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Methylation microarray data of human clear cell renal cell carcinoma

ABSTRACT: Human tumor cell lines are important tools in tumor biological studies, here the authors report the establishment and characterization of 7 new ccRCC stable cell lines with complete clinical data. Gene expression and methylation were profiled with microarrays between the new cells and those had a finite in vitro life span, and the results prompt that genes such as SLC34A2 and VHL play key roles in the continuous in vitro growth and development of ccRCC. In order to find out what genetic features are related to the successful establishment of stable cell lines, early stage cells of 5 stable cell lines (UT14(P2), UT16(P2), UT33a(P3), UT48(P2), UT56(P1) ), named as P group and 5 finite cell lines (UT13a(P3), UT27(P3), UT37(P2), UT41(P2), UT54(P3) ) which could not be cultured more than 10 generations named as N group were chosen to do gene expression chip. Features such as age, gender, tumor size and Fuhrman nuclear grading were matched in these two groups.

ORGANISM(S): Homo sapiens

PROVIDER: GSE89648 | GEO | 2017/11/04

SECONDARY ACCESSION(S): PRJNA352797

REPOSITORIES: GEO

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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.

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Methylation microarray data of human clear cell renal cell carcinoma

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