Alberto Risueño Pérez - Gredos - Universidad de Salamanca

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Risueño et al. BMC Bioinformatics 2010, 11:221 http://www.biomedcentral.com/1471-2105/11/221 probes reduces cross-platform inconsistencies in cancer-associated gene expression measurements. BMC Bioinformatics 2005, 6:107. 26. Leong HS, Yates T, Wilson C, Miller CJ: ADAPT: a database of affymetrix probesets and transcripts. Bioinformatics 2005, 21:2552-2553. 27. Lu J, Lee JC, Salit ML, Cam MC: Transcript-based redefinition of grouped oligonucleotide probe sets using AceView: high-resolution annotation for microarrays. BMC Bioinformatics 2007, 8:108. 28. Liu H, Zeeberg BR, Qu G, Koru AG, Ferrucci A, Kahn A, Ryan MC, Nuhanovic A, Munson PJ, Reinhold WC, Kane DW, Weinstein JN: AffyProbeMiner: a web resource for computing or retrieving accurately redefined Affymetrix probe sets. Bioinformatics 2007, 23:2385-2390. 29. Ferrari F, Bortoluzzi S, Coppe A, Sirota A, Safran M, Shmoish M, Ferrari S, Lancet D, Danieli GA, Bicciato S: Novel definition files for human GeneChips based on GeneAnnot. BMC Bioinformatics 2007, 8:446. 30. Yates T, Okoniewski MJ, Miller CJ: X:Map: annotation and visualization of genome structure for Affymetrix exon array analysis. Nucleic Acids Res 2008, 36:D780-786. 31. Gellert P, Uchida S, Braun T: Exon Array Analyzer: a web interface for Affymetrix exon array analysis. Bioinformatics 2009, 25:3323-3324. doi: 10.1186/1471-2105-11-221 Cite this article as: Risueño et al., GATExplorer: Genomic and Transcriptomic Explorer; mapping expression probes to gene loci, transcripts, exons and ncRNAs BMC Bioinformatics 2010, 11:221 Page 12 of 12
ORIGINAL ARTICLE Deregulation of microRNA expression in the different genetic subtypes of multiple myeloma and correlation with gene expression profiling NC Gutiérrez 1,4 , ME Sarasquete 1,4 , I Misiewicz-Krzeminska 1 , M Delgado 1 , J De Las Rivas 2 , FV Ticona 1 , E Fermiñán 3 , P Martín-Jiménez 1 , C Chillón 1 , A Risueño 2 , JM Hernández 1 , R García-Sanz 1 , M González 1 and JF San Miguel 1 1 Servicio de Hematología, Hospital Universitario, Centro de Investigación del Cáncer-IBMCC (USAL-CSIC), Salamanca, Spain; 2 Grupo de Bioinformática y Genómica Funcional, Centro de Investigación del Cáncer-IBMCC (USAL-CSIC), Salamanca, Spain and 3 Unidad de Genómica, Centro de Investigación del Cáncer-IBMCC (USAL-CSIC), Salamanca, Spain Specific microRNA (miRNA) signatures have been associated with different cytogenetic subtypes in acute leukemias. This finding prompted us to investigate potential associations between genetic abnormalities in multiple myeloma (MM) and singular miRNA expression profiles. Moreover, global gene expression profiling was also analyzed to find correlated miRNA gene expression and select miRNA target genes that show such correlation. For this purpose, we analyzed the expression level of 365 miRNAs and the gene expression profiling in 60 newly diagnosed MM patients, selected to represent the most relevant recurrent genetic abnormalities. Supervised analysis showed significantly deregulated miRNAs in the different cytogenetic subtypes as compared with normal PC. It is interesting to note that miR-1 and miR-133a clustered on the same chromosomal loci, were specifically overexpressed in the cases with t(14;16). The analysis of the relationship between miRNA expression and their respective target genes showed a conserved inverse correlation between several miRNAs deregulated in MM cells and CCND2 expression level. These results illustrate, for the first time, that miRNA expression pattern in MM is associated with genetic abnormalities, and that the correlation of the expression profile of miRNA and their putative mRNA targets is useful to find statistically significant protein-coding genes in MM pathogenesis associated with changes in specific miRNAs. Leukemia (2010) 24, 629–637; doi:10.1038/leu.2009.274; published online 7 January 2010 Keywords: microRNA; myeloma; gene expression Introduction The genetics of multiple myeloma (MM) has been increasingly investigated in recent years. 1,2 Genomic data generated by high-throughput technologies in the last decade, particularly by gene expression profiling analysis, has contributed to demonstrate the enormous genetic diversity exhibited by MM 3–6 and genetic classifications which incorporate genomic signatures, cyclin D expression, ploidy status and translocations of the immunoglobulin heavy-chain gene (IGH) have been proposed. Their final goal is to identify a connection between clinical behaviour of MM patients and biological features of myeloma cells to eventually individualize treatment. 5,6 However, all these advances in the understanding of MM biology are not sufficient to explain the genesis and evolution of this malignancy. The discovery of small non-coding RNAs called microRNAs Correspondence: Professor JF San Miguel, Hospital Universitario de Salamanca, Paseo de San Vicente, 58-182, Salamanca 37007, Spain. E-mail: sanmigiz@usal.es 4 These authors contributed equally to this work. Received 9 June 2009; revised 27 October 2009; accepted 12 November 2009; published online 7 January 2010 Leukemia (2010) 24, 629–637 & 2010 Macmillan Publishers Limited All rights reserved 0887-6924/10 $32.00 www.nature.com/leu (miRNA), which control gene expression at post-transcriptional level, by degrading or repressing target mRNAs, revealed a new mechanism of gene regulation. 7,8 It is well-known that miRNAs are involved in critical biological processes, including cellular growth and differentiation. 9 miRNA expression patterns have been explored in several hematological malignancies, such as chronic lymphocytic leukemia 10,11 and acute myeloid leukemia; 12,13 however, the available information in MM is limited. 14,15 Pichiorri et al, 14 have recently investigated the possible role of miRNA in the malignant transformation of plasma cells (PCs) using 49 MM-derived cell lines and a small number of MM (16) and monoclonal gammopathies of undetermined significance (6) patients. In acute leukemias and recently in chronic lymphocytic leukemia, specific miRNA signatures have been associated with different genetic subtypes. 12,13,16–18 Following this approach, we wanted to search for such types of associations in MM patients. For this purpose, we have investigated the expression level of 365 miRNAs by quantitative PCR in 60 primary MM patient samples, specifically selected according to their cytogenetic features, in order to include the most relevant genetic abnormalities in MM. Although animal miRNAs were initially reported to function as translational repressors without mRNA cleavage, it is now evident that miRNAs can also induce mRNA degradation, even if the target sites do not have complete complementarity to the miRNA. 19,20 These findings prompted us to investigate the global gene expression profiling in the same 60 patients to look for candidate mRNAs that were susceptible to miRNA induced knockdown. Our results show the presence of deregulation in miRNA expression of MM cells, which seems to be associated with cytogenetic abnormalities and correlated with geneexpression changes characteristic of MM genetic subtypes. Materials and methods Patients In all, 60 patients with symptomatic newly diagnosed MM were included in the study. Five healthy controls of bone marrow (BM) samples were obtained from subjects undergoing BM harvest for allogeneic transplantation. In all the BM samples a CD138 positive PC isolation using the AutoMACs automated separation system (Miltenyi-Biotec, Auburn, CA, USA) was carried out (purity was above 90%). All patients as well as healthy donors provided written informed consent in accordance with the Helsinki Declaration, and the research ethics committee of the University Hospital of Salamanca approved the study. The total 65 samples were analyzed from both miRNAs and mRNA gene expression profiling.
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Introducción general Bioinformáti
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Alberto Risueño Pérez - Gredos - Universidad de Salamanca

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