MicroRNA-193b Represses Cell Proliferation and Regulates Cyclin D1 in Melanoma
2010; Elsevier BV; Volume: 176; Issue: 5 Linguagem: Inglês
10.2353/ajpath.2010.091061
ISSN1525-2191
AutoresJiamin Chen, Harriet Feilotter, Geneviève C. Paré, Xiao Zhang, Joshua G. Pemberton, Cherif Garady, Dulcie Lai, Xiaolong Yang, Victor A. Tron,
Tópico(s)Cancer-related molecular mechanisms research
ResumoCutaneous melanoma is an aggressive form of human skin cancer characterized by high metastatic potential and poor prognosis. To better understand the role of microRNAs (miRNAs) in melanoma, the expression of 470 miRNAs was profiled in tissue samples from benign nevi and metastatic melanomas. We identified 31 miRNAs that were differentially expressed (13 up-regulated and 18 down-regulated) in metastatic melanomas relative to benign nevi. Notably, miR-193b was significantly down-regulated in the melanoma tissues examined. To understand the role of miR-193b in melanoma, functional studies were undertaken. Overexpression of miR-193b in melanoma cell lines repressed cell proliferation. Gene expression profiling identified 314 genes down-regulated by overexpression of miR-193b in Malme-3M cells. Eighteen of these down-regulated genes, including cyclin D1 (CCND1), were also identified as putative miR-193b targets by TargetScan. Overexpression of miR-193b in Malme-3M cells down-regulated CCND1 mRNA and protein by ≥50%. A luciferase reporter assay confirmed that miR-193b directly regulates CCND1 by binding to the 3′untranslated region of CCND1 mRNA. These studies indicate that miR-193b represses cell proliferation and regulates CCND1 expression and suggest that dysregulation of miR-193b may play an important role in melanoma development. Cutaneous melanoma is an aggressive form of human skin cancer characterized by high metastatic potential and poor prognosis. To better understand the role of microRNAs (miRNAs) in melanoma, the expression of 470 miRNAs was profiled in tissue samples from benign nevi and metastatic melanomas. We identified 31 miRNAs that were differentially expressed (13 up-regulated and 18 down-regulated) in metastatic melanomas relative to benign nevi. Notably, miR-193b was significantly down-regulated in the melanoma tissues examined. To understand the role of miR-193b in melanoma, functional studies were undertaken. Overexpression of miR-193b in melanoma cell lines repressed cell proliferation. Gene expression profiling identified 314 genes down-regulated by overexpression of miR-193b in Malme-3M cells. Eighteen of these down-regulated genes, including cyclin D1 (CCND1), were also identified as putative miR-193b targets by TargetScan. Overexpression of miR-193b in Malme-3M cells down-regulated CCND1 mRNA and protein by ≥50%. A luciferase reporter assay confirmed that miR-193b directly regulates CCND1 by binding to the 3′untranslated region of CCND1 mRNA. These studies indicate that miR-193b represses cell proliferation and regulates CCND1 expression and suggest that dysregulation of miR-193b may play an important role in melanoma development. Cutaneous melanoma is a form of skin cancer characterized by aggressive metastatic growth and poor prognosis.1Cummins DL Cummins JM Pantle H Silverman MA Leonard AL Chanmugam A Cutaneous malignant melanoma.Mayo Clin Proc. 2006; 81: 500-507Abstract Full Text Full Text PDF PubMed Scopus (241) Google Scholar The incidence of melanoma continues to increase in many parts of the world.2Bevona C Sober AJ Melanoma incidence trends.Dermatol Clin. 2002; 20 (vii.): 589-595Abstract Full Text Full Text PDF PubMed Scopus (80) Google Scholar The median survival time of patients with metastatic melanoma is 6 months, and the 5-year survival rate is less than 5%.3Gray-Schopfer V Wellbrock C Marais R Melanoma biology and new targeted therapy.Nature. 2007; 445: 851-857Crossref PubMed Scopus (1047) Google Scholar Genetic factors and exposure to ultraviolet radiation are risk factors for melanoma pathogenesis.4Miller AJ Mihm Jr, MC Melanoma.N Engl J Med. 2006; 355: 51-65Crossref PubMed Scopus (1171) Google Scholar MicroRNAs (miRNAs) are a class of small (≈22 nucleotides) noncoding regulatory RNAs found in animals, plants, and viruses.5Bartel DP MicroRNAs: genomics, biogenesis, mechanism, and function.Cell. 2004; 116: 281-297Abstract Full Text Full Text PDF PubMed Scopus (29553) Google Scholar miRNAs regulate gene expression through imperfect or perfect base pairing with the 3′ untranslated region (3′ UTR) of targeted mRNA, resulting in translational repression or mRNA destabilization and degradation.5Bartel DP MicroRNAs: genomics, biogenesis, mechanism, and function.Cell. 2004; 116: 281-297Abstract Full Text Full Text PDF PubMed Scopus (29553) Google Scholar The exact mechanisms by which miRNAs recognize and regulate target genes are not well understood.6Bartel DP MicroRNAs: target recognition and regulatory functions.Cell. 2009; 136: 215-233Abstract Full Text Full Text PDF PubMed Scopus (15903) Google Scholar Experimental data demonstrated that a 6-nucleotide seed sequence, from nucleotides 2 to 7 at the 5′ end of the miRNA, called miRNA “seed,” is involved in target recognition.7Lewis BP Burge CB Bartel DP Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets.Cell. 2005; 120: 15-20Abstract Full Text Full Text PDF PubMed Scopus (9866) Google Scholar Genes targeted by a miRNA often contain seed-matched sites at their 3′ UTR. Nevertheless, a single miRNA can regulate expression of hundreds of genes,8Selbach M Schwanhausser B Thierfelder N Fang Z Khanin R Rajewsky N Widespread changes in protein synthesis induced by microRNAs.Nature. 2008; 455: 58-63Crossref PubMed Scopus (2793) Google Scholar, 9Baek D Villen J Shin C Camargo FD Gygi SP Bartel DP The impact of microRNAs on protein output.Nature. 2008; 455: 64-71Crossref PubMed Scopus (2983) Google Scholar and at least one third of human protein-coding genes are thought to be regulated by miRNAs.10Chen K Rajewsky N Natural selection on human microRNA binding sites inferred from SNP data.Nat Genet. 2006; 38: 1452-1456Crossref PubMed Scopus (383) Google Scholar Importantly, miRNA target sites are often evolutionarily conserved in the genomes of many species, suggesting that miRNA:mRNA interactions are functionally significant and biologically important. Consistent with this, functional studies have implicated miRNAs in many biological processes, including development, differentiation, apoptosis, and cell proliferation.5Bartel DP MicroRNAs: genomics, biogenesis, mechanism, and function.Cell. 2004; 116: 281-297Abstract Full Text Full Text PDF PubMed Scopus (29553) Google Scholar Recent studies have characterized diverse miRNA regulatory networks and suggested that miRNA dysregulation plays an important role in human cancer. Cancer-specific miRNA expression profiles have been identified in a variety of human malignancies.11Calin GA Croce CM MicroRNA signatures in human cancers.Nat Rev Cancer. 2006; 6: 857-866Crossref PubMed Scopus (6614) Google Scholar Depending on the specific miRNA and the cellular context, miRNAs are reported to act as either tumor suppressors or oncogenes.12Esquela-Kerscher A Slack FJ Oncomirs - microRNAs with a role in cancer.Nat Rev Cancer. 2006; 6: 259-269Crossref PubMed Scopus (6194) Google Scholar Differential expression of miRNAs in cancer cells may in part reflect the fact that many miRNA genes are located in cancer-associated genomic regions.13Calin GA Sevignani C Dumitru CD Hyslop T Noch E Yendamuri S Shimizu M Rattan S Bullrich F Negrini M Croce CM Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers.Proc Natl Acad Sci USA. 2004; 101: 2999-3004Crossref PubMed Scopus (3576) Google Scholar Abnormal epigenetic regulation and transcriptional factor deregulation may also contribute to distinct patterns of miRNA expression in cancer cells.14Lujambio A Calin GA Villanueva A Ropero S Sanchez-Cespedes M Blanco D Montuenga LM Rossi S Nicoloso MS Faller WJ Gallagher WM Eccles SA Croce CM Esteller M A microRNA DNA methylation signature for human cancer metastasis.Proc Natl Acad Sci U S A. 2008; 105: 13556-13561Crossref PubMed Scopus (935) Google Scholar, 15Chang TC Yu D Lee YS Wentzel EA Arking DE West KM Dang CV Thomas-Tikhonenko A Mendell JT Widespread microRNA repression by Myc contributes to tumorigenesis.Nat Genet. 2008; 40: 43-50Crossref PubMed Scopus (1108) Google Scholar Several previous studies have examined possible roles of miRNA dysregulation in melanoma. One study examined the relative expression of 157 miRNAs in primary melanomas and benign nevi using quantitative real-time PCR.16Schultz J Lorenz P Gross G Ibrahim S Kunz M MicroRNA let-7b targets important cell cycle molecules in malignant melanoma cells and interferes with anchorage-independent growth.Cell Res. 2008; 18: 549-557Crossref PubMed Scopus (379) Google Scholar Schultz et al showed that let-7 family miRNAs were significantly down-regulated in primary melanomas, and let-7b inhibited melanoma cell cycle progression.16Schultz J Lorenz P Gross G Ibrahim S Kunz M MicroRNA let-7b targets important cell cycle molecules in malignant melanoma cells and interferes with anchorage-independent growth.Cell Res. 2008; 18: 549-557Crossref PubMed Scopus (379) Google Scholar Another study examined miRNA expression profiles in melanocytes and cell lines derived from primary or metastatic melanoma and identified large numbers of miRNAs associated with melanoma progression and metastatic colonization.17Mueller DW Rehli M Bosserhoff AK miRNA expression profiling in melanocytes and melanoma cell lines reveals miRNAs associated with formation and progression of malignant melanoma.J Invest Dermatol. 2009; 129: 1740-1751Crossref PubMed Scopus (207) Google Scholar However, it has been suggested that global miRNA abundance is generally higher in tissues compared with cell lines,18Hwang HW Wentzel EA Mendell JT Cell-cell contact globally activates microRNA biogenesis.Proc Natl Acad Sci U S A. 2009; 106: 7016-7021Crossref PubMed Scopus (112) Google Scholar and we believe a study using tissues can add important information to this field. In this study, we profiled 470 miRNAs in metastatic melanomas and benign nevi using a microarray platform and identified 31 miRNAs that were differentially expressed in melanomas compared with nevi. One candidate miRNA identified in this study is miR-193b. We demonstrated miR-193b represses melanoma cell proliferation and that CCND1 is a direct target of miR-193b. Metastatic melanoma cell lines Malme-3M, SKMEL-28, and SKMEL-5 were grown in RPMI medium 1640 (Hyclone, Logan, UT) supplemented with 10% fetal bovine serum (Hyclone) at 37°C and 5% CO2. Formalin-fixed paraffin-embedded (FFPE) tissues from eight benign nevi, and eight metastatic melanomas were obtained from the Department of Pathology and Molecular Medicine, Kingston General Hospital. All cases were diagnosed and classified by a Dermatopathologist (V.A.T.). Tissue samples used in this study were all within 3 years of formalin fixation/embedding. Ethics approval was obtained from the Faculty of Health Sciences Ethics Board at Queen's University. Total RNA was isolated from FFPE samples using the RecoverAll Total RNA Isolation kit (Ambion, Austin, TX) according to the manufacturer's instructions. For each sample, three 20-μm sections were used for RNA isolation. Agilent MicroRNA V1 arrays, which detect 470 human miRNAs, were used for profiling as described previously.19Zhang X Chen J Radcliffe T Lebrun DP Tron VA Feilotter H An array-based analysis of microRNA expression comparing matched frozen and formalin-fixed paraffin-embedded human tissue samples.J Mol Diagn. 2008; 10: 513-519Abstract Full Text Full Text PDF PubMed Scopus (108) Google Scholar Briefly, 100 ng of total RNA from each sample was dephosphorylated and ligated with pCp-Cy3 (Agilent, Santa Clara, CA). Labeled RNA was purified and hybridized in a rotating oven at 55°C for 20 hours. The chips were scanned with the Agilent DNA Microarray scanner, and signals were quantified using the Agilent Feature Extraction 9.5.3.1 software. Raw data can be accessed via the National Center for Biotechnology Information Gene Expression Omnibus website (http://www.ncbi.nlm.nih.gov/geo/accession number GSE18512, release date Dec 20, 2009). To measure specific miRNA expression patterns in FFPE tissues, the same total RNA described above was used for real-time PCR assays. As well, total RNA from transfected cell lines was isolated using the miRNeasy Mini kit (Qiaqen, Valencia, CA) according to the manufacturer's protocol. miRNA levels were determined using the TaqMan MicroRNA Assays (Applied Biosystems, Foster City, CA) according to the manufacturer's protocol. Briefly, miRNAs were reverse transcribed using miRNA specific stem-loop RT primers purchased from Applied Biosystems. Subsequent real-time PCR reactions were performed using the Eppendorf Realplex system (Eppendorf, Hamburg, Germany). PCR reactions were incubated in a 96-well plate at 95°C for 10 minutes, followed by 40 cycles of 95°C for 15 seconds and 60°C for 1 minute. All miRNAs were assayed in triplicate and data were normalized to endogenous RNU6B. The relative levels were calculated using the ΔΔCt method. The Pre-miR hsa-miR-193b miRNA Precursor and Pre-miR Negative Control used for miR-193b overexpression studies were purchased from Ambion. The miRNA precursors are modified double-stranded RNA molecules designed to mimic endogenous mature miRNAs. The CCND1 siRNA and the negative control siRNA were purchased from Applied Biosystems. Transfection reagent was Lipofectamine 2000 (Invitrogen, Carlsbad, CA). Dicer-substrate Mcl-1 siRNA was obtained from Integrated DNA Technologies (Coralville, IA). The transfection efficiency was >95% (data not shown). miR-193b overexpression after transfection was confirmed by real-time PCR (see supplemental Figure S1 at http://ajp.amjpathol.org). Cells were seeded in 6-well plates at 100,000 cells per well the day before transfection. Malme-3M cells were transfected with 5 nmol/L miRNA precursors (either miR-193b or negative control); SKMEL-28 and SKMEL-5 were transfected with 50 nmol/L miRNA precursors (either miR-193b or negative control). Proliferation was measured using the Cell Proliferation ELISA, BrdU (chemiluminescence) by Roche Applied Biosciences (Laval, Quebec, Canada) following the manufacturer's instructions. Briefly, cells were harvested 72 hours posttransfection, counted, and reseeded in 96-well black plates (Corning®, Corning, NY) at 3500 cells per well. Cells were incubated for 24 hours in the presence of BrdU before fixing and labeling with anti-BrdU antibody. Chemiluminescence signal was measured using a EG&G Berthold microplate luminometer. Results are presented as relative level of proliferation and are the mean of three independent experiments ± SEM. For apoptosis analysis, the proportion of cells undergoing apoptosis and necrosis was measured using the Annexin V FITC Apoptosis Detection kit (Calbiochem, San Diego, CA). In brief, cells were collected 72 hours posttransfection, washed twice with cold PBS, then resuspended in annexin V binding buffer. FITC-conjugated annexin V (1.25 μl/sample) was added and cells incubated for 30 minutes at room temperature in the dark. Cells were centrifuged, resuspended in binding buffer, and propidium iodide was added (10 μl per sample). Samples were kept on ice and analyzed immediately by flow cytometry, using a Beckman Coulter EPICS Altra HSS flow cytometer. For positive control, Malme-3M cells were treated with 10 nmol/L Mcl-1 DsiRNA and 10 μmol/L ABT-737 as described previously.20Keuling AM Felton KE Parker AA Akbari M Andrew SE Tron VA RNA silencing of Mcl-1 enhances ABT-737-mediated apoptosis in melanoma: role for a caspase-8-dependent pathway.PLoS One. 2009; 4: e6651Crossref PubMed Scopus (67) Google Scholar Representative data from one of three independent experiments are shown. For cell cycle analysis, samples were harvested 72 hours posttransfection, fixed overnight in ice-cold ethanol (70% v/v), and stained for 3 hours at 4°C with 50 μg ml−1 propidium iodide (PI, Calbiochem) in PBS containing 3.8 mmol/L sodium citrate and 0.5 μg ml−1 RNase A (Sigma-Aldrich, Oakville, ON, Canada) in 10 mmol/L Tris pH 7.5, 15 mmol/L NaCl. DNA content was determined using a Beckman Coulter EPICS Altra HSS flow cytometer. Results are presented as % of cell population in each cell cycle phase. Data are the mean of three independent experiments ± SEM. P value was calculated using G1 population by independent samples t test. Malme-3M cells were seeded 100,000 cells per well in six-well plate and transfected the following day with 5 nmol/L miRNA precursors (either miR-193b or negative control). Total RNA was harvested 24 hours after transfection using miRNeasy Mini kit (Qiagen). The Agilent Microarray Platform for One-Color Analysis of Gene Expression was used for profiling (Agilent). Briefly, 500 ng total RNA of each sample was mixed with 5 μl of a 5000-fold dilution of Agilent One-Color Spike-in RNA control. The mixture was amplified and labeled using the One color, Quick Amp Labeling kit (Agilent). mRNA was primed with an oligo (dT) primer containing a T7 RNA polymerase promoter to synthesize double-stranded cDNA as a template for in vitro transcription to generate Cy3-labeled cRNA. After amplification and labeling, cRNA yield and specific activity were assessed using Nanodrop ND-1000 (Nanodrop, Wilmington, DE). Only samples with cRNA yields >1.65 μg and specific activities >9.0 pmol Cy3/μg cRNA were processed further. Successfully amplified and labeled samples were fragmented at 60°C for 30 minutes and hybridized to Agilent Human 4X44K Whole genome microarrays in a rotating oven at 65°C for 17 hours. Microarray chips were scanned with the Agilent DNA Microarray scanner and quantified as described above for miRNA chips. Raw data can be accessed via National Center for Biotechnology Information Gene Expression Omnibus website (http://www.ncbi.nlm.nih.gov/geo/accession number GSE18512, release date Dec 20, 2009). Total RNA from transfected cell cultures was isolated using miRNeasy Mini kit (Qiaqen), and then reverse transcribed to cDNA using TaqMan Reverse Transcription Reagents (Applied Biosystems). 300 ng total RNA was random primed and reverse transcribed on a thermal cycler. CCND1 quantification was then performed using CCND1 TaqMan Gene Expression Assay (Applied Biosystems) on an Eppendorf Realplex platform (Eppendorf). The PCR mixture was incubated at 50°C for 2 minutes, 95°C for 10 minutes, followed by 40 cycles of 95°C for 15 s, 60°C for 60 s. β-actin was used as housekeeping gene for normalization. The relative levels were calculated using the ΔΔCt method. 30 μg cell lysates were separated on 15% SDS-polyacrylamide gels, and then were transferred to PVDF membrane (Millipore, Bedford, MA). The CCND1 antibody used for blotting was purchased from BD Biosciences (San Jose, CA), and gamma tubulin was purchased from Sigma-Aldrich. Densitometry was performed using Quantity One software (Bio-Rad, Mississauga, ON, Canada). We generated pGL3-CCND1 by amplifying a 512 bp 3′ UTR fragment of CCND1 gene harboring the miR-193b binding site predicted by the TargetScan (http://www.targetscan.org/, accession date Oct 27, 09) and subsequently cloning it into the pGL3 control vector (Promega, Madison, WI) at the XbaI site immediately downstream of firefly luciferase. The primer sequences used for amplification were (XbaI sites are in bold): sense 5′-GCTCTAGAGGAGGCTGCGTGCCAGTCAAGAAG-3′ and antisense 5′-GCTCTAGACCTTGCACCCATGCCTGTCCAATC-3′. pGL3-CCND1 was subsequently used as a template to generate the control vector pGL3-CCND1 MM, which has two mismatch mutations in the miR-193b seed complementary site. Overlapping PCR was used to introduce mutations into the control vector. The following primers were used for PCR amplification: sense 5′-GCAGAGGATGTTCATAAGGGCAGAATGATTTATAAATGCAATCTCC-3′ and antisense 5′-GGAGATTGCATTTATAAATCATTCTGCCCTTATGAACATCCTCTGC-3′ (mismatch nucleotides are in bold). Malme-3M cells were seeded at 75,000 cells per well in a 12-well plate the day before transfection. The cells were cotransfected with 5 nmol/L miRNA precursor (either miR-193b or negative control), 400 ng of firefly luciferase vector (either pGL3-CCND1 or pGL3-CCND1 MM), and 50 ng of Renilla luciferase vector (pRL-TK). Luciferase activity was measured 24 hours after transfection using the Dual-Glo Luciferase Assay System (Promega). The Renilla luciferase activity served as internal control. Immunohistochemistry was performed in the Department of Pathology and Molecular Medicine at the Kingston General Hospital using a standard protocol on tissue microarray slides. Anti-Cyclin D1 antibody (NeoMarkers, clone SP4) was used at a 1/100 dilution and incubated for 32 minutes at 37C. Stained slides were scanned on an Aperio scanner (Vista, CA), and the percentage of CCND1-positive nuclei in cell population was quantified using immunohistochemistry Image Analysis software. In microRNA microarray study, unsupervised hierarchical clustering was performed on log2 transformed data (signal values less 1 were reassigned to 1) with Cluster 3.0 using uncentered correlation metric and average linkage methods.21Porkka KP Pfeiffer MJ Waltering KK Vessella RL Tammela TL Visakorpi T MicroRNA expression profiling in prostate cancer.Cancer Res. 2007; 67: 6130-6135Crossref PubMed Scopus (795) Google Scholar The results were visualized by Java Treeview 1.1.1 (http://jtreeview.sourceforge.net/, accession date Oct 27, 09). To identify differentially expressed miRNAs, significance analysis of microarray (SAM) was performed on the array data without log transformation.22Tusher VG Tibshirani R Chu G Significance analysis of microarrays applied to the ionizing radiation response.Proc Natl Acad Sci USA. 2001; 98: 5116-5121Crossref PubMed Scopus (9768) Google Scholar, 23Ryu B Kim DS Deluca AM Alani RM Comprehensive expression profiling of tumor cell lines identifies molecular signatures of melanoma progression.PLoS One. 2007; 2: e594Crossref PubMed Scopus (226) Google Scholar miRNAs were excluded after SAM analysis when the absolute mean difference of their expression between melanomas and nevi (numerator r) was <15. The heatmap, presenting the log2-transformed fold changes of miRNAs, was generated using Cluster 3.0 and Java Treeview as described above. In gene expression microarray study, raw data were normalized and analyzed using GeneSpring GX 10.0.2 (Agilent). For quality control, probe sets were filtered to include only genes that were described as “Present” or “Marginal” by GeneSpring in all 4 samples, and genes with raw signals <25.0 were removed from subsequent analyses. P values were calculated for two pair-wise comparisons between Malme-3M cells with or without miR-193b overexpression using the paired t test. In the bar graphs, data were analyzed by t test using SPSS Statistics 17.0 (SPSS Inc., Chicago, IL). A P value <0.05 was considered statistically significant. Our initial studies examined the expression of 470 miRNAs in FFPE samples from eight benign nevi and eight metastatic melanomas using the Agilent miRNA microarray platform (version 1.5) to identify possible miRNA candidates for functional studies. We used these two groupings because they represent two biologically and clinically distinct melanocytic tissues. In our opinion, nevus is the best surrogate for benign melanocytes, whereas metastatic melanoma, by virtue of the fact that it has spread, is clearly malignant. The validity of using this method with FFPE tissue samples was confirmed previously by us and others.19Zhang X Chen J Radcliffe T Lebrun DP Tron VA Feilotter H An array-based analysis of microRNA expression comparing matched frozen and formalin-fixed paraffin-embedded human tissue samples.J Mol Diagn. 2008; 10: 513-519Abstract Full Text Full Text PDF PubMed Scopus (108) Google Scholar, 24Glud M Klausen M Gniadecki R Rossing M Hastrup N Nielsen FC Drzewiecki KT MicroRNA expression in melanocytic nevi: the usefulness of formalin-fixed, paraffin-embedded material for miRNA microarray profiling.J Invest Dermatol. 2009; 129: 1219-1224Crossref PubMed Scopus (76) Google Scholar Data were analyzed by unsupervised hierarchical clustering, and the results were summarized in a dendrogram (Figure 1A), which clearly shows that benign nevi cluster separately from metastatic melanomas. We compared the expression of miRNAs between metastatic melanomas and benign nevi, and identified differentially expressed miRNAs by SAM. By using 1000 permutations and selecting a false discovery rate q < 0.001, we identified 31 differentially expressed miRNAs including 13 up-regulated and 18 down-regulated in metastatic melanomas compared with benign nevi (Figure 1B). To provide a technical validation, 5 significantly up-regulated miRNAs and 10 significantly down-regulated miRNAs were quantified in four metastatic melanoma samples and four benign nevus samples by real-time PCR using the same RNA samples isolated for the microarray studies. The levels of miRNAs detected by real-time PCR agreed with the microarray results (Figure 2). On average, the five up-regulated miRNAs were expressed at a fourfold higher level in metastatic melanomas than in nevi, and the 10 down-regulated miRNAs, with the exception of miR-214, were expressed on average at twofold lower level in metastatic melanoma samples. In the SAM analysis,22Tusher VG Tibshirani R Chu G Significance analysis of microarrays applied to the ionizing radiation response.Proc Natl Acad Sci USA. 2001; 98: 5116-5121Crossref PubMed Scopus (9768) Google Scholar miR-193b had the largest relative difference (score d = −6.9) among the down-regulated miRNAs, and its expression was 3.4-fold lower in metastatic melanomas compared with benign nevi. The down-regulation of miR-193b was also confirmed by real-time PCR (Figure 2). Its function in melanoma is unknown. To investigate the functional roles of miR-193b, three metastatic melanoma cell lines, Malme-3M, SKMEL-28, and SKMEL-5 were transfected with miRNA precursors (either miR-193b or negative control). Cell proliferation was measured using the BrdU incorporation assay (Roche). Overexpression of miR-193b repressed cell proliferation in all three melanoma cell lines (Figure 3A). Among them, Malme-3M cells were the most responsive, showing a nearly 60% reduction in proliferation after miR-193b overexpression. Thus, additional functional studies on miR-193b were conducted in Malme-3M cells. To determine whether reduced cell proliferation was apoptosis-independent, we performed Annexin V–FITC staining to detect apoptosis. Annexin V–FITC data showed that overexpression of miR-193b did not significantly alter the fraction of necrotic or apoptotic Malme-3M cells (Figure 3B). Cell cycle analysis by PI staining was performed. Overexpression of miR-193b increased the fraction of cells in the G1 phase from 62% to 85% while decreasing the fraction of cells in the S phase and G2 phase from 27% and 12% to 10% and 6%, respectively (Figure 3C). This result suggests that miR-193b represses cell proliferation by arresting cells in the G1 phase, without inducing cell death. It is crucial to identify functionally important miRNA targets to understand how a specific miRNA functions. Recent studies showed that mRNA destabilization is the major component of the miRNA repression mechanism in targets with robust protein reduction.9Baek D Villen J Shin C Camargo FD Gygi SP Bartel DP The impact of microRNAs on protein output.Nature. 2008; 455: 64-71Crossref PubMed Scopus (2983) Google Scholar Thus, we performed gene expression analysis to globally screen for miR-193b targets that may affect cell proliferation. By comparing mRNA expression levels in Malme-3M cells transfected with miRNA precursors (either miR-193b or negative control) using the whole human genome microarray (Agilent), we identified 314 genes that were down-regulated more than 1.5 fold (P < 0.05) by miR-193b overexpression (see supplemental Table S1 at http://ajp.amjpathol.org). Ingenuity pathways analysis functional analysis was performed to examine the molecular and cellular functions of those genes. Ingenuity pathways analysis revealed that the most significantly enriched gene ontology category among down-regulated genes was cell cycle, indicating miR-193b, directly or indirectly, regulates genes involved in cell cycle progression (Figure 4). Interestingly, 18 of the genes down-regulated after miR-193b overexpression were also the targets of miR-193b predicted by TargetScan (Human 5.1, http://www.targetscan.org/, accession date Oct 27, 09; Table 1). We reasoned that genes predicted by TargetScan are more likely to be the direct targets of miR-193b because they contain the predicted evolutionary conserved miR-193b seed binding sites. Of those 18 genes, CCND1 was of particular interest. CCND1 plays an important role in regulating the G1/S transition during cell cycle progression. This is consistent with the observation that overexpression of miR-193b inhibited cell growth and increased G1 cell cycle arrest, effects that could be mediated by repression of CCND1.Table 1Genes Down-regulated by miR-193b That Are Predicted by TargetScanDown-regulated genesFold changeHomo sapiens Abl interactor 2 (ABI2)3 Adenylate cyclase 9 (ADCY9)1.94 Rho GTPase activating protein 19 (ARHGAP19)2.38 Atonal homolog 8 (Drosophila) (ATOH8)1.54 Cyclin D1 (CCND1)2.02 Calsyntenin 1 (CLSTN1)1.81 CCR4-NOT transcription complex, subunit 6 (CNOT6)2.17 E2F transcription factor 6 (E2F6)1.54 v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS)2.63 Leucine rich repeat containing 8 family, member A (LRRC8A)1.77 Myeloid cell leukemia sequence 1 (BCL2-related) (MCL1)1.64 RNA binding motif protein 8A (RBM8A)1.72 Remodeling and spacing factor 1 (RSF1)1.67 Selenoprotein N, 1 (SEPN1)2.05 Stathmin 1/oncoprotein 18 (STMN1)4.47 Tumor necrosis factor receptor superfamily, member 21 (TNFRSF21)2.16 WD repeat domain 68 (WDR68)2.89 Zinc finger protein 365 (ZNF365)1.74Gene expression microarray analysis was performed on Malme-3M
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