Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA312839 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:LncRNA from metastatic clear cell renal cell carcinoma (ccRCC) compared with non-metastatic clear cell renal carcinoma
| PRJNA349174 | ENA
Project description:While early stages of clear cell renal cell carcinoma (ccRCC) are curable, survival outcome for metastatic ccRCC remains poor. The purpose of the current study was to apply a new individualized bioinformatics analysis (IBA) strategy to these transcriptome data in conjunction with Gene Set Enrichment Analysis of the Connectivity Map (C-MAP) database to identify and reposition FDA-approved drugs for anti-cancer therapy. We demonstrated that one of the drugs predicted to revert the RCC gene signature towards normal kidney, pentamidine, is effective against RCC cells in culture and in a RCC xenograft model. Most importantly, pentamidine slows tumor growth in the 786-O human ccRCC xenograft mouse model. To determine which genes are regulated by pentamidine in a human RCC cell line, 786-O, we treated these cells with pentamidine and performed transcriptional profiling analysis. We used microarrays to determine the set of genes regulated by pentamidine in 786-O renal cell cancer cells. Total RNA was isolated from 786-O cells treated with 25 μM pentamidine or vehicle control (DMSO) for 6 hours and hybridized to Affymetrix microarrays.
2014-08-05 | E-GEOD-54709 | biostudies-arrayexpress
Project description:While early stages of clear cell renal cell carcinoma (ccRCC) are curable, survival outcome for metastatic ccRCC remains poor. The purpose of the current study was to apply a new individualized bioinformatics analysis (IBA) strategy to these transcriptome data in conjunction with Gene Set Enrichment Analysis of the Connectivity Map (C-MAP) database to identify and reposition FDA-approved drugs for anti-cancer therapy. We demonstrated that one of the drugs predicted to revert the RCC gene signature towards normal kidney, pentamidine, is effective against RCC cells in culture and in a RCC xenograft model. Most importantly, pentamidine slows tumor growth in the 786-O human ccRCC xenograft mouse model. To determine which genes are regulated by pentamidine in a human RCC cell line, 786-O, we treated these cells with pentamidine and performed transcriptional profiling analysis. We used microarrays to determine the set of genes regulated by pentamidine in 786-O renal cell cancer cells.
2014-08-05 | GSE54709 | GEO
Project description:We are examining the regulatory pathway of ZHX2 and p65 in clear cell renal cell carcinoma cell line 786-O
2018-06-30 | GSE110094 | GEO
Project description:To understand the relationship of radiomic and transcriptomic features of metastatic clear cell renal cell carcinoma, we performed RNA-sequencing in clear cell renal cell carcinomas (ccRCCs).
2019-09-30 | GSE135091 | GEO
Project description:We performed a microRNA (miRNA) microarray on 10 metastatic RCC tumors and compared differential miRNA expresison to 19 primary clear cell renal cell carcinomas (ccRCC). We found there were 65 significantly dysregulated miRNAs; 9 miRNAs were significantly upregulated and 56 miRNAs were significantly downregulated in metastatic RCC when compared to primary clear cell renal cell carcinoma. miRNA microarray was performed on 10 metastatic RCC tumors
2012-08-13 | E-GEOD-39440 | biostudies-arrayexpress
Project description:In recent years, genome wide RNA expression analysis has become a routine tool that offers a great opportunity to study and understand the key role of genes that contribute to carcinogenesis. Various microarray platforms and statistical approaches are implemented to identify genes that might serve as prognostic bio-markers and used for anti-tumor therapies in future. Metastatic renal cell carcinoma (mRCC) is a serious life-threatening disease. There are few treatment options for metastatic RCC patients. We performed one-color microarray gene expression (4X44K) analysis of metastatic RCC cell line Caki-1 and healthy kidney cell line ASE-5063. 1921 genes were differentially expressed in Caki-1 cell line (1023 up-regulated and 898 down-regulated). Gene set enrichment analysis (GSEA) and Ingenuity Pathway Analysis (IPA) approach was used to analyse these differentially expressed data from Caki-1. The objective of this research is to identify complex biological changes that occur during metastatic development using Caki-1 as a model RCC cell line. Our data suggests that there are multiple de-regulated pathways associated with mccRCC including ILK Signaling, Leukocyte Extravasation Signaling, IGF-1 Signaling, CXCR4 Signaling, and PI3K/AKT Signaling. The IPA upstream analysis predicted top transcriptional regulators which are wither activated or inhibited such as ER, TP53, KDM5B, SPDEF, CDKN1A. The GSEA approach was used to further confirm enriched pathway data following IPA analysis.
2016-06-17 | GSE78179 | GEO
Project description:We performed a microRNA (miRNA) microarray on 10 metastatic RCC tumors and compared differential miRNA expresison to 19 primary clear cell renal cell carcinomas (ccRCC). We found there were 65 significantly dysregulated miRNAs; 9 miRNAs were significantly upregulated and 56 miRNAs were significantly downregulated in metastatic RCC when compared to primary clear cell renal cell carcinoma.
2012-08-14 | GSE39440 | GEO
Project description:The aim of this study was to investigate the effect of VEGF targeted therapy (sunitinib) on intratumoral heterogeneity (ITH) in metastatic clear cell renal cancer (mRCC). 138 samples from patients with clear cell renal cell carcinoma, including biological replicates of nephrectomy samples. RNA extracted fresh frozen tissue samples.
2015-05-25 | E-GEOD-65615 | biostudies-arrayexpress
Project description:Clear cell papillary renal cell carcinoma (CCPRCC) is a low-grade renal neoplasm with morphological characteristics mimicking both clear cell renal cell carcinoma (CCRCC) and papillary renal cell carcinoma (PRCC). However, despite some overlapping features, their morphological, immunohistochemical, and molecular profiles are distinct. To better understand the biology of this tumor, we analyze the miRNA expression profiles of a set of CCPRCC by microarrays.
2017-02-28 | GSE95385 | GEO