RESUMO
BACKGROUND: Previous studies identified microRNAs (miRNAs) and messenger RNAs with significantly different expression between normal pancreas and pancreatic cancer (PDAC) tissues. Due to technological limitations of microarrays and real-time PCR systems these studies focused on a fixed set of targets. Expression of other RNA classes such as long intergenic non-coding RNAs or sno-derived RNAs has rarely been examined in pancreatic cancer. Here, we analysed the coding and non-coding transcriptome of six PDAC and five control tissues using next-generation sequencing. RESULTS: Besides the confirmation of several deregulated mRNAs and miRNAs, miRNAs without previous implication in PDAC were detected: miR-802, miR-2114 or miR-561. SnoRNA-derived RNAs (e.g. sno-HBII-296B) and piR-017061, a piwi-interacting RNA, were found to be differentially expressed between PDAC and control tissues. In silico target analysis of miR-802 revealed potential binding sites in the 3' UTR of TCF4, encoding a transcription factor that controls Wnt signalling genes. Overexpression of miR-802 in MiaPaCa pancreatic cancer cells reduced TCF4 protein levels. Using Massive Analysis of cDNA Ends (MACE) we identified differential expression of 43 lincRNAs, long intergenic non-coding RNAs, e.g. LINC00261 and LINC00152 as well as several natural antisense transcripts like HNF1A-AS1 and AFAP1-AS1. Differential expression was confirmed by qPCR on the mRNA/miRNA/lincRNA level and by immunohistochemistry on the protein level. CONCLUSIONS: Here, we report a novel lncRNA, sncRNA and mRNA signature of PDAC. In silico prediction of ncRNA targets allowed for assigning potential functions to differentially regulated RNAs.
Assuntos
Perfilação da Expressão Gênica , Regulação Neoplásica da Expressão Gênica , Sequenciamento de Nucleotídeos em Larga Escala/métodos , MicroRNAs/genética , Neoplasias Pancreáticas/genética , RNA Longo não Codificante/genética , RNA Interferente Pequeno/genética , Células Acinares/metabolismo , Células Acinares/patologia , Sequência de Bases , Estudos de Casos e Controles , Simulação por Computador , Regulação para Baixo/genética , Redes Reguladoras de Genes , Humanos , Imuno-Histoquímica , MicroRNAs/metabolismo , Dados de Sequência Molecular , Proteínas de Neoplasias/genética , Proteínas de Neoplasias/metabolismo , Análise de Sequência com Séries de Oligonucleotídeos , Fases de Leitura Aberta/genética , RNA Longo não Codificante/metabolismo , RNA Mensageiro/genética , RNA Mensageiro/metabolismo , RNA Interferente Pequeno/metabolismo , Reação em Cadeia da Polimerase em Tempo Real , Reprodutibilidade dos Testes , Regulação para Cima/genéticaRESUMO
Alternative polyadenylation (APA) is a widespread mechanism that contributes to the sophisticated dynamics of gene regulation. Approximately 50% of all protein-coding human genes harbor multiple polyadenylation (PA) sites; their selective and combinatorial use gives rise to transcript variants with differing length of their 3' untranslated region (3'UTR). Shortened variants escape UTR-mediated regulation by microRNAs (miRNAs), especially in cancer, where global 3'UTR shortening accelerates disease progression, dedifferentiation and proliferation. Here we present APADB, a database of vertebrate PA sites determined by 3' end sequencing, using massive analysis of complementary DNA ends. APADB provides (A)PA sites for coding and non-coding transcripts of human, mouse and chicken genes. For human and mouse, several tissue types, including different cancer specimens, are available. APADB records the loss of predicted miRNA binding sites and visualizes next-generation sequencing reads that support each PA site in a genome browser. The database tables can either be browsed according to organism and tissue or alternatively searched for a gene of interest. APADB is the largest database of APA in human, chicken and mouse. The stored information provides experimental evidence for thousands of PA sites and APA events. APADB combines 3' end sequencing data with prediction algorithms of miRNA binding sites, allowing to further improve prediction algorithms. Current databases lack correct information about 3'UTR lengths, especially for chicken, and APADB provides necessary information to close this gap. Database URL: http://tools.genxpro.net/apadb/.