Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

MSKCC-A Primary Lung Cancer Specimens

ABSTRACT: Develop an EGFR mutation gene expression signature to aid in predicting response and clinical outcome and to identify genes associated with the EGFR-dependent phenotype

ORGANISM(S): Homo sapiens

PROVIDER: GSE31547 | GEO | 2011/09/06

SECONDARY ACCESSION(S): PRJNA154973

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

UMCCC Primary Lung Cancer Specimens

Project description:Develop an EGFR mutation gene expression signature to aid in predicting response and clinical outcome and to identify genes associated with the EGFR-dependent phenotype

2011-09-06 | GSE31546 | GEO

MSKCC-B Primary Lung Cancer Specimens

Project description:Develop an EGFR mutation gene expression signature to aid in predicting response and clinical outcome and to identify genes associated with the EGFR-dependent phenotype

2011-09-06 | GSE31548 | GEO

UMCCC Primary Lung Cancer Specimens

Project description:Develop an EGFR mutation gene expression signature to aid in predicting response and clinical outcome and to identify genes associated with the EGFR-dependent phenotype 17 primary lung adenocarcinomas were analyzed with Affymetrix U133-plus2

2011-09-05 | E-GEOD-31546 | biostudies-arrayexpress

MSKCC-A Primary Lung Cancer Specimens

Project description:Develop an EGFR mutation gene expression signature to aid in predicting response and clinical outcome and to identify genes associated with the EGFR-dependent phenotype 30 primary lung adenocarcinomas and 20 adjacent normal lung controls were analyzed with Affymetrix U133A

2011-09-05 | E-GEOD-31547 | biostudies-arrayexpress

MSKCC-B Primary Lung Cancer Specimens

Project description:Develop an EGFR mutation gene expression signature to aid in predicting response and clinical outcome and to identify genes associated with the EGFR-dependent phenotype 30 primary lung adenocarcinomas and 20 adjacent normal lung controls were analyzed with Affymetrix U133B

2011-09-05 | E-GEOD-31548 | biostudies-arrayexpress

Genome-wide analysis of microRNA expression in surgical specimens of primary glioblastoma multiform

2012-07-13 | GSE25631 | GEO

Genome-wide analysis of microRNA expression in surgical specimens of primary glioblastoma multiform

Project description:MicroRNA has a great potential in predicting survival of cancer patient. We used a genome-wide microRNA expression profiling to identify a miRNA signature for the prediction of clinical outcome of primary GBM patients. Total RNA obtained from 82 surgical specimens of primary glioblastoma multiform and 5 normal brain tissues from areas surrounding arteriovenous malformations (AVM) as control.

2012-07-12 | E-GEOD-25631 | biostudies-arrayexpress

Chemorefractory non-small cell lung cancer gene expression profiles from the Biomarker-Integrated Approaches of Targeted Therapy for Lung Cancer Elimination (BATTLE) trial

Project description:This SuperSeries is composed of the following subset Series: GSE27389: Substitutions in the KRas oncogene determine protein behavior: Implications for signaling and clinical outcome. GSE31428: Final efficacy and biomarker analysis of the sorafenib arm of the BATTLE (Biomarker-Integrated Approaches of Targeted Therapy for Lung Cancer Elimination) trial GSE31852: An EGFR-mutation signature reveals features of the EGFR-dependent phenotype and identifies MACC1 as an EGFR-associated regulator of MET. GSE33072: An epithelial-mesenchymal transition (EMT) gene signature predicts resistance to erlotinib and PI3K pathway inhibitors and identifies Axl as a novel EMT marker in non-small cell lung cancer. Refer to individual Series

2012-01-01 | E-GEOD-31437 | biostudies-arrayexpress

Expression profiling of lung cancer cell lines (UTSW Lung Panel V2)

Project description:Epithelial/mesenchymal transition (EMT) is associated with loss of cell adhesion molecules, such as E-cadherin, and increased invasion, migration, and proliferation in epithelial cancers. In non-small cell lung cancer (NSCLC), EMT is associated with greater resistance to EGFR inhibitors. However, its potential to predict response to other targeted drugs or chemotherapy has not been well characterized. The goal of this study was to develop a robust, platform-independent EMT gene expression signature and to investigate the association of EMT and drug response in NSCLC. A 76-gene EMT signature was derived in 54 DNA-fingerprinted NSCLC cell lines and tested in an independent set of cell lines and in NSCLC patients from the BATTLE clinical trial. The signature classified cell lines as epithelial or mesenchymal independent of the microarray platform and correlated strongly with E-cadherin protein levels, as measured by reverse phase protein array. Higher protein expression of Rab25 (in epithelial lines) and Axl (in mesenchymal lines), two signature genes associated with in EMT in other cancer types, was also confirmed. Mesenchymal cell lines demonstrated significantly greater resistance to EGFR inhibition, independent of EGFR mutation status and were more resistant to drugs targeting the PI3K/Akt pathway. We observed no association between EMT and response to cytotoxic chemotherapies, including cisplatin, pemetrexed, and docetaxel monotherapy and/or doublets (p-values ?0.2). In NSCLC patients, the EMT signature predicted 8-week disease control in the erlotinib arm, but not in other treatment arms. In conclusion, we have developed a robust EMT signature that predicts resistance to EGFR inhibitors and PI3K/Akt pathway inhibitors. To develop gene expression signatures for in vitro drug response and other phenotypes. Profiling was done on 68 NSCLC cell lines and 2 HBEC-KT cell lines (normal lung cells immortalized with CDK4 and hTERT).

2012-10-25 | E-GEOD-32989 | biostudies-arrayexpress

Comprehensive microRNA profiling of Nasopharyngeal Carinoma Specimens

Project description:Publication: Identification of a microRNA signature associated with risk of distant metastasis in nasopharyngeal carcinoma Purpose Despite significant improvement in locoregional control in the contemporary era of nasopharyngeal carcinoma (NPC) treatment, patients still suffer from a significant risk of distant metastasis (DM). Identifying those patients at risk of DM would aid in personalized treatment in the future. MicroRNAs (miRNAs) play many important roles in human cancers; hence, we proceeded to address the primary hypothesis that there is a miRNA expression signature capable of predicting DM for NPC patients. Methods and results The expression of 734 miRNAs was measured in 125 (Training) and 121 (Validation) clinically annotated NPC diagnostic biopsy samples. A 4-miRNA expression signature associated with risk of developing DM was identified by fitting a penalized Cox Proportion Hazard regression model to the Training data set (HR 8.25; p < 0.001), and subsequently validated in an independent Validation set (HR 3.2; p = 0.01). Pathway enrichment analysis indicated that the targets of miRNAs associated with DM appear to be converging on cell-cycle pathways. Conclusions This 4-miRNA signature adds to the prognostic value of the current “gold standard” of TNM staging. In-depth interrogation of these 4-miRNAs will provide important biological insights that could facilitate the discovery and development of novel molecularly targeted therapies to improve outcome for future NPC patients.

2015-07-17 | GSE70970 | 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