Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

YAP conveys an invasive phenotype to clear cell renal cell carcinoma cell lines via endothelin-2

ABSTRACT: To determine the biological mechanisms underlying the oncogenic properties of YAP in ccRCC the human ccRCC cell line MZ1774 was transduced with lentivirus containing a shRNA-cassette targeting YAP-mRNA. Expression profiles of MZ1774 YAP knockdown cells were compared to mock-transduced control cells.

ORGANISM(S): Homo sapiens

PROVIDER: GSE50053 | GEO | 2014/12/23

SECONDARY ACCESSION(S): PRJNA215872

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

YAP conveys an invasive phenotype to clear cell renal cell carcinoma cell lines via endothelin-2

Project description:To determine the biological mechanisms underlying the oncogenic properties of YAP in ccRCC the human ccRCC cell line MZ1774 was transduced with lentivirus containing a shRNA-cassette targeting YAP-mRNA. Expression profiles of MZ1774 YAP knockdown cells were compared to mock-transduced control cells. Total RNA from MZ1774 cells stably expressing shRNA directed against YAP compared to mock-transduced MZ1174 cells

2014-12-23 | E-GEOD-50053 | biostudies-arrayexpress

Nuclear YAP overexpression drives the human alveolar type 1 cell (AT1) cprogram in a cell autonomous manner in lentiviral transduced iPSC-derived alveolar type 2 cells (iAT2s)

Project description:SPC2B2 iAT2s were transduced with either control WT YAP or constitutively active nuclear YAP (YAP5SA) lentivirus in a single cell suspension and were then grown in iAT2 media (CK + DCI) in 3D matrigel for 7 days.

2023-08-08 | GSE221344 | GEO

Urinary multi-omics reveal non-invasive diagnostic biomarkers in clear cell renal cell carcinoma

Project description:Clear cell renal cell carcinoma (ccRCC) is the most common kidney malignancy. Yet, no rapid, non-invasive biomarkers are available for diagnosis or screening. Urine represents an ideal analyte matrix due to its accessibility, low invasiveness, longitudinal sampling and the kidney’s central role in filtration. Here, we integrated proteomic, lipidomic, and metabolomic analyses of urine from ccRCC patients and controls to identify diagnostic biomarkers. Multi-omics profiling revealed urogenital metabolic dysregulation in ccRCC, including increased lipid metabolism, altered mitochondrial respiration signatures, and elevated urinary lipid content. We identified three urinary protein biomarkers: serum amyloid A1 (SAA1), haptoglobin (HP), and lipocalin 15 (LCN15). Using a parallel reaction monitoring mass spectrometry workflow, we developed a rapid and sensitive assay and combined these markers into a diagnostic UrineScore. The UrineScore achieved 96% accuracy in receiver operating characteristic analysis in the discovery cohort and 95% accuracy in an independent validation cohort. Together, these results support the feasibility of multi-omics-guided urinary biomarker discovery and represent a step toward accessible diagnostic platforms for ccRCC.

2026-08-18 | PXD078983 | Pride

HIF2ɑ Requires Engagement with YAP/TAZ and AP-1 Transcription Factors to Maintain Oncogenic Transcription in Clear Cell Renal Cell Carcinoma [CUT&Tag]

Project description:Clear Cell Renal Cell Carcinoma (ccRCC) is characterized by loss of tumor suppressor von Hippel-Lindau (VHL), leading to activation of Hypoxia-inducible Factor 2ɑ (HIF2ɑ) oncogenic transcription factor and pseudo-hypoxia. Integrated analysis of public ccRCC multi-omic datasets revealed frequent inactivation of the Hippo tumor suppressor pathway and corresponding increase in YAP/TAZ transcription activity in ccRCC tumors, which is associated with worse overall survival in treatment naïve patients. By combining Cut&Tag and BRB-seq analysis, we assessed the chromatin binding and gene regulation of YAP and HIF2ɑ, and unveiled that these two proteins are co-recruited to AP-1 sites through interactions with the AP-1 transcription factors. YAP/TAZ, HIF2ɑ and JUN are dependent on each other to maintain their expression, and function cooperatively to promote the expression of highly expressed transcription factors and other important oncogenes. Our findings not only revealed the therapeutic potentials of adjunct YAP/TAZ-based therapies in the treatment of advanced ccRCC, but also revealed novel mechanistic insights into the dynamic interactions among YAP, HIF2ɑ and AP-1 proteins that could be further exploited to improve treatment for ccRCC.

2026-03-31 | GSE295183 | GEO

HIF2ɑ Requires Engagement with YAP/TAZ and AP-1 Transcription Factors to Maintain Oncogenic Transcription in Clear Cell Renal Cell Carcinoma [RNA-Seq]

2026-03-31 | GSE295181 | GEO

Urinary multi-omics reveal non-invasive diagnostic biomarkers in clear cell renal cell carcinoma

Project description:<p>Clear cell renal cell carcinoma (ccRCC) is the most common kidney malignancy. Yet, no rapid, non-invasive biomarkers are available for diagnosis or screening. Urine represents an ideal analyte matrix due to its accessibility, low invasiveness, longitudinal sampling and the kidney’s central role in filtration. Here, we integrated proteomic, lipidomic, and metabolomic analyses of urine from ccRCC patients and controls to identify diagnostic biomarkers. Multi-omics profiling revealed urogenital metabolic dysregulation in ccRCC, including increased lipid metabolism, altered mitochondrial respiration signatures, and elevated urinary lipid content. We identified three urinary protein biomarkers: serum amyloid A1 (SAA1), haptoglobin (HP), and lipocalin 15 (LCN15). Using a parallel reaction monitoring mass spectrometry workflow, we developed a rapid and sensitive assay and combined these markers into a diagnostic UrineScore. The UrineScore achieved 96% accuracy in receiver operating characteristic analysis in the discovery cohort and 95% accuracy in an independent validation cohort. Together, these results support the feasibility of multi-omics-guided urinary biomarker discovery and represent a step toward accessible diagnostic platforms for ccRCC.</p>

2026-08-16 | MTBLS12025 | MetaboLights

Urinary multi-omics reveal non-invasive diagnostic biomarkers in clear cell renal cell carcinoma (Lipidomics)

2026-07-15 | MTBLS14671 | MetaboLights

High-throughput transcriptome sequencing of DNAJC2-knockdown clear cell renal cell carcinoma cells（shDNAJC2 vs shCtrl）

Project description:This project was designed to characterize transcriptomic changes caused by DNAJC2 knockdown in clear cell renal cell carcinoma (ccRCC) cells using high-throughput RNA sequencing. Cells transduced with control shRNA and cells with DNAJC2 knockdown were subjected to next-generation transcriptome sequencing to identify differentially expressed genes and pathways regulated by DNAJC2. This dataset was used to investigate the role of DNAJC2 in ccRCC cell metabolism and ferroptosis-related regulation

2026-06-21 | GSE335539 | GEO

Genome-wide analysis of differentially expressed genes and splicing isoforms in clear cell Renal Cell Carcinoma

Project description:In this study we performed a genome wide analysis of the entire complement of mRNAs in clear cell renal cell carcinomas (ccRCC) by means of the Affymetrix Exon Array platform. The analyses were performed both at gene and exon level. Under our parameters over 2,000 genes resulted differentially expressed, and about 250 genes resulted alternative spliced showing differential inclusion of specific cassette exons comparing tumor and non tumoral tissues.

2013-09-06 | GSE47032 | GEO

Proteomics characterization of clear cell renal cell carcinoma

Project description:The aims of the study was to explore the tumor proteome of patients diagnosed with localized ccRCC and treated with surgery and the identification of altered pathways that could be the target of new treatments. A total of 165 FFPE tumor samples from patients diagnosed with ccRCC were analyzed using DIA-proteomics. Proteomics ccRCC subtypes were defined using a Consensus Cluster Algorithm (CCA) and characterized by a functional approach using probabilistic graphical models and survival analyses. Two proteomics subtypes of ccRCC (CCA1 and CCA2) were identified by CCA using the high confidence proteins only. Characterization of molecular differences between CCA1 and CCA2 was performed in two steps. First, we defined 514 proteins showing differential expression between the two subtypes using a significance analysis of microarrays analysis. Proteins overexpressed in CCA1 were mainly related to translation and ribosome, while proteins overexpressed in CCA2 were mainly related to focal adhesion and membrane. Second, a functional analysis using probabilistic graphical models was performed. The CCA1 subtype is characterized by an increased expression of proteins related to glycolysis, mitochondria, translation, adhesion proteins related to cytoskeleton and actin, nucleosome, and spliceosome, while CCA2 subtype showed higher expression o proteins involved in focal adhesion, extracellular matrix and collagen organization.

2025-05-09 | PXD039258 | Pride

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