Antisense intronic non-coding RNA levels correlate to the degree of tumor differentiation in prostate cancer

Eduardo M. Reis, Helder I. Nakaya, Rodrigo Louro, Flavio C. Canavez, Áurea V.F. Flatschart, Giulliana T. Almeida, Camila M. Egidio, Apuã C. Paquola, Abimael A. Machado, Fernanda Festa, Denise Yamamoto, Renato Alvarenga, Camille C. Da Silva, Glauber C. Brito, Sérgio D. Simon, Carlos A. Moreira-Filho, Katia R. Leite, Luiz H. Camara-Lopes, Franz S. Campos, Etel GimbaGiselle M. Vignal, Hamza El-Dorry, Mari C. Sogayar, Marcello A. Barcinski, Aline M. Da Silva, Sergio Verjovski-Almeida

Research output: Contribution to journalArticlepeer-review

131 Scopus citations


A large fraction of transcripts are expressed antisense to introns of known genes in the human genome. Here we show the construction and use of a cDNA microarray platform enriched in intronic transcripts to assess their biological relevance in pathological conditions. To validate the approach, prostate cancer was used as a model, and 27 patient tumor samples with Gleason scores ranging from 5 to 10 were analyzed. We find that a considerably higher fraction (6.6%, [23/346]) of intronic transcripts are significantly correlated (P ≤ 0.001) to the degree of prostate tumor differentiation (Gleason score) when compared to transcripts from unannotated genomic regions (1%, [6/539]) or from exons of known genes (2%, [27/1369]). Among the top twelve transcripts most correlated to tumor differentiation, six are antisense intronic messages as shown by orientation-specific RT-PCR or Northern blot analysis with strand-specific riboprobe. Orientation-specific real-time RT-PCR with six tumor samples, confirmed the correlation (P = 0.024) between the low/high degrees of tumor differentiation and antisense intronic RASSF1 transcript levels. The need to use intron arrays to reveal the transcriptome profile of antisense intronic RNA in cancer lias clearly emerged.

Original languageEnglish (US)
Pages (from-to)6684-6692
Number of pages9
Issue number39
StatePublished - Aug 26 2004

All Science Journal Classification (ASJC) codes

  • Molecular Biology
  • Genetics
  • Cancer Research


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