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Profiling MicroRNA Expression in Hepatocellular Carcinoma Reveals MicroRNA-224 Up-regulation and Apoptosis Inhibitor-5 as a MicroRNA-224-specific Target

2008; Elsevier BV; Volume: 283; Issue: 19 Linguagem: Inglês

10.1074/jbc.m707629200

ISSN

1083-351X

Autores

Yu Wang, Alvin T.C. Lee, Z. Joel, Jingbo Wang, Jianwei Ren, Yuchen Yang, Erwin Tantoso, Kuo-Bin Li, London Lucien Ooi, Patrick Tan, Caroline Lee,

Tópico(s)

Cancer-related molecular mechanisms research

Resumo

Like other cancers, aberrant gene regulation features significantly in hepatocellular carcinoma (HCC). MicroRNAs (miRNAs) were recently found to regulate gene expression at the post-transcriptional/translational levels. The expression profiles of 157 miRNAs were examined in 19 HCC patients, and 19 up-regulated and 3 down-regulated miRNAs were found to be associated with HCC. Putative gene targets of these 22 miRNAs were predicted in silico and were significantly enriched in 34 biological pathways, most of which are frequently dysregulated during carcinogenesis. Further characterization of microRNA-224 (miR-224), the most significantly up-regulated miRNA in HCC patients, revealed that miR-224 increases apoptotic cell death as well as proliferation and targets apoptosis inhibitor-5 (API-5) to inhibit API-5 transcript expression. Significantly, miR-224 expression was found to be inversely correlated with API-5 expression in HCC patients (p < 0.05). Hence, our findings define a true in vivo target of miR-224 and reaffirm the important role of miRNAs in the dysregulation of cellular processes that may ultimately lead to tumorigenesis. Like other cancers, aberrant gene regulation features significantly in hepatocellular carcinoma (HCC). MicroRNAs (miRNAs) were recently found to regulate gene expression at the post-transcriptional/translational levels. The expression profiles of 157 miRNAs were examined in 19 HCC patients, and 19 up-regulated and 3 down-regulated miRNAs were found to be associated with HCC. Putative gene targets of these 22 miRNAs were predicted in silico and were significantly enriched in 34 biological pathways, most of which are frequently dysregulated during carcinogenesis. Further characterization of microRNA-224 (miR-224), the most significantly up-regulated miRNA in HCC patients, revealed that miR-224 increases apoptotic cell death as well as proliferation and targets apoptosis inhibitor-5 (API-5) to inhibit API-5 transcript expression. Significantly, miR-224 expression was found to be inversely correlated with API-5 expression in HCC patients (p < 0.05). Hence, our findings define a true in vivo target of miR-224 and reaffirm the important role of miRNAs in the dysregulation of cellular processes that may ultimately lead to tumorigenesis. Hepatocellular carcinoma (HCC) 5The abbreviations used are: HCC, hepatocellular carcinoma; miRNA, microRNA; RQ, relative quantity; GO, gene ontology; BrdUrd, bromode-oxyuridine; UTR, untranslated region; β-gal, β-galactosidase; MRP1, multidrug resistance-associated protein 1; EGFP, enhanced green fluorescence protein; PE, phycoerythrin. 5The abbreviations used are: HCC, hepatocellular carcinoma; miRNA, microRNA; RQ, relative quantity; GO, gene ontology; BrdUrd, bromode-oxyuridine; UTR, untranslated region; β-gal, β-galactosidase; MRP1, multidrug resistance-associated protein 1; EGFP, enhanced green fluorescence protein; PE, phycoerythrin. is among the top 10 most prevalent cancers worldwide (1Seeff L.B. Hoofnagle J.H. Oncogene. 2006; 25: 3771-3777Crossref PubMed Scopus (143) Google Scholar), accounting for ∼600,000 deaths annually (2Parkin D.M. Bray F. Ferlay J. Pisani P. CA-Cancer J. Clin. 2005; 55: 74-108Crossref PubMed Scopus (17301) Google Scholar). The overall 5-year survival rate for HCC patients is less than 5% (3El-Serag H.B. Mason A.C. Key C. Hepatology. 2001; 33: 62-65Crossref PubMed Scopus (342) Google Scholar). Chemotherapeutic interventions are ineffective, and surgical resection/liver transplantation is the only treatment modality to confer survival benefit in HCC patients. Late clinical presentations have also led to poor prognosis for HCC patients. It is thus necessary to elucidate the molecular mechanisms underlying HCC and identify novel therapeutic targets and biomarkers for the early detection of HCC. Like other cancers, aberrant gene regulation features significantly in HCC. Several reports on gene expression profiling of HCC patients have identified numerous pathways (e.g. proliferation, cell cycle regulation, apoptosis, angiogenesis, etc.) that may be dysregulated during hepatocarcinogenesis (see review in Ref. 4Thorgeirsson S.S. Lee J.S. Grisham J.W. Hepatology. 2006; 43: S145-150Crossref PubMed Scopus (124) Google Scholar). Recently, an increasing number of reports have described a new class of small noncoding RNAs that are implicated in the regulation of gene expression at the post-transcriptional and translational level. These regulators are termed microRNAs (miRNAs), and their dysregulation may have implications in carcinogenesis. miRNAs represent a class of noncoding RNAs whose processed products are ∼22 nucleotides in length and regulate gene expression in plants and animals (5Ambros V. Nature. 2004; 431: 350-355Crossref PubMed Scopus (9048) Google Scholar). To date, more than 500 miRNAs are predicted to be expressed in humans (6Griffiths-Jones S. Nucleic Acids Res. 2004; 32: D109-D111Crossref PubMed Google Scholar, 7Griffiths-Jones S. Grocock R.J. van Dongen S. Bateman A. Enright A.J. Nucleic Acids Res. 2006; 34: D140-D144Crossref PubMed Scopus (3636) Google Scholar). These miRNAs are estimated to regulate the expression of >5000 human genes or ∼30% of all human proteins (8Lewis B.P. Burge C.B. Bartel D.P. Cell. 2005; 120: 15-20Abstract Full Text Full Text PDF PubMed Scopus (9835) Google Scholar). It is likely that the interaction between miRNAs and their numerous mRNA targets may represent an important level of gene regulatory control in the cell (5Ambros V. Nature. 2004; 431: 350-355Crossref PubMed Scopus (9048) Google Scholar). The importance of miRNAs in cancer is highlighted by the observation that ∼50% of miRNA genes are located in cancer-associated genomic regions or fragile sites (9Calin G.A. Liu C.G. Sevignani C. Ferracin M. Felli N. Dumitru C.D. Shimizu M. Cimmino A. Zupo S. Dono M. Dell'Aquila M.L. Alder H. Rassenti L. Kipps T.J. Bullrich F. Negrini M. Croce C.M. Proc. Natl. Acad. Sci. U. S. A. 2004; 101: 11755-11760Crossref PubMed Scopus (1152) Google Scholar, 10Calin G.A. Sevignani C. Dumitru C.D. Hyslop T. Noch E. Yendamuri S. Shimizu M. Rattan S. Bullrich F. Negrini M. Croce C.M. Proc. Natl. Acad. Sci. U. S. A. 2004; 101: 2999-3004Crossref PubMed Scopus (3570) Google Scholar, 11Sevignani C. Calin G.A. Siracusa L.D. Croce C.M. Mamm. Genome. 2006; 17: 189-202Crossref PubMed Scopus (280) Google Scholar). Importantly, miRNA expression is frequently dysregulated in several cancers including B-cell chronic lymphocytic leukemia (9Calin G.A. Liu C.G. Sevignani C. Ferracin M. Felli N. Dumitru C.D. Shimizu M. Cimmino A. Zupo S. Dono M. Dell'Aquila M.L. Alder H. Rassenti L. Kipps T.J. Bullrich F. Negrini M. Croce C.M. Proc. Natl. Acad. Sci. U. S. A. 2004; 101: 11755-11760Crossref PubMed Scopus (1152) Google Scholar, 12Calin G.A. Dumitru C.D. Shimizu M. Bichi R. Zupo S. Noch E. Aldler H. Rattan S. Keating M. Rai K. Rassenti L. Kipps T. Negrini M. Bullrich F. Croce C.M. Proc. Natl. Acad. Sci. U. S. A. 2002; 99: 15524-15529Crossref PubMed Scopus (4216) Google Scholar), Burkitt lymphoma (13Metzler M. Wilda M. Busch K. Viehmann S. Borkhardt A. Genes Chromosomes Cancer. 2004; 39: 167-169Crossref PubMed Scopus (500) Google Scholar), colorectal cancer (14Michael M.Z. SM O.C. van Holst Pellekaan N.G. Young G.P. James R.J. Mol. Cancer Res. 2003; 1: 882-891PubMed Google Scholar), lung cancer (15Takamizawa J. Konishi H. Yanagisawa K. Tomida S. Osada H. Endoh H. Harano T. Yatabe Y. Nagino M. Nimura Y. Mitsudomi T. Takahashi T. Cancer Res. 2004; 64: 3753-3756Crossref PubMed Scopus (2151) Google Scholar, 16Yanaihara N. Caplen N. Bowman E. Seike M. Kumamoto K. Yi M. Stephens R.M. Okamoto A. Yokota J. Tanaka T. Calin G.A. Liu C.G. Croce C.M. Harris C.C. Cancer Cell. 2006; 9: 189-198Abstract Full Text Full Text PDF PubMed Scopus (2690) Google Scholar), and hepatocellular carcinoma (17Murakami Y. Yasuda T. Saigo K. Urashima T. Toyoda H. Okanoue T. Shimotohno K. Oncogene. 2006; 25: 2537-2545Crossref PubMed Scopus (1029) Google Scholar). Additionally, differential expression of miRNAs have been found to be associated with post-operative survival in lung cancer patients (15Takamizawa J. Konishi H. Yanagisawa K. Tomida S. Osada H. Endoh H. Harano T. Yatabe Y. Nagino M. Nimura Y. Mitsudomi T. Takahashi T. Cancer Res. 2004; 64: 3753-3756Crossref PubMed Scopus (2151) Google Scholar) and are diagnostic and prognostic markers of lung cancer (16Yanaihara N. Caplen N. Bowman E. Seike M. Kumamoto K. Yi M. Stephens R.M. Okamoto A. Yokota J. Tanaka T. Calin G.A. Liu C.G. Croce C.M. Harris C.C. Cancer Cell. 2006; 9: 189-198Abstract Full Text Full Text PDF PubMed Scopus (2690) Google Scholar). miRNAs have been implicated to play both tumor suppressor and oncogenic roles (18Esquela-Kerscher A. Slack F.J. Nat. Rev. Cancer. 2006; 6: 259-269Crossref PubMed Scopus (6186) Google Scholar). Although much is known about the profiles of miRNAs in the various tissues/developmental stages, embryonic stem cell differentiation, brain development, hematopoietic lineage differentiation, as well as their deregulation in various cancers, less is known about the function of each of these miRNAs or their true cellular targets. Numerous algorithms have been developed to predict the putative cellular targets of these miRNAs including PicTar (19Krek A. Grun D. Poy M.N. Wolf R. Rosenberg L. Epstein E.J. MacMenamin P. da Piedade I. Gunsalus K.C. Stoffel M. Rajewsky N. Nat. Genet. 2005; 37: 495-500Crossref PubMed Scopus (3892) Google Scholar), miRBase Targets (7Griffiths-Jones S. Grocock R.J. van Dongen S. Bateman A. Enright A.J. Nucleic Acids Res. 2006; 34: D140-D144Crossref PubMed Scopus (3636) Google Scholar), and TargetScan (8Lewis B.P. Burge C.B. Bartel D.P. Cell. 2005; 120: 15-20Abstract Full Text Full Text PDF PubMed Scopus (9835) Google Scholar). Some of the cellular targets that have been experimentally validated for the various miRNAs are HoxB8 (miR-196) (20Yekta S. Shih I.H. Bartel D.P. Science. 2004; 304: 594-596Crossref PubMed Scopus (1406) Google Scholar), Hand2 (miR-1) (21Zhao Y. Samal E. Srivastava D. Nature. 2005; 436: 214-220Crossref PubMed Scopus (1356) Google Scholar), E2F1 (miR-17–5p and miR-20a) (22O'Donnell K.A. Wentzel E.A. Zeller K.I. Dang C.V. Mendell J.T. Nature. 2005; 435: 839-843Crossref PubMed Scopus (2460) Google Scholar), Hox-A11 (miR-181) (23Naguibneva I. Ameyar-Zazoua M. Polesskaya A. Ait-Si-Ali S. Groisman R. Souidi M. Cuvellier S. Harel-Bellan A. Nat. Cell Biol. 2006; 8: 278-284Crossref PubMed Scopus (503) Google Scholar), LATS2 (miR-372/3) (24Voorhoeve P.M. le Sage C. Schrier M. Gillis A.J. Stoop H. Nagel R. Liu Y.P. van Duijse J. Drost J. Griekspoor A. Zlotorynski E. Yabuta N. De Vita G. Nojima H. Looijenga L.H. Agami R. Cell. 2006; 124: 1169-1181Abstract Full Text Full Text PDF PubMed Scopus (1085) Google Scholar), Rb1 (miR-106a), TGFBR2 (miR-20a) (25Volinia S. Calin G.A. Liu C.G. Ambs S. Cimmino A. Petrocca F. Visone R. Iorio M. Roldo C. Ferracin M. Prueitt R.L. Yanaihara N. Lanza G. Scarpa A. Vecchione A. Negrini M. Harris C.C. Croce C.M. Proc. Natl. Acad. Sci. U. S. A. 2006; 103: 2257-2261Crossref PubMed Scopus (4942) Google Scholar), as well as IRAK1 and TRAF6 (miR-146) (26Taganov K.D. Boldin M.P. Chang K.J. Baltimore D. Proc. Natl. Acad. Sci. U. S. A. 2006; 103: 12481-12486Crossref PubMed Scopus (3513) Google Scholar). Here, we characterized the expression profiles of 157 miRNAs in 19 HCC patients and identified a set of significantly differentially expressed miRNAs associated with HCC. We also functionally characterized one of the differentially expressed miRNAs and identified its gene target. Samples—Paired tumorous and adjacent nontumorous liver tissues from 19 hepatocellular carcinoma patients were obtained from the National Cancer Centre of the Singapore Tissue Repository with prior approval from the National Cancer Centre Institutional Review Board. miRNA Extraction and Expression Profiling—The MirVana™ miRNA isolation kit (Ambion, Austin, TX) was used to isolate total RNA including low molecular weight RNA from patient samples and cell lines according to the manufacturer's protocol. Expression of 157 verified human microRNAs was analyzed using the TaqMan MicroRNA assay human panel early access kit (Applied Biosystems), according to the manufacturer's instructions as previously described (27Bandres E. Cubedo E. Agirre X. Malumbres R. Zarate R. Ramirez N. Abajo A. Navarro A. Moreno I. Monzo M. Garcia-Foncillas J. Mol. Cancer. 2006; 5: 29Crossref PubMed Scopus (772) Google Scholar). Briefly, patient RNA samples were used as template for reverse transcription. Together with the high capacity cDNA archive kit, RNase inhibitors, and miRNA-specific reverse transcription primers (Applied Biosystems), the reverse transcription reactions were carried out in a 96-well plate format. Real time PCR was then performed with the reverse transcription products, TaqMan 2× Universal PCR Master Mix without UNG Amperase (Applied Biosystems), miRNA-specific TaqMan probes, and primers (Applied Biosystems) on an Applied Biosystems 7500 Fast Real Time PCR system with an initial denaturation at 95 °C, followed by 40 cycles at 95 °C for 15 s and 60 °C for 1 min. The threshold cycle (CT) was then determined and defined as the fractional cycle number at which the fluorescence detected passes a fixed threshold. The Applied Biosystems 7500 Fast software was used to analyze the CT values of different miRNAs normalized to an endogenous control (let-7a or U6). The normalized values (dCT) from tumorous tissue were then compared with its paired nontumorous tissue, yielding miRNA differential expression profiles. In Silico Analyses of miRNA Expression Data, Identification of Putative miRNA Targets, and Categorization of Biological Processes of These Putative miRNA Targets—Relative quantitation of the expression of miRNA was determined using the 2-ΔΔCt method (28Livak K.J. Schmittgen T.D. Methods. 2001; 25: 402-408Crossref PubMed Scopus (123392) Google Scholar), and the results were expressed as log2 of the relative quantity (RQ) of the target miRNA normalized against hsa-let-7a (log2RQ). Differentially expressed miRNAs were identified by significant analysis of microarrays (29Tusher V.G. Tibshirani R. Chu G. Proc. Natl. Acad. Sci. U. S. A. 2001; 98: 5116-5121Crossref PubMed Scopus (9751) Google Scholar), with the false discovery rate threshold set at <5%. Clustering and visualization of the normalized data were performed with Cluster and TreeView (30de Hoon M.J. Imoto S. Nolan J. Miyano S. Bioinformatics. 2004; 20: 1453-1454Crossref PubMed Scopus (2336) Google Scholar), using average linkage and Pearson's correlation as a measurement for similarity. Computational identification of the putative miRNA targets was performed using PicTar (19Krek A. Grun D. Poy M.N. Wolf R. Rosenberg L. Epstein E.J. MacMenamin P. da Piedade I. Gunsalus K.C. Stoffel M. Rajewsky N. Nat. Genet. 2005; 37: 495-500Crossref PubMed Scopus (3892) Google Scholar), miRBase Targets Version 3.0 (7Griffiths-Jones S. Grocock R.J. van Dongen S. Bateman A. Enright A.J. Nucleic Acids Res. 2006; 34: D140-D144Crossref PubMed Scopus (3636) Google Scholar), and TargetScan Release 3.0 (8Lewis B.P. Burge C.B. Bartel D.P. Cell. 2005; 120: 15-20Abstract Full Text Full Text PDF PubMed Scopus (9835) Google Scholar). A gene was considered to be a putative target of a given miRNA only if it was predicted by at least two of the three methods. Categorization of the biological processes of the putative miRNA gene target was performed with gene ontology (GO) using the Database for Annotation, Visualization, and Integrated Discovery GoCharts module (31Dennis Jr., G. Sherman B.T. Hosack D.A. Yang J. Gao W. Lane H.C. Lempicki R.A. Genome Biol. 2003; 4: R60Crossref Google Scholar), at level 5 annotations. Validation of the Expression of miR-224 in Tumors of HCC Patients—Northern blot analysis was performed to validate miR-224 overexpression in the tumors of HCC patients. Briefly, 1 μg of total RNA (HCT116 cells transfected with Pre-miR™ miR-224 precursor) or 2 μg of low molecular weight RNA from both the tumor and adjacent nontumorous tissues of a few of the same HCC patients that were previously profiled was separated on a 15% denaturing polyacrylamide gel and electroblotted onto a nylon membrane (Schleicher & Schuell GmbH; Dassel, Germany) at 300 mA for 30 min. The miRNA-224 probe (5′-TAAACGGAACCACTAGTGACTTG-3′ (17Murakami Y. Yasuda T. Saigo K. Urashima T. Toyoda H. Okanoue T. Shimotohno K. Oncogene. 2006; 25: 2537-2545Crossref PubMed Scopus (1029) Google Scholar)) and U6-probe (5′-ATGTGCTGCCGAAGCGAGCAC-3′) were end-labeled with Redivue [γ-32P]ATP (Amersham Biosciences) using T4 Polynucleotide Kinase (New England Biolabs, Ipswich, MA) and purified using the nucleotide removal kit according to the manufacturer's instructions (Qiagen). Hybridization was performed using Express Hybridization solution (Clontech, Mountain View, CA) at 42 °C for 16 h, and the blots were exposed to Hyperfilm MP (Amersham Biosciences). Growth and Viability of HCT116 Cells Transfected with miR-224—The human colon cancer cell line, HCT116, was grown in McCoy's medium supplemented with 10% fetal calf serum at 37 °C in a humidified atmosphere of 5% CO2. To determine the effect of miR-224 on growth and viability properties of HCT116 cells, 4 × 105 cells were transfected with either 30 nm of Pre-miR™ miR-224 precursor molecule (miR-224 precursor) or 30 nm of Pre-miR™ miRNA Precursor Molecules-Negative Control 1 (Control) (AM17110) (Ambion) using siPORT™ amine transfection agent (Ambion) following the manufacturer's protocol. The time when transfection commenced was considered as time 0. Sixteen hours after incubation in medium containing siPORT™ amine transfection agent, these transfected cells were transferred into normal growth medium. Viable cells were determined through trypan blue dye exclusion. The growth properties of these cells were expressed as percentages of viable cells at the respective time points relative to time 0. Viability of these cells was expressed as the percentages of viable cells relative to the total number of cells (both dead and alive) at each individual time point. The results were obtained by counting cells from the same experiment twice in three independent experiments. Apoptotic and Cell Proliferation Properties of HCT116 Cells Transfected with miR-224—HCT116 cells were transfected using siPORT™ amine transfection agent with either 60 nm control or 30 nm miR-224 precursor and 30 nm control or 30 nm miR-224 precursor and 30 nm anti-miRTM miR-224 inhibitor (miR-224 inhibitor; AM17000, Ambion). Apoptosis assay was performed 48 h post-transfection using the Annexin V-PE apoptosis detection kit I (BD Biosciences) according to the manufacturer's protocols and analyzed using a FACSCalibur flow cytometer (BD Biosciences). Apoptotic cells were represented by high PE-Annexin V and low 7-amino-actinomycin fluorescence signals. Cell proliferation assays were performed 24 h post-transfection using the BrdUrd cell proliferation assay kit (Calbiochem, San Diego, CA) following the manufacturer's protocol. BrdUrd incorporation measured as absorbance at A450 in a SpectroMAX PLUS microplate reader (Molecular Devices, Sunnyvale, CA) 48 h after it was added to the cells. Apoptotic Properties of Primary Liver Cell Line Immortalized with SV40 T-antigen, THLE-3, Transfected with miR-224 Inhibitor—To evaluate whether miR-224 influence the apoptotic potential of a primary liver cell line transformed with SV40 T-antigen, THLE-3 cells were transfected in collagen-coated plates with either 60 nm control or 60 nm miR-224 inhibitor using siPORT™ amine transfection agent. The transfected cells were then treated with ∼20 J/m2 UV 24 h post-transfection, and apoptosis assay was performed 48 h after transfection. Generation of the miR-224 Target, API-5 3′-UTR-Reporter Construct—To experimentally validate whether the API-5 gene is an in vivo target of miR-224, the 3′-UTR of the API-5 gene was amplified from nontumorous human liver tissue using primers API5primerF1 and API5primerR1 as shown in supplemental Fig. S1. The 3′-UTR was then cloned downstream to a β-galactosidase (β-gal) reporter gene driven by the human multidrug resistance-associated protein 1 (MRP1) promoter in a construct that also contained the enhanced green fluorescence protein (EGFP) gene for normalization of transfection efficiency (32Wang Z. Wang B. Tang K. Lee E.J. Chong S.S. Lee C.G. Hum. Mol. Genet. 2005; 14: 2075-2087Crossref PubMed Scopus (51) Google Scholar) (see Fig. 3B). The human MRP1 promoter was chosen over the constitutive human cytomegalovirus promoter, because the MRP1 promoter is ∼30 times weaker than the cytomegalovirus promoter (data not shown), which will facilitate the measurement of subtler changes in reporter gene activity. A mutant pAPI5-3UTR-MUT was also generated by PCR mutagenesis using primers as shown in supplemental Fig. S1. Three point mutations were generated on each of the three miR-224 target recognition sites/seed as shown in Fig. 3C. These mutant recognition sites were verified in silico not to bind to any of the known human miRNAs using miRBase (Release 8.1, May 2006). The mutant construct generated was confirmed by sequencing. Characterization of the Effect of miR224 on API-5 3′-UTR-Reporter Construct—HCT116 cells were transfected in 6-well plates by using siPORT™ amine transfection agent (Ambion, Austin, TX) according to the manufacturer's instructions with either 1.0 μg of the β-gal reporter construct containing the wild type 2035-bp 3′-UTR sequence of human API-5 (termed pAPI5-3UTR-WT) or β-gal reporter construct containing the mutant 3′-UTR sequence of human API-5 (termed pAPI5-3UTR-MUT) and co-transfected with either 30 nm of miR-224 precursor (Ambion) or 30 nm of control (Ambion). β-Gal reporter gene activity was assayed kinetically using chlorophenol red-β-d-galactopyranoside as substrate and measured at 1-min intervals over 60 min at 570 nm in a SpectraMAX PLUS microplate reader (Molecular Devices) with crude lysate from the transfected cells harvested 24 h post-transfection. To normalize for differences in transfection efficiencies, Western blot analyses were performed using 0.02 μg/ml mouse anti-EGFP (Roche Applied Science) and 1:100,000 horseradish peroxidase-conjugated goat anti-mouse (Pierce) secondary antibodies. β-Gal activity was then normalized against EGFP expression levels. The data was also normalized against differences in basal β-gal activity when either the pAPI5-3UTR-WT or pAPI5-3UTR-MT construct, but not miR-224 precursor or Control, was transfected. Quantitation of the API-5 mRNA Levels in Patient Samples and HCT116/THLE-3 Cells Transfected with miR-224—Reverse transcription real time PCR was performed to quantitate the API-5 transcript levels in patient samples and transfected HCT116/THLE-3 cells. cDNA was synthesized from total RNA using a high capacity cDNA archive kit (Applied Biosystems) according to the manufacturer's instructions. Real time PCR was performed in an Applied Biosystems 7500 real time PCR system using the QuantiTect™ SYBR Green PCR kit (Qiagen). Amplification reactions included cDNA template (25 ng), API-5 primers (forward, 5′-TAGTGGGTTTGGAGAAGTTC-3′; reverse, 5′-TCACTTGATAGGCATCTTTATG-3′) (0.25 pmol/μl), and 2× PCR Master Mix (5 μl; Qiagen) in a total volume of 10 μl. Amplification conditions include an initial denaturation at 95 °C for 15 min, followed by 40 cycles at 95 °C for 30 s, 55 °C for 30 s, and 72 °C for 30 s. SYBR Green fluorescence was measured after each extension step. Statistical Analysis of Experimental Data—Student's t test was performed to analyze the significance of differences between sample means obtained from at least three experiments. miRNA Expression Profiling Identifies Dysregulation of miRNAs That Are Associated with HCC—In this study, the expression profiles of 157 mature miRNAs were determined in 19 HCC tumors and adjacent nontumorous liver tissues using the TaqMan MicroRNA assays human panel early access kit (Applied Biosystems) and normalized against hsa-let-7a as recommended by the manufacturer. Similar results were obtained when the same data set was also normalized against U6 RNA levels (data not shown) (27Bandres E. Cubedo E. Agirre X. Malumbres R. Zarate R. Ramirez N. Abajo A. Navarro A. Moreno I. Monzo M. Garcia-Foncillas J. Mol. Cancer. 2006; 5: 29Crossref PubMed Scopus (772) Google Scholar). Of the 157 miRNAs, 133 exhibited differential expression in at least 50% of the HCC patients, and these are presented in Fig. 1A as a TreeView Heat Map. From the TreeView Heat Map, there seem to be clusters of 20 miRNAs (red box) and 14 miRNAs (green box) that were up-regulated and down-regulated, respectively, in the tumors of HCC patients. The trends of differential expression of some of these miRNAs (miR-199a, miR-200a, miR-125a, and miR-224) were consistent with those observed in the only other previous report on miRNA expression in HCC (17Murakami Y. Yasuda T. Saigo K. Urashima T. Toyoda H. Okanoue T. Shimotohno K. Oncogene. 2006; 25: 2537-2545Crossref PubMed Scopus (1029) Google Scholar). Significance analysis of microarrays (21Zhao Y. Samal E. Srivastava D. Nature. 2005; 436: 214-220Crossref PubMed Scopus (1356) Google Scholar) was then utilized to identify miRNAs that displayed significant differential expression between the tumor and adjacent nontumorous liver tissues of HCC patients (supplemental Fig. S2). When the false discovery rate was set to <5%, only 19 miRNAs were found to be significantly up-regulated, whereas three were determined to be significantly down-regulated, with the mean fold change of the most highly up-regulated miRNA (miR-224) being log2RQ = 3.50 and that for the most down-regulated miRNA (miR-139) being log2RQ = -3.26 (Fig. 1B). Two of the three significantly down-regulated miRNAs (miR-145 and miR-214) reside in the cluster of down-regulated miRNAs (green box), whereas 14 of the 19 up-regulated miRNAs (red box) reside in the cluster of up-regulated miRNAs shown in Fig. 1A. Majority of the Predicted Targets of These 22 Differentially Regulated miRNAs Reside in Pathways Reported to Be Dysregulated during Carcinogenesis—An in silico strategy was employed to obtain a glimpse of the potential roles of these 22 differentially expressed miRNAs in HCC carcinogenesis. Putative gene targets of all 22 miRNAs (Fig. 1B) were predicted using PicTar (19Krek A. Grun D. Poy M.N. Wolf R. Rosenberg L. Epstein E.J. MacMenamin P. da Piedade I. Gunsalus K.C. Stoffel M. Rajewsky N. Nat. Genet. 2005; 37: 495-500Crossref PubMed Scopus (3892) Google Scholar), miRBase Targets Version 3.0 (7Griffiths-Jones S. Grocock R.J. van Dongen S. Bateman A. Enright A.J. Nucleic Acids Res. 2006; 34: D140-D144Crossref PubMed Scopus (3636) Google Scholar), and TargetScan Release 3.0 (8Lewis B.P. Burge C.B. Bartel D.P. Cell. 2005; 120: 15-20Abstract Full Text Full Text PDF PubMed Scopus (9835) Google Scholar), and only gene targets predicted by at least two of the three algorithms (supplemental Fig. S3) were further analyzed to reduce the chance of false positives (19Krek A. Grun D. Poy M.N. Wolf R. Rosenberg L. Epstein E.J. MacMenamin P. da Piedade I. Gunsalus K.C. Stoffel M. Rajewsky N. Nat. Genet. 2005; 37: 495-500Crossref PubMed Scopus (3892) Google Scholar, 34Miranda K.C. Huynh T. Tay Y. Ang Y.S. Tam W.L. Thomson A.M. Lim B. Rigoutsos I. Cell. 2006; 126: 1203-1217Abstract Full Text Full Text PDF PubMed Scopus (1567) Google Scholar, 35Lewis B.P. Shih I.H. Jones-Rhoades M.W. Bartel D.P. Burge C.B. Cell. 2003; 115: 787-798Abstract Full Text Full Text PDF PubMed Scopus (4215) Google Scholar). Between 12 and more than 500 gene targets were predicted for each of the 19 miRNAs that were significantly up-regulated in tumors of HCC patients (Fig. 1B, bottom left panel), whereas 147–173 gene targets were predicted for each of the three miRNAs that were significantly down-regulated (Fig. 1B, bottom right panel). The pathways that these predicted gene targets reside were annotated using GO (36Ashburner M. Ball C.A. Blake J.A. Botstein D. Butler H. Cherry J.M. Davis A.P. Dolinski K. Dwight S.S. Eppig J.T. Harris M.A. Hill D.P. Issel-Tarver L. Kasarskis A. Lewis S. Matese J.C. Richardson J.E. Ringwald M. Rubin G.M. Sherlock G. Nat. Genet. 2000; 25: 25-29Crossref PubMed Scopus (27005) Google Scholar) and the Database for Annotation, Visualization, and Integrated Discovery (GoCharts module) (31Dennis Jr., G. Sherman B.T. Hosack D.A. Yang J. Gao W. Lane H.C. Lempicki R.A. Genome Biol. 2003; 4: R60Crossref Google Scholar) to determine biological pathways, which were significantly over-represented. Based on a p value of 0.01, 48% (1148/2391) of the predicted nonoverlapping gene targets of the miRNAs resided within 35 biological pathways including several classical cancer-associated pathways like transcription, regulation of progression through cell cycle and Wnt receptor signaling pathway (supplemental Table S1). 80% of these 35 biological pathways have been reported to be implicated in the carcinogenesis process (supplemental Table S1), strongly suggesting that the miRNAs we observed to be differentially expressed in HCC patients target genes whose dysregulation may play significant roles in carcinogenesis. miR-224 Overexpression Decreases Cell Viability and Sensitizes Cells to Apoptotic Cell Death—To gain further insights into how dysregulation of these miRNAs may play a role in carcinogenesis, we further characterized miR-224, the most up-regulated miRNA (log2RQ = 3.5 or fold change of 11.28) in our study and the only miRNA that was also reported in another study to be up-regulated in HCC patients. Northern blot analysis confirmed that miR-224 was up-regulated in the tumors of HCC patients (Fig. 2A). The functional

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