Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Expression data from spatially separated samples of different ccRCC patients

ABSTRACT: We have sampled several tumour regions from nine clear cell renal cell carcinoma (ccRCC) patients to investigate intra-tumour heterogeneity.

ORGANISM(S): Homo sapiens

PROVIDER: GSE53000 | GEO | 2014/01/06

SECONDARY ACCESSION(S): PRJNA230646

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

Expression data from spatially separated samples of different ccRCC patients

Project description:We have sampled several tumour regions from nine clear cell renal cell carcinoma (ccRCC) patients to investigate intra-tumour heterogeneity. We selected 56 tumour samples and 6 normal samples from the 9 patients for expression analysis using microarray data. All samples were fresh frozen upon extraction.

2014-01-06 | E-GEOD-53000 | biostudies-arrayexpress

Expression data from different samples of a single ccRCC patient: 7 primary intra-tumor samples and 2 metastatic tumor samples

2011-08-25 | GSE31610 | GEO

Expression data from different samples of a single ccRCC patient: 8 primary intra-tumor samples and 2 metastatic tumor samples

Project description:We have sampled several tumour regions from a single ccRCC patient after 6 weeks everolimus treatment, including both primary and metastatic site samples to investigate intra-tumour heterogeneity. We selected 8 samples from the primary tumour, and 2 samples from a chestwall metastatic site for expression analysis using microarray data. All samples were fresh frozen upon extraction.

2011-08-24 | E-GEOD-31610 | biostudies-arrayexpress

Expression data from different samples of a single ccRCC patient.

2011-08-06 | GSE31232 | GEO

Expression data from different samples of a single ccRCC patient.

Project description:We have sampled several tumour regions from a single patient before and after everolimus treatment, including both primary and metastatic site samples to investigate intra-tumour heterogeneity. We selected 4 primary tumour regions, including a pre-treatment biopsy, and 1 metastatic region for expression analysis using microarray data. Two samples were used per region (1 fresh frozen and 1 formalin-fixed).

2011-08-05 | E-GEOD-31232 | biostudies-arrayexpress

Transcriptomic profiling of ccRCC nephrectomy samples by Direct RNAseq

Project description:Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer. Following primary tumour resection approximately 30% of patients experience disease recurrence associated with metastasis. To date, long-read RNA sequencing has not been applied to kidney cancer. Here, we used ONT long-read Direct RNA sequencing to profile the transcriptomes of ccRCC archival tumours, 6 of which were from patients who went on to relapse. Our results revealed a loss of immune infiltrate in tumours of patients who relapse. Moreover, thousands of novel isoforms were discovered, including a novel PD-L1 transcript encoding for the soluble version of the protein but having a longer 3'UTR than the currently annotated transcript. Finally, we have identified a novel non-coding gene that was over-expressed in patients who experience recurrence. Our data shows that DRS can be used in archival tumour samples to comprehensively characterise tumour transcriptomes, and to reveal novel features that would have been missed by short-read RNAseq.

2023-09-04 | GSE241932 | GEO

Transcriptomic profiling of ccRCC nephrectomy samples by PCR-cDNAseq

Project description:Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer. Following primary tumour resection approximately 30% of patients experience disease recurrence associated with metastasis. To date, long-read RNA sequencing has not been applied to kidney cancer. Here, we used ONT long-read PCR-cDNAseq to profile the transcriptomes of ccRCC archival tumours, 6 of which were from patients who went on to relapse. Our results revealed a loss of immune infiltrate in tumours of patients who relapse. Moreover, thousands of novel isoforms were discovered, including a novel PD-L1 transcript encoding for the soluble version of the protein but having a longer 3'UTR than the currently annotated transcript. Finally, we have identified a novel non-coding gene that was over-expressed in patients who experience recurrence. Our data shows that ONT long-read PCR-cDNAseq can be used in archival tumour samples to comprehensively characterise tumour transcriptomes, and to reveal novel features that would have been missed by short-read RNAseq.

2023-09-04 | GSE242204 | GEO

Illumina RNAseq of ccRCC tumour cell line RCC4

Project description:Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer. Here, we used Illumina RNAseq to profile the transcriptomes of a ccRCC cell line RCC4 treated with pro-inflammatory cytokines. Our results here validates the existence of novel isoforms and genes that were discovered in the archival tumour samples by long-read sequencing. In addition, results here revealed potential tumour origin of these novel isoforms and genes.

2023-10-30 | GSE246408 | GEO

Multi-region copy-number analysis

Project description:Intra-tumour heterogeneity (ITH) foster tumour adaptation and hamper the efficiency of personalised medicine approaches. We investigated the extent of ITH within individual clear cell renal cell carcinomas (ccRCC) by multi-region sampling and copy number analysis. We analyzed 63 tumour regions and 8 normal samples from eight clear cell renal cell carcinomas using Affymetrix SNP6 arrays.

2013-06-04 | GSE47077 | GEO

Long read transcriptome sequencing of ccRCC tumour cell line RCC4

Project description:Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer. To date, long-read RNA sequencing has not been applied to kidney cancer. Here, we used ONT long-read Direct RNA sequencing to profile the transcriptomes of ccRCC cell line RCC4, with and without exposure to pro-inflammatory cytokines. Our results revealed differentially expressed genes induced by the pro-inflammatory cytokines. Moreover, results here revealed potential tumour origin of novel isoforms and genes that were discovered in the archival tumour samples by long-read sequencing.

2023-09-04 | GSE242084 | GEO

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