Expression of lncRNAs in Low-Grade Gliomas and Glioblastoma Multiforme: An In Silico Analysis

Identification of glioblastoma stem cell-associated lncRNAs using single-cell RNA sequencing datasets

Glioblastoma multiforme (GBM) is an aggressive, heterogeneous brain tumor in which glioblastoma stem cells (GSCs) are known culprits of therapy resistance. Long non-coding RNAs (lncRNAs) have been shown to play a critical role in both cancer and normal biology. A few studies have suggested that aberrant expression of lncRNAs is associated with GSCs. However, a comprehensive single-cell analysis of the GSC-associated lncRNA transcriptome has not been carried out. Here, we analyzed recently published single-cell RNA sequencing datasets of adult GBM tumors, GBM organoids, GSC-enriched GBM tumors, and developing human brain samples to identify lncRNAs highly expressed in GSCs. We further revealed that the GSC-specific lncRNAs GIHCG and LINC01563 promote proliferation, migration, and stemness in the GSC population. Together, this study identified a panel of uncharacterized GSC-enriched lncRNAs and set the stage for future in-depth studies to examine their role in GBM pathology and their potential as biomarkers and/or therapeutic targets in GBM.

Deciphering glioma epitranscriptome: focus on RNA modifications

Gliomas are highly malignant tumors accounting for the majority of brain neoplasms. They are characterized by nuclear atypia, high mitotic rate and cellular polymorphism that often contributes to aggressiveness and resistance to standard therapy. They often associate with challenging treatment approaches and poor outcomes. New treatment strategies or regimens to improve the efficacy of glioma treatment require a deeper understanding of glioma occurrence and development as well as elucidation of their molecular biological characteristics. Recent studies have revealed RNA modifications as a key regulatory mechanism involved in tumorigenesis, tumor progression, immune regulation, and response to therapy. The present review discusses research advances on several RNA modifications involved in glioma progression and tumor microenvironment (TME) immunoregulation as well as in the development of adaptive drug resistance, summarizing current progress on major RNA modification targeting strategies.

Identification of glioblastoma stem cell-associated lncRNAs using single-cell RNA-sequencing datasets

Glioblastoma multiforme (GBM) is an aggressive, heterogeneous grade IV brain tumor. Glioblastoma stem cells (GSCs) initiate the tumor and are known culprits of therapy resistance. Mounting evidence has demonstrated a regulatory role of long non-coding RNAs (lncRNAs) in various biological processes, including pluripotency, differentiation, and tumorigenesis. A few studies have suggested that aberrant expression of lncRNAs is associated with GSCs. However, a comprehensive single-cell analysis of the GSC-associated lncRNA transcriptome has not been carried out. Here, we analyzed recently published single-cell RNA-sequencing datasets of adult human GBM tumors, GBM organoids, GSC-enriched GBM tumors, and developing human brains to identify lncRNAs highly expressed in GBM. To categorize GSC populations in the GBM tumors, we used the GSC marker genes SOX2, PROM1, FUT4, and L1CAM. We found three major GSC population clusters: radial glia, oligodendrocyte progenitor cells, and neurons. We found 10â€"100 lncRNAs significantly enriched in different GSC populations. We also validated the level of expression and localization of several GSC-enriched lncRNAs using qRT-PCR, single-molecule RNA FISH, and sub-cellular fractionation. We found that the radial glia GSC-enriched lncRNA PANTR1 is highly expressed in GSC lines and is localized to both the cytoplasmic and nuclear fractions. In contrast, the neuronal GSC-enriched lncRNAs LINC01563 and MALAT1 are highly enriched in the nuclear fraction of GSCs. Together, this study identified a panel of uncharacterized GSC-specific lncRNAs. These findings set the stage for future in-depth studies to examine their role in GBM pathology and their potential as biomarkers and/or therapeutic targets in GBM.

An in silico approach to the identification of diagnostic and prognostic markers in low-grade gliomas

Low-grade gliomas (LGG) are central nervous system Grade I tumors, and as they progress they are becoming one of the deadliest brain tumors. There is still great need for timely and accurate diagnosis and prognosis of LGG. Herein, we aimed to identify diagnostic and prognostic biomarkers associated with LGG, by employing diverse computational approaches. For this purpose, differential gene expression analysis on high-throughput transcriptomics data of LGG versus corresponding healthy brain tissue, derived from TCGA and GTEx, respectively, was performed. Weighted gene co-expression network analysis of the detected differentially expressed genes was carried out in order to identify modules of co-expressed genes significantly correlated with LGG clinical traits. The genes comprising these modules were further used to construct gene co-expression and protein-protein interaction networks. Based on the network analyses, we derived a consensus of eighteen hub genes, namely, CD74, CD86, CDC25A, CYBB, HLA-DMA, ITGB2, KIF11, KIFC1, LAPTM5, LMNB1, MKI67, NCKAP1L, NUSAP1, SLC7A7, TBXAS1, TOP2A, TYROBP, and WDFY4. All detected hub genes were up-regulated in LGG, and were also associated with unfavorable prognosis in LGG patients. The findings of this study could be applicable in the clinical setting for diagnosing and monitoring LGG.

LncRNA as potential biomarker and therapeutic target in glioma

Glioma is the most frequent type of malignant tumor in the central nervous system, accounting for about 80% of primary malignant brain tumors, usually with a poor prognosis. A number of studies have been conducted on the molecular abnormalities in glioma to further understand its pathogenesis, and it has been found that lncRNAs (long non-coding RNA) play a key role in angiogenesis, tumor growth, infiltration and metastasis of glioma. Since specific lncRNAs have an aberrant expression in brain tissue, cerebrospinal fluid as well as peripheral circulation of glioma patients, they are considered to be potential biomarkers. This review focuses on the biological characteristics of lncRNA and its value as a biomarker for glioma diagnosis and prognosis. Moreover, in view of the role of lncRNAs in glioma proliferation and chemoradiotherapy resistance, we discussed the feasibility for lncRNAs as therapeutic targets. Finally, the persisting deficiencies and future prospects of using lncRNAs as clinical biomarkers and therapeutic targets were concluded.

Serine hydroxymethyltransferase 1 promotes low-grade glioma progression by activating mTORC1 signaling

OBJECTIVES

This research aimed to explore the role and potential mechanism of serine hydroxymethyltransferase 1 (SHMT1) involvement in low-grade glioma (LGG).

METHODS

GEPIA were employed to analyze the expression and the correlation of LGG patient survival with the levels of SHMT1 in LGG based on the The Cancer Genome Atlas (TCGA) database. qRT-PCR and western blot were used to detect the expression of SHMT1 in LGG cells. Clone formation, EdU staining, MTT, Transwell and wound healing assays were conducted to analyze the proliferation, cell activity, migration and invasion of LGG cells. KEEG analysis was performed for enrichment pathways of SHMT1 in LGG.

RESULTS

SHMT1 was up-regulated in LGG tissues and cells, and SHMT1 level was negatively correlated with survival of patients with LGG. SHMT1 overexpression evidently promoted cell proliferation, migration and invasion, whereas SHMT1 silence obtained the opposite results. Next, KEEG analysis revealed that SHMT1 activated the mTORC1 pathway in LGG. SHMT1 overexpression significantly promoted the phosphorylation of downstream proteins (P70SK6 and S6) in LGG cells. Further, inhibition of the mTORC1 signaling pathway partially abolished the promotion of LGG progression by SHMT1 overexpression.

CONCLUSION

SHMT1 promoted proliferation, invasion and migration of LGG cells via activating mTORC1 signaling pathway. This provided a novel perspective for the treatment of LGG.

Comprehensive Analysis of the Prognostic Value and Molecular Function of CRNDE in Glioma at Bulk and Single-Cell Levels

Colorectal neoplasia differentially expressed (CRNDE) is an oncogenic long noncoding RNA (lncRNA) overexpressed in diverse malignancies. Here, we comprehensively analyze the prognostic value and molecular function of CRNDE in glioma. Bulk RNA-sequencing data from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA), and single-cell RNA-sequencing data from the Tumor Immune Single-Cell Hub (TISCH) were analyzed. Kaplan-Meier survival analysis was applied to verify the prognostic value of CRNDE. Then, a nomogram based on multivariate Cox regression was established for individualized survival prediction. Subsequently, the expression characteristic and biological function of CRNDE were analyzed at the single-cell level. Lastly, the effects of CRNDE on the proliferation and invasion of glioma cell were explored in vitro. We discovered that CRNDE was a powerful marker for risk stratification of glioma patients. Regardless of the status of IDH and 1p/19q, CRNDE could effectively stratify patients' prognosis. The nomogram that incorporated the CRNDE expression was proved to be a reliable tool for survival prediction. In addition, epithelial-mesenchymal transition may be the most important biological process regulated by CRNDE, which was identified at both the bulk and single-cell levels. Moreover, CRNDE knockdown significantly inhibited the proliferation and invasion of glioma cell. Overall, CRNDE is a vital oncogene and may be a valuable supplement to improve the clinical stratification of glioma.

Foreboding lncRNA markers of low-grade gliomas dependent on metabolism

At present, there is no systematic study on the signature of long-chain noncoding RNAs (lncRNAs) involved in metabolism that can fully predict the prognosis in patients with low-grade gliomas (LGGs). Therefore, consistent metabolic-related lncRNA signatures need to be established. The Cancer Genome Atlas (TCGA) was used to identify the expression profile of lncRNAs containing 529 LGGs samples. LncRNAs and genes related to metabolism are used to establish a network in the form of coexpression to screen lncRNAs related to metabolism. LncRNA was more clearly described by univariate Cox regression. Moreover, lncRNA signatures were explored by multivariate Cox regression and lasso regression. The risk score was established according to the signature and it was an unattached prognostic marker according to Cox regression analysis. Functional enrichment of lncRNAs was shown by employing Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Univariate Cox retrospective analysis showed that 543 metabolism-related lncRNAs were independent prognostic factors of LGG, and multivariate Cox regression analysis confirmed that 19 metabolism-related lncRNAs were prognostic genes of LGG. In the risk model, the low-risk group had a higher Overall survival (OS) than the high-risk group (P < .001). Univariate Cox regression analysis of risk score and clinical factors showed that risk score was an independent prognostic factor (P < .001, HR = 1.047, 95% CI: 1.038-1.056). Multivariate Cox results showed that risk score could predict the prognosis of LGG (P < .001, HR = 1.036, 95% CI: 1.026-1.045). ROC curve analysis showed that risk score could predict the prognosis of LGG. The areas of 1-year, 3-years, and 5 years are 0.891, 0.904 and 0.832. GO and KEGG analysis showed that metabolism-related lncRNAs was mainly concentrated in the pathways related to tumor metabolism. In order to find a more stable and reliable target for the treatment of LGG, we established 19 metabolic-related lncRNAs prognostic model, and determined that it can predict the prognosis of LGG patients. This provides a new solution approach to the poor prognosis of patients with LGG and may reverse the trend of LGG's transformation to high-grade gliomas.

Next-Generation Grade and Survival Expression Biomarkers of Human Gliomas Based on Algorithmically Reconstructed Molecular Pathways

In gliomas, expression of certain marker genes is strongly associated with survival and tumor type and often exceeds histological assessments. Using a human interactome model, we algorithmically reconstructed 7494 new-type molecular pathways that are centered each on an individual protein. Each single-gene expression and gene-centric pathway activation was tested as a survival and tumor grade biomarker in gliomas and their diagnostic subgroups (IDH mutant or wild type, IDH mutant with 1p/19q co-deletion, MGMT promoter methylated or unmethylated), including the three major molecular subtypes of glioblastoma (proneural, mesenchymal, classical). We used three datasets from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas, which in total include 527 glioblastoma and 1097 low grade glioma profiles. We identified 2724 such gene and 2418 pathway survival biomarkers out of total 17,717 genes and 7494 pathways analyzed. We then assessed tumor grade and molecular subtype biomarkers and with the threshold of AUC > 0.7 identified 1322/982 gene biomarkers and 472/537 pathway biomarkers. This suggests roughly two times greater efficacy of the reconstructed pathway approach compared to gene biomarkers. Thus, we conclude that activation levels of algorithmically reconstructed gene-centric pathways are a potent class of new-generation diagnostic and prognostic biomarkers for gliomas.

LINC01088 promotes the growth and invasion of glioma cells through regulating small nuclear ribonucleoprotein polypeptide A transcription

Altered long non-coding RNAs (LncRNAs) exert pivotal parts in pathogenic processes in glioma. Here, we uncovered a differentially expressed long intergenic non-coding RNA 1088 (LINC01088) in glioma and elucidated the molecular mechanism by which LINC01088 affected the malignant phenotypes of glioma cells. Functionally, LINC01088 silencing degraded cell proliferation, invasion in glioma, while LINC01088 overexpression elicited opposite results. Mechanistically, we verified LINC01088 physically interacted with small nuclear ribonucleoprotein polypeptide A (SNRPA) and regulated the expression of SNRPA at the transcription level. Phenotypic analysis ascertained that LINC01088 substantively aggravated glioma cell progression in an SNRPA-dependent manner, and SNRPA played a pivotal part in the tumor-promoting properties of LINC01088. Our findings revealed a novel mechanism by which LINC01088 exerted pro-oncogenic functions through binding with SNRPA and transcriptionally regulating SNRPA mRNA in glioma.

5-Methylcytosine Related LncRNAs Reveal Immune Characteristics, Predict Prognosis and Oncology Treatment Outcome in Lower-Grade Gliomas

5-Methylcytosine (m5C) methylation is an important RNA modification pattern that can participate in oncogenesis and progression of cancers by affecting RNA stability, expression of oncogenes, and the activity of cancer signaling pathways. Alterations in the expression pattern of long non-coding RNAs (lncRNAs) are potentially correlated with abnormalities in the m5C regulation features of cancers. Our aim was to reveal the mechanisms by which lncRNAs regulated the m5C process, to explore the impact of aberrant regulation of m5C on the biological properties of lower-grade gliomas (LGG), and to optimize current therapeutic. By searching 1017 LGG samples from the Cancer Genome Atlas and Chinese Glioma Genome Atlas, we first clarified the potential impact of m5C regulators on LGG prognosis in this study and used univariate Cox analysis and least absolute shrinkage and selection operator regression to explore clinically meaningful lncRNAs. Consequently, we identified four lncRNAs, including LINC00265, CIRBP-AS1, GDNF-AS1, and ZBTB20-AS4, and established a novel m5C-related lncRNAs signature (m5CrLS) that was effective in predicting prognosis. Notably, mutation rate, WHO class II, IDH mutation, 1p/19q co-deletion and MGMT promoter methylation were increased in the low m5CrLS score group. Patients with increased m5CrLS scores mostly showed activation of tumor malignancy-related pathways, increased immune infiltrating cells, and decreased anti-tumor immune function. Besides, the relatively high expression of immune checkpoints also revealed the immunosuppressed state of patients with high m5CrLS scores. In particular, m5CrLS stratification was sensitive to assess the efficacy of LGG to temozolomide and the responsiveness of immune checkpoint blockade. In conclusion, our results revealed the molecular basis of LGG, provided valuable clues for our understanding of m5C-related lncRNAs, and filled a gap between epigenetics and tumor microenvironment.

TUNAR lncRNA Encodes a Microprotein that Regulates Neural Differentiation and Neurite Formation by Modulating Calcium Dynamics

Long noncoding RNAs (lncRNAs) are regulatory molecules which have been traditionally considered as “non-coding”. Strikingly, recent evidence has demonstrated that many non-coding regions, including lncRNAs, do in fact contain small-open reading frames that code for small proteins that have been called microproteins. Only a few of them have been characterized so far, but they display key functions in a wide variety of cellular processes. Here, we show that TUNAR lncRNA encodes an evolutionarily conserved microprotein expressed in the nervous system that we have named pTUNAR. pTUNAR deficiency in mouse embryonic stem cells improves their differentiation potential towards neural lineage both in vitro and in vivo. Conversely, pTUNAR overexpression impairs neuronal differentiation by reduced neurite formation in different model systems. At the subcellular level, pTUNAR is a transmembrane protein that localizes in the endoplasmic reticulum and interacts with the calcium transporter SERCA2. pTUNAR overexpression reduces cytoplasmatic calcium, consistent with a possible role of pTUNAR as an activator of SERCA2. Altogether, our results suggest that our newly discovered microprotein has an important role in neural differentiation and neurite formation through the regulation of intracellular calcium. From a more general point of view, our results provide a proof of concept of the role of lncRNAs-encoded microproteins in neural differentiation.

Expression and regulatory roles of lncRNAs in G-CIMP-low vs G-CIMP-high Glioma: an in-silico analysis

BACKGROUND

Clinically relevant glioma subtypes, such as the glioma-CpG island methylator phenotype (G-CIMP), have been defined by epigenetics. In this study, the role of long non-coding RNAs in association with the poor-prognosis G-CMIP-low phenotype and the good-prognosis G-CMIP-high phenotype was investigated. Functional associations of lncRNAs with mRNAs and miRNAs were examined to hypothesize influencing factors of the aggressive phenotype.

METHODS

RNA-seq data on 250 samples from TCGA's Pan-Glioma study, quantified for lncRNA and mRNAs (GENCODE v28), were analyzed for differential expression between G-CIMP-low and G-CIMP-high phenotypes. Functional interpretation of the differential lncRNAs was performed by Ingenuity Pathway Analysis. Spearman rank order correlation estimates between lncRNA, miRNA, and mRNA nominated differential lncRNA with a likely miRNA sponge function.

RESULTS

We identified 4371 differentially expressed features (mRNA = 3705; lncRNA = 666; FDR ≤ 5%). From these, the protein-coding gene TP53 was identified as an upstream regulator of differential lncRNAs PANDAR and PVT1 (p = 0.0237) and enrichment was detected in the "development of carcinoma" (p = 0.0176). Two lncRNAs (HCG11, PART1) were positively correlated with 342 mRNAs, and their correlation estimates diminish after adjusting for either of the target miRNAs: hsa-miR-490-3p, hsa-miR-129-5p. This suggests a likely sponge function for HCG11 and PART1.

CONCLUSIONS

These findings identify differential lncRNAs with oncogenic features that are associated with G-CIMP phenotypes. Further investigation with controlled experiments is needed to confirm the molecular relationships.

The Effect and Mechanism of LINC00663 on the Biological Behavior of Glioma

Glioma is the most frequent primary malignant brain tumor, which is characterized by high incidence and mortality, with a poor prognosis. Numerous studies have revealed the abnormal expression of long non-coding RNAs in gliomas. This study explored the effects and potential mechanism of LINC00663 in glioma. The LINC00663 levels and their prognostic values were analyzed from the GEO databases using bioinformatics. Also, LINC00663 expression in tissue samples and cell lines was measured using qRT-PCR. The roles of LINC00663 in glioma were confirmed using CCK8, EdU assay as well as Transwell tests. Moreover, the influences of LINC00663 on the AKT/mTOR signal cascades were detected using western blotting assay. LINC00663 expression was higher in both glioma tissues and cell lines than that in the normal brain tissues and human astrocytes. High expression of LINC00663 led to the low overall survival rate of patients with glioma. LINC00663 knockdown notably restrained cell proliferation, migration, and invasion abilities by decreasing the activation of AKT and mTOR. This study indicated that LINC00663 might have a cancer-promoting role in accelerating glioma development and progression through regulating AKT/mTOR pathway.

LncRNAs associated with glioblastoma: From transcriptional noise to novel regulators with a promising role in therapeutics

Glioblastoma multiforme (GBM) is the most widespread and aggressive subtype of glioma in adult patients. Numerous long non-coding RNAs (lncRNAs) are deregulated or differentially expressed in GBM. These lncRNAs possess unique regulatory functions in GBM cells, ranging from high invasion/migration to recurrence. This review outlines the present status of specific involvement of lncRNAs in GBM pathogenesis, with a focus on their association with key molecular and cellular regulatory mechanisms. Also, we highlighted the potential of different novel RNA-based strategies that may be beneficial for therapeutic purposes.

Noncoding RNAs in Glioblastoma: Emerging Biological Concepts and Potential Therapeutic Implications

Simple Summary

Since the completion of the Human Genome Project, noncoding RNAs (ncRNAs) have emerged as an important class of genetic regulators. Several classes of ncRNAs, which include microRNAs (miRNAs), long noncoding RNAs (lncRNAs), circular RNAs (circRNAs), and piwi-interacting RNAs (piRNAs), have been shown to play important roles in controlling developmental and disease processes. In this article, we discuss the potential roles of ncRNAs in regulating glioblastoma (GBM) formation and progression as well as potential strategies to exploit the diagnostic and therapeutic potential of ncRNAs in GBM.

Abstract

Noncoding RNAs (ncRNAs) have emerged as a novel class of genomic regulators, ushering in a new era in molecular biology. With the advent of advanced genetic sequencing technology, several different classes of ncRNAs have been uncovered, including microRNAs (miRNAs), long noncoding RNAs (lncRNAs), circular RNAs (circRNAs), and piwi-interacting RNAs (piRNAs), which have been linked to many important developmental and disease processes and are being pursued as clinical and therapeutic targets. Molecular phenotyping studies of glioblastoma (GBM), the most common and lethal cancer of the adult brain, revealed that several ncRNAs are frequently dysregulated in its pathogenesis. Additionally, ncRNAs regulate many important aspects of glioma biology including tumour cell proliferation, migration, invasion, apoptosis, angiogenesis, and self-renewal. Here, we present an overview of the biogenesis of the different classes of ncRNAs, discuss their biological roles, as well as their relevance to gliomagenesis. We conclude by discussing potential approaches to therapeutically target the ncRNAs in clinic.

Prediction and analysis of hub genes between glioblastoma and low-grade glioma using bioinformatics analysis

ABSTRACT

Gliomas are an intractable tumor in the central nervous system. The present study aimed to identify the differentially expressed genes (DEGs) between glioblastoma multiforme (GBM) and low-grade gliomas (LGG) in order to investigate the mechanisms of different grades of gliomas. The Cancer Genome Atlas (TCGA) database was used to identify DEGs between GBM and LGG, and 2641 genes have been found differentially expressed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to determine the related functions and pathways of DEGs. Protein-protein interaction (PPI) network extracted a total of 444 nodes and 1953 interactions, and identified the top 6 hub genes in gliomas. The microarray data of the datasets GSE52009 and GSE4412, which were obtained from Gene Expression Omnibus (GEO) database, were used to externally validate DEGs expression levels. Gene Expression Profiling Interactive Analysis (GEPIA) database which was based on TCGA was used to explore the survival of hub genes in LGG and GBM. Additionally, the Oncomine database and Chinese Glioma Genome Atlas (CGGA) database were used to validate the mRNA expression level and prognostic value of hub genes. Gene Set Enrichment Analysis (GSEA) identified further hub genes-related pathways. In summary, through biological information and survival analysis, 6 hub genes may be new biomarkers for diagnosis and for guiding the choice of treatment strategies for different grades of gliomas.

Oncogenic ZEB2/miR-637/HMGA1 signaling axis targeting vimentin promotes the malignant phenotype of glioma

Glioma is the most common primary tumor of the central nervous system. We previously confirmed that zinc finger E-box binding homeobox (ZEB) 2 promotes the malignant progression of glioma, while microRNA-637 (miR-637) is associated with favorable prognosis in glioma. This study aimed to investigate the potential interaction between ZEB2 and miR-637 and its downstream signaling pathway in glioma. The results revealed that ZEB2 could directly bind to the E-box elements in the miR-637 promoter and promote cell proliferation, migration, and invasion via miR-637 downregulation. Subsequent screening confirmed that HMGA1 was a direct target of miR-637, while miR-637 could drive the malignant phenotype of glioma by suppressing HMGA1 both in vitro and in vivo. Furthermore, interaction between cytoplasmic HMGA1 and vimentin was observed, and vimentin inhibition could abolish increased migration and invasion induced by HMGA1 overexpression. Both HMGA1 and vimentin were associated with an unfavorable prognosis in glioma. Additionally, upregulated HMGA1 and vimentin were found in isocitrate dehydrogenase (IDH) wild-type and 1p/19q non-codeletion diffusely infiltrating glioma. In conclusion, we identified an oncogenic ZEB2/miR-637/HMGA1 signaling axis targeting vimentin that promotes both migration and invasion in glioma.

Identification of Glioma Specific Genes as Diagnostic and Prognostic Markers for Glioma

Background:

Malignant gliomas are the most prevalent malignancy of the brain. However, there was still lack of sensitive and accurate biomarkers for gliomas.

Objective:

To explore the mechanisms underlying glioma progression and identify novel diagnostic and prognostic markers for glioma.

Methods:

By analyzing TCGA dataset, whole-genome genes expression levels were evaluated in 19 different types of human cancers. A protein-protein interacting network was constructed to reveal the potential roles of these glioma special genes. KEGG and GO analysis revealed the potential effect of these genes.

Results:

We identified 698 gliomas specially expressed genes by analyzing TCGA dataset. A protein-protein interacting network was constructed to reveal the potential roles of these glioma special genes. KEGG and GO analysis showed gliomas specially expressed genes were involved in regulating neuroactive ligand-receptor interaction, retrograde endocannabinoid signaling, Glutamatergic synapse, chemical synaptic transmission, nervous system development, central nervous system development, and learning. Of note, GRIA1, GNAO1, GRIN1, CACNA1A, CAMK2A, and SYP were identified to be down-regulated and associated with poor prognosis in gliomas.

Conclusion:

GRIA1, GNAO1, GRIN1, CACNA1A, CAMK2A, and SYP were identified to be down-regulated and associated with poor prognosis in gliomas. We thought this study will provide novel biomarkers for gliomas.

Development of a prognostic model of glioma based on immune-related genes

Glioma is the most common type of primary brain cancer, and the prognosis of most patients with glioma, and particularly that of patients with glioblastoma, is poor. Tumor immunity serves an important role in the development of glioma. However, immunotherapy for glioma has not been completely successful, and thus, comprehensive examination of the immune-related genes (IRGs) of glioma is required. In the present study, differentially expressed genes (DEGs) and differentially expressed IRGs (DEIRGs) were identified using the edgeR package. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was used for functional enrichment analysis of DEIRGs. Survival-associated IRGs were selected via univariate Cox regression analysis. A The Cancer Genome Atlas prognostic model and GSE43378 validation model were established using lasso-penalized Cox regression analysis. Based on the median risk score value, patients were divided into high-risk and low-risk groups for clinical analysis. Receiver operating characteristic curve and nomogram analyses were used to assess the accuracy of the models. Reverse transcription-quantitative PCR was performed to measure the expression levels of relevant genes, such as cyclin-dependent kinase 4 (CDK4), interleukin 24 (IL24), NADPH oxidase 4 (NOX4), bone morphogenetic protein 2 (BMP2) and baculoviral IAP repeat containing 5 (BIRC5). A total of 3,238 DEGs, including 1,950 upregulated and 1,288 downregulated DEGs, and 97 DEIRGs, including 60 upregulated and 37 downregulated DEIRGs, were identified. ‘Neuroactive ligand-receptor interaction’ and ‘Cytokine-cytokine receptor interaction’ were the most significantly enriched pathways according to KEGG pathway analysis. A prognostic model and a validation prognostic model were created for glioma, including 15 survival-associated IRGs (FCER1G, NOX4, TRIM5, SOCS1, APOBEC3C, BIRC5, VIM, TNC, BMP2, CMTM3, IL24, JAG1, CALCRL, HNF4G and CDK4). Furthermore, multivariate Cox regression analysis results suggested that age, high WHO Grade by histopathology, wild type isocitrate dehydrogenase 1 and high risk score were independently associated with poor overall survival. The infiltration of B cells, CD8⁺ T cells, dendritic cells, macrophages and neutrophils was positively associated with the prognostic risk score. In the present study, several clinically significant survival-associated IRGs were identified, and a prognosis evaluation model of glioma was established.

SNHG1 Promotes Malignant Progression of Glioma by Targeting miR-140-5p and Regulating PI3K/AKT Pathway

PURPOSE

To explore the regulatory mechanism of long non-coding RNA small nucleolar RNA host gene 1 (SNHG1) in glioma.

MATERIALS AND METHODS

The expression of SNHG1 and miR-140-5p in glioma tissues and glioma cell lines (LN-18, KNS-81, and KALS-1) was determined, and the effect of the two on cell proliferation, invasion, and PI3K/AKT pathway was analyzed.

RESULTS

SNHG1 was overexpressed in glioma tissues, while miR-140-5p was underexpressed in them, and there was a significant negative correlation between SNHG1 and miR-140-5p. In addition, both down-regulation of SNHG1 and up-regulation of miR-140-5p significantly inhibited the malignant proliferation and invasion of glioma, intensified the apoptosis, and also significantly suppressed the activation of the PI3K/AKT pathway. The dual-luciferase reporter assay, RNA pull-down assay, and RIP determination all confirmed that there was a targeting relationship between SNHG1 and miR-140-5p, and there was no difference between KNS-81 and KALS-1 cells transfected with SNHG1+mimics and si-SNHG1+inhibitor and those in the si-NC group with unrelated sequences in terms of cell malignant progression.

CONCLUSION

SNHG1/miR-140-5p axis and its regulation on PI3K/AKT pathway might be a novel therapeutic direction to curb the malignant progression of glioma.

Identification of a three-long non-coding RNA signature for predicting survival of temozolomide-treated isocitrate dehydrogenase mutant low-grade gliomas

Temozolomide (TMZ) is the major chemotherapy agent in glioma, and isocitrate dehydrogenase (IDH) is a well-known prognostic marker in glioma. O6-methylguanine-DNA methyltransferase promoter methylation (MGMTmethyl) is a predictive biomarker in overall gliomas rather than in IDH mutant gliomas. To discover effective biomarkers that could predict TMZ efficacy in IDH mutant low-grade gliomas (LGGs), we retrieved data of IDH mutant LGGs from TMZ arm of the EORTC22033-26033 trial as the training-set (n = 83), analyzed correlations between long non-coding RNAs (lncRNAs) and progression-free survival (PFS) using Lasso-Cox regression, and created a risk score (RS) to stratify patients. We identified a three-lncRNA signature in TMZ-treated IDH mutant LGGs. All of the three lncRNAs, as well as the RS derived, were significantly correlated with PFS. Patients were classified into high-risk and low-risk groups according to RS. PFS of the high-risk group was significantly worse than that of the low-risk group (P < 0.001). AUCs of the three-, four-, and five-year survival probability predicted by RS were 0.73, 0.79, and 0.76, respectively. The predictive role of the three-lncRNA signature was further validated in an independent testing-set, the TCGA-LGGs, which resulted in a significantly worse PFS (P < 0.001) in the high-risk group. Three-, four-, and five-year survival probabilities predicted by RS were 0.65, 0.69, and 0.84, respectively. Functions of these three lncRNAs involve cell proliferation and differentiation, predicted by their targeting cancer genes. Conclusively, we created a scoring model based on the expression of three lncRNAs, which can effectively predict the survival of IDH mutant LGGs treated with TMZ.

Non-coding RNAs in Brain Tumors, the Contribution of lncRNAs, circRNAs, and snoRNAs to Cancer Development-Their Diagnostic and Therapeutic Potential

Brain tumors are one of the most frightening ailments that afflict human beings worldwide. They are among the most lethal of all adult and pediatric solid tumors. The unique cell-intrinsic and microenvironmental properties of neural tissues are some of the most critical obstacles that researchers face in the diagnosis and treatment of brain tumors. Intensifying the search for potential new molecular markers in order to develop new effective treatments for patients might resolve this issue. Recently, the world of non-coding RNAs (ncRNAs) has become a field of intensive research since the discovery of their essential impact on carcinogenesis. Some of the most promising diagnostic and therapeutic regulatory RNAs are long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and small nucleolar RNAs (snoRNAs). Many recent reports indicate the important role of these molecules in brain tumor development, as well as their implications in metastasis. In the following review, we summarize the current state of knowledge about regulatory RNAs, namely lncRNA, circRNAs, and snoRNAs, and their impact on the development of brain tumors in children and adults with particular emphasis on malignant primary brain tumors-gliomas and medulloblastomas (MB). We also provide an overview of how these different ncRNAs may act as biomarkers in these tumors and we present their potential clinical implications.

Identification of two core genes in glioblastomas with different isocitrate dehydrogenase mutation status

Glioblastoma (GBM) is one of the most common malignancies of the central nervous system, and the Isocitrate Dehydrogenase (IDH) mutation status of GBM has been recognized as a critical prognostic indicator. However, the molecular mechanism underlying the GBM with different IDH mutation status is still not unclear. In this study, a total of 353 DEGs including 207 up-regulated and 146 down-regulated were screened from multiple GBM data sets. Moreover, the biological processes and pathways enriched by DEGs were mainly associated with tumor progression, especially invasion and migration. Then, eight hub genes, including SDC4, SERPINE1, TNC, THBS1, COL1A1, CXCL8, TIMP1 and VEGFA, were selected from a PPI network. Finally, core genes, SERPINE1 and TIMP1, were identified from hub genes by survival analysis and sample validation. Overall, in this study, we revealed underlying molecular mechanisms in GBMs with different IDH mutation status and identified core genes that could be potential markers and targets for diagnosis and treatment of GBMs.

Zinc as a plausible epigenetic modulator of glioblastoma multiforme

Glioblastoma Multiforme (GBM) is an aggressive brain tumor (WHO grade 4 astrocytoma) with unknown causes and is associated with a reduced life expectancy. The available treatment options namely radiotherapy, surgery and chemotherapy have failed to improve life expectancy. Out of the various therapeutic approaches, epigenetic therapy is one of the most studied. Epigenetic therapy is involved in the effective treatment of GBM by inhibiting DNA methyltransferase, histone deacetylation and non-coding RNA. It also promotes the expression of the tumor suppressor gene and is involved in the suppression of the oncogene. Various targets are being studied to implement proper epigenetic regulation to control GBM effectively. Zinc is one of the micronutrients which is considered to maintain epigenetic regulation by promoting the proper DNA folding, protecting genetic material from the oxidative damage and controlling the enzyme activation involved in the epigenetic regulation. Here, we are discussing the importance of zinc in regulating the epigenetic modifications and assessing its role in glioblastoma research. The discussion also highlights the importance of artificial intelligence using epigenetics for envisaging the glioma progression, diagnosis and its management.

Interfering with long non-coding RNA MIR22HG processing inhibits glioblastoma progression through suppression of Wnt/β-catenin signalling

Long non-coding RNAs play critical roles in tumour progression. Through analysis of publicly available genomic datasets, we found that MIR22HG, the host gene of microRNAs miR-22-3p and miR-22-5p, is ranked among the most dysregulated long non-coding RNAs in glioblastoma. The main purpose of this work was to determine the impact of MIR22HG on glioblastoma growth and invasion and to elucidate its mechanistic function. The MIR22HG/miR-22 axis was highly expressed in glioblastoma as well as in glioma stem-like cells compared to normal neural stem cells. In glioblastoma, increased expression of MIR22HG is associated with poor prognosis. Through a number of functional studies, we show that MIR22HG silencing inhibits the Wnt/β-catenin signalling pathway through loss of miR-22-3p and -5p. This leads to attenuated cell proliferation, invasion and in vivo tumour growth. We further show that two genes, SFRP2 and PCDH15, are direct targets of miR-22-3p and -5p and inhibit Wnt signalling in glioblastoma. Finally, based on the 3D structure of the pre-miR-22, we identified a specific small-molecule inhibitor, AC1L6JTK, that inhibits the enzyme Dicer to block processing of pre-miR-22 into mature miR-22. AC1L6JTK treatment caused an inhibition of tumour growth in vivo. Our findings show that MIR22HG is a critical inducer of the Wnt/β-catenin signalling pathway, and that its targeting may represent a novel therapeutic strategy in glioblastoma patients.

LINC00294 negatively modulates cell proliferation in glioma through a neurofilament medium-mediated pathway via interacting with miR-1278

BACKGROUND

Accumulating long noncoding RNAs (lncRNAs) have been recognized to participate in glioma development. Nevertheless, knowledge of the role of linc00294 in glioma remains incomplete.

METHODS

Bioinformatics analysis predicted the differential expression of LINC00294 and neurofilament medium (NEFM) in tumors and normal tissues, as well as the binding between LINC00294 and miR-1278, miR-1278 and NEFM. Luciferase and RNA immunoprecipitation assays were used for the verification of interactions. The potential role of LINC00294 in glioma development was investigated using functional assays, singly and in parallel with its interplay with miR-1278 and NEFM. Cell counting kit-8 and EdU assays were applied to measure cellular proliferation, whereas the terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) method was employed to detect apoptosis.

RESULTS

A new lncRNA, LINC00294, was highly expressed in normal brain tissues. However, it was markedly down-regulated in GBM tissues and glioma cell lines. Overexpression of LINC00294 abates glioma cell proliferation but induces apoptosis. Meanwhile, tumor suppressor NEFM was revealed to be distinctly diminished in cancerous conditions and enhanced in glioma cells by LINC00294 up-regulation. Interactions of miR-1278 with LINC00294 or NEFM occur, and the expression of NEFM is up-regulated by LINC00294 through their competition with respect to binding to miR-1278. Finally, the rescue assays further confirmed that LINC00294 inhibits glioma cell proliferation by absorbing miR-1278 to enhance NEFM.

CONCLUSIONS

Collectively, our observations demonstrate the tumor-suppressive function of LINC00294 in glioma development by sponging miR-1278 and promoting NEFM, suggesting a potential use in therapy for glioma.

Overexpression of LncRNA PSMG3-AS1 Distinguishes Glioblastomas from Sarcoidosis

In clinical practices, glioblastomas (GBM) in some cases can be misdiagnosed as sarcoidosis. This study aimed to develop a biomarker to distinguish GBM from sarcoidosis. In this study, we found that PSMG3-AS1 was upregulated in plasma of GBM patients in comparison with that in sarcoidosis patients and healthy controls. Receiver operating characteristic (ROC) curve analysis showed that upregulation of PSMG3-AS1 effectively separated GBM patients from sarcoidosis patients and healthy controls. In GBM cells, overexpression of PSMG3-AS1 led to downregulated miR-34a and increased methylation of miR-34a gene. In addition, overexpression of PSMG3-AS1 reduced the inhibitory effects of miR-34a on GBM cell proliferation. In conclusion, overexpression of PSMG3-AS1 distinguishes GBM patients from patients with sarcoidosis, and PSMG3-AS1 may promote GBM cell proliferation by downregulating miR-34a through methylation.

LncRNA SNHG4 regulates miR-138/c-Met axis to promote the proliferation of glioblastoma cells

LncRNA SNHG4 has been reported to be an oncogenic lncRNA in osteosarcoma. Our preliminary analysis of the cancer genome atlas dataset revealed the upregulation of SNHG4 in glioblastoma (GBM). In this study, we confirmed the upregulation of SNHG4 in GBM tissues collected from GBM patients. In addition, lower survival rate of GBM patients was observed in patients with high SNHG4 expression level. SNHG4 can directly interact with miR-138, while SNHG4 expression was no altered after miR-138 overexpression. Interestingly, SNHG4 overexpression led to the upregulation of c-Met, a target of miR-138. Cell counting kit-8 assay showed that miR-138 overexpression resulted in decreased proliferation rate of GBM cells. SNHG4 and c-Met overexpression played opposite roles and reduced the effects of miR-138. Therefore, SNHG4 regulates miR-138/c-Met axis to promote the proliferation of GBM cells.

Comprehensive Transcriptomic Analysis and Experimental Validation Identify lncRNA HOXA-AS2/miR-184/COL6A2 as the Critical ceRNA Regulation Involved in Low-Grade Glioma Recurrence

Purpose

The recurrence and metastasis of glioma are closely related to complex regulatory networks among protein-coding genes, lncRNAs and microRNAs. The aim of this study was to investigate core genes, lncRNAs, miRNAs and critical ceRNA regulatory mechanisms, which are involved in lower-grade glioma (LGG) recurrence.

Materials and Methods

We employed multiple datasets from Chinese Glioma Genome Atlas (CGGA) database and The Cancer Genome Atlas (TCGA) to perform comprehensive transcriptomic analysis. Further in vitro experiments including cell proliferation assay, luciferase reporter assay, and Western blot were performed to validate our results.

Results

Recurrent LGG and glioblastoma (GBM) showed different transcriptome characteristics with less overlap of differentially expressed protein-coding genes (DEPs), lncRNAs (DELs) and miRNAs (DEMs) compared with primary samples. There were no overlapping gene in ontology (GO) terms related to GBM recurrence in the TCGA and CGGA databases, but there were overlaps associated with LGG recurrence. GO analysis and protein–protein interaction (PPI) network analysis identified three core genes: TIMP1, COL1A1 and COL6A2. By hierarchical cluster analysis of them, LGGs could be clustered as Low_risk and High_risk group. The High_risk group with high expression of TIMP1, COL1A1, and COL6A2 showed worse prognosis. By coexpression networks analysis, competing endogenous RNA (ceRNA) network analysis, cell proliferation assay and luciferase reporter assay, we confirmed that lncRNA HOXA-AS2 functioned as a ceRNA for miR-184 to regulate expression of COL6A2, which induced cell proliferation of low-grade glioma.

Conclusion

In this study, we revealed a 3-hub protein-coding gene signature to improve prognostic prediction in LGG, and identified a critical ceRNA regulation involved in LGG recurrence.

In silico analysis of long non-coding RNAs in medulloblastoma and its subgroups

Medulloblastoma is the most common malignant pediatric brain tumor with high fatality rate. Recent large-scale studies utilizing genome-wide technologies have sub-grouped medulloblastomas into four major subgroups: wingless (WNT), sonic hedgehog (SHH), group 3, and group 4. However, there has yet to be a global analysis of long non-coding RNAs, a crucial part of the regulatory transcriptome, in medulloblastoma. Here, we performed bioinformatic analysis of RNA-seq data from 175 medulloblastoma patients. Differential lncRNA expression sub-grouped medulloblastomas into the four main molecular subgroups. Some of these lncRNAs were subgroup-specific, with a random forest-based machine-learning algorithm identifying an 11-lncRNA diagnostic signature. We also validated the diagnostic signature in patient derived xenograft (PDX) models. We further identified a 17-lncRNA prognostic model using LASSO based penalized Cox' PH model (Score HR = 13.6301, 95% CI = 8.857-20.98, logrank p-value ≤ 2e-16). Our analysis represents the first global lncRNA analysis in medulloblastoma. Our results identify putative candidate lncRNAs that could be evaluated for their functional role in medulloblastoma genesis and progression or as diagnostic and prognostic biomarkers.

Long Noncoding RNA LINC00467 Promotes Glioma Progression through Inhibiting P53 Expression via Binding to DNMT1

Purpose: This study aimed to investigate whether long noncoding RNA (lncRNA) LINC00467 could regulate proliferative and invasive abilities of glioma cells via p53 and DNA methyltransferase 1 (DNMT1), so as to participate in the occurrence and progression of glioma. Methods: LINC00467 expression in glioma was analyzed by GEPIA database and LINC00467 expression in glioma cell lines was detected by qRT-PCR. The regulatory effects of LINC00467 and p53 on proliferative, invasive capacities and cell cycle were conducted by CCK-8 and EdU assays, transwell assay and flow cytometry, respectively. The binding conditions between LINC00467, DNMT1 and p53 were determined by RNA immunoprecipitation (RIP) and Chromatin immunoprecipitation (ChIP) assays. Western blot was conducted to determine whether LINC00467 could regulate p53 in glioma cells. Finally, rescue experiments were carried out to evaluate whether LINC00467 regulates proliferative and invasive abilities of glioma cells through p53. Results: The expression of LINC00467 was significantly up-regulated in tumor samples than that in normal samples, which was not correlated with patient survival time. Besides, expression of LINC00467 was higher in glioma cells than that of negative control cells. Upregulation of LINC00467 promoted proliferative and invasive abilities, and accelerated cell cycle in G0/G1 phase of U87 and LN229 cells. The results of RIP and ChIP assays demonstrated that LINC00467 could bind to DNMT1 and inhibit p53 expression. Overexpression of p53 partially reversed the enhancement of LINC00467 on proliferative and invasive abilities of glioma cells. Conclusion: These results indicated that high expression of LINC00467 could promote proliferative and invasive abilities of glioma cells through targeting inhibition of p53 expression by binding to DNMT1.

Transcriptome Analysis of lncRNAs in Pheochromocytomas and Paragangliomas

CONTEXT

Pheochromocytomas and paragangliomas (PPGLs) are neuroendocrine tumors explained by germline or somatic mutations in about 70% of cases. Patients with SDHB mutations are at high risk of developing metastatic disease, yet no reliable tumor biomarkers are available to predict tumor aggressiveness.

OBJECTIVE

We aimed at identifying long noncoding RNAs (lncRNAs) specific for PPGL molecular groups and metastatic progression.

DESIGN AND METHODS

To analyze the expression of lncRNAs, we used a mining approach of transcriptome data from a well-characterized series of 187 tumor tissues. Clustering consensus analysis was performed to determine a lncRNA-based classification, and informative transcripts were validated in an independent series of 51 PPGLs. The expression of metastasis-related lncRNAs was confirmed by RT-qPCR. Receiver operating characteristic (ROC) curve analysis was used to estimate the predictive accuracy of potential markers.

MAIN OUTCOME MEASURE

Univariate/multivariate and metastasis-free survival (MFS) analyses were carried out for the assessment of risk factors and clinical outcomes.

RESULTS

Four lncRNA-based subtypes strongly correlated with mRNA expression clusters (chi-square P-values from 1.38 × 10-32 to 1.07 × 10-67). We identified one putative lncRNA (GenBank: BC063866) that accurately discriminates metastatic from benign tumors in patients with SDHx mutations (area under the curve 0.95; P = 4.59 × 10-05). Moreover, this transcript appeared as an independent risk factor associated with poor clinical outcome of SDHx carriers (log-rank test P = 2.29 × 10-05).

CONCLUSION

Our findings extend the spectrum of transcriptional dysregulations in PPGL to lncRNAs and provide a novel biomarker that could be useful to identify potentially metastatic tumors in patients carrying SDHx mutations.

A nomogram combining long non-coding RNA expression profiles and clinical factors predicts survival in patients with bladder cancer

Bladder cancer (BCa) is a heterogeneous disease with various tumorigenic mechanisms and clinical behaviors. The current tumor-node-metastasis (TNM) staging system is inadequate to predict overall survival (OS) in BCa patients. We developed a BCa-specific, long-non-coding-RNA (lncRNA)-based nomogram to improve survival prediction in BCa. We obtained the large-scale gene expression profiles of samples from 414 BCa patients in The Cancer Genome Atlas database. Using an lncRNA-mining computational framework, we identified three OS-related lncRNAs among 826 lncRNAs that were differentially expressed between BCa and normal samples. We then constructed a three-lncRNA signature, which efficiently distinguished high-risk from low-risk patients and was even viable in the TNM stage-II, TNM stage-III and ≥65-year-old subgroups (all P<0.05). Using clinical risk factors, we developed a signature-based nomogram, which performed better than the molecular signature or clinical factors alone for prognostic prediction. A bioinformatical analysis revealed that the three OS-related lncRNAs were co-expressed with genes involved in extracellular matrix organization. Functional assays demonstrated that RNF144A-AS1, one of the three OS-related lncRNAs, promoted BCa cell migration and invasion in vitro. Our three-lncRNA signature-based nomogram effectively predicts the prognosis of BCa patients, and could potentially be used for individualized management of such patients.

Circular RNA MAPK4 (circ-MAPK4) inhibits cell apoptosis via MAPK signaling pathway by sponging miR-125a-3p in gliomas

Background

Recent evidences have shown that circular RNAs (circRNAs) are frequently dysregulated and play paramount roles in various cancers. circRNAs are abundant in central nervous system (CNS); however, few studies describe the clinical significance and role of circRNAs in gliomas, which is the most common and aggressive primary malignant tumor in the CNS.

Methods

A bioinformatics analysis was performed to profile and screen the dyregulated circRNAs during early neural development. Quantitative real-time PCR was used to detect the expression of circ-MAPK4 and target miRNAs. Glioma cells were transfected with circ-MAPK4 siRNAs, then cell proliferation, apoptosis, transwell assays, as well as tumorigenesis and TUNEL assays, were performed to examine effect of circ-MAPK4 in vitro and vivo. Biotinylated-circ-MAPK4 probe based pull-down assay was conducted to confirm the relationship between circ-MAPK4 and miR-125-3p.

Results

In this study, we identified a circRNA, circ-MAPK4 (has_circ_0047688), which was downregulated during early neural differentiation. In gliomas, circ-MAPK4 acted as an oncogene, was inversely upregulated and linked to clinical pathological stage of gliomas (P < 0.05). Next, we verified that circ-MAPK4 promoted the survival and inhibited the apoptosis of glioma cells in vitro and in vivo. Furthermore, we proved that circ-MAPK4 was involved in regulating p38/MAPK pathway, which affected glioma proliferation and apoptosis. Finally, miR-125a-3p, a miRNA exhibited tumor-suppressive function through impairing p38/MAPK pathway, which was increased by inhibiting circ-MAPK4 and could be pulled down by circ-MAPK4. Inhibition of miR-125a-3p could partly rescue the increased phosphorylation levels of p38/MAPK and the elevated amount of apoptosis inducing by knockdown of circ-MAPK4.

Conclusions

Our findings suggest that circ-MAPK4 is a critical player in glioma cell survival and apoptosis via p38/MAPK signaling pathway through modulation of miR-125a-3p, which can serve as a new therapeutic target for treatment of gliomas.

Prediction of the Outcome for Patients with Glioblastoma with lncRNA Expression Profiles

Background

Progress in gene sequencing has paved the way for precise outcome prediction of the heterogeneous disease of glioblastoma. The aim was to assess the potential of utilizing the lncRNA expression profile for predicting glioblastoma patient survival.

Materials and Methods

Clinical and lncRNA expression data were downloaded from the public database of the cancer genome atlas. Differentially expressed lncRNAs between glioblastoma and normal brain tissue were screened by bioinformatics analysis. The samples were randomly separated into the training and testing sets. Univariate Cox regression, least absolute shrinkage, selection operator regression, and multivariate Cox regression were performed to develop the prediction model with the training set, which was presented as a forest plot. The performance of the model was validated by discrimination and calibration analysis in both the training and testing sets. Patient survival between model-predicted low- and high-risk subgroups was compared in both the training and testing sets.

Results

One thousand two hundred and fifty-five differentially expressed lncRNAs between glioblastoma and normal brain tissues were screened. After univariate Cox regression and the least absolute shrinkage and selection operator regression, a 12 lncRNA constituted prediction model was developed by multivariate Cox regression. Of the 12 lncRNAs, 4 lncRNAs were independent risk factors for patient survival. The areas under the receiver operating characteristic curves of the model for predicting 0.5-, 1-, 1.5-, and 2-year patient survival was 0.788, 0.824, 0.874, and 0.886, respectively in the training set and 0.723, 0.84, 0.816, and 0.773 in the testing set. The calibration curves of the prediction model fitted well. Significant survival disparity was observed between the model dichotomized low- and high-risk subgroups in both the training and testing set.

Conclusions

LncRNA expression signature can predict glioblastoma patient survival, promising lncRNA-based survival prediction.

DNA repair genes in astrocytoma tumorigenesis, progression and therapy resistance

Glioblastoma (GBM) is the most common and malignant type of primary brain tumor, showing rapid development and resistance to therapies. On average, patients survive 14.6 months after diagnosis and less than 5% survive five years or more. Several pieces of evidence have suggested that the DNA damage signaling and repair activities are directly correlated with GBM phenotype and exhibit opposite functions in cancer establishment and progression. The functions of these pathways appear to present a dual role in tumorigenesis and cancer progression. Activation and/or overexpression of ATRX, ATM and RAD51 genes were extensively characterized as barriers for GBM initiation, but paradoxically the exacerbated activity of these genes was further associated with cancer progression to more aggressive stages. Excessive amounts of other DNA repair proteins, namely HJURP, EXO1, NEIL3, BRCA2, and BRIP, have also been connected to proliferative competence, resistance and poor prognosis. This scenario suggests that these networks help tumor cells to manage replicative stress and treatment-induced damage, diminishing genome instability and conferring therapy resistance. Finally, in this review we address promising new drugs and therapeutic approaches with potential to improve patient survival. However, despite all technological advances, the prognosis is still dismal and further research is needed to dissect such complex mechanisms.

Long non-coding RNA PAXIP1-AS1 facilitates cell invasion and angiogenesis of glioma by recruiting transcription factor ETS1 to upregulate KIF14 expression

Background

Gliomas are common life-threatening cancers, mainly due to their aggressive nature and frequent invasiveness and long non-coding RNAs (lncRNAs) are emerging as promising molecular targets. Therefore, we explored the regulatory mechanisms underlying the putative involvement of the lncRNA PAX-interacting protein 1- antisense RNA1/ETS proto-oncogene 1/kinesin family member 14 (PAXIP1-AS1/ETS1/KIF14) axis in glioma cell invasion and angiogenesis.

Methods

Firstly, we identified differentially expressed lncRNA PAXIP1-AS1 as associated with glioma based on bioinformatic data. Then, validation experiments were conducted to confirm a high expression level of lncRNA PAXIP1-AS1 in glioma tissues and cells, accompanied by upregulated KIF14. We further examined the binding between lncRNA PAXIP1-AS1, KIF14 promoter activity, and transcription factor ETS1. Next, overexpression vectors and shRNAs were delivered to alter the expression of lncRNA PAXIP1-AS1, KIF14, and ETS1 to analyze their effects on glioma progression in vivo and in vitro.

Results

LncRNA PAXIP1-AS1 was mainly distributed in the nucleus of glioma cells. LncRNA PAXIP1-AS1 could upregulate the KIF14 promoter activity by recruiting transcription factor ETS1. Overexpression of lncRNA PAXIP1-AS1 enhanced migration, invasion, and angiogenesis of human umbilical vein endothelial cells in glioma by recruiting the transcription factor ETS1 to upregulate the expression of KIF14, which was further confirmed by accelerated tumor growth in nude mice.

Conclusions

The key findings of this study highlighted the potential of the lncRNA PAXIP1-AS1/ETS1/KIF14 axis as a therapeutic target for glioma treatment, due to its role in controlling the migration and invasion of glioma cells and its angiogenesis.

Functions and mechanism of noncoding RNA in the somatic cells of the testis

ncRNAs are involved in numerous biological processes by regulating gene expression and cell stability. Studies have shown that ncRNAs also contribute to spermatogenesis. Leydig cells (LCs) and Sertoli cells (SCs) are somatic cells of the testis that support spermatogenesis and are vital to male fertility. In this review, we summarized the findings from studies on ncRNAs in SCs and LCs. In SCs, ncRNAs play key roles in phagocytosis, immunoprotection and development of SCs. In LCs, ncRNAs are involved in steroidogenesis, in particular production of testosterone as well as development of LCs. Here, we discuss the possible target genes and functions of ncRNAs in both types of cells. These ncRNAs regulate the expression of target genes or mRNA coding sequence regions, resulting in a chain reaction that influences cell function. In addition, microRNAs, lncRNAs, piRNA-like RNAs (pilRNAs) and natural antisense transcripts (NATs) are discussed in this review. In summary, we suggest that these ncRNAs might act in coordination to control spermatogenesis and maintain the environmental homeostasis of the testis.

LINC00680 and TTN-AS1 Stabilized by EIF4A3 Promoted Malignant Biological Behaviors of Glioblastoma Cells

Glioblastomas are the most common and malignant intracranial tumors with a low survival rate. Dysregulation of long non-coding RNAs and RNA-binding protein causes various diseases, including cancers. However, the function of LINC00680 and TTN-AS1 in the progression of glioblastomas is still elusive. In this study, we detected that LINC00680 and TTN-AS1 were upregulated in glioblastoma cells. RNA-binding protein EIF4A3 could prolong the half-life of LINC00680 and TTN-AS1. Knockdown of EIF4A3, LINC00680, and TTN-AS1 impaired proliferation, migration, and invasion and inhibited the growth of tumor in vivo and promoted apoptosis of glioblastoma cells. miR-320b was proven to be a target of LINC00680 and TTN-AS1. They interacted with miR-320b as competing endogenous RNAs, which resulted in the reduction of binding between transcriptional factor EGR3 (early growth response 3) mRNA and miR-320b. The accumulation of EGR3 promoted expression of plakophilin (PKP)2, which could activate the epidermal growth factor receptor (EFGR) pathway, leading to the malignant biological behaviors of glioblastoma cells. In summary, LINC00680 and TTN-AS1 promoted glioblastoma cell malignant biological behaviors via the miR-320b/EGR3/PKP2 axis by being stabilized by EIF4A3, which may provide a novel strategy for glioblastoma therapy.

Systematic identification of lncRNA-based prognostic biomarkers for glioblastoma

Glioblastoma (GBM), a primary malignant tumor of the central nervous system, has a very poor prognosis. Analysis of global GBM samples has revealed a variety of long non-coding RNAs (lncRNAs) associated with prognosis; nevertheless, there remains a lack of accurate prognostic markers. Using RNA-Seq, methylation, copy number variation (CNV), mutation and clinical follow-up data for GBM patients from The Cancer Genome Atlas, we performed univariate analysis, multi-cluster analysis, differential analysis of different subtypes of lncRNA and coding genes, weighted gene co-expression network analyses, gene set enrichment analysis, Kyoto Encyclopedia of Genes and Genomes analysis, Gene Ontology analysis, and lncRNA CNV analyses. Our analyses yielded five lncRNAs closely related to survival and prognosis for GBM. To verify the predictive role of these five lncRNAs on the prognosis of GBM patients, the corresponding RNA-seq data from Chinese Glioma Genome Atlas were downloaded and analyzed, and comparable results were obtained. The role of one lncRNA LINC00152 has been observed previously; the others are novel findings. Expression of these lncRNAs could become effective predictors of survival and potential prognostic biomarkers for patients with GBM.

Long intergenic noncoding RNA profiles of pheochromocytoma and paraganglioma: A novel prognostic biomarker

Many long intergenic noncoding RNAs (lincRNAs) serve as cancer biomarkers for diagnosis or prognostication. To understand the role of lincRNAs in the rare neuroendocrine tumors pheochromocytoma and paraganglioma (PCPG), we performed first time in-depth characterization of lincRNA expression profiles and correlated findings to clinical outcomes of the disease. RNA-Seq data from patients with PCPGs and 17 other tumor types from The Cancer Genome Atlas and other published sources were obtained. Differential expression analysis and a machine-learning model were used to identify transcripts specific to PCPGs, as well as established PCPG molecular subtypes. Similarly, lincRNAs specific to aggressive PCPGs were identified, and univariate and multivariate analysis was performed for metastasis-free survival. The results were validated in independent samples using RT-PCR. From a pan-cancer context, PCPGs had a specific and unique lincRNA profile. Among PCPGs, five different molecular subtypes were identified corresponding to the established molecular classification. Upregulation of 13 lincRNAs was found to be associated with aggressive/metastatic PCPGs. RT-PCR validation confirmed the overexpression of four lincRNAs in metastatic compared to non-metastatic PCPGs. Kaplan-Meier analysis identified five lincRNAs as prognostic markers for metastasis-free survival of patients in three subtypes of PCPGs. Stratification of PCPG patients with a risk-score formulated using multivariate analysis of lincRNA expression profiles, presence of key driver mutations, tumor location, and hormone secretion profiles showed significant differences in metastasis-free survival. PCPGs thus exhibit a specific lincRNA expression profile that also corresponds to the established molecular subgroups and can be potential marker for the aggressive/metastatic PCPGs.

Identification of a long noncoding RNA signature to predict outcomes of glioblastoma

Long noncoding RNAs (lncRNAs) are a novel class of gene regulators involved in tumor biogenesis. Glioblastoma is the most common and malignant type of brain tumor. The function and prognostic significance of lncRNAs in glioblastoma remain unclear. In the present study, updated gene annotations were adopted to investigate lncRNA expression profiles in publicly available glioma microarray datasets from the Gene Expression Omnibus and the Repository for Molecular Brain Neoplasia Data. In a training set of 108 samples of glioblastoma, using univariate Cox regression analysis with a permutation P<0.005, four lncRNAs, including insulin‑like growth factor binding protein 7‑antisense 1 (IGFBP7‑AS1), were significantly associated with patient overall survival. These four lncRNAs were integrated as an expression‑based molecular signature to divide patients in the training set into high‑risk and low‑risk subgroups, with distinct survival rates (hazard ratio, 2.72; 95% CI, 1.71‑4.31; P<0.001). The prognostic value of the lncRNA signature was confirmed in two additional datasets comprising a total of 147 samples from patients with glioblastoma. The prognostic value of this signature was independent of age and Karnofsky performance status. This signature was also able to predict different outcomes in cases of glioblastoma associated with an isocitrate dehydrogenase 1 mutation. Further bioinformatics analyses revealed that 'epithelial‑mesenchymal transition' and 'p53 pathway' gene sets were enriched in glioblastoma samples with higher IGFBP7‑AS1 expression. Furthermore, in vitro experiments demonstrated that knockdown of IGFBP7‑AS1 inhibited the viability, migration and invasion of U87 and U251 glioma cells. In conclusion, the present study identified a lncRNA signature able to predict glioblastoma outcomes, and provided novel information regarding the role of IGFBP7‑AS1 in glioma development.

Low LINC00599 expression is a poor prognostic factor in glioma

LINC00599 has been suggested to be involved in physiological and pathological processes including carcinogenesis. However, the clinical and prognostic significance of LINC00599 in glioma patients and the effect of LINC00599 on glioma cell migration and invasion remain unknown. In our results, we first observe the expression of LINC00599 in 31 types of human cancers including tumor tissues and corresponding normal tissues at The Cancer Genome Atlas (TCGA) database, and found that LINC00599 expression levels were only reduced in lower grade glioma (LGG) tissues and glioblastoma multiforme (GBM) tissues compared with normal brain tissues. Moreover, we confirmed levels of LINC00599 expression were decreased in glioma tissues and cell lines compared with matched adjacent normal tissues and normal human astrocytes (NHAs), respectively. Meanwhile, we found that glioma tissues with WHO III-IV grade exhibited lower levels of LINC00599 expression than glioma tissues with I-II grade. The survival analysis at TCGA data showed low LINC00599 expression was associated with poor disease-free survival and overall survival in glioma patients. In vitro study suggested up-regulation of LINC00599 depressed glioma cell migration and invasion through regulating epithelial–mesenchymal transition (EMT) process. In conclusion, LINC00599 acts as a tumor-suppressing long non-coding RNA (lncRNA) in glioma.

Oligonucleotide Therapeutics as a New Class of Drugs for Malignant Brain Tumors: Targeting mRNAs, Regulatory RNAs, Mutations, Combinations, and Beyond

Malignant brain tumors are rapidly progressive and often fatal owing to resistance to therapies and based on their complex biology, heterogeneity, and isolation from systemic circulation. Glioblastoma is the most common and most aggressive primary brain tumor, has high mortality, and affects both children and adults. Despite significant advances in understanding the pathology, multiple clinical trials employing various treatment strategies have failed. With much expanded knowledge of the GBM genome, epigenome, and transcriptome, the field of neuro-oncology is getting closer to achieve breakthrough-targeted molecular therapies. Current developments of oligonucleotide chemistries for CNS applications make this new class of drugs very attractive for targeting molecular pathways dysregulated in brain tumors and are anticipated to vastly expand the spectrum of currently targetable molecules. In this chapter, we will overview the molecular landscape of malignant gliomas and explore the most prominent molecular targets (mRNAs, miRNAs, lncRNAs, and genomic mutations) that provide opportunities for the development of oligonucleotide therapeutics for this class of neurologic diseases. Because malignant brain tumors focally disrupt the blood-brain barrier, this class of diseases might be also more susceptible to systemic treatments with oligonucleotides than other neurologic disorders and, thus, present an entry point for the oligonucleotide therapeutics to the CNS. Nevertheless, delivery of oligonucleotides remains a crucial part of the treatment strategy. Finally, synthetic gRNAs guiding CRISPR-Cas9 editing technologies have a tremendous potential to further expand the applications of oligonucleotide therapeutics and take them beyond RNA targeting.

Integrating multiple-level molecular data to infer the distinctions between glioblastoma and lower-grade glioma

Glioblastomas (GBMs) and lower-grade gliomas (LGGs) are the most common malignant brain tumors. Despite extensive studies that have suggested that there are differences between the two in terms of clinical profile and treatment, their distinctions on a molecular level had not been systematically analyzed. Here, we investigated the distinctions between GBM and LGG based on multidimensional data, including somatic mutations, somatic copy number variants (SCNVs), gene expression, lncRNA expression and DNA methylation levels. We found that GBM patients had a higher mutation frequency and SCNVs than LGG patients. Differential mRNAs and lncRNAs between GBM and LGG were identified and a differential mRNA-lncRNA network was constructed and analyzed. We also discovered some differential DNA methylation sites could distinguish between GBM and LGG samples. Finally, we identified some key GBM- and LGG-specific genes featuring multiple-level molecular alterations. These specific genes participate in diverse functions; moreover, GBM-specific genes are enriched in the glioma pathway. Overall, our studies explored the distinctions between GMB and LGG using a comprehensive genomics approach that may provide novel insights into studying the mechanism and treatment of brain tumors.

Identification of a multidimensional transcriptome signature for survival prediction of postoperative glioblastoma multiforme patients

Background

Glioblastoma multiform (GBM) is a devastating brain tumor with maximum surgical resection, radiotherapy plus concomitant and adjuvant temozolomide (TMZ) as the standard treatment. Diverse clinicopathological and molecular features are major obstacles to accurate predict survival and evaluate the efficacy of chemotherapy or radiotherapy. Reliable prognostic biomarkers are urgently needed for postoperative GBM patients.

Methods

The protein coding genes (PCGs) and long non-coding RNA (lncRNA) gene expression profiles of 233 GBM postoperative patients were obtained from The Cancer Genome Atlas (TCGA), TANRIC and Gene Expression Omnibus (GEO) database. We randomly divided the TCGA set into a training (n = 76) and a test set (n = 77) and used GSE7696 (n = 80) as an independent validation set. Survival analysis and the random survival forest algorithm were performed to screen survival associated signature.

Results

Six PCGs (EIF2AK3, EPRS, GALE, GUCY2C, MTHFD2, RNF212) and five lncRNAs (CTD-2140B24.6, LINC02015, AC068888.1, CERNA1, LINC00618) were screened out by a risk score model and formed a PCG-lncRNA signature for its predictive power was strongest (AUC = 0.78 in the training dataset). The PCG-lncRNA signature could divide patients into high- risk or low-risk group with significantly different survival (median 7.47 vs. 18.27 months, log-rank test P < 0.001) in the training dataset. Similar result was observed in the test dataset (median 11.40 vs. 16.80 months, log-rank test P = 0.001) and the independent set (median 8.93 vs. 16.22 months, log-rank test P = 0.007). Multivariable Cox regression analysis verified that it was an independent prognostic factor for the postsurgical patients with GBM. Compared with IDH mutation status, O-(6)-methylguanine DNA methyltransferase promoter methylation status and age, the signature was proved to have a superior predictive power. And stratified analysis found that the signature could further separated postoperative GBM patients who received TMZ-chemoradiation into high- and low-risk groups in TCGA and GEO dataset.

Conclusions

The PCG-lncRNA signature was a novel prognostic marker to predict survival and TMZ-chemoradiation response in GBM patients after surgery.

Electronic supplementary material

The online version of this article (10.1186/s12967-018-1744-8) contains supplementary material, which is available to authorized users.

A Prognostic Signature for Lower Grade Gliomas Based on Expression of Long Non-Coding RNAs

Diffuse low-grade and intermediate-grade gliomas (together known as lower grade gliomas, WHO grade II and III) develop in the supporting glial cells of brain and are the most common types of primary brain tumor. Despite a better prognosis for lower grade gliomas, 70% of patients undergo high-grade transformation within 10 years, stressing the importance of better prognosis. Long non-coding RNAs (lncRNAs) are gaining attention as potential biomarkers for cancer diagnosis and prognosis. We have developed a computational model, UVA8, for prognosis of lower grade gliomas by combining lncRNA expression, Cox regression, and L1-LASSO penalization. The model was trained on a subset of patients in TCGA. Patients in TCGA, as well as a completely independent validation set (CGGA) could be dichotomized based on their risk score, a linear combination of the level of each prognostic lncRNA weighted by its multivariable Cox regression coefficient. UVA8 is an independent predictor of survival and outperforms standard epidemiological approaches and previous published lncRNA-based predictors as a survival model. Guilt-by-association studies of the lncRNAs in UVA8, all of which predict good outcome, suggest they have a role in suppressing interferon-stimulated response and epithelial to mesenchymal transition. The expression levels of eight lncRNAs can be combined to produce a prognostic tool applicable to diverse populations of glioma patients. The 8 lncRNA (UVA8) based score can identify grade II and grade III glioma patients with poor outcome, and thus identify patients who should receive more aggressive therapy at the outset.

Characterization of Transcriptome Transition Associates Long Noncoding RNAs with Glioma Progression

Long noncoding RNAs (lncRNAs) have been implicated in cancer biogenesis and prognosis. However, we still lack knowledge on their function during glioma progression. In this study, we analyzed the lncRNA expression profile across 907 glioma patients in grades II, III, and IV. Widespread dynamic expression of lncRNAs during glioma progression was revealed, and we identified 33 onco-lncRNAs and 61 tumor suppressor lncRNAs. We found that the expression of these oncogenic lncRNAs is regulated by grade-specific expressed transcription factors. Based on the “guilt by association” rule, we predicted the potential functions of oncogenic lncRNAs, and the majority of these lncRNAs are involved in cancer hallmarks. Especially we found that CARD8-AS1 regulates the metastatic potential of glioma cell lines in vitro. Integrating clinical information, we identified the 12 protective and 8 risk lncRNAs (such as PWAR6 and CARD8-AS1) in glioma. Finally, an lncRNA-gene functional module was identified to be associated with the survival of patients. The predictive ability of this module signature was further validated in an independent dataset. Our results revealed the dynamic transcriptome transition during glioma progression, indicating that the lncRNA signature could be a useful biomarker that may improve upon our understanding of the molecular mechanisms underlying glioma progression.