OR Oncology Reports 1021-335X 1791-2431 D.A. Spandidos 10.3892/or.2016.5070 or-36-05-2911 Articles Identification and functional characterization of lncRNAs acting as ceRNA involved in the malignant progression of glioblastoma multiforme ZhangKun12 LiQi3 KangXixiong4 WangYajie34* WangShuo1* Department of Neurosurgery, Beijing Tian Tan Hospital, Capital Medical University, Beijing 100050 Department of Neurosurgery, Beijing Chuiyangliu Hospital, Beijing 100020 Core Laboratory for Clinical Medical Research Department of Clinical Laboratory Diagnosis, Beijing Tian Tan Hospital, Capital Medical University, Beijing 100050, P.R. China Correspondence to: Professor Yajie Wang, Core Laboratory for Clinical Medical Research, Beijing Tian Tan Hospital, Capital Medical University, 6 Tiantan Xili, Beijing 100050, P.R. China, E-mail: tiantanwyj@163.com Professor Shuo Wang, Department of Neurosurgery, Beijing Tian Tan Hospital, Capital Medical University, 6 Tiantan Xili, Beijing 100050, P.R. China, E-mail: captain0330@163.com

Contributed equally

 11 2016 05 09 2016 36 5 2911 2925 06 04 2016 16 08 2016 Copyright © 2016, Spandidos Publications 2016

Glioblastoma multiforme (GBM) is the most common brain malignancy. Long non-coding RNAs (lncRNAs) are aberrantly expressed in many cancers and involved in pathogenesis, progression and metastasis of tumors. In particular, lncRNAs can function as competing endogenous RNAs (ceRNAs). The functional roles of lncRNA associated-ceRNAs in GBM are not fully understood. Human Exon 1.0 Microarray (Affymetrix) and Human MicroRNA Microarray (Agilent) were used to detect the expression of 955 microRNAs (miRNAs), 33,125 lncRNAs, and 17,453 mRNAs in 8 GBM and 8 normal brain samples. The function of differential mRNA was determined by Gene Ontology (GO) and pathway analysis. The distinctly expressed miRNAs, lncRNAs and mRNAs were subjected to construct miRNA-lncRNA-mRNA interaction network. The expression of miRNAs, lncRNAs and mRNAs in GBM tissues vs. normal brain tissues was examined by quantitative real-time RT-PCR. A total of 41 miRNAs, 398 lncRNAs and 1,995 mRNAs were found to be differentially expressed between the GBM and normal brain groups. GO and pathway analyses had proven that the functions of differentially expressed mRNAs in GBM related closely with many processes important in the cancer pathogenesis. Fifty-five lncRNAs acting as ceRNAs were identified based on the miRNA-lncRNA-mRNA interaction network. The potential roles of the 39 ceRNAs were revealed, which participated in 23 diverse cancer biological pathways, including proliferation, cell apoptosis, adhesion, angiogenesis and metastasis. The identified sets of miRNAs, lncRNAs and mRNAs specific to GBM were verified by qRT-PCR experiment in GBM samples. Our study predicts the biological functions of a multitude of lncRNA associated-ceRNAs in GBM. Moreover, our study provides a road map for the identification and analysis of lncRNA acting as ceRNA in tumors.

 glioblastoma multiforme microarray analysis long non-coding RNA competing endogenous RNA biological function Introduction

Mammalian genomes generate thousands of regulatory RNAs that are either long non-coding RNAs (lncRNAs) or microRNAs (miRNAs) (1,2). lncRNAs are more than 200 nucleotides, and synthesized by RNA polymerase II, spliced and sometimes polyadenylated (3). They are pervasively transcribed, and exhibit spatially and temporally regulated expression patterns (4). Unlike small ncRNAs, lncRNAs can fold into complex secondary and higher order structures to provide greater potential and versatility for both protein and target recognition (5). lncRNAs have been found to play crucial regulatory roles in a diverse range of cellular processes and biological pathways, including genomic imprinting, chromosome inactivation, differentiation and development of many human diseases (6). lncRNAs are emerging as new players in the cancer biology paradigms and their dysfunction are correlated with tumorigenesis and malignancy transformation in various types of cancers (7,8).

miRNAs, the most well characterized ncRNAs, are short endogenous molecules, approximately 22 nucleotides in length, that are processed by the RNase III enzymes Drosha and Dcr. miRNAs post-transcriptionally regulate the gene expression through interaction between the 5′ end and the 3′ untranslated region (3′UTR) of mRNA. miRNA can guide the RNA-induced silencing complex (RISC) to miRNA response element (MRE) on target transcript, usually resulting in degradation of the transcript or inhibition of its translation (9). Dysregulation of miRNA expression is involved in various diseases (10). Accumulating evidence highlights the role of miRNA-mediated regulation in cell growth, differentiation, proliferation and apoptosis. Alterations in the miRNA balance in the cell can lead to dysregulation of tumor suppressor genes and/or oncogenes regulated by aberrantly expressed miRNAs, leading to cancer (11,12).

Recent studies have described a complicated interplay among diverse RNA species, including coding and non-coding RNAs. These RNAs inclusive of mRNA, pseudogene, lncRNA or circular RNA, interact and co-regulate with each other by acting as competing endogenous RNAs (ceRNAs). ceRNAs have MRE, and serve as miRNA sponges to control miRNAs available to their target RNAs. ceRNA can sequester miRNAs, thereby protecting their target RNAs from repression (13). Understanding this novel RNA interaction will lead to significant insight into gene regulatory networks in human development and disease. Although lacking 3′UTRs, lncRNAs have been reported to be downregulated by miRNAs and work as ceRNAs. The experimental evidence is already emerging of lncRNAs as competitive platforms for both miRNAs and mRNAs (14,15).

Glioblastoma multiforme (GBM) is the most common and malignant brain tumor with poor prognosis. According to the 2007 World Health Organization classification, gliomas are classified into 4 histopathological grades based on malignancy degree, and GBM is the highest-grade glioma (grade IV) (16). Patients with newly diagnosed GBM exhibit a median survival of approximately 15 months (17). Despite maximal surgical, radiological and chemotherapeutic interventions, these figures have changed little in the past two decades (18). New therapeutic strategies will likely evolve from a better understanding of GBM biology.

Efforts have been made to study the relationship between the lncRNA expression and the GBM pathogenesis (8,19–21), but many more lncRNAs playing crucial roles in GBM remain to be determined. The aberrant miRNA expression has features of GBM (22). Nevertheless, the miRNA-lncRNA-mRNA regulation networks in the GBM, as well as the potential roles of ceRNAs in the biogenesis and development of GBM have not been explored.

In this study, we aimed at profiling the miRNA, lncRNA and mRNA expression signature, and constructing miRNA-lncRNA-mRNA crosstalk by analyzing a cohort of sample-matched exon and miRNA expression microarrays from the Cancer Genome Atlas (TCGA), and predicting the functions of lncRNAs acting as ceRNAs in GBM. The identified sets of lncRNA, miRNA and mRNA specific to GBM were subsequently confirmed by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) in GBM samples.

 Materials and methods Data-set characteristics

The sample matched whole-transcript and miRNA expression profiling upon GBM were obtained from the TCGA database (https://tcga-data.nci.nih.gov/tcga/). To compare the miRNA, lncRNA and mRNA expression signatures in GBM, we selected 16 data-sets that included 8 GBM and 8 non-tumoral brain samples. Two panels of data-sets were included in our study: Affymetrix Human Exon 1.0 array and Agilent Human MicroRNA array 8×15K.

 Data analysis

Two-class differential was used to determine the differentially expressed miRNA, lncRNA and mRNA between the normal and GBM groups. The random variance model (RVM) t-test was applied to filter the differentially expressed genes for it can effectively increase the degrees of freedom in cases of small samples. The false discovery rate (FDR) was calculated to correct the P-value. We selected the differentially expressed miRNAs, lncRNAs and mRNAs according to the P-value and FDR. P-values <0.05 and FDR <0.05 were considered significant.

The differentially expressed probe sets were imported into Cluster and TreeView (Stanford University) to perform hierarchical cluster analysis (HCA) (23).

 Gene Ontology (GO) and pathway analysis

A GO analysis was applied to analyze the main functions of the differentially expressed mRNAs (24). Specifically, a two-sided Fisher's exact test and a χ2 test were used to classify the GO category. We computed P-values of the GO for each differential gene. Enrichment provides a measure for the significant function: As the enrichment increases, the corresponding function is more specific. Within the significant category, the enrichment Re was given as follows: Re = (nf/n)/(Nf/N), where nf is the number of flagged genes within the particular category, n is the total number of genes within the same category, Nf is the number of flagged genes in the entire microarray, and N is the total number of genes in the microarray.

Pathway analysis was used to identify the significant pathway of the differential mRNAs according to KEGG, BioCarta and Reactome. We used Fisher's exact test and the χ2 test to select the significant pathway, and the threshold of significance was defined by P-value and FDR. The enrichment Re was calculated as described above (25).

 Construction of lncRNA-mRNA co-expression network

The lncRNA-mRNA networks were built according to the normalized signal intensity of specific mRNA and lncRNA expression in microarray. For each pair of mRNA-lncRNA, mRNA-mRNA or lncRNA-lncRNA, we calculated the Pearson correlation and chose the significant correlation pairs to construct the network (26). In a network analysis, degree is the most important measure of an mRNA or lncRNA centrality within a network. Degree centrality is defined as the link numbers one node has to the other (27). The clustering coefficient represents the density of each gene with the adjacent gene, and the larger the clustering coefficient, the greater importance the gene has in regulating the network.

 Patient samples

GBM specimens were derived from patients with GBM who underwent surgical treatment at Beijing Tian Tan Hospital. All histologic diagnoses were made on formalin fixed, paraffin-embedded H&E sections and were reviewed blinded to the original diagnosis according to the 2007 World Health Organization classification. Normal brain tissues were obtained from severe head trauma patients for whom partial resection of normal brain was required during surgery at Beijing Tian Tan Hospital. Samples were collected immediately after surgical resection, snap-frozen and stored in liquid nitrogen. The study was approved by the institutional review board of Beijing Tian Tan Hospital.

 RNA preparation and qRT-PCR

Total RNA from tissue specimens was extracted using the TRIzol reagent (Invitrogen Life Technologies, Carlsbad, CA, USA). RNA integrity was analyzed on a 1.2% agarose gel. RNA quantity was determined using a NanoDrop 2000c Spectrophotometer (Thermo Fisher Scientific, Inc., Waltham, MA, USA). RNA (1 μg) was reverse transcribed with a PrimeScript™ RT reagent kit (Takara Biotechnology Co., Ltd., Dalian, China) for cDNA synthesis and genomic DNA removal. For miRNA detection, total RNA was reverse transcribed using miRNA specific primers. qPCRs were performed according to the instructions of the SYBR Premix Ex Taq™ II kit (Takara Biotechnology Co., Ltd.) and carried out in the Takara real-time PCR system. Gene-specific primers were designed using online primer designing tools primer-blast (http://www.ncbi.nlm.nih.gov/tools/primer-blast/). The primer sequences are listed in Table I. The lengths of amplifications are between 100 and 250 bp. Standard deviations were calculated from three PCR replicates. The specificity of amplification was assessed by dissociation curve analysis and the relative abundance of genes was determined using the comparative ΔΔCt method.

 Results GBM demonstrates significantly altered miRNA, lncRNA and mRNA expression patterns comparing with that of the normal brain

In terms of the Sanger miRBase database, 866 human and 89 human viral miRNAs were authenticated on the Agilent Human MicroRNA array 8×15K. Based on the NetAffx annotation of the probe sets, the Ensemble, NOCODE3.0, and UCSC annotations of lncRNAs, and the RefSeq, Ensemble and GenBank annotations of mRNAs, we identified 33,125 lncRNAs (corresponding to 44,482 probe sets) and 17,453 mRNAs (corresponding to 22,011 probe sets) represented on the Affymetrix Human Exon 1.0 array (data not shown).

The expression patterns of miRNAs, lncRNAs and mRNAs were detected in 8 GBMs and 8 normal brain samples. We identified 41 miRNAs, 398 lncRNAs and 1,995 mRNAs that had significant differential expression in the GBM group comparing with the normal brain group (fold change ≥2.0 or ≤0.5 and P-value <0.05, data not shown).

The hierarchical clustering analysis showed that with the differential expression of these miRNAs, lncRNAs and mRNAs, samples were non-random partitioned, they were divided into 2 groups, the first group containing 8 normal brain samples and the second group containing 8 GBM samples (Fig. 1). Thus, the miRNA, lncRNA and mRNA expression signatures identified here were likely to be representative.

 Construction of miRNA-lncRNA-mRNA interaction network and identification lncRNAs acting as ceRNAs

The miRNA-lncRNA-mRNA network was constructed according to the study flow summarized in Fig. 2.

First, the target mRNAs of the differentially expressed miRNA were analyzed by TargetScan and miRanda method, termed as target 1 mRNAs (6,737 mRNAs, data not shown). The intersection of the target 1 mRNAs and differentially expressed mRNAs in GBM was picked and obtained target 2 mRNAs (1,034 mRNAs, data not shown). Of the target 2 mRNAs, the mRNAs were selected with expression levels negatively correlated with miRNA expression, and were termed the N&T mRNAs (749 mRNAs, data not shown).

Then, GO and pathway analysis were applied to analyze the significant function and pathway of the N&T mRNAs. GO analysis results showed that upregulated and downregulated mRNAs respectively were involved in 156 and 240 items with significant functions (P-value <0.01, data not shown). The pathway analysis revealed that there were 65 and 24 significant pathways corresponding to the up and downregulated mRNAs respectively (P-value <0.01, data not shown).

The third step, the mRNAs that contained both the significant function and pathway were termed G&P mRNAs (248 mRNAs, data not shown). The G&P mRNAs and differently expressed lncRNAs were used to build the lncRNA-mRNA co-expression network, respectively, in the normal and GBM group (data not shown).

The TargetScan method was used to analysis the target lncRNAs of differentially expressed miRNA and obtained the 55 miRNA targeted lncRNAs. These 55 lncRNAs were identified ceRNAs. Based on the interaction network of miRNA-mRNA, miRNA-lncRNA and lncRNA-mRNA, we obtained 224 feed-forward loop networks and constructed general miRNA-lncRNA-mRNA feed-forward loop network (data not shown). All of miRNAs, lncRNAs and mRNAs and their relations in this network are listed in Table II.

 Biological prediction of lncRNA function as ceRNAs in the GBM

The functions of 55 lncRNAs acting as ceRNAs were predicted through pathway analysis of 67 mRNAs in the miRNA-lncRNA-mRNA interaction network. The results indicated that 30 mRNAs participated in 7 upregulated and 16 downregulated pathways which involved in diverse biological processes of cancer, including proliferation, cell apoptosis, adhesion, angiogenesis and metastasis (Fig. 3A and B). As a consequence, we predicted the important roles of the 39 ceRNAs in GBM pathogenesis. The miRNAs, lncRNAs, mRNAs, and their participated pathways are listed in Table III.

 Quantitative real-time RT-PCR analysis of the distinctive expression of lncRNAs, miRNAs and mRNAs in GBM samples

To validate the conclusions of microarray analysis, we selected 10 miRNAs with larger fold change from the microarray results and analyzed their expression levels by qRT-PCR in 20 normal brain and 30 GBM samples. Our results confirmed the findings of the miRNA microarray dataset (Fig. 4A and B).

Based on the analysis of 224 miRNA-lncRNA-mRNA feed-forward loops in Table II, we evaluated the expression levels of 4 miRNA, 4 lncRNA and 4 mRNA that, respectively, located in 4 feed-forward loops. The average expression levels of miR-15a and miR-21 were significantly increased, while miR-29b and miR-29c were reduced in GBM compared with normal brain tissues. Analysis showed relatively high expression of miRNA and low expression of lncRNA and mRNA, and low expression of miRNA and high expression of lncRNA and mRNA (Fig. 4C and D). The 4 feed-forward loops detection by qRT-PCR are presented in Fig. 4E.

 Discussion

In recent years, the emerging significance of ceRNAs in cancers has drawn attention of researchers. ceRNA activity is determined by factors such as miRNA/ceRNA abundance, ceRNA binding affinity to miRNAs and RNA-binding proteins. The alteration of any of these factors may lead to ceRNA network imbalance and thus contribute to cancer (28). ceRNA study processes generally include: ceRNA prediction, ceRNA validation and ceRNA functional investigation.

Recently, several studies have confirmed the dysregulation of lncRNAs by acting as ceRNAs have profound implications for tumor initiation, maintenance or progression. lncRNAs acting as ceRNAs are involvd in the pathogenesis of several common cancers such as thyroid cancer, gastric cancer and hepatocellular cancer (29–33). The ceRNA activity of lncRNAs has also been shown to have an oncogenic effect: The lncRNA HOTAIR was shown to display ceRNA activity in gastric cancer cells, in which it was found to specifically bind the tumor suppressor miR-331-3p, modulating HER2 derepression (31). The other example of lncRNA-mediated ceRNA regulation involves the tumor suppressor gene BARD1. The lncRNA BARD1 9′L is transcribed by an alternative intronic promoter of the BARD1 gene and share both miR-203 and miR-101 MREs with BARD1 mRNA in their homologous 3′UTRs. BARD1 mRNAs were downregulated by miR-203 and miR-101, and BARD1 9′L counteracted the effect of these miRNAs. These data support a role for BARD1 9′L as a tumor suppressor transcript through its ceRNA activity (33). These findings provide important clues for understanding the key roles of lncRNA-miRNA functional network in cancers. Exploring the interplay of lncRNA function as a ceRNA in cancer provides new insight into cancer pathogenesis and opportunities for therapy exploration.

Understanding the novel miRNA-lncRNA-mRNA crosstalk will lead to significant insight into gene regulatory networks in cancers. In this study, we investigated the miRNA, lncRNA and mRNA expression signatures in GBM, constructed the miRNA-lncRNA-mRNA regulation network, on this basis, identified the lncRNA acting as ceRNAs and predicted the possible biology functions of these ceRNAs.

We re-annotated the Affymetrix Human Exon 1.0 probe sets and identified the lncRNAs and mRNAs on this array. The sample matched miRNA expression profiling of the Agilent Human MicroRNA array 8×15K was analyzed to determine differently expressed miRNAs in GBM. We identified a set of 41 miRNAs, 398 lncRNAs and 1,995 mRNAs with differentiated expression between GBM and normal brain tissues. Such differentiation signified their potential roles in tumorigenesis.

The complexity and diversity of potential ceRNA interactions have been described with the identification of abundant lncRNAs. We discussed the effect of miRNA competition on the regulation of both lncRNAs and mRNAs, as well as the implications of lncRNA function as ceRNA for the development of GBM. To our knowledge, this is the first study to show the roles of lncRNA acting as ceRNAs in GBM. Understanding the key roles of 'miRNA-lncRNA' module will lead to the identification of new therapeutic targets for treating GBM.

Our qRT-PCR expression analysis confirmed there are a series of miRNAs, lncRNAs and mRNAs aberrantly expressed in GBM tissues, which indicated that the differently expressed non-coding and coding RNAs may be one of characters of GBM. The aberrant miR-21, miR-27a, miR-210, miR-23a, miR-155, miR-139, miR-338, miR-137, miR-7, miR-124a, miR-15a, miR-29b and miR-29c expression levels in GBM were detected, our results were in concordance with the previous findings, and these deregulated miRNAs have been reported to be aberrantly expressed in GBM (34–42). In our expression profiling analysis, the lncRNA ENST00000520186, ENST00000559981, ENST00000547415 and ENST00000518554 were separately considered as the ceRNA of miR-15a, miR-21, miR-29b and miR-29c in GBM. So far, these ceRNAs have not been reported implicated in GBM. Four mRNAs may be regulated by these miRNAs and lncRNAs, the PPP3CA have been reported to be aberrantly expressed in other tumors, but have not been studied in GBM; in addition, AKT3, TNFRSF1A and LAMC1 have been studied to different expression in GBM (36,43,44).

Overall, our study identified and analyzed lncRNA function as ceRNA in GBM and showed they may play crucial biological roles during GBM formation and development, and provide important theory and experimental foundations for future study of drug target and treatment for GBM.

 Acknowledgments

This study was supported by the Natural Science Foun dation of China (nos. 81572474 and 81303268), the Natural Science Foundation of Beijing City (no. 7152098), the Excellence Talents Training Projects of Beijing City (no. 2013D009008000006) and the Science and Technology Development Fund Project of Traditional Chinese Medicine of Beijing (JJ2015-14). The authors would like to thank the Genminix Company (Shanghai, China) for assistance with bioinformatics analysis.

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Hierarchical clustering analysis of miRNA, lncRNA and mRNA expression levels change between two groups (normal brain and GBM). (A) Forty-one miRNAs and (B) 398 lncRNAs. (C) mRNAs (1,995) are differentially expressed in GBM tissue (≥2-fold or ≤0.5-fold change; P<0.05 and FDR<0.05). Columns represent samples and rows, respectively, represent miRNA, lncRNA or mRNA probe sets. Red, represents high expression; green, represents low expression, indicating expression above and below the median expression value across all of the samples, respectively (log scale, 2; from −1.80 to +1.80). miRNA, microRNA; lncRNA, long non-coding RNA; GBM, glioblastoma multiforme; FDR, false discovery rate.

Schematic overview of the study flow for construction of miRNA-lncRNA-mRNA interaction network. miRNA, microRNA; lncRNA, long non-coding RNA.

Function prediction of the ceRNAs based on pathway analysis of mRNAs located in miRNA-lncRNA-mRNA interaction network in GBM. The pathway analysis applied for 30 mRNAs showed the 7 upregulated and 16 downregulated tumor associated signaling pathways (P<0.05). ceRNAs, competing endogenous RNAs; miRNA, microRNA; lncRNA, long non-coding RNA; GBM, glioblastoma multiforme.

Expression analysis of miRNA, lncRNA and mRNA in normal brain and GBM tissues. (A and B) The expression level of 10 miRNAs, (C and D) 4 miRNAs, 4 lncRNAs and 4 mRNAs that, respectively, located in (E) 4 feed-forward loops were analyzed using qRT-PCR in normal brain (20 samples) and GBM (30 patients) tissues, with the GAPDH (for lncRNA and mRNA) and U6 (for miRNA) gene as an internal control. Error bars represent the standard errors of independent samples. miRNA, microRNA; lncRNA, long non-coding RNA; GBM, glioblastoma multiforme.

The miRNA, lncRNA and mRNA primers for qRT-PCR.

Primers Sequences (5′-3′)
miR-21 RT: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGATCAACATG
F: CTCAACTGGTGTCGTGGAGT
R: ACACTCCAGCTGGGTAGCTTATCAGACTG
miR-27a RT: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAGCGGAACTT
F: CTCAACTGGTGTCGTGGAGT
R: ACACTCCAGCTGGGTTCACAGTGGCTAAG
miR-210 RT: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGATCAGCCGC
F: CTCAACTGGTGTCGTGGAGT
R: CACTCCAGCTGGGCTGTGCGTGTGACAG
miR-23a RT: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAGGAAATCCC
F: CTCAACTGGTGTCGTGGAGT
R: CACTCCAGCTGGGATCACATTGCCAGGG
miR-155 RT: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAACCCCTATC
F: CTCAACTGGTGTCGTGGAGT
R: ACACTCCAGCTGGGTTAATGCTAATCGTG
miR-139 RT: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAACTGGAGA
F: CTCAACTGGTGTCGTGGAGT
R: CACTCCAGCTGGGTCTACAGTGCACGTG
hsa-miR-338 RT: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGACAACAAAAT
F: CTCAACTGGTGTCGTGGAGT
R: ACACTCCAGCTGGGTATTGCACTCGTCC
miR-137 RT: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGACTACGCGTA
F: CTCAACTGGTGTCGTGGAGT
R: ACACTCCAGCTGGGTTATTGCTTAAGAAT
miR-7 RT: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAACAACAAA
F: CTCAACTGGTGTCGTGGAGT
R: CACTCCAGCTGGGTGGAAGACTAGTGAT
miR-124a RT: TCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAGGCATTCAC
F: CTCAACTGGTGTCGTGGAGT
R: CACTCCAGCTGGGTAAGGCACGCGGTGA
miR-15a RT: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGACACAAACCA
F: CTCAACTGGTGTCGTGGAGT
R: CACTCCAGCTGGGTAGCAGCACATAATG
miR-29b RT: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAAACACTGAT
F: CTCAACTGGTGTCGTGGAGT
R: CACTCCAGCTGGGTAGCACCATTTGAAA
miR-29c RT: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGATAACCGATT
F: CTCAACTGGTGTCGTGGAGT
R: CACTCCAGCTGGGTAGCACCATTTGAAA
ENST00000520186 F: GTTGGACCTTACTGAGGCCG
R: GGAGACACCATGGCTGGAAC
ENST00000559981 F: AGAGTGAAATTTTGTATAAGCACCA
R: GCCTGGAGACATACTGAGATGG
ENST00000547415 F: TGCCATCTGCAGAGTGAAACT
R: GGCTTTCCAGTCTAGGGCAG
ENST00000518554 F: TGGCATTTTGTCAGTTTTCCCG
R: GCAAATGCACACACCACTCC
GAPDH F: GCACCGTCAAGGCTGAGAAC
R: TGGTGAAGACGCCAGTGGA
RNU6 F: CTCGCTTCGGCAGCACA
R: AACGCTTCACGAATTTGCGT
AKT3 F: TTGCTTTCAGGGCTCTTGAT
R: CATAATTTCTTTGCATCATCTGG
PPP3CA F: TGTGATATCCTGTGGTCAGA
R: CTGACTGTGTTGTGAGTGAA
LAMC1 F: TGGGCATTCTTCTGTCTGTACAA
R: GCCACCCATCCTCATCAATC
TNFRSF1A F: TGCCTACCCCAGATTGAGAA
R: ATTTCCCACAAACAATGGAGTAG

miRNA, microRNA; lncRNA, long non-coding RNA.

The 224 feed-forward loops including miRNAs, lncRNAs and mRNAs.

No. miRNA lncRNA mRNA
1 miR-15a n339339 PAK7
2 miR-15a n339339 CACNA1E
3 miR-15a ENST00000520186 PAK7
4 miR-15a ENST00000533229 PAK7
5 miR-15a ENST00000566630 PAK7
6 miR-15a n341995 PAK7
7 miR-15a n346032 CACNA1E
8 miR-15a n346032 NMNAT2
9 miR-15a ENST00000520186 MAPK9
10 miR-15a ENST00000520186 AKT3
11 miR-15a ENST00000559981 VAMP1
12 miR-15a ENST00000559981 SYNJ1
13 miR-15a ENST00000596580 VAMP1
14 miR-15a ENST00000596580 AKT3
15 miR-15a ENST00000596580 SYNJ1
16 miR-15a ENST00000596580 SLC9A6
17 miR-15a ENST00000569946 VAMP1
18 miR-15a ENST00000532691 CACNA1E
19 miR-15a ENST00000566942 HTR2A
20 miR-15a n338128 PTPRR
21 miR-15a ENST00000566630 CACNA1E
22 miR-15a ENST00000524501 CACNA1E
23 miR-15a ENST00000578746 CACNA1E
24 miR-15a n341995 CACNA1E
25 miR-15a n410578 SYNJ1
26 miR-15a ENST00000524501 NMNAT2
27 miR-15a ENST00000578746 NMNAT2
28 miR-15a n411142 AKT3
29 miR-15a ENST00000492667 AKT3
30 miR-15a ENST00000434383 SGCD
31 miR-15a n411142 SYNJ1
32 miR-15a ENST00000492667 SYNJ1
33 miR-15b n339339 PAK7
34 miR-15b n339339 CACNA1E
35 miR-15b ENST00000520186 PAK7
36 miR-15b ENST00000533229 PAK7
37 miR-15b ENST00000566630 PAK7
38 miR-15b n341995 PAK7
39 miR-15b n406352 PAK7
40 miR-15b n346032 CACNA1E
41 miR-15b n346032 NMNAT2
42 miR-15b ENST00000520186 MAPK9
43 miR-15b ENST00000520186 AKT3
44 miR-15b ENST00000559981 VAMP1
45 miR-15b ENST00000559981 SYNJ1
46 miR-15b ENST00000596580 VAMP1
47 miR-15b ENST00000596580 AKT3
48 miR-15b ENST00000596580 SYNJ1
49 miR-15b ENST00000596580 SLC9A6
50 miR-15b ENST00000569946 VAMP1
51 miR-15b ENST00000532691 CACNA1E
52 miR-15b ENST00000566942 HTR2A
53 miR-15b n338128 PTPRR
54 miR-15b ENST00000566630 CACNA1E
55 miR-15b ENST00000524501 CACNA1E
56 miR-15b n341995 CACNA1E
57 miR-15b n406352 CACNA1E
58 miR-15b n410578 SYNJ1
59 miR-15b ENST00000524501 NMNAT2
60 miR-15b n411142 AKT3
61 miR-15b ENST00000492667 AKT3
62 miR-15b ENST00000434383 SGCD
63 miR-15b n411142 SYNJ1
64 miR-15b ENST00000492667 SYNJ1
65 miR-23a n339339 SLIT1
66 miR-23a n339339 RXRG
67 miR-23a n339339 SLC1A1
68 miR-23a ENST00000562191 GABRB2
69 miR-23a ENST00000562191 NEFL
70 miR-23a ENST00000562191 MEF2C
71 miR-23a n346032 GABRB3
72 miR-23a n346032 PCLO
73 miR-23a ENST00000522102 SRGAP3
74 miR-23a n385835 GABRA4
75 miR-23a n383510 FUT9
76 miR-23a n383510 CADM3
77 miR-23a ENST00000559981 ATP6V1C1
78 miR-23a ENST00000559981 SYNJ1
79 miR-23a ENST00000559981 TLN2
80 miR-23a ENST00000555811 GABRB3
81 miR-23a ENST00000566630 GABRB3
82 miR-23a ENST00000524501 GABRB3
83 miR-23a ENST00000555811 FUT9
84 miR-23a ENST00000555811 PCLO
85 miR-23a n411142 ATP6V1C1
86 miR-23a n373066 FUT9
87 miR-23a ENST00000524501 PCLO
88 miR-23a ENST00000524501 NRXN3
89 miR-23a ENST00000434383 RXRG
90 miR-23a ENST00000434383 SGCD
91 miR-23a ENST00000502752 RAB11FIP2
92 miR-23a n384012 TLN2
93 miR-23a n411142 SYNJ1
94 miR-30a n346032 GRM5
95 miR-30a ENST00000522102 SRGAP3
96 miR-30a n373066 CAMK4
97 miR-30a ENST00000520186 PSD3
98 miR-30a ENST00000473866 GNAO1
99 miR-30a ENST00000532691 GRM5
100 miR-30a ENST00000569946 GRM3
101 miR-30a ENST00000569946 CACNA1C
102 miR-30a n339481 CACNA1C
103 miR-30a ENST00000532691 B4GALT6
104 miR-30a ENST00000569946 NEFL
105 miR-30a ENST00000566630 B4GALT6
106 miR-30a n374560 GDA
107 miR-30a ENST00000471736 GRIA2
108 miR-30a ENST00000569946 NEFM
109 miR-30a ENST00000530447 B4GALT6
110 miR-27a n339339 IQSEC1
111 miR-27a n339339 PDE3B
112 miR-27a ENST00000564076 CACNB2
113 miR-27a ENST00000562191 SNAP25
114 miR-27a n346032 GABRB3
115 miR-27a n346032 SYT1
116 miR-27a n346032 PCLO
117 miR-27a ENST00000522102 SRGAP3
118 miR-27a ENST00000566630 GABRB3
119 miR-27a n406352 GABRB3
120 miR-27a n371475 CDS1
121 miR-27a n338494 CACNB2
122 miR-27a n345100 SYT1
123 miR-27a n345100 SNAP25
124 miR-27a n373066 FUT9
125 miR-27a n339978 SYT1
126 miR-27a n406352 PDE3B
127 miR-27a n406352 ATP6V1A
128 miR-27a ENST00000492667 ATP2B1
129 miR-34a n339339 CACNA1E
130 miR-34a n346032 CACNA1E
131 miR-34a n346032 GABRA3
132 miR-34a n346032 SYT1
133 miR-34a n383510 FUT9
134 miR-34a ENST00000549205 PSD3
135 miR-34a ENST00000549205 PRKCE
136 miR-34a ENST00000596580 SYNJ1
137 miR-34a ENST00000555811 CACNA1E
138 miR-34a ENST00000555811 FUT9
139 miR-34a ENST00000555811 PCLO
140 miR-34a n384244 CNTN2
141 miR-34a ENST00000566630 CACNA1E
142 miR-34a n406352 CACNA1E
143 miR-34a n410578 SYNJ1
144 miR-34a ENST00000569946 CPLX2
145 miR-34a n339978 SYT1
146 miR-34a n406352 WASF1
147 miR-34a n406352 PRKCE
148 miR-34a ENST00000492667 SYNJ1
149 miR-106b ENST00000440363 PDE3B
150 miR-106b ENST00000522102 SRGAP3
151 miR-106b ENST00000596580 PIP4K2A
152 miR-106b ENST00000596580 AKT3
153 miR-106b n345100 MAPK9
154 miR-106b n337874 PIP4K2A
155 miR-106b n337874 GABBR1
156 miR-106b ENST00000555811 RIMS2
157 miR-106b ENST00000555811 B4GALT6
158 miR-106b n345100 RIMS2
159 miR-106b n337874 B4GALT6
160 miR-106b n345100 SCN1A
161 miR-106b n411142 AKT3
162 miR-106b ENST00000434383 SGCD
163 miR-25 ENST00000493303 PRKCE
164 miR-25 ENST00000549205 MAP2K4
165 miR-25 ENST00000555811 ST6GAL2
166 miR-25 n337874 ST6GAL2
167 miR-25 ENST00000566630 ST6GAL2
168 miR-25 ENST00000530447 ST6GAL2
169 miR-25 ENST00000549205 PRKCE
170 miR-25 n345100 CACNA1C
171 miR-25 n345100 NEFL
172 miR-25 ENST00000555811 RIMS2
173 miR-25 n345100 RIMS2
174 miR-25 n345100 SYT1
175 miR-2 n410578 SYNJ1
176 miR-25 n406352 PRKCE
177 miR-25 n411142 SYNJ1
178 miR-25 ENST00000492667 SYNJ1
179 miR-223 ENST00000493303 PRKCE
180 miR-223 n371741 ATP2B1
181 miR-223 n406352 PRKCE
182 miR-223 ENST00000492667 ATP2B1
183 miR-155 n345100 GABRA1
184 miR-155 n346032 DYNC1I1
185 miR-155 n341006 RAB11FIP2
186 miR-155 ENST00000596580 ATP6V1C1
187 miR-155 n345100 CACNA1C
188 miR-155 ENST00000535764 ATP6V1C1
189 miR-155 n411142 ATP6V1C1
190 miR-155 n345100 SCN1A
191 miR-155 n345100 DYNC1I1
192 miR-155 ENST00000578746 DYNC1I1
193 miR-2 ENST00000559981 PPP3CA
194 miR-21 n411142 PPP3CA
195 miR-21 ENST00000492667 PPP3CA
196 miR-92b ENST00000555811 ST6GAL2
197 miR-92b n337874 ST6GAL2
198 miR-92b ENST00000530447 ST6GAL2
199 miR-92b ENST00000596580 SYNJ1
200 miR-92b n345100 CACNA1C
201 miR-92b n345100 NEFL
202 miR-92b ENST00000555811 RIMS2
203 miR-92b n345100 RIMS2
204 miR-92b n345100 SYT1
205 miR-92b n410578 SYNJ1
206 miR-92b n411142 SYNJ1
207 miR-92b ENST00000492667 SYNJ1
208 miR-339 n383510 CADM3
209 miR-339 ENST00000555811 DAAM2
210 miR-339 ENST00000555811 PCLO
211 miR-339 ENST00000523571 DAAM2
212 miR-339 ENST00000481854 SGCD
213 miR-10b ENST00000221169 TIAM1
214 miR-10b ENST00000555811 RIMS2
215 miR-10b ENST00000524501 RIMS2
216 miR-29b ENST00000481203 TNFRSF1A
217 miR-29b ENST00000518554 TNFRSF1A
218 miR-29b ENST00000547415 LAMC1
219 miR-29b ENST00000559148 MYBL2
220 miR-377 n338229 LAMC1
221 miR-124 n376998 EDNRB
222 miR-29c ENST00000547415 LAMC1
223 miR-29c ENST00000559148 MYBL2
224 miR-29c ENST00000518554 TNFRSF1A

lncRNAs, long non-coding RNAs; miRNAs, microRNAs.

Functional prediction of the lncRNA ceRNAs based on pathway analysis of mRNAs that location together in the miRNA-lncRNA-mRNA feed-forward loop in GBM.

miRNA lncRNA mRNA Pathway
hsa-miR-15a-5p n339339 PAK7 ErbB signaling
ENST00000520186
ENST00000533229
ENST00000566630
n341995
hsa-miR-15a-5p n339339 CACNA1E Calcium, MAPK signaling
n346032
ENST00000532691
ENST00000566630
ENST00000524501
ENST00000578746
n341995
hsa-miR-15a-5p ENST00000520186 MAPK9 MAPK, ErbB, Wnt signaling, focal adhesion, pathways in cancer
hsa-miR-15a-5p ENST00000520186 AKT3 MAPK, ErbB, PI3K-Akt, VEGF, mTOR signaling, glioma, apoptosis, focal adhesion, pathways in cancer
ENST00000596580
n411142
ENST00000492667
hsa-miR-15a-5p ENST00000559981 SYNJ1 Phosphatidylinositol signaling
ENST00000596580
n410578
n411142
ENST00000492667
hsa-miR-15a-5p ENST00000566942 HTR2A Calcium signaling
hsa-miR-15a-5p n338128 PTPRR MAPK signaling
hsa-miR-15b-5p n339339 PAK7 ErbB signaling
ENST00000520186
ENST00000533229
ENST00000566630
n341995
n406352
hsa-miR-15b-5p n339339 CACNA1E Calcium, MAPK signaling
n346032
ENST00000532691
ENST00000566630
ENST00000524501
n341995
n406352
hsa-miR-15b-5p ENST00000520186 AKT3 MAPK, ErbB, PI3K-Akt, VEGF, mTOR signaling, glioma, apoptosis, focal adhesion, pathways in cancer
ENST00000596580
n411142
ENST00000492667
hsa-miR-15b-5p ENST00000559981 SYNJ1 Phosphatidylinositol signaling
ENST00000596580
n410578
n411142
ENST00000492667
hsa-miR-15b-5p ENST00000520186 MAPK9 MAPK, ErbB, Wnt signaling, focal adhesion, pathways in cancer
hsa-miR-15b-5p ENST00000566942 HTR2A Calcium signaling
hsa-miR-15b-5p n338128 PTPRR MAPK signaling
hsa-miR-23a-3p n339339 SLIT1 Phosphatidylinositol signaling
hsa-miR-23a-3p n339339 RXRG Pathways in cancer
ENST00000434383
hsa-miR-23a-3p ENST00000559981 SYNJ1 Phosphatidylinositol signaling
n411142
hsa-miR-23a-3p ENST00000562191 MEF2C MAPK signaling
hsa-miR-23a-3p n383510 CADM3 Cell adhesion molecules
hsa-miR-23a-3p ENST00000559981 TLN2 Focal adhesion
hsa-miR-23a-3p ENST00000524501 NRXN3 Cell adhesion molecules
hsa-miR-30a-5p n346032 GRM5 Calcium signaling
ENST00000532691
hsa-miR-30a-5p ENST00000569946 CACNA1C Calcium signaling, MAPK signaling
n339481
hsa-miR-30a-5p n373066 CAMK4 Calcium signaling
hsa-miR-27a-3p n339339 PDE3B Proteoglycans in cancer
hsa-miR-27a-3p ENST00000564076 CACNB2 MAPK signaling
n338494
hsa-miR-27a-3p n371475 CDS1 Phosphatidylinositol signaling
hsa-miR-27a-3p ENST00000492667 ATP2B1 Calcium signaling
hsa-miR-34a-5p n339339 CACNA1E Calcium, MAPK signaling
n346032
ENST00000555811
ENST00000566630
n406352
hsa-miR-34a-5p ENST00000596580 SYNJ1 Phosphatidylinositol signaling
n410578
ENST00000492667
hsa-miR-34a-5p ENST00000549205 PRKCE Tight junction
n406352
hsa-miR-34a-5p n384244 CNTN2 Cell adhesion molecules
hsa-miR-34a-5p n406352 WASF1 Regulation of actin cytoskeleton,
Adherens junction
hsa-miR-106b-5p ENST00000596580 PIP4K2A Phosphatidylinositol signaling, regulation of actin cytoskeleton
n337874
hsa-miR-106b-5p ENST00000596580 AKT3 MAPK, ErbB, PI3K-Akt, VEGF,
n411142 mTOR signaling, glioma, apoptosis, focal adhesion, pathways in cancer
hsa-miR-106b-5p n345100 MAPK9 MAPK, ErbB, Wnt signaling, focal adhesion, pathways in cancer
hsa-miR-25-3p ENST00000493303 PRKCE Tight junction
ENST00000549205
n406352
hsa-miR-25-3p n410578 SYNJ1 Phosphatidylinositol signaling
n411142
ENST00000492667
hsa-miR-25-3p ENST00000549205 MAP2K4 MAPK, ErbB signaling
hsa-miR-223-3p ENST00000493303 PRKCE Tight junction
n406352
hsa-miR-223-3p n371741 ATP2B1 Calcium signaling
ENST00000492667
hsa-miR-21-5p ENST00000559981 PPP3CA Calcium, MAPK, Wnt, VEGF signaling
n411142
ENST00000492667
hsa-miR-92b-3p ENST00000596580 SYNJ1 Phosphatidylinositol signaling
n410578
n411142
ENST00000492667
hsa-miR-339-5p ENST00000555811 DAAM2 Wnt signaling
ENST00000523571
hsa-miR-339-5p n383510 CADM3 Cell adhesion molecules
hsa-miR-10b-5p ENST00000221169 TIAM1 Regulation of actin cytoskeleton, proteoglycans in cancer
hsa-miR-29b-3p ENST00000481203 TNFRSF1A MAPK signaling, cytokine-cytokine receptor interaction, apoptosis
ENST00000518554
hsa-miR-29b-3p ENST00000547415 LAMC1 PI3K-Akt signaling, focal adhesion, ECM-receptor interaction, pathways in cancer
hsa-miR-377-3p n338229 LAMC1 PI3K-Akt signaling, focal adhesion, ECM-receptor interaction, pathways in cancer
hsa-miR-29c-3p ENST00000547415 LAMC1 PI3K-Akt signaling, focal adhesion, ECM-receptor interaction, pathways in cancer
hsa-miR-29c-3p ENST00000518554 TNFRSF1A MAPK signaling, cytokine-cytokine receptor interaction, apoptosis

lncRNA, long non-coding RNA; ceRNAs, competing endogenous RNAs; miRNA, microRNA; GBM, glioblastoma multiforme.