Changes in microRNA expression in the MG-63 osteosarcoma cell line compared with osteoblasts

  • Authors:
    • Hao Hu
    • Yi Zhang
    • Xian-Hua Cai
    • Ji-Feng Huang
    • Lin Cai
  • View Affiliations

  • Published online on: August 16, 2012     https://doi.org/10.3892/ol.2012.866
  • Pages: 1037-1042
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Abstract

Osteosarcoma (OS) is the most common primary malignant bone tumor, particularly in adolescents and young adults. Early diagnosis remains a significant problem in the clinical treatment of OS as we remain far from a comprehensive understanding of the molecular genetic mechanisms and the biology involved. In addition, microRNAs (miRNAs or miRs), a large family of small non-coding RNAs, may provide a greater understanding of OS as they play a complex role in gene expression regulation in vitro and in vivo. In the current study, the differential expression profiles of miRNAs between OS and osteoblast cell lines were investigated by miRNA microarrays and real-time quantitative PCR (RT-qPCR). A total of 268 miRNAs were identified that were significantly dysregulated in OS compared with the osteoblast cell line, including miR-9, miR-99, miR-195, miR-148a and miR-181a, which had been validated as overexpressed, and miR-143, miR-145, miR-335 and miR-539, which were confirmed to be downregulated. This differential expression may aid future OS diagnosis and prognosis prediction and illustration of the potential mechanisms in the oncogenesis, development and metastasis of OS. Bioinformatic research on these differentially expressed miRNAs suggests that they are able to regulate the biological behaviors of OS in a complex and effective manner. Further study on the function of these miRNAs is likely to provide new insights into OS biology and treatment.

Introduction

Although it accounts for less than 0.5% of all types of cancer, osteosarcoma (OS) is the most frequent primary malignancy of the bone and occurs mainly in adolescents and young adults (1). The initiation of combinational chemotherapy with aggressive surgical resection has markedly improved the prognosis of OS patients during the last few decades (2). However, the current neoadjuvant chemotherapy outcome for OS remains unsatisfactory in the presence of metastases (35). Despite the various efforts of basic research and clinical practice, the molecular genetic mechanisms and the biology involved in OS remain poorly understood. A greater understanding of OS is essential for developing novel approaches to increase survival rates (3).

As a large family of naturally occurring small non-coding RNAs, microRNAs (miRNAs or miRs) employ a post-transcriptional gene regulation mechanism that is involved in numerous cellular processes, playing a role in development regulation, differentiation, cell proliferation, differentiation, apoptosis, cell cycle and tumorigenesis (6). Previous studies have shown that miRNAs may play complex regulatory roles by binding to the 3′ untranslated region of mRNAs; a single miRNA affects the expression of hundreds of protein-coding target genes, while a protein-coding target gene is regulated by a variety of miRNAs (7).

There is growing evidence that the aberrant expression of specific miRNAs is correlated with various human tumors, including breast cancer, hepatocellular carcinoma, leukemia and colon cancer (8,9). It has been reported that miRNAs regulate cancer cell apoptosis, cell cycle arrest, migration and invasion. The alteration of specific miRNAs may lead to various responses to the chemotherapy and several miRNAs have been demonstrated to participate in the development of tumor metastasis (10).

The current study was designed to investigate the differential expression profiles of miRs between an OS and osteoblast cell line. miRNA expression levels were determined using bead-based array performing oligonucleotide capture probes specific for miRNAs, which is feasible and attractive for its high speed and heightened accuracy. In this study, the differential miRNAs were explored through screening 1,146 mature miRNAs between the MG-63 and hFOB1.19 (HOB) cell lines and the expression of selected miRNAs was confirmed using real-time quantitative PCR (RT- qPCR) in these two cell lines. The tumor function-associated targeted mRNAs of selected miRNAs by bioinformatics and previous literature were also investigated. These findings provide insights into the role of miRNAs in OS.

Materials and methods

Cell lines and reagents

Human OS MG-63 and osteoblast HOB cell lines were obtained from the Type Culture Collection of Chinese Academy of Sciences (Shanghai, China). MG-63 cells were cultured in MEM/EBSS (Hyclone, Logan, UT, USA) supplemented with 10% heat-inactivated fetal bovine serum (FBS, Hyclone), 50 U/ml penicillin and 50 mg/ml streptomycin in a humidified incubator with 5% CO2 at 37°C. The HOB cells were maintained in the same conditions, except that DMEM/F12 (v/v: 1:1, Hyclone) supplemented with 10% FBS and 0.3 mg/ml G418 (Sigma, St. Louis, MO, USA) was used.

RNA extraction

Total RNA was extracted from each cell line using an miRNeasy Mini kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. This effectively recovered mRNA and miRNA. RNA concentration and quality were measured using the spectrophotometer (ND-2000, NanoDrop, Wilmington, DE, USA).

miRNA expression profiling by Illumina miRNA microassay

The Illumina® TotalPrep™ RNA amplification kit (Ambion, Austin, TX, USA) was used in cDNA synthesis and purification with 200 ng total RNA from each treated cell, followed by hybridizing on Human MicroRNA Expression profiling v2 panels (Illumina, San Diego, CA, USA) according to the manufacturer’s instructions (Illumina MicroRNA Expression Profiling Assay Guide) and the method described previously (11). The Human v2 MicroRNA Expression Profiling kit contains 1,146 assays for detecting >97% of the miRNAs described in the miRBase database, plus additional novel content derived using Illumina sequencing technology.

Array data processing and analysis were performed with Illumina BeadStudio software (www.illumina.com). The microRNA expression array was scanned and extracted using BeadScan, with the data corrected by background subtraction in the GenomeStudio module. The array intensity data were imported into BeadStudio v3.2 (Illumina), a software package that permits visualization and normalization of the data. The ‘Average’ normalization method was used for all analyses reported, with the exception of assay reproducibility, given the number of replicates. The normalized intensities and detection P-values were exported and further analyzed using the R environment (version 2.6), in combination with Bio-conductor packages (12).

miRNAs were considered significantly differentially expressed if the P-values were <0.05 and the fold change ratio (FCR) was >2.

RT-qPCR of specific miRNAs

Validation of differential gene expression was performed for selected miRNAs, including miR-181a, miR-148a, miR-99a, miR-195, miR-9, miR-335, miR-143, miR-145 and miR-539. These miRNAs were amplified using the Bulge-Loop™ miRNA qRT-PCR Primer Set (Ribobio, Guangzhou, China) (13). The thermal profile for the RT-qPCR was at 95°C for 1 min, followed by 40 cycles of 95°C for 10 sec, 60°C for 20 sec and 72°C for 5 sec on a Bio-Rad CFX96 RT-qPCR system (Bio-Rad, Hercules, CA, USA). All qPCR reactions, including no-template controls, were performed in triplicate. Expression levels of each miRNA were evaluated using a comparative threshold cycle (Ct) method normalized to that of U6. The fold changes of each miRNA were calculated from the expression levels in the MG-63 and HOB cell lines.

Bioinformatics analysis

The TarBase 6.0 database (http://diana.cslab.ece.ntua.gr/) was used to investigate the validated target genes in cancer research (14). Moreover, following the collection of all the validated genes, the function of these genes was analyzed by previous literature and bioinformatics research. The chromosome location of these miRNAs and their target genes was investigated to exclude the potential bias of sex chromosomes and illustrate the complex and comprehensive mechanisms in miRNA regulation of the target gene expression.

Results

miRNA expression in the MG-63 and HOB cell lines

The fold changes (MG-63/HOB) were auto-analyzed by software (BeadStudio v3.2, Illumina). Of the 1,146 miRNAs detected in the microarray, 159 miRNAs were shown to be decreased and 109 miRNAs as increased. The various miRNAs were selected for further analysis as follows: i) the minimum value should be >100 in the two cell lines to eliminate the background value; ii) the fold changes should be >5 for improved accuracy. As Fig. 1 shows, 46 miRNAs were selected as differentially expressed between the MG-63 and HOB cell lines, of which 26 were underexpressed and 20 were overexpressed. The fold change was mainly <10, while several miRNAs in MG-63 cells were markedly changed compared with the HOB cell line, including miR-335, miR-493, miR-494, miR-195 and miR-9.

Validation of miRNAs in the MG-63 and HOB cell lines

The RT-qPCR was employed to validate the differential expression of selected miRNAs. As Fig. 2 shows, it was revealed that 9 specific miRNAs were differentially expressed between the OS MG-63 and HOB cell lines and the differences are consistent with the microarray results shown. Therefore, it was demonstrated that these are the differentially expressed miRNAs in OS MG-63 compared with the HOB cell line.

Bioinformatics research on these differential miRNAs and their target genes

Tables I and II show the target genes involved in the biological behavior of cancer and validated by previous literature. The functions of these target genes are complex as they are correlated with various cellular processes, including cell proliferation, differentiation, cell cycle, apoptosis, signaling, migration and invasion. Moreover, miRNAs may regulate the expression and function of their target genes although they are located on various chromosomes.

Table I

Validated target genes of the miRNAs in the increased group.

Table I

Validated target genes of the miRNAs in the increased group.

miRNALocationValidated targets (ref.)LocationFunctions in cancer
miR-19517p13.1CDK6 (15)7q21-q22Cell cycle and arrest
E2F3 (15)6p22Cell cycle and arrest
CCND1 (15)11q13Cell cycle and arrest
VEGFA (16)6p12Angiogenesis and metastasis regulation
Bcl-2 (17)18q21.3Apoptosis regulation
SKI (18)1q22-q24Proto-oncogene
BCL2L11 (18)2q13Apoptosis regulation
CDK4 (19)12q14Cell cycle and arrest
miR-99a21q21.1MTOR (20)1p36.2Response to anti-cancer drugs
FGFR3 (20)4p16.3Mitogenesis and differentiation
SKI (21)1q22-q24Proto-oncogene
IGF1 (22)12q23.2Anti-apoptosis
miR-91q22NF-KB1 (23)4q24Transcription regulation
CDH1 (24)16q22.1Metastasis regulation
VEGFA (24)6p12Angiogenesis and metastasis regulation
VIM (24)10p13Cell attachment, migration and signaling
MMP13 (24)11q22.3Invasion and metastasis regulation
BIK (25)22q13.31Apoptosis regulation
miR-148a7p15.2CDC25B (26)20p13Cell cycle and arrest
PTPN4 (21)2q14.2Cell growth, differentiation, mitotic cycle and oncogenic transformation
CDK19 (21)6q21Cell cycle and arrest
ROCK1 (27)18q11.1Invasion and metastasis
miR-181a1q32.1CDKN1B (28)12p13.1-p12Cell cycle and arrest
Bcl-2 (29)18q21.3Apoptosis regulation
Hras (30)11p15.5Signal transduction
CDX2 (31)13q12.3Cell growth and differentiation
S100A1 (31)1q21Cell cycle and differentiation
KLF6 (32)10p15Tumor suppressor

[i] miR, miRNA, microRNA.

Table II

Validated target genes of the miRNAs in the decreased group.

Table II

Validated target genes of the miRNAs in the decreased group.

miRNALocationValidated targets (ref.)LocationFunctions in cancer
miR-1455q32FSCN1 (33)7p22Cell migration, motility, adhesion and cellular interactions
MMP1 (34)11q22.3Invasion and metastasis regulation
MMP12 (34)11q22.3Invasion and metastasis regulation
MMP14 (34)14q11-q12Invasion and metastasis regulation
TP53 (35)17p13.1Proliferation and apoptosis regulation
miR-1435q32MAPK7 (36)17p11.2Proliferation, differentiation, transcription regulation
MMP13 (37)11q22.3Invasion and metastasis regulation
Bcl-2 (38)18q21.3Apoptosis regulation
Hras (39)11p15.5Signal transduction
TP53 (35)17p13.1Proliferation and apoptosis regulation
miR-3357q32.2SP1 (40)12q13.1Cell proliferation, differentiation, apoptosis regulation
IGF1R (40)15q26.3Anti-apoptosis
BRCA1 (40)17q21Tumor suppressor
BIK (41)22q13.31Apoptosis regulation
SMAD3 (41)15q22.33Carcinogenesis
SMAD9 (41)2q26Carcinogenesis
PML (41)15q22Tumor suppressor
miR-53914q32.31MITF (42)3p14.2-p14.1Cell proliferation

[i] miR, miRNA, microRNA.

Discussion

The significance of miRNAs in the regulation of cellular processes has been increasingly noted (43). Up- and/or downregulation of miRNA expression in cancer suggests that miRNAs function as classical tumor suppressor genes or oncogenes (68). The expression fold changes of several miRNAs may aid in tumor stratification and clinical outcome prognosis (44,45). Previous research shows that specific miRNA expression may be correlated with cancer recurrence. Therefore, the distinct difference between normal and abnormal cells may be correlated with the early diagnosis and treatment of the primary cancer or its recurrence.

Although there are several studies concerning specific miRNAs as the key biomarkers for the diagnosis, treatment and evaluation of the chemoresponse or chemoprevention in cancer therapy (46,47), little is known about miRNA profiling and its signature in OS. The explosion of microarray technology has led to its wide application in miRNA expression analysis. The miRNA microarray was employed to detect the miRNA profiling in the OS and HOB cell lines, respectively, and the real-time PCR was employed to validate the miRNA of interest or marked differences between these two cell lines. In the current study, 1,146 miRNAs were detected by the micro-array, revealing 159 miRNAs as being part of the decreased group and 109 miRNAs as the increased group. Following further analysis of the miRNA microarray result, 46 miRNAs were selected as the differentially expressed miRNAs between the MG-63 and HOB cell lines.

Furthermore, based on previous research and the potential biological targets predicted by the various databases, including Targetscan and PicTar, 9 miRNAs were selected to validate their expression and demonstrate the difference between the two cell lines. The stem-loop RT-PCR method described in the present study is designed to detect and analyze mature miRNAs in a fast, specific, accurate and reliable manner (48). Therefore, RT-qPCR was employed to validate the expression of specific miRNAs of interest. Fig. 2 shows the expression of the selected 9 miRNAs quantified in the MG-63 and HOB cell lines. The differences of these miRNAs between the two cell lines are consistent with the microarray results shown. Therefore, these 9 miRNAs are accepted as the differentially expressed miRNAs between the MG-63 and HOB cell lines.

It is well known that the miRNAs involved in complex cancer-related cellular processes by regulating the various target mRNA expression and miRNAs are thought to be components of vast regulatory networks (49,50). Previous research has confirmed that multiple miRNAs target the same gene, suggesting that the correlation between miRNAs and target genes are complex and interactive (51). Therefore, analysis of the target genes of these differential miRNAs may reveal their functions as oncogenes or anti-oncogenes. Furthermore, this analysis is likely to aid the fuller understanding of the biological function of specific miRNAs through analysis of their target genes and vice versa (5254).

The validated target genes of these 9 miRNAs were obtained from bioinformatics research. Tables I and II show the validated target genes which have been demonstrated by previous research to be involved in various cellular process in cancer biology, including proliferation, differentiation, cell cycle, apoptosis, signaling, migration and invasion. These target genes are located on different chromosomes, suggesting that miRNAs may regulate the expression and function of mRNA although they are located on various chromosomes. These 9 miRNAs may play a significant role in the biological behavior of cancer, although they alter the target gene expression in different directions (7).

A total of 9 miRNAs have been reported that may act as biomarkers in the diagnosis, treatment and prediction of the prognosis of cancer. Previous evidence has demonstrated that miR-143 and miR-145, that belong to the same miRNA cluster, regulate the expression and function of various target genes. It is well known that the underexpression of the miR-143/145 cluster, the expression of which was decreased in OS in the current study, are strongly associated with carcinogenesis in various tumor types, suggesting that they may act as significant tumor suppressors (37). As Tables I and II demonstrate, tumor protein p53(TP53), fascin homolog 1(FSCN1), several matrix metallopeptidases (MMPs) and mitogen-activated protein kinases (MAPKs), which are regulated by the miR-143/145 cluster, may be involved in cancer cell proliferation, differentiation, gene transcription, apoptosis, migration and invasion (55). The similar effect of miR-143 and/or miR-145 has been demonstrated in OS cell lines by previous research (56). Therefore, we may conclude that the aberrant expression levels of the miR-143/145 clusters are correlated with the carcinogenesis and development of OS compared with the HOB cell line.

miR-9 is another of the widely-researched miRNAs in cancer biology (2325). It has been shown that miR-9 is over-expressed in various tumor types, particularly in tumors with micro-metastasis. The validated target genes (NF-KB1, CDH1, VEGFA, VIM, MMP13 and BIK) shown in Table I suggest that miR-9 may act as a significant regulatory miRNA, which was also increased in OS in the current study compared with the HOB cell line.

A previous study demonstrated that 6 other miRNAs that were validated in the current study are also involved in the biology of cancer. Of these, miR-99a may play a significant role in cell growth and correlates with the prognosis of patients with specific tumors (57,58). The aberrant expression of miR-195 in certain types of cancer may be an effective biomarker in diagnosis (59,60). The differential expression of miR-148a has been reported to be a potential marker for colorectal cancer screening and prognosis (61). miR-181a, which has been recently demonstrated to be overexpressed miRNA in OS tissue, is correlated with cancer development, apoptosis evasion and cell proliferation (62). With regard to the reduced expression group, miR-335, which is also underexpressed in certain types of cancer, has also been demonstrated to be significant as a biomarker of metastatic tumor and maintain differentiation (6365). Recently, it has been demonstrated that miR-539 may inhibit cell proliferation through suppressing the MITF expression (42). However, the functional study of the 6 miRNAs in the OS cell line are limited and ongoing research concerning their function may illustrate the further mechanism of these miRNAs in OS oncogenesis, development and metastasis.

In conclusion, the aberrant expression levels of specific miRNAs, including miR-9, miR-99a, miR-195, miR-148a, miR-181a, miR-143, miR-145, miR-335 and miR-539, may act as potential biomarkers in the diagnosis, treatment and prognosis prediction of OS. Further research on the function of their target genes may provide new insights into the biology and treatment of OS.

Acknowledgements

This study was supported by the Natural Science Foundation of China (No.30772185), the Fundamental Research Funds for the Central Universities (201130302020010).

References

1. 

A JemalR SiegelE WardT MurrayJ XuMJ ThunCancer statistics, 2007CA Cancer J Clin574366200710.3322/canjclin.57.1.43

2. 

PJ MesserschmittAN RettewRE BrookoverRM GarciaPJ GettyEM GreenfieldSpecific tyrosine kinase inhibitors regulate human osteosarcoma cells in vitroClin Orthop Relat Res46621682175200810.1007/s11999-008-0338-918607665

3. 

G BacciA LonghiM VersariM MercuriA BriccoliP PicciPrognostic factors for osteosarcoma of the extremity treated with neoadjuvant chemotherapy: 15-year experience in 789 patients treated at a single institutionCancer10611541161200616421923

4. 

A LonghiC ErraniM De PaolisM MercuriG BacciPrimary bone osteosarcoma in the pediatric age: state of the artCancer Treat Rev32423436200610.1016/j.ctrv.2006.05.00516860938

5. 

Y ZhangRX WeiXB ZhuL CaiW JinH HuTanshinone IIA induces apoptosis and inhibits the proliferation, migration and invasion of the osteosarcoma MG-63 cell line in vitroAnticancer Drugs23212219201210.1097/CAD.0b013e32834e559222126901

6. 

E KobayashiFJ HornicekZ DuanMicroRNA involvement in osteosarcomaSarcoma2012359739201210.1155/2012/35973922550419

7. 

RR LullaFF CostaJM BischofIdentification of differentially expressed microRNAs in osteosarcomaSarcoma2011732690201110.1155/2011/73269021789031

8. 

A LujambioSW LoweThe microcosmos of cancerNature482347355201210.1038/nature1088822337054

9. 

V RottiersAM NäärMicroRNAs in metabolism and metabolic disordersNat Rev Mol Cell Biol13239250201210.1038/nrm331322436747

10. 

W ZhangME DolanThe emerging role of microRNAs in drug responsesCurr Opin Mol Ther12695702201021154161

11. 

L WangAL ObergYW AsmannGenome-wide transcriptional profiling reveals microRNA-correlated genes and biological processes in human lymphoblastoid cell linesPLoS One11e5878200910.1371/journal.pone.000587819517021

12. 

H ZhaoJ ShenL MedicoD WangCB AmbrosoneS LiuA pilot study of circulating miRNAs as potential biomarkers of early stage breast cancerPLoS One5e13735201010.1371/journal.pone.001373521060830

13. 

L GuoY LiuY BaiY SunF XiaoY GuoGene expression profiling of drug-resistant small cell lung cancer cells by combining microRNA and cDNA expression analysisEur J Cancer4616921702201010.1016/j.ejca.2010.02.04320371173

14. 

T VergoulisIS VlachosP AlexiouTarBase 6.0: capturing the exponential growth of miRNA targets with experimental supportNucleic Acids Res40Database issueD222D229201210.1093/nar/gkr116122135297

15. 

T XuY ZhuY XiongYY GeJP YunSM ZhuangMicroRNA-195 suppresses tumorigenicity and regulates G1/S transition of human hepatocellular carcinoma cellsHepatology50113121200910.1002/hep.2291919441017

16. 

W YeQ LvCK WongThe effect of central loops in miRNA:MRE duplexes on the efficiency of miRNA-mediated gene regulationPLoS One3e1719200810.1371/journal.pone.000171918320040

17. 

L LiuL ChenY XuR LiX DumicroRNA-195 promotes apoptosis and suppresses tumorigenicity of human colorectal cancer cellsBiochem Biophys Res Commun400236240201010.1016/j.bbrc.2010.08.04620727858

18. 

Y MurakamiT YasudaK SaigoComprehensive analysis of microRNA expression patterns in hepatocellular carcinoma and non-tumorous tissuesOncogene2525372345200610.1038/sj.onc.120928316331254

19. 

Y LinJ WuH ChenCyclin-dependent kinase 4 is a novel target in micoRNA-195-mediated cell cycle arrest in bladder cancer cellsFEBS Lett586442447201210.1016/j.febslet.2012.01.02722289176

20. 

C OneyamaJ IkedaD OkuzakiMicroRNA-mediated downregulation of mTOR/FGFR3 controls tumor growth induced by Src-related oncogenic pathwaysOncogene3034893501201110.1038/onc.2011.6321383697

21. 

M HafnerM LandthalerL BurgerTranscriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIPCell141129141201010.1016/j.cell.2010.03.00920371350

22. 

M DoghmanA El WakilB CardinaudRegulation of insulin-like growth factor-mammalian target of rapamycin signaling by microRNA in childhood adrenocortical tumorsCancer Res7046664675201010.1158/0008-5472.CAN-09-397020484036

23. 

LM GuoY PuZ HanMicroRNA-9 inhibits ovarian cancer cell growth through regulation of NF-kappaB1FEBS J27655375546200910.1111/j.1742-4658.2009.07237.x19702828

24. 

L MaJ YoungH PrabhalamiR-9, a MYC/MYCN-activated microRNA, regulates E-cadherin and cancer metastasisNat Cell Biol12247256201020173740

25. 

A GrimsonKK FarhWK JohnstonP Garrett-EngeleLP LimDP BartelMicroRNA targeting specificity in mammals: determinants beyond seed pairingMol Cell2791105200710.1016/j.molcel.2007.06.01717612493

26. 

ST LiffersJB MundingM VogtMicroRNA-148a is down-regulated in human pancreatic ductal adenocarcinomas and regulates cell survival by targeting CDC25BLab Invest9114721479201110.1038/labinvest.2011.9921709669

27. 

B ZhengL LiangC WangMicroRNA-148a suppresses tumor cell invasion and metastasis by downregulating ROCK1 in gastric cancerClin Cancer Res1775747583201110.1158/1078-0432.CCR-11-171421994419

28. 

R CuestaA Martínez-SánchezF GebauermiR-181a regulates cap-dependent translation of p27(kip1) mRNA in myeloid cellsMol Cell Biol2928412851200910.1128/MCB.01971-0819273599

29. 

W ZhuX ShanT WangY ShuP LiumiR-181b modulates multidrug resistance by targeting BCL2 in human cancer cell linesInt J Cancer12725202529201010.1002/ijc.2526020162574

30. 

KH ShinSD BaeHS HongRH KimMK KangNH ParkmiR-181a shows tumor suppressive effect against oral squamous cell carcinoma cells by downregulating K-rasBiochem Biophys Res Commun404896902201110.1016/j.bbrc.2010.12.05521167132

31. 

J JiT YamashitaA BudhuIdentification of microRNA-181 by genome- wide screening as a critical player in EpCAM-positive hepatic cancer stem cellsHepatology50472480200910.1002/hep.2298919585654

32. 

X ZhangY NieY DuJ CaoB ShenY LiMicroRNA-181a promotes gastric cancer by negatively regulating tumor suppressor KLF6Tumour Biol33921928201210.1007/s13277-012-0414-322581522

33. 

T ChiyomaruH EnokidaS TataranomiR-145 and miR-133a function as tumour suppressors and directly regulate FSCN1 expression in bladder cancerBr J Cancer102883891201010.1038/sj.bjc.660557020160723

34. 

M KanoN SekiN KikkawamiR-145, miR-133a and miR-133b: Tumor-suppressive miRNAs target FSCN1 in esophageal squamous cell carcinomaInt J Cancer12728042814201010.1002/ijc.2528421351259

35. 

J ZhangQ SunZ ZhangS GeZG HanWT ChenLoss of microRNA- 143/145 disturbs cellular growth and apoptosis of human epithelial cancers by impairing the MDM2-p53 feedback loopOncogene2810381046201222330136

36. 

Y AkaoY NakagawaT NaoeMicroRNA-143 and -145 in colon cancerDNA Cell Biol26311320200710.1089/dna.2006.055017504027

37. 

M OsakiF TakeshitaY SugimotoMicroRNA-143 regulates human osteosarcoma metastasis by regulating matrix metalloprotease-13 expressionMol Ther1911231130201110.1038/mt.2011.5321427707

38. 

PM BorralhoBT KrenRE CastroIB da SilvaCJ SteerCM RodriguesMicroRNA-143 reduces viability and increases sensitivity to 5-fluorouracil in HCT116 human colorectal cancer cellsFEBS J27666896700200910.1111/j.1742-4658.2009.07383.x19843160

39. 

X ChenX GuoH ZhangRole of miR-143 targeting KRAS in colorectal tumorigenesisOncogene2813851392200910.1038/onc.2008.47419137007

40. 

H HeynM EngelmannS SchreekMicroRNA miR-335 is crucial for the BRCA1 regulatory cascade in breast cancer developmentInt J Cancer12927972806201110.1002/ijc.2596221618216

41. 

SF TavazoieC AlarcónT OskarssonEndogenous human microRNAs that suppress breast cancer metastasisNature451147152200810.1038/nature0648718185580

42. 

YN LeeS BrandalP NoelKIT signaling regulates MITF expression through miRNAs in normal and malignant mast cell proliferationBlood11736293640201110.1182/blood-2010-07-29354821273305

43. 

SK PatnaikE KannistoS YendamuriOverexpression of microRNA miR-30a or miR-191 in A549 lung cancer or BEAS-2B normal lung cell lines does not alter phenotypePLoS One5e9219201010.1371/journal.pone.000921920169152

44. 

J KimDM CoffeyCJ CreightonZ YuSM HawkinsMM MatzukHigh-grade serous ovarian cancer arises from fallopian tube in a mouse modelProc Natl Acad Sci USA10939213926201210.1073/pnas.111713510922331912

45. 

P Puerta-GilR García-BaqueroAY JiamiR-143, miR-222 and miR-452 are useful as tumor stratification and noninvasive diagnostic biomarkers for bladder cancerAm J Pathol18018081815201210.1016/j.ajpath.2012.01.03422426337

46. 

MA CortezJW WelshGA CalinCirculating microRNAs as noninvasive biomarkers in breast cancerRecent Results Cancer Res195151161201210.1007/978-3-642-28160-0_1322527502

47. 

JT MendellEN OlsonMicroRNAs in stress signaling and human diseaseCell14811721187201210.1016/j.cell.2012.02.00522424228

48. 

E Varkonyi-GasicRP HellensQuantitative stem-loop RT-PCR for detection of microRNAsMethods Mol Biol744145157201110.1007/978-1-61779-123-9_1021533691

49. 

T SaitoP SaetromMicroRNAs - targeting and target predictionN Biotechnol27243249201010.1016/j.nbt.2010.02.01620219708

50. 

ME PeterTargeting of mRNAs by multiple miRNAs: the next stepOncogene2921612164201010.1038/onc.2010.5920190803

51. 

S WuS HuangJ DingMultiple microRNAs modulate p21Cip1/Waf1 expression by directly targeting its 3′ untranslated regionOncogene2923022308201020190813

52. 

DW ThomsonCP BrackenGJ GoodallExperimental strategies for microRNA target identificationNucleic Acids Res3968456853201110.1093/nar/gkr33021652644

53. 

TA FaraziJI SpitzerP MorozovT TuschlmiRNAs in human cancerJ Pathol223102115201110.1002/path.2806

54. 

SK ShenoudaSK AlahariMicroRNA function in cancer: oncogene or a tumor suppressor?Cancer Metastasis Rev28369378200910.1007/s10555-009-9188-520012925

55. 

H ZhangX CaiY WangH TangD TongF JimicroRNA-143, down-regulated in osteosarcoma, promotes apoptosis and suppresses tumorigenicity by targeting Bcl-2Oncol Rep2413631369201020878132

56. 

L FanQ WuX XingY WeiZ ShaoMicroRNA-145 targets vascular endothelial growth factor and inhibits invasion and metastasis of osteosarcoma cellsActa Biochim Biophys Sin (Shanghai)44407414201210.1093/abbs/gms01922472569

57. 

D LiX LiuL LinMicroRNA-99a inhibits hepatocellular carcinoma growth and correlates with prognosis of patients with hepatocellular carcinomaJ Biol Chem2863667736685201110.1074/jbc.M111.27056121878637

58. 

D SunYS LeeA MalhotramiR-99 family of MicroRNAs suppresses the expression of prostate-specific antigen and prostate cancer cell proliferationCancer Res7113131324201110.1158/0008-5472.CAN-10-103121212412

59. 

DM ÖzataS CaramutaD Velázquez-FernándezThe role of microRNA deregulation in the pathogenesis of adrenocortical carcinomaEndocr Relat Cancer18643655201121859927

60. 

R MahnLC HeukampS RogenhoferA von RueckerSC MüllerJ EllingerCirculating microRNAs (miRNA) in serum of patients with prostate cancerUrology771265.e916201110.1016/j.urology.2011.01.02021539977

61. 

WC ChoEpigenetic alteration of microRNAs in feces of colorectal cancer and its clinical significanceExpert Rev Mol Diagn11691694201110.1586/erm.11.5721902530

62. 

KB JonesZ SalahS Del MaremiRNA signatures associate with pathogenesis and progression of osteosarcomaCancer Res7218651877201210.1158/0008-5472.CAN-11-266322350417

63. 

NM WhiteTT BaoJ GrigullmiRNA profiling for clear cell renal cell carcinoma: biomarker discovery and identification of potential controls and consequences of miRNA dysregulationJ Urol18610771083201110.1016/j.juro.2011.04.11021784468

64. 

MM VickersJ BarI Gorn-HondermannStage-dependent differential expression of microRNAs in colorectal cancer: potential role as markers of metastatic diseaseClin Exp Metastasis29123132201210.1007/s10585-011-9435-322120473

65. 

M ShuY ZhouW ZhuMicroRNA 335 is required for differentiation of malignant glioma cells induced by activation of cAMP/protein kinase A pathwayMol Pharmacol81292298201210.1124/mol.111.07616622172575

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November 2012
Volume 4 Issue 5

Print ISSN: 1792-1074
Online ISSN:1792-1082

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APA
Hu, H., Zhang, Y., Cai, X., Huang, J., & Cai, L. (2012). Changes in microRNA expression in the MG-63 osteosarcoma cell line compared with osteoblasts. Oncology Letters, 4, 1037-1042. https://doi.org/10.3892/ol.2012.866
MLA
Hu, H., Zhang, Y., Cai, X., Huang, J., Cai, L."Changes in microRNA expression in the MG-63 osteosarcoma cell line compared with osteoblasts". Oncology Letters 4.5 (2012): 1037-1042.
Chicago
Hu, H., Zhang, Y., Cai, X., Huang, J., Cai, L."Changes in microRNA expression in the MG-63 osteosarcoma cell line compared with osteoblasts". Oncology Letters 4, no. 5 (2012): 1037-1042. https://doi.org/10.3892/ol.2012.866