03230nas a2200709 4500008004100000022001400041245010600055210006900161260001600230300001100246490000800257520120600265653001801471653002001489653002401509653002101533653001101554653003001565653004301595653001801638653001101656653001401667653002101681653002201702653002101724653001901745653002201764100001501786700002101801700001801822700002601840700001901866700001401885700002001899700002501919700002301944700002001967700002601987700002102013700001702034700001802051700001502069700001602084700001602100700002402116700001802140700002402158700002902182700002002211700002502231700002402256700002202280700001802302700001802320700002002338700002202358700002302380700003002403700002002433700001902453856004802472 2008 eng d a1091-649000aGenomic and epigenetic alterations deregulate microRNA expression in human epithelial ovarian cancer.0 aGenomic and epigenetic alterations deregulate microRNA expressio c2008 May 13 a7004-90 v1053 a
MicroRNAs (miRNAs) are an abundant class of small noncoding RNAs that function as negative gene regulators. miRNA deregulation is involved in the initiation and progression of human cancer; however, the underlying mechanism and its contributions to genome-wide transcriptional changes in cancer are still largely unknown. We studied miRNA deregulation in human epithelial ovarian cancer by integrative genomic approach, including miRNA microarray (n = 106), array-based comparative genomic hybridization (n = 109), cDNA microarray (n = 76), and tissue array (n = 504). miRNA expression is markedly down-regulated in malignant transformation and tumor progression. Genomic copy number loss and epigenetic silencing, respectively, may account for the down-regulation of approximately 15% and at least approximately 36% of miRNAs in advanced ovarian tumors and miRNA down-regulation contributes to a genome-wide transcriptional deregulation. Last, eight miRNAs located in the chromosome 14 miRNA cluster (Dlk1-Gtl2 domain) were identified as potential tumor suppressor genes. Therefore, our results suggest that miRNAs may offer new biomarkers and therapeutic targets in epithelial ovarian cancer.
10aDNA, Neoplasm10aDown-Regulation10aEpigenesis, Genetic10aEpithelial Cells10aFemale10aGene Expression Profiling10aGene Expression Regulation, Neoplastic10aGenome, Human10aHumans10aMicroRNAs10aNeoplasm Staging10aOvarian Neoplasms10aRibonuclease III10aRNA, Messenger10aSurvival Analysis1 aZhang, Lin1 aVolinia, Stefano1 aBonome, Tomas1 aCalin, George, Adrian1 aGreshock, Joel1 aYang, Nuo1 aLiu, Chang-Gong1 aGiannakakis, Antonis1 aAlexiou, Pangiotis1 aHasegawa, Kosei1 aJohnstone, Cameron, N1 aMegraw, Molly, S1 aAdams, Sarah1 aLassus, Heini1 aHuang, Jia1 aKaur, Sippy1 aLiang, Shun1 aSethupathy, Praveen1 aLeminen, Arto1 aSimossis, Victor, A1 aSandaltzopoulos, Raphael1 aNaomoto, Yoshio1 aKatsaros, Dionyssios1 aGimotty, Phyllis, A1 aDeMichele, Angela1 aHuang, Qihong1 aBützow, Ralf1 aRustgi, Anil, K1 aWeber, Barbara, L1 aBirrer, Michael, J1 aHatzigeorgiou, Artemis, G1 aCroce, Carlo, M1 aCoukos, George uhttp://megraw.cgrb.oregonstate.edu/node/32802198nas a2200301 4500008004100000022001400041245009100055210006900146260001300215300001200228490000700240520133700247653001201584653003701596653002801633653001301661653001101674653001301685653000901698653001401707653000901721653002801730100001801758700002401776700001801800700003001818856004801848 2007 eng d a1362-496200amiRGen: a database for the study of animal microRNA genomic organization and function.0 amiRGen a database for the study of animal microRNA genomic organ c2007 Jan aD149-550 v353 amiRGen is an integrated database of (i) positional relationships between animal miRNAs and genomic annotation sets and (ii) animal miRNA targets according to combinations of widely used target prediction programs. A major goal of the database is the study of the relationship between miRNA genomic organization and miRNA function. This is made possible by three integrated and user friendly interfaces. The Genomics interface allows the user to explore where whole-genome collections of miRNAs are located with respect to UCSC genome browser annotation sets such as Known Genes, Refseq Genes, Genscan predicted genes, CpG islands and pseudogenes. These miRNAs are connected through the Targets interface to their experimentally supported target genes from TarBase, as well as computationally predicted target genes from optimized intersections and unions of several widely used mammalian target prediction programs. Finally, the Clusters interface provides predicted miRNA clusters at any given inter-miRNA distance and provides specific functional information on the targets of miRNAs within each cluster. All of these unique features of miRGen are designed to facilitate investigations into miRNA genomic organization, co-transcription and targeting. miRGen can be freely accessed at http://www.diana.pcbi.upenn.edu/miRGen.
10aAnimals10aData Interpretation, Statistical10aDatabases, Nucleic Acid10aGenomics10aHumans10aInternet10aMice10aMicroRNAs10aRats10aUser-Computer Interface1 aMegraw, Molly1 aSethupathy, Praveen1 aCorda, Benoit1 aHatzigeorgiou, Artemis, G uhttp://megraw.cgrb.oregonstate.edu/node/32901507nas a2200301 4500008004100000022001400041245010700055210006900162260001300231300001000244490000600254520059300260653002800853653002800881653001200909653002600921653001900947653001100966653001400977653003000991653001901021653003201040653001301072100002401085700001801109700003001127856004801157 2006 eng d a1548-709100aA guide through present computational approaches for the identification of mammalian microRNA targets.0 aguide through present computational approaches for the identific c2006 Nov a881-60 v33 aComputational microRNA (miRNA) target prediction is a field in flux. Here we present a guide through five widely used mammalian target prediction programs. We include an analysis of the performance of these individual programs and of various combinations of these programs. For this analysis we compiled several benchmark data sets of experimentally supported miRNA-target gene interactions. Based on the results, we provide a discussion on the status of target prediction and also suggest a stepwise approach toward predicting and selecting miRNA targets for experimental testing.
10a3' Untranslated Regions10a5' Untranslated Regions10aAnimals10aComputational Biology10aGene Targeting10aHumans10aMicroRNAs10aPredictive Value of Tests10aRNA, Messenger10aSensitivity and Specificity10aSoftware1 aSethupathy, Praveen1 aMegraw, Molly1 aHatzigeorgiou, Artemis, G uhttp://megraw.cgrb.oregonstate.edu/node/330