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. 2017:2017:2312318.
doi: 10.1155/2017/2312318. Epub 2017 Sep 12.

Identifying Novel Glioma-Associated Noncoding RNAs by Their Expression Profiles

Affiliations

Identifying Novel Glioma-Associated Noncoding RNAs by Their Expression Profiles

Alenka Matjašič et al. Int J Genomics. 2017.

Abstract

Long noncoding RNAs (lncRNAs) and microRNAs (miRNAs) play a significant role in cancer development as regulators of protein-coding genes. Their dysregulation was in some extent already associated with glioma, the most aggressive primary brain tumours in adults. The correct diagnosis and treatment selection due to high tumour heterogeneity might be difficult and inadequate, resulting in poor prognosis. Studies of expression patterns of noncoding RNAs (ncRNAs) could provide useful insight in glioma molecular development. We used the qPCR approach to screen and investigate the expression of lncRNAs that were previously deregulated in other cancer types. The study showed altered expression levels for numerous lncRNAs across histologically different glioma samples. Validation of few lncRNAs showed association of expression levels with histological subtype and/or malignancy grade. We also observed deregulated and subtype-distinctive expression for four lncRNA-associated miRNAs. Expression of few lncRNAs and miRNA was also associated with patients' survival, showing potential prognostic value. Several ncRNAs, some already related to glioma and some, to the best of our knowledge, investigated for the first time, might be of greater importance in glioma molecular development and progression. Finding the subtype-specific lncRNA and/or miRNA expression patterns may contribute additional information for a more objective classification.

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Figures

Figure 1
Figure 1
Heat map of lncRNA profiling analyses of glioma samples. The figure represents ∆∆CT values of differentially expressed lncRNAs in glioma samples compared to human brain reference RNA. Data are presented on a colour scale where shades of blue represent decreased expression and pink as increased expression, with ∆∆CT cut-off values set at −1 and 1. On the top of the figure is presented unsupervised Pearson's hierarchical clustering of samples. AC: astrocytoma of WHO grade II or III; OAC: oligoastrocytoma; ODG: oligodendroglioma. Genes denoted by red dot were selected for further qPCR validation and analysis.
Figure 2
Figure 2
Principal component analysis of individual samples, generated with expression of 74 differentially expressed lncRNAs. AC: astrocytoma of grade II or III; GBMs: glioblastoma; ODG: oligodendroglioma; OAC: oligoastrocytoma. Letters at the end mean a consecutive sample.
Figure 3
Figure 3
qPCR results of lncRNA gene expression regarding the WHO malignancy grade. Expression analyses of 7 lncRNAs, previously determined as differentially expressed, between low and high malignancy grade. Data are presented as ∆∆CT box plots ± standard error.
Figure 4
Figure 4
qPCR results of lncRNA gene expression in glioma subtypes. Expression analyses of glioma samples and human brain reference RNA for a subset of seven lncRNAs previously determined as differentially expressed. Data are presented as mean fold change (FC) ± standard FC error. p shows statistical significance for Kruskal-Wallis test of expression differences among all five subgroups (threshold set at p < 0.05).
Figure 5
Figure 5
miRNA expression levels regarding the WHO malignancy grade. Expression analyses of four lncRNA-associated miRNAs between low and high malignancy grade glioma. Data are presented as ∆∆CT box plots ± standard error.
Figure 6
Figure 6
Expression results of miRNAs related to differentially expressed lncRNAs in glioma subtypes. (a) Expression analyses of miRNA, found to be associated with lncRNAs analysed, on the same cohort of sample as for lncRNAs as well as on human brain reference RNA. Data are presented as mean fold change (FC) ± standard FC error. Bars with asterisks represent significance for in-between-group comparison (0.01 ≤ p < 0.05; ∗∗0.001 ≤ p < 0.01; ∗∗∗p < 0.001). (b) Correlation relationship of expression levels in individual sample for miRNA and its related lncRNA. Letter r represents the magnitude of correlation and p the significance value.
Figure 7
Figure 7
Kaplan-Meier survival curve analysis shows poor prognosis for patients older than 50 years at time of diagnosis and with diagnosed GBM.
Figure 8
Figure 8
Expression of lncRNAs and miRNAs shows prognostic significance. Expression of individual sample was classified either low or high regarding the gene's ΔΔCt mean expression value.

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