Homo sapiens
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ABSTRACT:
PROVIDER: PRJNA556675 | ENA |
REPOSITORIES: ENA
Similar Datasets
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:Introduction: The aim of this pilot study is to establish a radiogenomic characterisation of a clear-cell renal cell carcinoma (ccRCC) subpopulation, focusing on the transcriptomic underpinnings of radiomic features. Materials & Methods: To establish the viability of conducting a combined analysis of both radiomic and genomic data, a pilot cohort of 6 patients with <5cm G2 unilateral non-metastatic T1a-b ccRCC, who underwent surgery, was evaluated. Transcriptomic analysis was conducted through RNA-seq on tumor samples, while radiomic data was extracted from pre-operative 4 phase contrast-enhanced multidetector CT scans. Genomic heterogeneity was assessed with principal component analysis run on unrestricted data, on a clear-cell renal cell carcinoma associated gene list with zero-centered Reads Per Kilobase of transcript, per million mapped reads values. The underlying pathways and gene ontologies were established with enrichment analysis. In addition, Pearson’s correlation between radiomic data and the transcription of significant genes was fitted, and dendrogram and heatmap plots were drawn. Results: Even in a clinically homogeneous population, the employed analyses have demonstrated that RCC should be regarded as an intrinsically heterogeneous disease. The analysis of the radiomic features and gene expression correlation using heatmap and dendrogram showed four distinct radiogenomic correlation patterns: with one including 5 radiomic features, and the other three including 2 features each. Conclusion: The current pilot study is the first investigation demonstrating an innovative radiogenomic characterisation of clear-cell RCC. Based on such observations, further investigation into the radiomic and genomic approaches for the enhanced diagnosis of RCC is warranted.
2019-06-28 | GSE133460 | GEO
Project description:MicroRNAs (miRNAs), non-coding RNAs regulating gene expression, are frequently aberrantly expressed in human cancers. Next-generation deep sequencing technology enables genome-wide expression profiling of known miRNAs and discovery of novel miRNAs at unprecedented quantitative and qualitative accuracy. Deep sequencing was performed on 22 fresh frozen clear cell renal cell carcinoma (ccRCC), 11 non-tumoral renal cortex (NRC) samples and 2 ccRCC cell lines (n=35). The 22 ccRCCs patients belonged to 3 prognostic sub-groups, i.e. Those without disease recurrence, with recurrence and with metastatic disease at diagnosis Deep sequencing was performed on 22 fresh frozen clear cell renal cell carcinoma (ccRCC), 11 non-tumoral renal cortex (NRC) samples and 2 ccRCC cell lines (n=35). The 22 ccRCCs patients belonged to 3 prognostic sub-groups, i.e. Those without disease recurrence, with recurrence and with metastatic disease at diagnosis.
2012-06-21 | E-GEOD-37616 | biostudies-arrayexpress
Project description:LncRNA from metastatic clear cell renal cell carcinoma (ccRCC) compared with non-metastatic clear cell renal carcinoma
| PRJNA349174 | ENA
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:Multi-Omics analysis to gain novel insights into clear cell renal carcinoma aetiology and progression. The DNA methylation data of 121 clear clear renal carcinoma (ccRCC) were integrated with WGS and transcriptomic data using Multi-Omics Factor Analysis (MOFA) to detect the inter-patient variations related to aetiological and disease progression related factors.
2024-06-07 | GSE269180 | 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:Novel single cell technologies have paved the way for the characterization and improved biological understanding of clear cell renal cell carcinoma (ccRCC) where the focus has been mostly on the immunological compartments of the tumor microenvironment (TME). However, the identification of metastatic tumor cell clones, and the stromal compartments of TME of untreated ccRCC patients still remains to be elucidated. Here we perform single-cell RNA-sequencing on treatment naive ccRCC and adjacent normal kidney tissue.
2022-08-18 | GSE178481 | GEO
Project description:To understand the tumor immune microenvironment (TIME), we sequenced CD45+ tumor infiltrating leukocytes (TILs) isolated from three primary and three lung metastatic clear cell renal cell carcinoma (ccRCC) specimens.
2024-12-06 | GSE267835 | GEO
Project description:Renal cell carcinoma (RCC) is among the ten most common malignancies. By far, the most common histology is clear cell (ccRCC). The Cancer Genome Atlas and other large scale sequencing studies of ccRCC have been integral to the current understanding of molecular events underlying RCC and its biology. However, these data sets have focused on primary RCC which often demonstrates indolent behavior. In contrast, metastatic disease is the major cause of mortality associated with ccRCC. However, data sets examining metastatic tumor are sparse. We therefore undertook an integrative analysis of gene expression and DNA methylome profiling of metastatic ccRCC in addition to primary RCC and normal kidney. Integrative analysis of the methylome and transcriptome identified over 30 RCC specific genes whose mRNA expression inversely correlated with promoter methylation including several known targets of hypoxia inducible factors (HIFs). Notably, genes encoding several metabolism-related proteins were identified as differentially regulated via methylation. Collectively, our data provide novel insight into biology of aggressive RCC. Furthermore, they demonstrate a clear role for epigenetics in the promotion of HIF signaling and invasive phenotypes in renal cancer.
2018-10-16 | GSE105288 | GEO