the pre-malignant stroma. COPD stroma adjacent to lung cancer is unique and differs from non-malignant COPD tissue and is distinguished by the extracellular matrix and PI3K-Akt signaling pathways.

2019-05-28 | PXD007919 | Pride

Different miRNA expression profiles of CRC with or without lymph node metastasis

Project description:Identifying the exact molecules associated with CRC metastasis may be crucial to understand the process, which might also be translated to the diagnosis and treatment of CRC. In this study, we investigate the association of microRNA expression patterns with the lymph node metastasis of colorectal cancer. To investigate the association of microRNA expression patterns with the lymph node metastasis of colorectal cancer, eight primary colorectal cancer tissues derived from stage II–III colorectal cancer patients with (n = 4) or without (n = 4) lymph node metastasis were collected and the miRNA expression profiles of them were determined using Agilent miRNA microarray. Different miRNA expression profiles were identified in CRC tissues between lymph node metastasis positive and negative group.

2013-12-31 | E-GEOD-48074 | biostudies-arrayexpress

Deciphering metastatic route-specific signals and their microenvironment interactions in peritoneal metastasis of gastric cancer

Project description:Gastric cancer (GC) constitutes a significant cause of cancer-related mortality worldwide, with metastatic patterns including hematogenous, peritoneal, and ovarian routes. Although GC gene expression patterns have been extensively researched, the metastasis-specific gene expression landscape remains largely unexplored. This study undertook a whole transcriptome sequencing analysis of 66 paired primary and metastatic (hematogenous, peritoneal, or ovarian) GC tumors from 14 patients, leading to the identification of 122 unique metastasis-specific epithelial-mesenchymal transition (msEMT) genes. These genes demonstrated varying expression patterns depending on the metastatic route, suggesting route-specific molecular mechanisms in GC metastasis. High expression of msEMT genes in primary tumors was associated with more frequent CDH1 mutations, the genomically stable subtype, and poor prognosis in The Cancer Genome Atlas GC cohort. This association was further corroborated by poor prognosis and high predictive performance for peritoneal or ovarian recurrence in two independent cohorts (GSE66229; n=300, GSE84437; n=433). Single-cell RNA sequencing analysis of primary tumors (GSE167297) and four independent ascites samples from GC patients revealed that msEMT genes were predominantly expressed in diverse fibroblast sub-populations, rather than cancer cells. This study illuminates the route-specific mechanisms and underlines the significance of msEMT genes and cancer-associated fibroblasts in GC metastasis, highlighting potential directions for future research.

2024-07-01 | GSE237876 | 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