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Identification of differentially expressed microRNAs by microarray: a possible role for microRNAs gene in medulloblastomas

LIU, Wei; GONG, Yan-hua; CHAO, Teng-fei; PENG, Xiao-zhong; YUAN, Jian-gang; MA, Zhen-yu; JIA, Ge; ZHAO, Ji-zong

doi: 10.3760/cma.j.issn.0366-6999.2009.20.002
Original article
Free
SDC

Background MicroRNAs (miRNAs) are small noncoding regulatory RNAs whose aberrant expression may be observed in many malignancies. However, few data are yet available on human primary medulloblastomas. This work aimed to identify that whether miRNAs would be aberrantly expressed in tumor tissues compared with non-tumorous cerebellum tissues from same patients, and to explore a possible role during carcinogenesis.

Methods A high throughput microRNA microarray was performed in human primary medulloblastoma specimens to investigate differentially expressed miRNAs, and some miRNAs were validated using real-time quantitative RT-PCR method. In addition, the predicted target genes for the most significantly down- or up-regulated miRNAs were analyzed by using a newly modified ensemble algorithm.

Results Nine miRNA species were differentially expressed in medulloblastoma specimens versus normal non-tumorous cerebellum tissues. Of these, 4 were over expressed and 5 were under expressed. The changes ranged from 0.02-fold to 6.61-fold. These findings were confirmed using real-time quantitative RT-PCR for most significant deregulated miRNAs (miR-17, miR-100, miR-106b, and miR-218) which are novel and have not been previously published. Interestingly, most of the predicted target genes for these miRNAs were involved in medulloblastoma carcinogenesis.

Conclusions MiRNAs are differentially expressed between human medulloblastoma and non-tumorous cerebellum tissue. MiRNAs may play a role in the tumorigenesis of medulloblastoma and maybe serve as potential targets for novel therapeutic strategies in future.

Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100050, China (Liu W, Ma ZY, Jia G and Zhao JZ)

National Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing 100005, China (Gong YH, Chao TF, Peng XZ and Yuan JG)

Correspondence to: Dr. ZHAO Ji-zong, Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100050, China (Email: zhaojz@public.bta.net.cn) Dr. Liu Wei and Dr. GONG Yan-hua contribute equally to this article.

Dr. CHAO Teng-fei now works in Cancer Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.

This study was supported by a grant from the National High Technology Research and Development Program of China (No. 2002BA711A08).

(Received May 25, 2009)

Edited by JI Yuan-yuan

Medulloblastoma (MB) is one of the most common malignant pediatric cerebellar tumors (WHO grades IV), which has poor prognosis and is currently staged as average-risk or poor-risk on the basis of clinical findings. Despite current multimodality therapy, nearly 90% of patients with average-risk, non-disseminated MB have 5-year event-free survival; however, those with high-risk patients have only 25%-60% survival rate because of recurrence or dissemination within central nerve system, particularly worse in younger children.1,2 Furthermore long-term poor neurocognitive sequelae due to radiotherapy are rather common. Recent treatment trials have attempted to reduce such sequelae. On the other hand, the deep understanding of the molecular basis of MB is still far away from developing targeted treatments for MB. So, greater understanding for the molecular biology of MB carcinogenesis is needed so that more patients can be cured or have an improved quality of life.2–4

A recently identified class of non-protein-coding small RNAs, microRNAs (miRNAs), may provide a new insight in carcinogenesis research. They are an extensive class of endogenous small RNA molecules, 20-25 nucleotides in length and are important regulatory molecules in animals and plants. MiRNAs regulate gene expression by resulting in direct cleavage of the targeted mRNAs or inhibiting translation through perfect or nearly perfect complementarity to targeted mRNAs at the 3′ untranslated regions (UTRs) of the targets in animals.5 Including cancer, these targeted genes control multiple biological processes. Several examples of an existing association between specific miRNAs and cancer were shown,6–16 suggesting that these short molecules may represent a new class of genes involved in tumorigenesis and even some of them may function as oncogenes or tumor suppressors. Recognition of miRNAs that are differentially expressed between normal and tumor samples may help to identify those that are involved in human cancer and establish the basis to unravel their pathogenic role. In addition, the identification for miRNA expression signatures in MB may indicate new targets for novel therapeutic strategies. Ferretti et al17 has reported miRNA profiling in MB by comparing tumor specimen with normal cerebellum from different people. Here, we present results of a genome-wide miRNA expression profiling in tumor and non-tumorous cerebellum tissues from same patients and use our own algorithm to identify potential target genes for differentially regulated miRNAs.

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METHODS

Patients and samples

Surgical specimens of primary MB were collected from 6 patients with Institutional Review Board approval in the Department of Neurosurgery, Tiantan Hospital affiliated to Capital Medical University (Beijing, China). After informed consent, fresh samples from the tumor tissue MB (T-MB) and normal non-tumorous cerebella tonsil tissue adjacent to MB tumor (N-MB) of same patients which were used as controls were obtained from 6 patients with sporadic children (≤14 years) MB. N-MB samples were obtained at an average distance of 1.5-2.0 cm from the border of the enhanced tumor in tonsil of cerebellum, which did not show any evidence of tumor presence by macroscopical surgeon’s evaluation and postoperative pathohistological examination. Every sample was divided into two parts. One of them was frozen immediately (<10 minutes) after surgical resection until RNA isolation was performed. The other was fixed by 10% liquor formaldehyde for immunohistochemical analysis. Clinical and histopathology details of patients are showed in Table 1.

Table 1

Table 1

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RNA extraction

Sample preparation and processing were performed at the National Laboratory of Medical Molecular Biology in Peking Union Medical College. Total RNA isolation was done from each sample with TRIzol (Invitrogen, USA) according to the manufacturer's instructions. The extracted RNA was quantified using Agilent BioAnalyzer 2100 spectrophotometer (Agilent, Palo Alto, USA), and immediately stored at −80°C until analysis. RNA quality was assessed by 1.0% agarose gel electrophoresis.

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miRNA microarray

The miRNA microarray analysis was performed by L.C. Sciences (Houston, TX, USA). The assay started with approximated 5 μg total RNA sample, which was size fractionated using an YM-100 Microcon centrifugal filter (Millipore, Massachusetts, USA). The small RNAs (<300 nucleotide (nt)) isolated were 3′-extended with a poly (A) tail using poly (A) polymerase. An oligonucleotide tag was then ligated to the poly (A) tail for later fluorescent dye staining; two different tags were used for the two RNA samples in dual-sample experiments. Hybridization was performed overnight on a μParaflo microfluidic chip (Human_V7.1C_051017 miRNA array chip) (LC Sciences, Houston, USA) using a micro-circulation pump (Atactic Technologies, Houston, USA). One of the major advantages of the μParaflo microfluidic technology is that it allows efficient parallel synthesis of a large number of different oligonucleotide molecules.18 On the microfluidic chip, each detection probe consisted of a chemically modified nucleotide coding segment complementary to target microRNA (from miRBase, at http://microrna.sanger.ac.uk/sequences/). Hybridization reactions were performed in 100 μl 6×SSPE buffer (0.9 mol/L NaCl, 60 mmol/L Na2HPO4, 6 mmol/L EDTA, pH 6.8) containing 25% formamide at 34°C. Each pair of N-MB and T-MB sample was labelled with Cy3 and Cy5 fluorescent dyes. After RNA hybridization, tag-conjugating Cy3 and Cy5 dyes were circulated respectively for dye staining. Each analyzed miRNA was repeated six times. Hybridization images were collected using a laser scanner (GenePix 4000B, Molecular Device, Sunnyvale, USA) and digitized using Array-Pro image analysis software (Media Cybernetics Inc, USA).

Among the control probes, PUC2PM-20B and PUC2MM-20B are the perfect match and single-based match detection probes, respectively, of a 20-mer RNA positive control sequence that is spiked into the RNA samples before labelling. One may assess assay stringency from the intensity ratio of PUC2PM-20B and PUC2MM-20B, which is normally larger than 30.

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Data analysis for miRNA microarray

miRNA microarray data were analyzed by first subtracting the background and then normalizing the signals using a LOWESS filter (locally-weighted regression). A miRNA was listed as a detectable miRNA when it met at least three criteria: signal intensity higher than 3× (back-ground SD); spot coefficient of variation <0.5 (coefficient of variation=SD/signal intensity); and signals from at least 50% of the repeating probes above detection level. The array output was received in Excel spreadsheets as lists of raw data and also as “simple detectable” data. Those with P ≤0.01 are analyzed using 1-way, paired t test of the log2 value of each T-MB/N-MB pair of signals were calculated in every chip. All three chips were hybridized and statistical comparison was performed by using the analysis of variance (ANOVA, SPSS Inc, Chicago, USA). Those with P ≤0.05 are determinate to be aberrant expressive miRNAs in MBs.

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Analysis for real-time quantitative RT-PCR (qRT-PCR) miRNA expression

qRT-PCR were performed by using TIANScript MMLV-RTase (Tiangen, Germany) and standard PCR detection kit (Tiangen) following the manufacturer's instructions in an ABI7500 thermocycler (Applied Biosystems, USA). Reactions contained designed oligonucleotide qRT-PCR Primer Sets specific were generated by system software (DNAMAN 5.0 version, Lynnon Biosoft Inc, Quebec, Canada).

Specific matured microRNAs array were employed to detect using stem-loop real-time PCR principle.19 Reverse transcriptase reactions included purified total RNA (1-2 μg), 1 μmol/L stem-loop RT primer, 5×RT buffer, 0.25 mmol/L each of dNTPs, 50 U TIANScript M-MLV reverse transcriptase and 20 U RNase inhibitor. The 20 μl reactions were incubated in the ABI7500 thermocycler plate for 30 minutes at 16°C, 60 minutes at 42°C, 5 minutes at 85°C and hold at 4°C. The 20 μl PCR included 1 μl RT product, 1×TaqMan Universal PCR Master Mix, as recommended by the manufacturer. The reactions were incubated at 95°C for 10 seconds, followed by 40-45 cycles of 95°C for 5 seconds and 60°C for 34 seconds.

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Prediction of miRNA targets

The analysis of experimentally supported miRNA targets was done by using our newly modified ensemble algorithm to predict miRNA targets.20

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RESULTS

Analysis for isolated RNA quality

Total RNA was extracted from N-MB and T-MB samples using TRIzol reagent (Invitrogen) and agarose gel electrophoresis was done to analysis the quality of total RNA. The result showed clear strips of RNA isolation (28s/18s >2) without many degradation. So, the quality of the above RNA must meet the quality and requirement for further miRNA microarray.

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Data analysis for miRNA microarray

A microRNA expression signature discriminates between T-MB and N-MB. Differentially expressed patterns of miRNAs in MB were observed by using microarray chip (Figure 1). To identify miRNA whose expression was significantly different (P <0.05) between T-MB and N-MB samples, one-way ANOVA (SPSS12.0) was performed. In this study (Table 2), 4 miRNAs were over-expressed whose Cy3/Cy5 ratio is more than 1 (P <0.05), while 5 miRNAs were under-expressed in T-MB whose ratio less than 1 (P <0.05). Among these detected miRNAs, some of them, for example miR-100 was over-expressed with ratio higher than 2-fold and miR-218 was under-expressed with ratio lower than 50-fold (Table 2).

Figure 1.

Figure 1.

Table 2

Table 2

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Validation of differentially expressed miRNAs

To validate microarray results, we performed real-time qRT-PCR expression analysis on one tumor samples analyzed by microarray and furthermore the other three new patients' samples. Including additional miR-917,21miR-128,9miR-204 and miR-214, the expression of 8 selected miRNAs genes were analyzed (Figure 2). The expression data obtained by qRT-PCR analysis are comparable to the microarray data. The qRT-PCR for miR-17, miR-100, miR-106b, and miR-218 confirmed results obtained by microarray analysis.

Figure 2.

Figure 2.

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Target analysis

Given that biological significant of miRNA deregulation relies on their protein-coding gene targets, we analyzed the predicted targets of the most significantly down-regulated and up-regulated miRNAs: miR-17, miR-100, miR-106b, and miR-218. The analysis was done using the ensemble algorithm to predict human miRNA gene targets. Partial target genes (including oncogene and tumor suppressor gene) are showed in Table 3.

Table 3

Table 3

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DISCUSSION

Although MB represent the most frequent highly malignant brain tumors in childhood, their molecular pathogenesis is only partially understood. Calin et al22 demonstrated that >50% of miRNA genes are located at chromosomal regions, such as fragile sites, and regions of deletion or amplification that are genetically altered in human cancer, suggesting that miRNAs may play an important role in the pathogenesis of human cancers as a novel class of oncogenes or tumor suppressor genes. So, we reasoned that alterations in miRNA expression might contribute to MB. As far as we know, there is only one group research reported about miRNAs expression in human MB and normal tissue.17 To investigate whether miRNAs are differentially expressed among different MB individuals, we performed a high throughput microRNA microarray in human primary MB specimens to investigate microRNA involvement in carcinogenesis.

Although northern blotting and gene clone technique are widely used method for miRNA analysis, they have some limitations, such as difficulty in detecting multiple miRNAs simultaneously. MiRNA microarray analysis has become a comprehensive technology to help us better understand the relationship between cancer tissues and normal tissues.23 In addition, miRNA microarray technology has been widely used to study the roles of miRNA in cancers.6,12 An oligonucleotide miRNAs array chip has been a most widely used high throughput screening method to detect the expression profiles of hundreds of miRNAs in human cancer simultaneously.21

In this study, to reduce the bias from individual difference, the final microarray chip results were derived from the intersection set of three different samples. And then we recognized differentially expressed miRNAs which are same expression tendency in different chips as the final results and validated their reliability by qRT-PCR among extended samples range. The criteria for aberrant expression miRNAs in MB were as follows: (1) up- or down-expression change tendency in all chips and significantly different (P <0.05); (2) the detected signals ratio of T-MB and N-MB more than 2 or less than 0.5 fold at least.

Rapidly detect miRNA expression, real-time PCR can also be employed to quantify miRNAs expression profiles and study the potential function of miRNAs in cancer pathogenesis.24 We analyzed six MB samples to identify miRNAs whose expression were significantly deregulated in cancer versus non-tumorous cerebellum tissues by qRT-PCR analysis comparable to the microarray data. We have indeed identified four miRNAs whose expression were significantly deregulated (at P <0.05). These results leave few doubts that aberrant expression of miRNA is indeed involved in human MBs. Three of them, miR-17, miR-100, and miR-106b, were up-regulated and miR-218, was down-regulated, suggesting that they may potentially act as oncogenes or tumor suppressor genes, respectively. In line with our study, Uziel et al25 demonstrated that 3 miR-17-92 cluster miRNAs family (miR-92, miR-19a and miR-20) were also overexpressed in mouse MB with a constitutively activated Sonic Hedgehog (SHH) signalling pathway which involves the carcionogenesis in MB. In addition, Ferretti et al17 also confirmed that miR-106b and miR-17-5p were upregulated in MB vs normal cerebellum.

Besides miR-106 and miR-17-92 cluster family, several miRNAs were also deregulated in MB. At present, we have reviewed the biological functions deregulated by miR-17,26miR-100,27miR-106b,28 and miR-21829 aberrant expression in body solid tumors or leukemia, however, it has yet no reports about their function in brain tumors. So, we made use of presently available computational approaches to predict gene targets. Table 3 showed that various cancer-associated genes or genes encoding proteins with potential oncogenic or tumor suppressed functions are potentially regulated by miRNAs aberrantly expressed in MBs.

For the up-regulated miRNAs, it may be expected that their tagets include tumor suppressor genes or genes encoding proteins with potential promote tumor development by negatively inhibiting oncogenes. Interestingly, the tumor suppressor genes, fas-activated serine, FASTK and the p53-binding protein 3, TOPORS were potential targets of both miR-17 and miR-106b. It has been reported that the function of miR-17-92 cluster and miR-106b might play a role as synergistic effect each other involved same intracellular biological procedure.30 And then we discussed the same targets of both of them. Consequently, bioinformatics studies indicate that numerous genes are the targets of miR-17, miR-106b, and miR-100. Reasonably, among putative targets, several genes act as potential tumor suppressor genes, such as BAMBI, TOPORS, BTG2, TOB1, CASP8, and WEE1 could be found. TOPORS is encoding gene for tumor suppressor p53-binding protein, which results in the suppression of cell growth by cell cycle arrest and/or by the induction of apoptosis and mediates p53-dependent cellular responses as a tumor suppressor.31 It has been already reported in gliomas.32 BAMBI is an encoded protein to function as tumor suppressor gene. It is confirmed that the member of transforming growth factor (TGF)-beta family play important roles as an oncogenes in signal transduction in MB pathological process.33,34 BAMBI is a pseudoreceptor of TGF type I receptors and acts as a negative regulator of TGF-beta signalling. The antiproliferative genes BTG2 encode nerve growth factor (NGF)-inducible anti-proliferative protein which involved in the regulation of the G1/S transition of the cell cycle and act as anti-proliferative tumor suppressor. MB originate from cerebellar granule cell precursors (GCPs), located in the external granular layer (EGL) of the cerebellum while BTG2 promotes cerebellar neurogenesis by inducing GCPs to shift from proliferation to differentiation. Farioli-Vecchioli et al35 demonstrated up-regulation of BTG2 in mice resulted in a decrease of MB incidence. In addition, the tumor suppressor genes SUFU, PTCH1, and RB1 which were associated with MB carcinogenesis were predicted to be targeted by miR-100.

On the other hand, it may be expected that targets of down-regulated miRNAs include oncogenic functions. The pro-oncogenes ROS1, EGFR, and BCL2L11 (Bcl-2), CTNND2 (β-catenin), EGFR, MAPK9, MYBL1, TNFRSF1A (TNF) were predicted to be targeted by miR-218. ERBB1, oncogenes EGFR encoded protein, play an important role as a pro-oncogene in gliomas and as one of the therapeutic targets in MB;36CTNND2 is the encoded gene for β-catenin which be involved in the activation of APC/Wnt signal transduction pathway in MB.37 So, down-regulated of miR-218 would result in over-expression of the predicted target EGFR, which can activate mitogen-activated protein kinases (MAPK) pathway and β-catenin to promote development and invasion of tumor cell.

So, how did miRNA genes regulated in vivo? Epigenetic modification, such as chromosome loss of heterozygosity or remodelling, may produce aberrant miRNAs biogenesis. It has been reported that miRNA genes are frequently located in chromosomal regions characterized by nonrandom aberrations in human cancer, suggesting that resident miRNA expression might be affected by these genetic abnormalities.22 In our study, miR-106b and miR-218, which are up and down-modulated in MB, are located at chromosome 7q99 and 5q168 respectively (at www.microRNA.org), one of them in which aberrant gain and loss of heterozygosity could be verified in MB.38 So, it is reasonably concluded that abnormalities of chromosome can result in the aberrant expression of miRNAs and may consequently correlate with MB tumorigenesis by act as their target genes.

In conclusion, results reported here increase our understanding of the molecular basis of MB and suggest that aberrant expression of miRNA genes may be important for the pathogenesis of MB. There is a long way to go before artificial and natural miRNAs therapy could be used as cancer therapeutic tools and strategies for the clinical service. Additional studies will be required to further characterize role of the miRNAs gene regulation in MB.

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Keywords:

microRNA; oncogenes; medulloblastoma; target mRNA; carcinogenesis

© 2009 Chinese Medical Association