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Uncorrected Version. Published on March 12, 2010 as DOI:10.2353/jmoldx.2010.090116Journal of Molecular Diagnostics, Vol. 12, No. 3, May 2010Copyright American Society for Investigative Pathologyand the Association for Molecular PathologyDOI: 10.2353/jmoldx.2010.090116Bead Array–Based microRNA Expression Profiling ofPeripheral Blood and the Impact of Different RNAIsolation ApproachesAndrea Gaarz,* Svenja Debey-Pascher,*Sabine Classen,* Daniela Eggle,† Birgit Gathof,‡Jing Chen,§ Jian-Bing Fan,§ Thorsten Voss,¶Joachim L. Schultze,* and Andrea Staratschek-Jox*From Life and Medical Sciences (LIMES), Genomics andImmunoregulation,* University of Bonn, Bonn Germany;Department of Internal Medicine I, MTBTI, University of Cologne,Cologne Germany; the Institute for Transfusion Medicine,‡University of Cologne, Cologne, Germany; Illumina, Inc.,§ SanDiego, California; and QIAGEN GmbH,¶ Diagnostic SamplePreparation & Stabilization, R&D Department, Hilden, GermanyBlood-based mRNA expression profiling has alreadybecome an important issue in clinical applications.More recently , the characterization of the small RNAtranscriptome offers additional avenues for diagnostic approaches. However , when applying miRNA expression profiling in routine clinical settings, themethod of RNA preservation and the manner of RNAextraction as well as the reliability of the miRNA profiling procedure have to be carefully considered. Herewe evaluate a recently introduced bead array– basedtechnology as a robust method for the generation ofblood-based human miRNA expression profiles. Importantly the comparison of different RNA extractionstrategies resulted in dissimilar profiles depending onthe RNA extraction method as well as on the underlying source. Expression profiles obtained from peripheral mononuclear cells (PBMCs) substantially differed from those of whole blood samples , wherebyboth sources per se yielded reproducible and reliableresults. Expression profiles were also distinct whenusing either fresh or frozen PBMCs. Moreover RNAsize fractioning resulted in discriminative miRNAexpression profiles compared with total RNA basedprofiles. This study outlines important steps towardthe establishment of a robust strategy for bloodbased miRNA profiling and provides a reliable strategy for its implementation in routine handling fordiagnostic purposes. (J Mol Diagn 2010, 12:000 – 000;DOI: 10.2353/jmoldx.2010.090116)Gene expression profiling has already been widely accepted as a powerful tool to investigate the transcriptomeof a given source to describe disease-specific signaturesas well as to identify pathogenetic relevant genes on itsderegulated transcription. In peripheral blood, gene expression profiling is used to characterize specific signatures for differential diagnosis of hematological neoplasias such as leukemia and also to associate specificblood-based signatures to the occurrence of a variety ofother diseases such as infectious disease, cardiovascular disease, autoimmune disease, and cancer.1 In general, peripheral blood represents an archive of all ongoingprocesses in an organism and is easily accessible in clinicalsettings. Therefore, its use for diagnostic and prognosticapplications is widely established. However, the analysis ofthe blood-derived RNA transcriptome requires serial mandatory preconditions. Most important, the RNA should bestabilized immediately after blood taken because evenshort-time storage of blood cells either at room temperatureor under freezing conditions introduces dramatic changesat least to the mRNA composition.2More recently, the discovery of noncoding small RNAtranscripts including microRNA (miRNA) has opened newpromising avenues for diagnostic implementations of transcriptomics. miRNAs represent a family of functional RNAsof 19 to 23 nucleotides (nt) cleaved from 60- to 110-nthairpin precursor microRNA (pre miRNA) by Dicer, which isa RNase III enzyme.3 Pre miRNAs in turn are processedfrom the primary transcript (pri RNA) by the RNase III Drosha.4 The regulatory role of miRNAs is conducted by translational repression or degradation of specific targetmRNAs.5,6 MiRNAs exert important roles in developmentalSupported in part by a Sofja-Kovalevskaja award from the Alexander vonHumboldt-Foundation (to J.L.S.) and a grant from the Deutsche Krebshilfe(to S.D.-P.).A.G. and S.D.-P. contributed equally to this study.Current address of D.E.: Pharma Research Scientific Informatics,Roche Diagnostics, Penzberg, Germany.Present address of the author Sabine Classen: Miltenyi Biotech GmbH,Genomics Service Department, Bergisch Gladbach Germany.Jing Chen and Jian-Bing Fan are employees and stockholders ofIllumina Inc.Accepted for publication December 14, 2009.Supplemental material for this article can be found on http://jmd.amjpathol.org.Address reprint requests to Priv. Doz. Dr. Andrea Staratschek-Jox or Prof.Dr. Joachim L. Schultze, LIMES (Life and Medical Sciences Bonn), Genomics and Immunoregulation, University of Bonn, Carl Troll Str. 31, D-53115 Bonn,Germany. E-mail: staratschek-jox@uni-bonn.de or j.schultze@ uni-bonn.de.Copyright 2010 by the American Society for Investigative Pathology.1
2 Gaarz et alJMD May 2010, Vol. 12, No. 3processes, cell proliferation, hematopoietic differentiation, regulation of lymphoid subset lineage development, oncogenic transformation, and apoptosis.7 Manyreports have already described altered expression ofmiRNAs in cancer samples compared with normal tissues including breast cancer,8 sarcomas,9 leukemias,10,11 lymphomas,12prostate cancer,13 and autoimmune diseases.14 These data indicate that analyzingmiRNA expression can be used to define tumor subtypes, to identify new clinical and prognostic markers,and to classify human cancer entities. One importantresult of these efforts is that expression profiling derivedfrom miRNAs can be used for cancer classification withmore accuracy than mRNA expression profiles.15 Interestingly, miRNAs were reported to be actively secreted bytumor cells through the formation of microvesicles.16,17Such microvesicles can be traced back in peripheralblood,17 leading to the assumption that peripheral bloodmight be a perfect source to monitor tumor-associatedmiRNA expression signatures for early diagnosis and prediction of therapeutic outcome. Subsequently, most recentlyblood-based disease specific miRNA signatures were identified in lung cancer patients,18 patients suffering from multiplesclerosis,19 as well as in young stroke patients.20Until now, several methods have been developed toallow miRNA identification and quantification includingcloning approaches,3,21 Northern blots,22,23 real-timePCR,24 bead-based flow cytometric approaches,15,25and customized microarray-based methods.26 –28 Technical issues regarding high-throughput miRNA expression profiling are discussed by various authors.29,30 Withregard to peripheral blood, most of these studies werebased on RNA extracted from either whole blood or extracted peripheral blood mononuclear cells (PBMCs).More recently, a bead array– based assay was introduced comprising 735 human miRNAs allowing highthroughput expression profiling in a large number of samples.31 In the present study we evaluated this newlyintroduced array platform for miRNA expression profiling ofperipheral blood. We assessed miRNA expression in wholeblood as well as in separated PBMCs from healthy individuals. To evaluate the performance of the microarray westudied several aspects of technical reproducibility of thearray results, the effect of different normalization approaches, and the influence of total RNA input amount onmiRNA expression pattern results. Moreover, we addressedthe question whether the enrichment of small RNA fractionin comparison with the use of total RNA improves results ofmiRNA expression profiling by, e.g., reducing nonspecifichybridization of longer miRNA precursors or interference oftarget mRNA molecules within the assay. The influence ofcryopreservation of isolated PBMCs on miRNA expressionprofiles was investigated by comparing cryopreserved PBMCs to their directly lysed matched counterparts. Furthermore, we compared whole blood– derived PAXgene-basedRNA to a TRIZOL-based approach using PBMCs. Microarray expression values were exemplarily validated by qPCRof selected miRNA sequences. Our comprehensive miRNAscreen is intended to serve as a reference for future studiesassessing peripheral blood in the context of diagnosis andmonitoring of certain diseases in clinical studies.Materials and MethodsSubject Information and Blood SampleCollectionBlood samples from 29 apparently healthy blood donorswere collected in two cell preparation tubes with sodiumcitrate (CPT, Becton Dickinson, Heidelberg, Germany)after written informed consent had been obtained andafter approval by the institutional review board. PBMCswere prepared following the manufacturer’s protocol.To evaluate the influence of freezing cells in FCS with10% (v/v) DMSO and storage in liquid nitrogen on miRNAstability, one portion of the freshly isolated PBMCs waslysed in TRIZOL姞 reagent (1 ml/1 107 PBMCs, Invitrogen, Karlsruhe, Germany) and stored at 80 C until further processing. The other portion of isolated PBMCs wasresuspended in FCS with 10% (v/v) DMSO (1 ml/1 107PBMCs) and frozen at 80 C. The next day frozen PBMCswere cryopreserved in liquid nitrogen for several days toweeks until further processing.To analyze the difference between total RNA and lessabundant low-molecular-weight (LMW) RNA, we collected blood samples from additional six healthy blooddoners.RNA IsolationTotal RNA from PBMCs stored in TRIZOL姞 was isolatedaccording to the manufacturer’s protocol. For RNA isolation from PBMCs stored in liquid nitrogen, cells wereremoved from liquid nitrogen and transferred to a 37 Cwater bath until thawing. The thawed cell suspension wasquickly transferred to 40 ml chilled RPMI medium andcentrifuged at room temperature at 400 g for 10 minutes.Supernatant was removed, and PBMCs were washedonce with 50 ml of room temperature RPMI and centrifuged at room temperature at 400 g for 10 minutes.Supernatant was completely removed, and cells weresubsequently lysed in TRIZOL姞 reagent. RNA isolationwas then performed according to the manufacturer sprotocol.LMW RNA molecules were enriched using Invitrogen’sPureLink miRNA Isolation Kit (Invitrogen, Karlsruhe, Germany) according to manufacture’s protocol. LMW RNAs(50 to 350 ng) were enriched from 1 to 2 g of total RNAs,and 10 to 70 ng of the enriched RNAs were used forsample labeling and array hybridization.For the comparison of isolation techniques blood samples from six apparently healthy blood donors were collected either in CPT or in PAXgene Blood RNA Tubes(PreAnalytiX, Hombrechtikon, Switzerland). PAXgene BloodRNA Tubes were stored at 20 C until further processing. PBMCs were prepared from CPT following the manufacturer’s protocol and stored at 80 C. Total RNA fromPBMCs was isolated using TRIZOL姞 reagent (Invitrogen)according to the manufacturer’s protocol. RNA from PAXgene Blood RNA Tubes was isolated using the PAXgeneBlood miRNA Version extraction kit.
Blood Based miRNA Expression Profiles3JMD May 2010, Vol. 12, No. 3Analysis of RNA SamplesTotal RNA was quantified by UV-spectroscopy at 260 nm.The quality of the isolated RNA samples was determinedby measuring the A260/A280 ratio, and the integrity of theribosomal 28s and 18s bands was determined by agarose-gel electrophoresis.MiRNA-Microarray ProcedureMicroRNA expression profiling was performed using theMicroRNA Profiling -Test Assay Kit for Sentrix ArrayMatrixes (Illumina, CA). This system is a modification ofthe high throughput gene expression profiling assayDASL姞 (cDNA-mediated annealing, selection, extension,and ligation),32 which provides a novel highly multiplexedassay and 96-sample Sentrix Array Matrix (SAM) readout.The human miRNA panel used contained 735 miRNAspecific oligos detecting 470 well-annotated human miRNAsequences (miRBase: http://microrna.sanger.ac.uk/, version9.1, date of accession 02/2007) and 265 potential miRNAsthat were identified recently.33,34The miRNA microarray assays were generally performed with 500 ng total RNA if not otherwise stated. Allsteps were performed according to the manufacturer sprotocol. In brief, in a first step input RNA is polyadenylated and converted to cDNA using a biotinylated oligo-dTprimer with a universal PCR sequence at its 5 end. In asecond step the biotinylated cDNA is annealed to the 735miRNA-specific oligos. The mixture is bound to streptavidin-conjugated paramagnetic particles to select cDNA/oligo complexes. After washing out mis-hybridized andnon-hybridized oligos, a polymerase is added to extentthe miRNA-specific oligos. Oligos are only extended iftheir 3 bases are complementary to the cognate sequence in the cDNA template.A PCR-based universal amplification of the extendedmiRNA specific primers is then performed, creating fluorescently labeled products. The labeled PCR productscorrespond to specific original miRNAs in the RNA sample. After PCR amplification the single-stranded PCRproducts are prepared for hybridization to the SAM. PCRproducts were hybridized for 16 hours to the beads onthe arrays containing complementary address sequences.After hybridization signal intensities at each address location were measured using Illumina BeadArray Reader 500 (Illumina, CA). The intensities of the signals correspond tothe quantity of the respective miRNA in the original sample.analysis we used quantile normalization implemented inthe Bioconductor affy package.Variable miRNAs were defined by a coefficient of variation (SD/mean) between 0.5 and 10. Determination ofpresent calls was based on the detection P value assessed by Beadstudio software; a miRNA transcript wascalled present if the detection P value was 0.05. Otherwise the miRNA transcript was called absent. Differentially expressed miRNAs were selected using a foldchange/P value filter with the following criteria: Only Pvalues smaller than 0.05 and an expression changehigher than twofold and a difference between mean intensity signals greater 100 were considered statisticallysignificant for further analysis. The Benjamini–Hochbergmethod was used to adjust the raw P values to control thefalse discovery rate. The fold-change was calculated bydividing the mean intensity of the miRNAs in one groupby that in the other group. If this number was less thanone, the negative reciprocal was used.Hierarchical cluster analysis was performed using thehcluster method in R. Before clustering, the data werelog2 transformed. Distances of the samples were calculated using Pearson correlation, and clusters were formedby taking the average of each cluster. Principle componentanalysis was performed using the pcurve package in R.When visualizing principle component analysis results, thefirst three principal components (coordinates) were z-transformed (mean, 0, SD 1) and subsequently plotted in threedimensions.Validation of miRNA Expression ResultsQuantitative (q) PCR analysis of a selected number ofmiRNA targets was performed on the six aforementionedblood samples from healthy donors. Three RNA isolationapproaches were compared: total RNA, enriched smallRNA, and PAXgene-isolated RNA. Twelve miRNAs wereselected (hsa-miR-100, 125a, 125b, 135a, 146a, 150,17-3p, 221, 26a, 31, 93, and 328), and data were produced as described previously31 using those RNA samples that were also analyzed in array based miRNA profiling. Absolute association of normalized miRNA arrayexpression intensities (log10) versus the negative cycletreshhold (Ct) value was explored via Spearman’s correlation coefficient.ResultsStatistical and Bioinformatics AnalysisHigh Technical Reproducibility of the miRNAAssay in Peripheral BloodRaw data extraction of miRNA microarrays was performed with Illumina Beadstudio 3.1.1.0 software usingthe Beadstudio Gene Expression Analysis Module 3.1.8.All further analysis was performed in R statistical software(version 2.8.0) using Bioconductor packages.35 Prioranalysis data quality assessment was performed, andsamples with lower overall intensity distributions and decreased number of miRNA transcripts detected aspresent were excluded from further analysis. For furtherBefore analyzing miRNA expression profiles in peripheralblood we addressed technical aspects of the newly introduced microarray technology. Therefore, the technicalreproducibility of miRNA profiles was evaluated withinand between different SAM devices, which allow theassessment of 735 miRNA profiles of 96 samples in parallel.First, RNA samples derived from PBMCs of 11 differenthealthy donors (biological replicates) were analyzed in triplicates on one SAM (intra-SAM reproducibility), and in the
4 Gaarz et alJMD May 2010, Vol. 12, No. 3next step the same 11 RNA samples used for the intraSAM evaluation were analyzed on two additional SAMs(inter-SAM reproducibility). Before analyzing the data,quality assessment was performed according to the following criteria: lower overall intensity distributions anddecreased number of miRNA transcripts detected aspresent with both expression means and present callsbelow the 10% quantile. In general, good intra-SAM aswell as inter-SAM replication was achieved (Figure 1A).Of the 55 technical replicates, only six replicates wereidentified as hybridization outliers. As demonstrated inSupplemental Figure S1A at http://jmd.amjpathol.org,technical outliers exhibit both decreased median signalintensity and lower amount of present calls in box graphplots. Furthermore, the reduced correlation of the outliersresults in widespread scatter plots, as shown for replicatethree of sample one in comparison with replicates oneand two (see Supplemental Figure S1B at http://jmd.amjpathol.org). These five samples were removed fromfurther analysis. Different normalization procedures werecompared between replicate samples including quantile,variance stabilization normalization (VSN), invariant, andloess normalization (see Materials and Methods). Similarto results published by Rao et al,36 in our miRNA datasetthe highest overall correlation between samples and thelowest variance was observed after quantile normalization (Supplemental Figure S2 at http://jmd.amjpathol.org).Hence, quantile normalization was used in all followinganalyses.The intra- and inter-SAM reproducibility of the replicateswas estimated by calculating the Pearson correlations (r2)for all pair-wise combinations of individual miRNA profileswithin a given sample. The overall mean correlation coefficient in intrareproducibility was 0.9933 0.0066. For interSAM analysis the overall mean correlation coefficient was0.9880 0.0069. Both calculated r2-values are displayed inFigure 1A. Taken together, intra- and inter-SAM reproducibility of the miRNA microarray assay was very high. Toassess whether the variability in miRNA expression amongthe 29 healthy subjects is associated with specific interindividual parameters, we correlated the expression values ofall miRNAs with age and gender (see Supplemental TableS1 at http://jmd.amjpathol.org). Only one miRNA (hsa-miR126*) had a significant moderate correlation with age (r2 0.69), and none was significantly correlated with gender.To test the lowest amount of total RNA derived fromPBMCs, which still yields reliable results in the miRNAassay, a titration experiment was performed using abroad range of input amounts of total RNA (2, 12.5, 25,50, 100, 200, 500 ng) from three healthy individuals,which were tested in triplicates. Analysis of variance wasperformed to assess the reproducibility of miRNA microarray data in the titration experiments by comparingall RNA input amounts below 500 ng against the 500 ngRNA reference, and the correlation within each biologicalreplicate were calculated. As demonstrated in Figure 1B,correlations remained relatively constant when using 100to 500 ng total RNA (mean
MiRNA-Microarray Procedure MicroRNA expression profiling was performed using the MicroRNA Profiling -Test Assay Kit for Sentrix Array Matrixes (Illumina, CA). This system is a modification of the high throughput gene expression profiling assay DASL (cDNA-mediated annealing, selection, extension, and ligation),32 which provides a novel highly .
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