Dataset Information

An integrated molecular study of clear cell renal cell carcinoma (ccRCC) including whole-genome/exome and RNA sequencing as well as array-based gene expression/copy-number/methylation analyses

ABSTRACT: an integrated molecular study of clear cell renal cell carcinoma (ccRCC) including whole-genome/exome and RNA sequencing as well as array-based gene expression/copy-number/methylation analyses

PROVIDER: EGAS00001000509 | EGA |

REPOSITORIES: EGA

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Publications

ROTS: reproducible RNA-seq biomarker detector-prognostic markers for clear cell renal cell cancer.

Seyednasrollah Fatemeh F Rantanen Krista K Jaakkola Panu P Elo Laura L LL

Nucleic acids research 20150811 1

Recent comprehensive assessments of RNA-seq technology support its utility in quantifying gene expression in various samples. The next step of rigorously quantifying differences between sample groups, however, still lacks well-defined best practices. Although a number of advanced statistical methods have been developed, several studies demonstrate that their performance depends strongly on the data under analysis, which compromises practical utility in real biomedical studies. As a solution, we ...[more]

PMID: 26264667

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Project description:Tumorigenic processes are understood to be driven by epi-/genetic and genomic alterations from single point mutations to chromosomal alterations such as insertions and deletions of nucleotides up to gains and losses of large chromosomal fragments including products of chromosomal rearrangements e.g. fusion genes and proteins. Overall comparisons of copy number alterations (CNAs) present in 48 clear cell renal cell carcinoma (ccRCC) genomes result in ratios of gene losses versus gene gains between 26 ccRCC Fuhrman malignancy grades G1 (ratio 1.25) and 20 G3 (ratio 0.58). Gene losses and gains of 15762 CNA genes are mapped to 795 chromosomal cytoband loci including 280 KEGG pathways. CNAs are classified according to their contribution to Fuhrman tumour gradings G1 and G3. Gene gains and losses turn out to be highly structured processes in ccRCC genomes enabling the subclassification and stratification of ccRCC tumours in a genome-wide manner. CNAs of ccRCC seem to start with common tumour related gene losses flanked by CNAs specifying Fuhrman grade G1 losses and CNA gains favouring grade G3 tumours. The appearance of recurrent CNA signatures implies the presence of causal mechanisms most likely implicated in the pathogenesis and disease-outcome of ccRCC tumours distinguishing lower from higher malignant tumours. Finally, the diagnostic quality of initial 201 genes (108 genes supporting G1 and 93 genes G3 phenotypes) are successfully validated on published Swiss data (GSE19949) leading to a restricted CNA gene set of 171 CNA genes of which 85 genes favour Fuhrman grade G1 and 86 genes Fuhrman grade G3. Regarding these gene sets overall survival decreases with the number of G3 related gene losses plus the total number of gene gains. CNA gene sets presented define an entry to a gene-directed and pathway-related functional understanding of ongoing copy number alterations within and between individual ccRCC tumours leading to CNA genes of prognostic and predictive value.

Dataset Information

An integrated molecular study of clear cell renal cell carcinoma (ccRCC) including whole-genome/exome and RNA sequencing as well as array-based gene expression/copy-number/methylation analyses

Publications

ROTS: reproducible RNA-seq biomarker detector-prognostic markers for clear cell renal cell cancer.

Similar Datasets

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