Radiol Oncol 2017; 51(3):331-341. doi:10.1515/raon-2017-0004 331 research article Expression of LOC285758, a potential long non-coding biomarker, is methylation- dependent and correlates with glioma malignancy grade Alenka Matjasic1, Mara Popovic2, Bostjan Matos3 and Damjan Glavac1 1 Department of Molecular Genetics, Institute of Pathology, Faculty of Medicine, University of Ljubljana, Slovenia 2 Institute of Pathology, Faculty of Medicine, University of Ljubljana, Slovenia 3 Department of Neurosurgery, University Medical Center, Ljubljana, Slovenia Radiol Oncol 2017; 51(3):331-341. Received 24 October 2016 Accepted 22 November 2016 Correspondence to: Prof. Dr. Damjan Glavač, Department of Molecular Genetics, Institute of Pathology, Faculty of Medicine, University of Ljubljana, Korytkova 2, SI-1000 Ljubljana, Slovenia. E-mail: damjan.glavac@mf.uni-lj.si, Tel.: +386-1-543-7180 Disclosure: No potential conflicts of interest were disclosed. Background. Identifying the early genetic drivers can help diagnose glioma tumours in their early stages, before becoming malignant. However, there is emerging evidence that disturbance of epigenetic mechanisms also con- tributes to cell’s malignant transformation and cancer progression. Long non-coding RNAs are one of key epigenetic modulators of signalling pathways, since gene expression regulation is one of their canonical mechanisms. The aim of our study was to search new gliomagenesis-specific candidate lncRNAs involved in epigenetic regulation. Patients and methods. We used a microarray approach to detect expression profiles of epigenetically involved lncRNAs on a set of 12 glioma samples, and selected LOC285758 for further qPCR expression validation on 157 glioma samples of different subtypes. To establish if change in expression is a consequence of epigenetic alterations we determined methylation status of lncRNA’s promoter using MS-HRM. Additionally, we used the MLPA analysis for de- termining the status of known glioma biomarkers and used them for association analyses. Results. In all glioma subtypes levels of LOC285758 were significantly higher in comparison to normal brain reference RNA, and expression was inversely associated with promoter methylation. Expression substantially differs between astrocytoma and oligodendroglioma, and is elevated in higher WHO grades, which also showed loss of methylation. Conclusions. Our study revealed that lncRNA LOC285758 changed expression in glioma is methylation-dependent and methylation correlates with WHO malignancy grade. Methylation is also distinctive between astrocytoma I-III and other glioma subtypes and may thus serve as an additional biomarker in glioma diagnosis. Key words: glioma; lncRNA; LOC285758; over-expression; epigenetics; DNA methylation; MS-HRM; MLPA; IDH1; 1p/19q Introduction Glioma are the commonest primary brain tumours in adults and also the most aggressive, with over- all poor survival.1,2 Clinically, they are extremely heterogeneous primary brain tumours that are pre- senting a great challenge in clinical oncology. This heterogeneity is reflected in the lack of knowledge about the exact mechanisms of tumour formation and progression, subsequently leading to less ac- curate classification and choosing the appropriate treatment. It is why numerous researchers have focused to find new genetic factors and molecu- lar mechanisms involved in gliomagenesis, which may also contribute to developing new therapeutic approaches and improving the prognosis for glio- ma patients. LncRNAs are widely expressed in mamma- lian nervous system3 and several were identified to be specifically linked with neuro-oncological Radiol Oncol 2017; 51(3):331-341. Matjasic A et al. / LOC285758 expression is epigenetically regulated and differs in glioma subtype332 disorders4,5, and as such they could help explain the mechanisms of glioma malignant transforma- tion.6,7 LncRNAs are a class of non-coding RNAs that share many features with protein-coding RNAs (mRNAs), but lack the open reading frame, have lower sequence conservation and lower level of expression.8,9 However, they are more cell- and tissue-type specific than mRNAs.10 For many of them functional analyses showed to have key roles in numerous fundamental biological processes, such as cell cycle regulation, epigenetic regulation, imprinting, cell differentiation and apoptosis, and diseases, including tumorigenesis.11-17 The involve- ment of lncRNAs in disease processes as one of the most important factors controlling gene expression creates an urgency to understand the mechanisms by which these RNAs seek their targets and impact signalling pathways16, and how much their distur- bance might contribute to disease development. Gene expression regulation by lncRNAs appears to be mediated largely through epigenetic mecha- nisms, which play a crucial role in regulating gene expression and are closely associated with disease onset. A number of studies show that as much as 20-30% of lncRNAs have been able to physically interact with specific epigenetic enzymes and driv- ing them to specific genomic loci.18 By binding to the chromatin-modifying proteins, such as PRC2, G9a, hnRNPK, and SWI/SNF, they modulate the chromatin states and thus impact gene expression of cell cycle, cell differentiation, apoptosis, DNA repair, and cell adhesion.3,17,19 Moreover, they can directly modulate the transcription of proximally- located genes by interacting with promoters and transcription factors.3 In glioma, epigenetic alterations and mecha- nisms, including methylation of gene promoters, histone modifications and chromatin modifiers are relatively unexplored, although DNA methylation of O6-methylguanin-DNA methyltransferase (MGMT) expression was associated with the prognosis of glioma patients.20,21 DNA methylation is one of the primary epigenetic mechanisms in regulating gene expression, and disturbance of this process may cause various diseases, including cancer. It is also the most common epigenetic modification found in tumour cells.22 Moreover, DNA methylation is an important regulator of expression of not only the mRNAs but also of the lncRNAs, and it seems that DNA demethylation of silent lncRNAs results in their activation.23 Methylation patterns differ among various tissue-types and cell-types24, which means the cell-/tissue-specific methylation status, similarly to expression pattern, could be a useful biomarker. In this study, we performed an expressional profiling of lncRNAs potentially involved in epige- netic levels of regulation in glioma samples of dif- ferent histological subtypes compared to normal brain reference RNA. We used the microarray ap- proach (LncPath™ Human Epigenetic Pathway) to search for novel lncRNA biomarkers potentially in- volved in glioma development. To validate micro- array profiling results we used the qPCR method on a set of 125 glioma samples of different subtype and malignancy grade. In addition, we wanted to investigate if the change in gene’s expression is due to changed methylation pattern of its promoter, and if there is any association with the hallmark markers, such as IDH1/2 and TP53 mutation, copy number variation of genes CDKN2A and CDKN2B, and 1p/19q co-deletion. Patients and methods Patients Hundred and fifty-seven tumours that were surgi- cally removed from patients between the years 2007 and 2015 were chosen for the study. Immediately after surgical biopsy tumours were stabilized in RNAlater (Applied Biosystems, USA), incubated at TABLE 1. Patients’ demographics and glioma histopathological classification Patients demographic Number of patients 157 Gender (female/male) 67/90 (1 : 1.34) Mean age at diagnosis (years) 43.8 (SD ±18,89) # < 45 years 86 # > 45 years 71 Glioma classification Glioma subtype WHO grade Astrocytoma (AC) 15 pilocytic WHO I 9 diffuse WHO II 11 diffuse with signs of anaplasia WHO II-III 9 anaplastic WHO III 23 secondary GBM WHO IV 31 primary GBM WHO IV Oligodendroglioma (ODG) 4 diffuse WHO II 5 diffuse with signs of anaplasia WHO II-III 28 anaplastic WHO III Oligoastrocytoma (OAC) 2 diffuse WHO II 3 diffuse with signs of anaplasia WHO II-III 17 anaplastic WHO III Radiol Oncol 2017; 51(3):331-341. Matjasic A et al. / LOC285758 expression is epigenetically regulated and differs in glioma subtype 333 4°C for at least 24 hours and subsequently stored at −20°C until needed. All tumours were evaluated by neuro-pathologist in order to assess glioma sub- type and tumour grade (see Table 1), according to the WHO 2007 guidelines.25 We collected patient’s demographic data and results of immunohisto- chemical analyses, if they were performed, from our institutional database. The tumour biopsies used in the study belonged to 67 female and 90 male patients (mean age at diagnosis: 43.8 years). For reference RNA we used commercially availa- ble FirstChoice Human Brain Reference Total RNA (Cat.no. 6050, Ambion; Invitrogen, USA) (further referred to as brain reference RNA) obtained from the healthy brain tissue of 23 individuals without any signs of neurodegeneration. The study was ap- proved by the National Medical Ethics Committee of the Republic of Slovenia (115/5/14). As DNA control samples we used nine samples of freshly frozen brain tissue that were collected at the au- topsy of five patients (5 cerebrum and 4 cerebel- lum tissue samples). Samples were evaluated as a normal brain tissue, without any visible signs of neurodegeneration. Nucleic acid extraction For extraction and purification of nucleic acids we used the AllPrep DNA/RNA/miRNA Universal Kit (Qiagen, Germany). Total DNA and RNA were simultaneously extracted from the same piece of tissue (up to 20 mg) that was homogenized with TissueLyser LT (Qiagen, Germany) for 5 min at 50 Hz, and further processed according to manufac- turer’s instructions. The yield of both RNA and DNA was measured spectrophotometrically using the NanoDrop ND-1000 (Thermo Scientific, USA). The quality and fragmentation of the extracted RNA (RNA integrity) was determined by agarose gel electrophoresis on Bioanalyzer 2100 (Agilent Technologies, USA), using the RNA 6000 Nano kit (Agilent Technologies, USA) according to manu- facturer’s instructions. Only the samples with ap- propriate yield and quality were considered for further analyses; thus, not all samples were used for all analyses performed. Expressional profiling of epigenetically involved lncRNA We performed expressional profiling on 12 RNA samples of different glioma subtype and a brain reference RNA. Samples were chosen from a sam- ple set of our previous glioma study (unpublished study), and selected upon histopathologically de- termined glioma subtypes so that each of the four subgroups, i.e. astrocytoma (WHO grade II or III), primary GBM, secondary GBM and oligodendro- glioma (WHO grade III), included 3 samples of sufficient RNA concentration and high quality. Samples were sent to ArrayStar Inc, USA, where sample preparation and microarray hybridiza- tion were performed, based on the manufacturer’s standard protocols (Arraystar Inc.). One µg of RNA for individual sample was hybridized to the LncPath Human Epigenetic Pathway microarray (6x7K). Scanned slide images were processed by GenePix Pro 6.0 software (Axon) for raw data ex- traction, which were further normalized and pro- cessed using the R language. After filtering, only the probes for which at least 2 out of 13 samples had raw intensity above 32 were retained for fur- ther differential analyses. LncRNAs that showed significant change in expression between tumour group and brain reference RNA were identified through volcano plot filtering. After identifying groups’ candidate genes, each group was com- pared to others. The »fold change« cut-off value for lncRNA to be considered as differentially ex- pressed was set to < - 1.5 (expression is decreased) and > 1.5 (expression is increased), and p-value cut- off was set at 0.05. Quantitative real-time PCR (qPCR) validation of LOC285758 expression LOC285758 expression levels were validated with the quantitative real-time PCR method, based on the intercalating dye (SYBR Green) technology. Only the samples with total RNA concentration higher than 50 ng/µL and RIN above 5.5 were used for qPCR analysis. The first strand cDNA was generated with One Taq RT-PCR kit accord- ing to manufacturer’s instructions (New England Biolabs, UK) and using random primer mix. The reverse transcription reaction was prepared in a 10 µL reaction mixture with 300 ng of total input RNA. cDNA was properly diluted and amplified in a 10 µL reaction volume, using the SYBR Select Master Mix (Thermo Fisher Scientific, USA). We used GAPDH and U6 as reference genes (endog- enous controls) and brain reference RNA (men- tioned in section 2.1) as the control RNA. All qPCR reactions were performed in duplicate using the Rotor Gene-Q system (Qiagen, Germany) follow- ing the primer manufacturer’s standard cycling protocol for pre-designed primers for LOC285758 (PrimeTime qPCR Assay primer, IDT – Integrated Radiol Oncol 2017; 51(3):331-341. Matjasic A et al. / LOC285758 expression is epigenetically regulated and differs in glioma subtype334 DNA Technology, USA) and GAPDH (QuantiTect qPCR Primer Assay, Qiagen, Germany). The cy- cling protocol for designed U6 primers was similar to that of Qiagen with optimized TA (see Table 2). The signal was collected on the Green channel at the end point of every cycle, and following amplifi- cation melt curve analysis was performed to verify specificity of qPCR amplicon. Relative quantification levels of the target gene were calculated following the ∆∆CT method; ∆∆CT represents the difference between the quantity of target transcript in brain reference RNA (control RNA) (∆CT control) and in tumour (∆CT sample), after each sample and control were normalized to geometric mean expression of reference genes (GAPDH and U6).26 A positive ∆∆CT value in our calculations means higher expression level in tu- mour samples. Methylation-sensitive HRM For determining lncRNA’s promoter methylation status we used the methylation sensitive high reso- lution melt (MS-HRM) analysis. Primers for ampli- fying LOC285758 promoter’s target region were de- signed with a freely available software tool Methyl Primer Express software v1.0 (Applied Biosystems, USA) in such a manner that they amplify both methylated and unmethylated DNA. Primers were designed to target CpG specific region at 5’UTR end (flanking sequence/exon1). Prior to MS-HRM analysis, 500 ng of input amount of sample DNA were bisulphite converted (bsDNA) using innu- CONVERT Bisulfite Basic Kit (Analytik Jena AG, Germany) according to manufacturer’s protocol. We created two DNA control pools by mixing 5 control samples of cerebrum and 4 control samples of cerebellum, treated them with bisulphite and used them for comparing the methylation status between normal brain tissue and tumour sam- ples. For fully methylated/unmethylated (positive/ negative) controls we used commercially avail- able EpiTect Control DNA (Qiagen, Germany). All MS-HRM reactions were prepared with EpiTect HRM PCR Kit (Qiagen, Germany) in a 10 µL reac- tion mixture by manufacturer’s recommendations and adjustments according to primer optimiza- tion analysis (1.5 µL of each primer, 1 µL bsDNA (10 ng/µL)). We included the negative and posi- tive control, both control pools and no-template control in each MS-HRM experiment, which were carried out on Rotor Gene Q (Qiagen, Germany). Amplification conditions were set based on manu- facturer’s recommendations as follows: 5 minutes of initial denaturation at 95°C, 45 cycles: denatura- tion at 95°C for 10 seconds, annealing at optimized temperature (TA in Table 2) for 30 seconds, and elongation at 72°C for 20 seconds. After amplifica- tion, the HRM analysis was conducted by increas- ing the temperature from 65°C to 95°C by 0.1°C per 2 seconds. Fluorescence signal was collected from the green channel in elongation step and from the HRM channel during HRM analysis. For analys- ing MS-HRM results, we used the Rotor-Gene Q Series Software 2.3.1 (Qiagen, Germany). For de- termining methylation status of individual sample, samples HRM melting plots were normalized and further compared to controls. TABLE 2. Primers used for validation of LOC285758 expression profiling results, reference genes and determining methylation status of lncRNA’s promoter Quantitative real-time PCR Gene Assay ID Amplicon length (bp) Annealing temperature (°C) LOC285758 Hs.PT.58.26012748 129 60 GAPDH QT00079247 95 55 Gene Primer sequence (5’ - 3’) Amplicon length (bp) Annealing temperature (°C) U6 CTCGCTTCGGCAGCACA 94 60 AACGCTTCACGAATTTGCGT Methylation sensitive HRM Gene Oligonucleotide sequence (5’ – 3’) Amplicon length (bp) Annealing temperature (°C) LOC285758 F TTGTTTTTTGAAAGTTTTTTGA 118 55 LOC285758 R AAACACAAAAAACCTAACAAAAA Radiol Oncol 2017; 51(3):331-341. Matjasic A et al. / LOC285758 expression is epigenetically regulated and differs in glioma subtype 335 Multiplex ligation-dependent probe amplification We used the P088-C1 Oligodendroglioma SALSA MLPA probe mix (MRC-Holland, the Netherlands) to detect loss of chromosome arms 1p and 19q, copy number variations in CDKN2A and CDKN2B genes, and to determine the status of the most common mutations of IDH1 (R132H and R132C) and IDH2 (R172K and R172M) genes in different glioma subtypes. The results of MLPA analysis have been further considered as the criteria for sample sub-classification for additional compari- son, and determining possible differences in gene expression and promoter methylation. The MLPA experiment was prepared according to manu- facturer’s protocol and recommendations with 100 ng of input DNA amount. Capillary gel elec- trophoresis was performed using ABI Prism 310 Genetic Analyser (Applied Biosystems, USA), and we used Coffalyser software (MRC-Holland, the Netherlands) for fragment analysis. Data analysis All statistical tests were performed using IBM SPSS Statistics 20. software (IBM Corporation, New York, USA). We used the one-way ANOVA analysis for comparing differences in expression between all glioma subtypes, and Mann-Whitney 2-independ- ent test to cross test differences between two sub- types. Pearson’s correlation coefficient was used to establish association of expression with promoter’s methylation status, status of known biomarkers, and glioma subtype. Differences were considered statistically significant when they reached or were below p ≤ 0.05. Results Expression profiling of epigenetically involved lncRNAs Expression profiling of 12 glioma tumour samples of four different subtypes was performed with an ArrayStar microarray technology. Differential analysis of tumour samples compared to brain ref- erence RNA, with absolute fold change (FC) cut-off value at 1.5, showed 351 lncRNAs with altered ex- pression levels in at least one subtype (Figure 1A,B). Among these, 60 lncRNAs were differentially ex- pressed in all four subtypes (Figure 1B). A more stringent analysis with absolute FC cut-off set at 2 showed 187 lncRNAs with altered expression in at least one subtype and only 29 lncRNAs in all four subtypes (Figure 1A,B; numbers of lncR- NAs matching this criteria are in parentheses). In Table 3 are listed top 10 over-expressed and top 10 under-expressed lncRNAs in each glioma subtype. With the purpose to identify new potential bio- marker candidates we searched through public da- tabases, such as PubMed (https://www.ncbi.nlm. nih.gov/pubmed/), Ensembl (http://www.ensembl. org/index.html), HGNC (http://www.genenames. org/), and lncRNAdb (http://lncrnadb.com/), for information about gene’s location in the genome, its known function or involvement in cellular pathways, and previous mention in the literature. Among the most differentially changed was lncR- NA LOC285758, which showed increased expres- sion in all four glioma subtypes, but lower expres- sion in GBMs in comparison to astrocytoma and oligodendroglioma (Table 3). Also, it was signifi- cantly changed between the two GBM subtypes. Validation of LOC285758 expression To validate the microarray expression results of LOC285758 we used the quantitative real-time PCR method on a subset of 125 samples that met both the concentration and quality criteria. Expression levels were significantly increased in 105/125 samples (84%) compared to brain refer- ence RNA (Figure 2A), and all glioma subtypes showed positive ΔΔCT average values (Figure 2B). Data obtained by qPCR validation analysis were in concordance with results of microarray profiling that showed increased levels in all four subtypes (Figure 2B). However, the expression in GBMs did not significantly differ, as observed on microar- FIGURE 1. Venn’s diagram of lncRNAs that were significantly differentially expressed using microarray screening of lncRNAs involved in epigenetic mechanisms and/or pathways. (A) Number of lncRNAs in regard to the number of subtypes in which they were found differentially expressed (the number of subtypes rises from the outer circle (one subtype) towards the inner one (four subtypes)). (B) The number of lncRNAs found differentially expressed in all four analysed subtypes (using two levels of stringency – absolute fold change cut-off value of 1.5 and (2)). A B Radiol Oncol 2017; 51(3):331-341. Matjasic A et al. / LOC285758 expression is epigenetically regulated and differs in glioma subtype336 ray. We observed the highest average expression in oligoastrocytoma and oligodendroglioma, and statistical analysis of ANOVA showed significant differences comparing all groups (p = 0.004). Cross comparison of two subtypes using Mann-Whitney test showed significantly increased expression be- tween oligodendroglioma and astrocytoma I-III (p = 0.007), secondary GBM (p = 0.021), and pri- mary GBM (p = 0.014), respectively. Comparing astrocytoma to oligoastrocytoma showed lower ex- pression and borderline value of significance (p = 0.051), and similar was observed in comparison of secondary GBM and oligoastrocytoma (p = 0.052) (Figure 2). Methylation status of LOC285758 promoter After we quantified and analysed the lncRNA ex- pression, we wanted to see if this change could be a consequence of changed DNA methylation pat- tern. Methylation status of LOC285758 promoter was determined for individual sample from a subset of 125 samples with sufficient DNA con- centration and quality. We compared sample’s normalized and melting curve compared to fully methylated and fully unmethylated control. Fifty- one percent (64/125) of samples were methylated and we found methylation status to be inversely associated with LOC285758 expression (Figure 3A) (rs= -0.455, p < 0.001). We also compared normal- ized curves of tumour samples and control pools. LOC285758 promoter was shown as methylated in control pools (normal brain), but hypo-methylated against positive control, and 87% (109/125) of tu- mour samples were hypo-methylated or unmeth- ylated in regard to normal brain. Further analysis, regarding the glioma subtype (Figure 3C), showed astrocytoma of WHO grades I-III are methylated in 96% of samples, whereas astrocytoma of grade TABLE 3. Top 10 lncRNAs that showed significantly increased/decreased expression in four glioma subtypes, using the LncPath Human Epigenetic Pathway microarray (ArrayStar, USA) Astrocytoma II+III* Secondary GBM Primary GBM Oligodendroglioma FC(abs) Gene Name FC(abs) Gene Name FC(abs) Gene Name FC(abs) Gene Name TOP 10 OVER-EXPRESSED 9.775 RP11-434O22.1 9.840 APOC2 11.343 AK024556 10.085 RP6-201G10.2 7.863 LOC285758 9.105 AK024556 9.761 FJ209302 7.233 LOC285758 6.203 LOC100129034 7.971 LOC100129034 9.402 AK055628 6.241 GAS5 5.247 RP11-264F23.3 7.578 AK055628 9.267 H19 5.454 RP11-264F23.3 5.211 RP6-201G10.2 4.509 RP11-145M9.3 7.012 RP11-434O22.1 5.360 LOC100216546 5.107 APOC2 4.243 RP11-73E17.2 6.720 APOC2 5.043 SNRPE 4.374 RP11-770J1.3 3.657 KB-1836B5.1 5.527 LOC285758 4.991 AK024556 4.211 HOXA11-AS 3.394 H19 4.851 LOC100216546 4.930 AC009506.1 3.861 RP3-405J24.1 2.878 BANCR 4.770 LOC100129034 4.351 RP11-73E17.2 3.795 AK055628 2.695 AB447886 4.525 HOXA11-AS 3.846 LOC286059 TOP 10 UNDER-EXPRESSED 9.638 RP11-678P16.1 24.555 MEG3 22.494 MEG3 43.328 RP11-678P16.1 7.026 XLOC_013368 11.341 AK054921 16.532 AK054921 23.879 FABP5P3 6.797 AK054921 8.050 AF520792 11.157 RP11-678P16.1 18.840 DGCR5 6.148 MEG3 6.845 DGCR5 8.208 DGCR5 8.073 MEG3 6.003 RP11-18F14.2 6.623 XLOC_013368 8.207 XLOC_013368 7.092 AK054921 5.820 HAR1A 6.470 AK054970 7.979 HAR1B 6.887 XLOC_013368 5.052 SNAR-A2 6.243 HAR1A 6.325 HAR1A 6.318 NEAT1 4.216 FABP5P3 6.114 XIST 6.218 SNAR-A2 6.205 SEPT7P6 4.082 RP11-325F22.4 5.799 MIAT 6.066 RP11-208G20.2 6.090 CASC2 3.887 SEPT7P6 5.712 SNAR-A2 5.652 XLOC_008014 5.873 TMSB10P2 * = II+III – tumours of WHO grade II and III; (abs) = absolute value; FC = fold change Radiol Oncol 2017; 51(3):331-341. Matjasic A et al. / LOC285758 expression is epigenetically regulated and differs in glioma subtype 337 IV, i.e. GBM showed high percent of unmethylated cases (57% of secondary GBM (12/21) and 77% of primary GBM (20/26)). Cases of oligodendroglio- ma were unmethylated in 75% (21/28), whereas oligoastrocytoma were unmethylated in 44% (8/18) (Figure 3C). Also, classifying samples upon WHO grade showed tumours of lower grades are largely methylated (Figure 3B). Association of LOC285758 expression and methylation with glioma hallmark markers We wanted to search for a possible association of expression with already established glioma biomarkers. For determining mutation status of IDH1 and IDH2 gene, variation in copy number of CDKN2A and CDKN2B gene, and deletion of chro- mosome arm 1p and 19q we conducted the MLPA analysis. Additionally, results of routine immu- nohistochemical analyses were collected from our database. TP53 was mutated in 38% of samples (59 mutations (MUT), 36 wild type (WT), and 62 not acquired (NA)). IDH1 mutation R132H was found in 34% (54 MUT, 64 WT, and 38 NA) of samples, and R132C in one case (< 1%). In IDH2 we did not find any mutations. CDKN2A/CDKN2B were de- leted in 23% (37/37 deletions (DEL), 44/45 WT, 2/1 duplications (DUPL), and 74 NA). Chromosome arm 1p was lost completely in 17% (27 DEL, 7 par- tial DEL, 3 DUPL, 69 WT and 51 NA) and 19q in 19% (30 DEL, 14 partial DEL, 11 DUPL, 49 WT, and 53 NA). Duplication of 19q was found mainly in GBM tumours. Co-deletion of 1p and 19q arm was detected in 15% of samples (24 cases) and majority of them were oligodendroglioma. For correlation analysis we excluded partial deletions and dupli- cations of CDKN2A/B, 1p and 19q. We compared both LOC285758 expression and promoter methylation status to above biomarkers. Pearson’s correlation coefficient test showed both expression and methylation to be significantly as- sociated with WHO malignancy grade (Figure 3B). Expression was also positively associated with the IDH1 mutation – samples with IDH1 mutation had higher expression, but independently from promoter’s methylation. A more detailed analy- sis, regarding the subtype, showed expression of LOC285758 does not differ between IDH1 mutated and wildtype astrocytoma of lower grades. But significantly does in secondary GBM, oligoastrocy- toma and oligodendroglioma. We found methyla- tion to be in weak relation to age at diagnosis and loss of CDKN2A and CDKN2B, but in an inverse FIGURE 2. (A) Differential expression of LOC285758 in individual samples (y-axis presents ΔΔCT values). (B) Comparison of average ΔΔCT values for individual glioma subtype, determined by microarray and qPCR. Oligoastrocytoma samples were not included in microarray analysis. ΔΔCT represents difference of gene’s expression in comparison to brain reference RNA, and the positive values mean that gene’s levels are increased. p-values were determined for qPCR data (ANOVA for comparing all five subtypes and Mann-Whitney U-test for comparing two subtypes). A B TABLE 4. Association of LOC285758 expression with patients demographic data and glioma hallmark biomarkers: mutations of IDH1 and TP53, copy number variations of CDKN2A and CDKN2B, and loss of chromosome arm 1p and 19q (1p/19q co-deletion) LOC285758 expression LOC285758 promoter methylation rs p-value rs p-value Gender -0.044 0.634 0.009 0.920 Age at diagnosis (< 45y >) 0.065 0.475 -0.313 < 0.001 WHO grade (low/high) 0.213 0.019 -0.433 < 0.001 IDH1 (wt/mut) 0.375 < 0.001 0.096 0.331 TP53(wt/mut) -0.083 0.483 0.153 0.178 1p loss (wt/del) 0.310 0.005 -0.396 < 0.001 19q loss (wt/del) 0.267 0.032 -0.360 0.002 1p/19q loss (wt/del) 0.262 0.014 -0.373 < 0.001 CDKN2A (wt/del) 0.085 0.477 -0.231 0.042 CDKN2B (wt/del) 0.093 0.435 -0.240 0.033 rs = Pearson’s correlation/association coefficient (0.2–0.4 – weak, 0.4–05 – moderate, > 0.6 strong correlation); p-value cut-off is set at 0.05 (95% confidence interval) Radiol Oncol 2017; 51(3):331-341. Matjasic A et al. / LOC285758 expression is epigenetically regulated and differs in glioma subtype338 manner. The loss of chromosome arm 1p, 19q and both arms concurrently was associated with both expression and methylation (Table 4); however, as mentioned above, co-deletion was found mainly in oligodendroglioma. Discussion Due to the aggressive nature of glioma, poor prog- nosis and especially the resistance of tumour cells against established and/or even modern treatments there is a need for more precise definition of glioma molecular background and finding new biomark- ers. The simplest way to screen through high num- ber of genes potentially involved in tumour devel- opment is expression profiling using microarray technology. We analysed the differences in expres- sion of lncRNAs, potentially involved in epigenetic regulatory mechanisms. Among 879 lncRNA mi- croarray probes we identified 351 lncRNAs with significantly changed expression (with absolute FIGURE 3. Scatter plots showing (A) LOC285758 expression (qPCR) in association to methylation status. Unmethylated samples showed higher expression levels compared to methylated ones. (B) LOC285758 expression and promoter methylation status significantly differ regarding the WHO malignancy grade and (C) glioma subtype, especially comparing astrocytoma grade I-III (all samples were methylated) to grade IV (GBMs were largely unmethylated). Promoter methylation: 0 = unmethylated, 1 = methylated A B C Radiol Oncol 2017; 51(3):331-341. Matjasic A et al. / LOC285758 expression is epigenetically regulated and differs in glioma subtype 339 fold change cut-off of 1.5) in at least one glioma sub- type, which once again confirms molecularly het- erogeneous nature of glioma tumours.1 We deter- mined 60 lncRNAs with changed expression in all four analyzed subtypes and selected few lncRNAs due to their significantly changed expression either in or between all four subtypes either regarding a specific subtype. For many lncRNAs we did not find any previous reports; however, expression of few lncRNAs, such as MEG327,28, H1929, Xist30, and just recently NEAT131 and HOXA11-AS32, was al- ready shown to be significantly changed in glioma. Moreover, they were associated with disturbance of key cellular pathways and patient’s prognosis. To the best of our knowledge, one of the un- known cancer-related lncRNAs is LOC285758, or long intergenic non-protein coding RNA 1268 (LINC01268), that lies in close proximity of the MARCKS (myristoylated alanine-rich C-kinase substrate) gene, which encodes a cell cycle and mo- tility promoting protein. As LOC285758 expression on microarray appeared to be significantly lower in secondary GBM in comparison to primary GBM it represented a candidate biomarker for potential- ly distinguish these two entities, especially since many cases are morphologically alike and thus misclassified.6 However, validation results showed expression does not significantly differ between as- trocytic tumours, but methylation status does as al- most all primary GBM were un-methylated versus variable status in secondary GBM. This variation in DNA methylation might be associated with sec- ondary GBM developing through low-grade astro- cytic precursors33, since we found almost all astro- cytic tumours of lower grades methylated. It could also indicate that methylation pattern of lncRNA’s promoter changes as the tumour progresses. Nevertheless, LOC285758 expression levels do significantly differ between astrocytoma, oligoas- trocytoma and oligodendroglioma, respectively, which could also be a helpful discriminating fea- ture of oligoastrocytoma from astrocytic tumours of grade I-III, since these neoplasms are some- what a mix of genetic changes characteristic for astrocytic (IDH1 mutations) and oligodendroglial tumours (1p/19q co-deletion).1 Expression levels and methylation status of LOC285758 found in oli- goastrocytoma, compared to both subtypes, even more corroborate their mixed genetic background. Additionally, LOC285758 could be an additional feature to distinguish oligodendroglioma and as- trocytoma, since these entities might arise from the same cells of origin, but develop through different molecular pathways.1 Results of different methylation further high- light epigenetic alterations of lncRNAs. We chose the MS-HRM method for determining methylation status of gene’s promoter as it is simple, fast and highly sensitive; even one single base substitution can be observed as a significant fluorescence drop and melting peak shift.34,35 As lncRNAs principal mechanism is regulation of coding genes and many bind to chromatin-mod- ifying genes17, the potential targets of LOC285758 could be addressed by its genome location, with MARCKS and HDAC2 as neighbouring genes. In contrast to the anonymity of LOC585758, there are numerous reports of MARCKS being involved in various cancers, including glioma.36-39 It has the ability to regulate various signalling pathways; by sequestering the phosphatidylinositol 4,5-biphos- phate (PIP2) molecules, a PI3K target, MARCKS functions as a tumour suppressor of PI3K/Akt sig- nalling pathway.40,41 On contrary, it can also func- tion as tumour enhancer as its overexpression was associated with metastasis and poorer prognosis in patients with lung squamous cell carcinoma42, and promoting EGFRvIII-mediated GBM tumori- genesis.39 There is only one report showing associa- tion of LOC285758 expression with expression of its antisense mRNA, and changed methylation of intragenic CpG island; however, it was not cancer related.43 HDAC2 is an enzyme of histone deacety- lase family, the key players in epigenetic silencing of gene expression and one of the regulators of major cellular functions, such as cell cycle, apopto- sis, DNA damage repair, and senescence.44,45 Like MARCKS, HDAC2 is already extensively studied, largely due to its crucial biological function, and was found significantly deregulated in broad spec- trum of diseases.46-50 HDAC2 was overexpressed in astrocytoma, like HDAC1, and expression increas- es during tumour recurrence and progression, but it is not WHO-grade-related.50 Whether the func- tional association of LOC285758 and its neighbour- ing genes exist is yet to be investigated. Some limitations of our study are related to col- lecting patient’s data as no complete clinical data were available at the time of the study. Another limitation is the lack of knowledge about exact functions and roles of lncRNA LOC285758 in nor- mal brain and cancer tissue, but such studies are beyond our research timeframe. We can conclude the microarray expression profiling of glioma tumours proved useful for identification of novel lncRNAs involved in epi- genetic pathways of glioma development as we determined several potential lncRNAs with sig- Radiol Oncol 2017; 51(3):331-341. Matjasic A et al. / LOC285758 expression is epigenetically regulated and differs in glioma subtype340 nificantly changed expression, including lncRNA LOC285758. Our study is, to the best of our knowl- edge, the first to report disturbed expression of LOC285758 in glioma tumours. Elevated expres- sion of LOC285758 and its association to loss of cytosine methylation and higher malignancy grade suggest to an oncogenic function of this lncRNA in glioma biogenesis. Furthermore, significantly dif- ferent expression between astrocytoma and oligo- dendroglioma, and oligoastrocytoma, respectively, might suggests LOC285758 as a new biomarker candidate of glioma development with added di- agnostic value, but its exact function is yet to be revealed. Acknowledgment This research is a part of Alenka Matjašič doctoral thesis. This study was supported by the Slovenian Research Agency (P3-054). References 1. Louis DN, Molecular pathology of malignant gliomas. Annu Rev Pathol 2006; 1: 97-117. doi:10.1146/annurev.pathol.1.110304.100043 2. Mesti T, Moltara ME, Boc M, Rebersek M,Ocvirk J, Bevacizumab and irinote- can in recurrent malignant glioma, a single institution experience. Radiol Oncol 2015; 49: 80-5. doi:10.2478/raon-2014-0021 3. 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