Please note that we have stopped the regular imports of Gene Expression Omnibus (GEO) data into ArrayExpress. This may not be the latest version of this experiment.
E-GEOD-40911 - Expression analysis and in silico characterization of intronic long noncoding RNAs in renal cell carcinoma: emerging functional associations (RCC malignancy)
Released on 21 January 2014, last updated on 13 May 2014
Intronic and intergenic long noncoding RNAs (lncRNAs) are emerging gene expression regulators. The molecular pathogenesis of renal cell carcinoma (RCC) is still poorly understood, and in particular, limited studies are available for intronic lncRNAs expressed in RCC. Microarray experiments were performed with two different custom-designed arrays enriched with probes for lncRNAs mapping to intronic genomic regions. Samples from 18 primary clear cell RCC tumors and 11 nontumor adjacent matched tissues were analyzed with 4k-probes microarrays. Oligoarrays with 44k-probes were used to interrogate 17 RCC samples (14 clear cell, 2 papillary, 1 chromophobe subtypes) split into four pools. Meta-analyses were performed by taking the genomic coordinates of the RCC-expressed lncRNAs, and cross-referencing them with microarray expression data from three additional human tissues (normal liver, prostate tumor and kidney nontumor samples), and with large-scale public data for epigenetic regulatory marks and for evolutionarily conserved sequences. A signature of 29 intronic lncRNAs differentially expressed between RCC and nontumor samples was obtained (false discovery rate (FDR) <5%). An additional signature of 26 intronic lncRNAs significantly correlated with the RCC five-year patient survival outcome was identified (FDR <5%, p-value ≤0.01). We identified 4303 intronic antisense lncRNAs expressed in RCC, of which 25% were cis correlated (r >|0.6|) with the expression of the mRNA in the same locus across three human tissues. Gene Ontology (GO) analysis of those loci pointed to ‘regulation of biological processes’ as the main enriched category. A module map analysis of all expressed protein-coding genes in RCC that had a significant (r ≥|0.8|) trans correlation with the 20% most abundant lncRNAs identified 35 relevant (p <0.05) GO sets. In addition, we determined that 60% of these lncRNAs are evolutionarily conserved. At the genomic loci containing the intronic RCC-expressed lncRNAs, a strong association (p <0.001) was found between their transcription start sites and genomic marks such as CpG islands and histones methylation and acetylation. Intronic antisense lncRNAs are widely expressed in RCC tumors. Some of them are significantly altered in RCC in comparison with nontumor samples. The majority of these lncRNAs is evolutionarily conserved and possibly modulated by epigenetic modifications. Our data suggest that these RCC lncRNAs may contribute to the complex network of regulatory RNAs playing a role in renal cell malignant transformation. A total of 22 human kidney tissue samples consisting of 11 primary renal tumors and 11 matched adjacent nontumor tissues from clear cell renal cell carcinmoa (RCC) patients were evaluated in this study. We compared the expression profiles of tumor and non-tumor samples obtained from patients with clear cell RCC to evaluate a possible correlation of the lncRNAs with renal malignancy. The set of clear cell RCC expression profiles was generated using a custom-designed cDNA microarray platform with 4,608 unique elements in replicate (9,216) enriched in gene fragments that map to intronic regions of known human genes (GPL3985).
transcription profiling by array
Angela A. Fachel <email@example.com>, Ana C Tahira, Angela A Fachel, Eduardo M Reis, Etel R Gimba, Franz S Campos, Giselle M Vignal, Santiago A Vilella-Arias, Sergio Verjovski-Almeida, Vinicius Maracaja-Coutinho
Expression analysis and in silico characterization of intronic long noncoding RNAs in renal cell carcinoma: emerging functional associations. Fachel AA, Tahira AC, Vilella-Arias SA, Maracaja-Coutinho V, Gimba ER, Vignal GM, Campos FS, Reis EM, Verjovski-Almeida S. , PMID:24238219