Exploring Long Noncoding RNAs in Glioblastoma: Regulatory Mechanisms and Clinical Potentials

Zeng, Tao; Li, Lei; Zhou, Yan

doi:10.1155/2018/2895958

Cited by 20 publications

(30 citation statements)

References 171 publications

(155 reference statements)

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“…Genetics play a significant regulatory role in the occurrence and development of cancers. Owing to the advent of high‐throughput sequencing technology, several long noncoding RNAs (lncRNAs) have been discovered, some of which appear to have a significant regulatory function in the pathogenesis of GBM 2 …”

Section: Introductionmentioning

confidence: 99%

Construction of lncRNA‐associated ceRNA networks to identify prognostic lncRNA biomarkers for glioblastoma

Liu

Wang

Yang

et al. 2020

J of Cellular Biochemistry

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Long noncoding RNAs (lncRNAs) serve as competitive endogenous RNAs (ceRNAs) that play significant regulatory roles in the pathogenesis of tumors. However, the role of lncRNAs, especially the lncRNA-related ceRNA regulatory network, in glioblastoma (GBM) has not been fully elucidated. The goal of the current study was to construct lncRNA-microRNA-mRNA-related ceRNA networks for further investigation of their mechanism of action in GBM. We downloaded data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases and identified differential lncRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) associated with GBM. A ceRNA network was constructed and analyzed to examine the relationship between lncRNAs and patients' overall survival. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGGs) were used to analyze the related mRNAs to indirectly explain the mechanism of action of lncRNAs. The potential effective drugs for the treatment of GBM were identified using the connectivity map (CMap). After integrated analysis, we obtained a total of 210 differentially expressed lncRNAs, 90 differentially expressed miRNAs, and 2508 differentially expressed mRNAs (DEmRNAs) from the TCGA and GEO databases. Using these differential genes, we constructed a lncRNA-associated ceRNA network. Six lncRNAs in the ceRNA network were associated with the overall survival of patients with GBM. Through KEGG analysis, it was found that the DEmRNAs involved in the network are related to cancer-associated pathways, for instance, mitogen-activated protein kinase and Ras signaling pathways. CMap analysis revealed four small-molecule compounds that could be used as drugs for the treatment of GBM. In this study, a multi-database joint analysis was used to construct a lncRNA-related ceRNA network to help identify the regulatory functions of lncRNAs in the pathogenesis of GBM.

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Section: Introductionmentioning

confidence: 99%

Construction of lncRNA‐associated ceRNA networks to identify prognostic lncRNA biomarkers for glioblastoma

Liu

Wang

Yang

et al. 2020

J of Cellular Biochemistry

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“…Long non-coding RNAs are increasingly recognized as important players in cancer research [19], particularly as biomarkers and/or therapeutic targets [32][33][34][35][36], including in brain tumors [20,[37][38][39][40]. However, there is a lack of knowledge of lncRNAs' involvement in MBs.…”

Section: Discussionmentioning

confidence: 99%

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

Joshi

Perera

2019

Preprint

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AbstractMedulloblastoma 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.

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“…They can also derive from the mitochondrial genome [13]. lncRNAs are generally localized in the nucleus, have little polyadenylation, and are cell-type and tissue specific [1,18]. The cellular localization of lncRNAs appears to provide information about the mechanisms of cellular regulation [17].…”

Section: Long Noncoding Rnasmentioning

confidence: 99%

“…It has been reported that lncRNAs regulate glioblastoma development and malignancy through different cellular processes, including cell proliferation, differentiation, apoptosis, stemness, drug resistance, and response to hypoxia [6,42]. Approximately 40% of known lncRNAs are mainly expressed in the brain [18]. This suggests that lncRNAs have important functions in brain development, and also that changes in noncoding regions and expression can lead to disease-causing variants [43].…”

Section: Long Noncoding Rnas In Glioblastoma Subclassification and Pamentioning

confidence: 99%

Coding of Glioblastoma Progression and Therapy Resistance through Long Noncoding RNAs

Zottel

Šamec

Paska

et al. 2020

Cancers

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Glioblastoma is the most aggressive and lethal primary brain malignancy, with an average patient survival from diagnosis of 14 months. Glioblastoma also usually progresses as a more invasive phenotype after initial treatment. A major step forward in our understanding of the nature of glioblastoma was achieved with large-scale expression analysis. However, due to genomic complexity and heterogeneity, transcriptomics alone is not enough to define the glioblastoma “fingerprint”, so epigenetic mechanisms are being examined, including the noncoding genome. On the basis of their tissue specificity, long noncoding RNAs (lncRNAs) are being explored as new diagnostic and therapeutic targets. In addition, growing evidence indicates that lncRNAs have various roles in resistance to glioblastoma therapies (e.g., MALAT1, H19) and in glioblastoma progression (e.g., CRNDE, HOTAIRM1, ASLNC22381, ASLNC20819). Investigations have also focused on the prognostic value of lncRNAs, as well as the definition of the molecular signatures of glioma, to provide more precise tumor classification. This review discusses the potential that lncRNAs hold for the development of novel diagnostic and, hopefully, therapeutic targets that can contribute to prolonged survival and improved quality of life for patients with glioblastoma.

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Exploring Long Noncoding RNAs in Glioblastoma: Regulatory Mechanisms and Clinical Potentials

Cited by 20 publications

References 171 publications

Construction of lncRNA‐associated ceRNA networks to identify prognostic lncRNA biomarkers for glioblastoma

Construction of lncRNA‐associated ceRNA networks to identify prognostic lncRNA biomarkers for glioblastoma

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

Coding of Glioblastoma Progression and Therapy Resistance through Long Noncoding RNAs

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