Analysis of long non-coding RNA expression profiles identifies novel lncRNA biomarkers in the tumorigenesis and malignant progression of gliomas

A pilot study: Metabolic profiling of plasma and saliva samples from newly diagnosed glioblastoma patients

BACKGROUND

Despite aggressive treatment, more than 90% of glioblastoma (GBM) patients experience recurrences. GBM response to therapy is currently assessed by imaging techniques and tissue biopsy. However, difficulties with these methods may cause misinterpretation of treatment outcomes. Currently, no validated therapy response biomarkers are available for monitoring GBM progression. Metabolomics holds potential as a complementary tool to improve the interpretation of therapy responses to help in clinical interventions for GBM patients.

METHODS

Saliva and blood from GBM patients were collected pre and postoperatively. Patients were stratified conforming their progression-free survival (PFS) into favourable or unfavourable clinical outcomes (>9 months or PFS ≤ 9 months, respectively). Analysis of saliva (whole-mouth and oral rinse) and plasma samples was conducted utilising LC-QqQ-MS and LC-QTOF-MS to determine the metabolomic and lipidomic profiles. The data were investigated using univariate and multivariate statistical analyses and graphical LASSO-based graphic network analyses.

RESULTS

Altogether, 151 metabolites and 197 lipids were detected within all saliva and plasma samples. Among the patients with unfavourable outcomes, metabolites such as cyclic-AMP, 3-hydroxy-kynurenine, dihydroorotate, UDP and cis-aconitate were elevated, compared to patients with favourable outcomes during pre-and post-surgery. These metabolites showed to impact the pentose phosphate and Warburg effect pathways. The lipid profile of patients who experienced unfavourable outcomes revealed a higher heterogeneity in the abundance of lipids and fewer associations between markers in contrast to the favourable outcome group.

CONCLUSION

Our findings indicate that changes in salivary and plasma metabolites in GBM patients can potentially be employed as less invasive prognostic biomarkers/biomarker panel but validation with larger cohorts is required.

Influence of Long Non-Coding RNA in the Regulation of Cancer Stem Cell Signaling Pathways

Over the past two decades, cancer stem cells (CSCs) have emerged as an immensely studied and experimental topic, however a wide range of questions concerning the topic still remain unanswered; in particular, the mechanisms underlying the regulation of tumor stem cells and their characteristics. Understanding the cancer stem-cell signaling pathways may pave the way towards a better comprehension of these mechanisms. Signaling pathways such as WNT, STAT, Hedgehog, NOTCH, PI3K/AKT/mTOR, TGF-β, and NF-κB are responsible not only for modulating various features of CSCs but also their microenvironments. Recently, the prominent roles of various non-coding RNAs such as small non-coding RNAs (sncRNAs) and long non-coding RNAs (lncRNAs) in developing and enhancing the tumor phenotypes have been unfolded. This review attempts to shed light on understanding the influence of long non- coding RNAs in the modulation of various CSC-signaling pathways and its impact on the CSCs and tumor properties; highlighting the protagonistic and antagonistic roles of lncRNAs.

Long Noncoding RNA CTD-2589M5.4 Inhibits Ovarian Cancer Cell Proliferation, Migration, and Invasion Via Downregulation of the Extracellular Matrix-Receptor Interaction Pathway

Background: The authors' previous study showed that the long noncoding RNA CTD-2589M5.4 was significantly upregulated in multidrug-resistant ovarian cancer cells. However, the role of CTD-2589M5.4 in the progression of ovarian cancer remains unclear. The purpose of this current study was to illuminate the biological function and possible mechanism of CTD-2589M5.4 in ovarian cancer development. Materials and Methods: The expression of CTD-2589M5.4 was examined via real-time quantitative PCR in primary ovarian cancer tissues (POCTs) and ovarian cancer cell lines. The biological function of CTD-2589M5.4 was analyzed via CCK-8 proliferation, wound healing, transwell, and flow cytometry assays in CTD-2589M5.4-overexpressed/silenced and control ovarian cancer cells. The mechanism of CTD-2589M5.4 function in ovarian cancer progression was analyzed utilizing high-throughput RNA-sequencing, Kyoto Encyclopedia of Genes and Genomes analysis, qRT-PCR, Western blot, and rescue experiments. Results: CTD-2589M5.4 expression was decreased in the POCTs and ovarian cancer cells compared with the normal ovarian tissues (p < 0.05) and normal ovarian epithelial cells (p < 0.05). Overexpression of CTD-2589M5.4 inhibited the proliferation, invasion, and migration of ovarian cancer cells, while knockdown of CTD-2589M5.4 had the opposite effect. Furthermore, a total of 750 and 233 genes were notably upregulated and downregulated, respectively, in the CTD-2589M5.4-overexpressed A2780 cells, while the extracellular matrix (ECM)-receptor interaction pathway was significantly downregulated. In addition, overexpression of fibronectin 1 significantly abrogated the tumor suppressive function of CTD-2589M5.4. Conclusions: This study demonstrated that CTD-2589M5.4 could inhibit ovarian cancer cell proliferation, invasion, and migration, at least partially by way of downregulating the ECM-receptor interaction pathway, therefore providing a potential therapeutic target for the prevention and/or treatment of ovarian cancer.

Mechanisms of Long Non-Coding RNAs in Biological Characteristics and Aerobic Glycolysis of Glioma

Glioma is the most common and aggressive tumor of the central nervous system. The uncontrolled proliferation, cellular heterogeneity, and diffusive capacity of glioma cells contribute to a very poor prognosis of patients with high grade glioma. Compared to normal cells, cancer cells exhibit a higher rate of glucose uptake, which is accompanied with the metabolic switch from oxidative phosphorylation to aerobic glycolysis. The metabolic reprogramming of cancer cell supports excessive cell proliferation, which are frequently mediated by the activation of oncogenes or the perturbations of tumor suppressor genes. Recently, a growing body of evidence has started to reveal that long noncoding RNAs (lncRNAs) are implicated in a wide spectrum of biological processes in glioma, including malignant phenotypes and aerobic glycolysis. However, the mechanisms of diverse lncRNAs in the initiation and progression of gliomas remain to be fully unveiled. In this review, we summarized the diverse roles of lncRNAs in shaping the biological features and aerobic glycolysis of glioma. The thorough understanding of lncRNAs in glioma biology provides opportunities for developing diagnostic biomarkers and novel therapeutic strategies targeting gliomas.

Promoting Prognostic Model Application: A Review Based on Gliomas

Malignant neoplasms are characterized by poor therapeutic efficacy, high recurrence rate, and extensive metastasis, leading to short survival. Previous methods for grouping prognostic risks are based on anatomic, clinical, and pathological features that exhibit lower distinguishing capability compared with genetic signatures. The update of sequencing techniques and machine learning promotes the genetic panels-based prognostic model development, especially the RNA-panel models. Gliomas harbor the most malignant features and the poorest survival among all tumors. Currently, numerous glioma prognostic models have been reported. We systematically reviewed all 138 machine-learning-based genetic models and proposed novel criteria in assessing their quality. Besides, the biological and clinical significance of some highly overlapped glioma markers in these models were discussed. This study screened out markers with strong prognostic potential and 27 models presenting high quality. Conclusively, we comprehensively reviewed 138 prognostic models combined with glioma genetic panels and presented novel criteria for the development and assessment of clinically important prognostic models. This will guide the genetic models in cancers from laboratory-based research studies to clinical applications and improve glioma patient prognostic management.

Promoting Prognostic Model Application: A Review Based on Gliomas

Malignant neoplasms are characterized by poor therapeutic efficacy, high recurrence rate, and extensive metastasis, leading to short survival. Previous methods for grouping prognostic risks are based on anatomic, clinical, and pathological features that exhibit lower distinguishing capability compared with genetic signatures. The update of sequencing techniques and machine learning promotes the genetic panels-based prognostic model development, especially the RNA-panel models. Gliomas harbor the most malignant features and the poorest survival among all tumors. Currently, numerous glioma prognostic models have been reported. We systematically reviewed all 138 machine-learning-based genetic models and proposed novel criteria in assessing their quality. Besides, the biological and clinical significance of some highly overlapped glioma markers in these models were discussed. This study screened out markers with strong prognostic potential and 27 models presenting high quality. Conclusively, we comprehensively reviewed 138 prognostic models combined with glioma genetic panels and presented novel criteria for the development and assessment of clinically important prognostic models. This will guide the genetic models in cancers from laboratory-based research studies to clinical applications and improve glioma patient prognostic management.

Role of mammalian long non-coding RNAs in normal and neuro oncological disorders

Long non-coding RNAs (lncRNAs) are expressed at lower levels than protein-coding genes but have a crucial role in gene regulation. LncRNA is distinct, they are being transcribed using RNA polymerase II, and their functionality depends on subcellular localization. Depending on their niche, they specifically interact with DNA, RNA, and proteins and modify chromatin function, regulate transcription at various stages, forms nuclear condensation bodies and nucleolar organization. lncRNAs may also change the stability and translation of cytoplasmic mRNAs and hamper signaling pathways. Thus, lncRNAs affect the physio-pathological states and lead to the development of various disorders, immune responses, and cancer. To date, ~40% of lncRNAs have been reported in the nervous system (NS) and are involved in the early development/differentiation of the NS to synaptogenesis. LncRNA expression patterns in the most common adult and pediatric tumor suggest them as potential biomarkers and provide a rationale for targeting them pharmaceutically. Here, we discuss the mechanisms of lncRNA synthesis, localization, and functions in transcriptional, post-transcriptional, and other forms of gene regulation, methods of lncRNA identification, and their potential therapeutic applications in neuro oncological disorders as explained by molecular mechanisms in other malignant disorders.

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.

Potential of long non-coding RNAs as a therapeutic target and molecular markers in glioblastoma pathogenesis

Glioblastoma (GB) is by far the most hostile type of malignant tumor that primarily affects the brain and spine, derived from star-shaped glial cells that are astrocytes and oligodendrocytes. Despite of significant efforts in recent years in glioblastoma research, the clinical efficacy of existing medical intervention is still limited and very few potential diagnostic markers are available. Long non-coding RNAs (lncRNAs) that lacks protein-coding capabilities were previously thought to be "junk sequences" in mammalian genomes are quite indispensible epigenetic regulators that can positively or negatively regulate gene expression and nuclear architecture, with significant roles in the initiation and development of tumors. Nevertheless, the precise mechanism of these distortedly expressed lncRNAs in glioblastoma pathogenesis is not yet fully understood. Since the advent of high-throughput sequencing technologies, more and more research have elucidated that lncRNAs are one of the most promising prognostic biomarkers and therapeutic targets for glioblastoma. In this paper, I briefly outlined the existing findings of lncRNAs. And also summarizes the profiles of different lncRNAs that have been broadly classified in glioblastoma research, with emphasis on both their prognostic and therapeutic values.

Prognostic and Predictive Value of m6A "Eraser" Related Gene Signature in Gastric Cancer

Background

N6-methyladenosine (m6A) RNA modification plays a critical role in gastric cancer (GC). However, the relationship between the m6A “eraser”, FTO, and ALKBH5, and the prognosis of GC still remains unclear. This study aimed to evaluate the effect of FTO and ALKBH5 on the prognosis of patients and their potential roles in GC.

Materials and Methods

A total of 738 GC samples with clinical information obtained from two independent datasets were included and divided into training set and testing set. Differential expression analysis of the m6A “eraser” related genes was performed. The LASSO Cox regression model was constructed to analyze the m6A “eraser” related risk genes. The univariate and multivariate Cox regression model were employed to identify the independent prognostic factors. Kaplan-Meier method was used for survival analysis. A nomogram model was then carried out to predict the prognosis of GC patients. Additionally, GO and KEGG analyses were conducted to identify the potential role of the m6A “eraser” related genes in GC. The relative proportion of 22 different genotypes in immune infiltrating cells was calculated by CIBERSORT algorithm.

Results

In total, nine m6A “eraser” related risk genes and risk scores were obtained and calculated. Patients in high-risk group demonstrated significantly worse prognosis than those in low-risk group. Age, stage, and risk score were considered as independent prognostic factors. The nomogram model constructed accurately predicted the 3-year and 5-year overall survival (OS) of patients. Furthermore, m6A “eraser” might play a functional role in GC. The expression of m6A “eraser” leads to changes in tumor immune microenvironment.

Conclusions

FTO and ALKBH5 showed association with the prognosis of GC. The m6A “eraser” related genes, which is considered as a reliable prognostic and predictive tool, assists in predicting the OS in GC patients.

Long non-coding RNAs in brain tumors

Long non-coding RNAs (lncRNAs) have been found to be central players in the epigenetic, transcriptional and post-transcriptional regulation of gene expression. There is an accumulation of evidence on newly discovered lncRNAs, their molecular interactions and their roles in the development and progression of human brain tumors. LncRNAs can have either tumor suppressive or oncogenic functions in different brain cancers, making them attractive therapeutic targets and biomarkers for personalized therapy and precision diagnostics. Here, we summarize the current state of knowledge of the lncRNAs that have been implicated in brain cancer pathogenesis, particularly in gliomas and medulloblastomas. We discuss their epigenetic regulation as well as the prospects of using lncRNAs as diagnostic biomarkers and therapeutic targets in patients with brain tumors.

Prognostic and Predictive Value of a Long Non-coding RNA Signature in Glioma: A lncRNA Expression Analysis

The current histologically based grading system for glioma does not accurately predict which patients will have better outcomes or benefit from adjuvant chemotherapy. We proposed that combining the expression profiles of multiple long non-coding RNAs (lncRNAs) into a single model could improve prediction accuracy. We included 1,094 glioma patients from three different datasets. Using the least absolute shrinkage and selection operator (LASSO) Cox regression model, we built a multiple-lncRNA-based classifier on the basis of a training set. The predictive and prognostic accuracy of the classifier was validated using an internal test set and two external independent sets. Using this classifier, we classified patients in the training set into high- or low-risk groups with significantly different overall survival (OS, HR = 8.42, 95% CI = 4.99–14.2, p < 0.0001). The prognostic power of the classifier was then assessed in the other sets. The classifier was an independent prognostic factor and had better prognostic value than clinicopathological risk factors. The patients in the high-risk group were found to have a favorable response to adjuvant chemotherapy (HR = 0.4, 95% CI = 0.25–0.64, p < 0.0001). We built a nomogram that integrated the 10-lncRNA-based classifier and four clinicopathological risk factors to predict 3 and 5 year OS. Gene set variation analysis (GSVA) showed that pathways related to tumorigenesis, undifferentiated cancer, and epithelial–mesenchymal transition were enriched in the high-risk groups. Our classifier built on 10-lncRNAs is a reliable prognostic and predictive tool for OS in glioma patients and could predict which patients would benefit from adjuvant chemotherapy.

LncRNA SAMMSON Knockdown Inhibits the Malignancy of Glioblastoma Cells by Inactivation of the PI3K/Akt Pathway

Dysregulated lncRNAs are proposed to be tightly associated with the progression of various tumors including glioblastoma (GBM). LncRNA Survival Associated Mitochondrial Melanoma-Specific Oncogenic Non-Coding RNA (SAMMSON) has been reported to be an oncogenic lncRNA in several tumors. Nevertheless, the specific role and molecular mechanism of SAMMSON in GBM progression remain unknown. Expression of SAMMSON in GBM tissues and cells was detected by qRT-PCR. CCK-8 and LDH release assays were applied to evaluate cellular viability. Invasion effect was assessed by Transwell invasion assay and western blot analysis of E-cadherin and N-cadherin expression. Apoptosis was detected using flow cytometry analysis and caspase-3 activity assay. The protein levels of phosphatidylinositol-3-kinase (PI3K), phosphorylated (p)-PI3K, protein kinase B (Akt) and p-Akt were estimated by western blot. We found that SAMMSON was highly expressed in GBM tissues and cells. SAMMSON knockdown suppressed cell viability and increased LDH release in GBM cells. Moreover, SAMMSON silencing impeded the invasive ability of GBM cells by regulating epithelial-to-mesenchymal transition (EMT). Furthermore, SAMMSON downregulation increased the apoptotic rate and caspase-3 activity in GBM cells. Additionally, it was demonstrated that the PI3K/Akt pathway was inhibited following SAMMSON silencing in GBM cells. Rescue assays revealed that activation of the PI3K/Akt pathway by 740Y-P abolished SAMMSON knockdown-induced viability reduction, invasion suppression and apoptosis in GBM cells. Taken together, lncRNA SAMMSON knockdown inhibited the malignancy of GBM cells by inactivation of the PI3K/Akt pathway.

Circulating biomarkers in patients with glioblastoma

Gliomas are the most common tumours of the central nervous system and the most aggressive form is glioblastoma (GBM). Despite advances in treatment, patient survival remains low. GBM diagnosis typically relies on imaging techniques and postoperative pathological diagnosis; however, both procedures have their inherent limitations. Imaging modalities cannot differentiate tumour progression from treatment-related changes that mimic progression, known as pseudoprogression, which might lead to misinterpretation of therapy response and delay clinical interventions. In addition to imaging limitations, tissue biopsies are invasive and most of the time cannot be performed over the course of treatment to evaluate 'real-time' tumour dynamics. In an attempt to address these limitations, liquid biopsies have been proposed in the field. Blood sampling is a minimally invasive procedure for a patient to endure and could provide tumoural information to guide therapy. Tumours shed tumoural content, such as circulating tumour cells, cell-free nucleic acids, proteins and extracellular vesicles, into the circulation, and these biomarkers are reported to cross the blood-brain barrier. The use of liquid biopsies is emerging in the field of GBM. In this review, we aim to summarise the current literature on circulating biomarkers, namely circulating tumour cells, circulating tumour DNA and extracellular vesicles as potential non-invasively sampled biomarkers to manage the treatment of patients with GBM.

Blocking lncRNA MALAT1/miR-199a/ZHX1 Axis Inhibits Glioblastoma Proliferation and Progression

Zinc fingers and homeoboxes 1 (ZHX1) is a transcription repressor that has been implicated in the tumorigenesis and progression of diverse tumors. The functional role and regulating mechanism of ZHX1 has not been elucidated in glioblastoma (GBM). Previous reports have suggested that a large number of non-coding RNAs play a vital role in glioma initiation and progression. This study aimed to investigate the functional role and co-regulatory mechanisms of the metastasis-associated lung adenocarcinoma transcript-1 (MALAT1)/ microRNA-199a (miR-199a)/ZHX1 axis in GBM. We analyzed the expression of the MALAT1/miR-199a/ZHX1 axis and its correlation with patients' overall survival using two different glioma gene-expression datasets. A series of in vitro and in vivo studies including dual luciferase reporter assay, fluorescence in situ hybridization (FISH), RNA immunoprecipitation, and pull-down experiments were completed to elucidate the biological significance of the MALAT1/miR-199a/ZHX1 axis in promoting glioma proliferation and progression. Elevated ZHX1 expression correlated with poor prognosis in GBM patients, and in vitro studies demonstrated that ZHX1 attenuated GBM cell apoptosis by downregulation of pro-apoptotic protein (Bax) and upregulation of anti-apoptotic protein (Bcl-2). Furthermore, knockdown of MALAT1 inhibited GBM proliferation and progression in vitro and reduced tumor volume and prolonged survival in an orthotopic GBM murine model. Finally, we demonstrated that MALAT1 promoted ZHX1 expression via acting as a competing endogenous RNA by sponging miR-199a. The MALAT1/miR-199a/ZHX1 axis promotes GBM cell proliferation and progression in vitro and in vivo, and its expression negatively correlates with GBM patient survival. Blocking the MALAT1/miR-199a/ZHX1 axis can serve as a novel therapeutic strategy for treating GBM.

Linc00423 as a tumor suppressor in retroperitoneal liposarcoma via activing MAPK signaling pathway through destabilizing of NFATC3

Unraveling the noncoding RNA expression networks governing cancer initiation and development is essential while remains largely uncompleted in retroperitoneal liposarcoma (RLS). Through RNA-seq technologies and computational biology, deregulated long noncoding RNAs (lncRNAs) are being identified and reveal that lncRNAs are implicated in serial steps of RLS development. High-throughput sequencing with computational methods for assembling the transcriptome of five paired RLS patient’s tissues. We found that long intergenic noncoding RNA 423 (linc00423) was downregulated in RLS tissues. Gain-of-function assays revealed that overexpressed linc00423 obviously inhibited RLS cell growth in vitro and in vivo. Additionally, RNA sequence, RNA-pulldown and RIP assays evidenced that linc00423 involved in MAPK signaling pathway via destabilizing of nuclear factor of activated T-cells 3 (NFATC3). Summing up, our findings demonstrated that linc00423 acted as the tumor suppressor in RLS cells through regulating the protein level of NFATC3 at a post-transcriptional level and negatively regulated the MAPK signaling pathway at a transcriptional level. Linc00423 might serve as a candidate prognostic biomarker and a target for novel therapies of RLS patients.

Long non‑coding RNA H19 regulates cell growth and metastasis via the miR‑22‑3p/Snail1 axis in gastric cancer

Gastric cancer (GC) is the fifth most prevalent type of malignancy and the third leading cause of cancer‑related mortality worldwide, with the prognosis of patients with late‑stage GC remaining at poor levels. Long non‑coding RNA (lncRNA) H19 (H19) is involved in the growth and metastasis of tumors, and it is upregulated under hypoxic conditions and in certain types of cancer; however, the underlying mechanisms of action of this lncRNA as regards the initiation and development of GC remain unknown. Thus, in the present study, we aimed to determine the role of lncRNA H19 in GC and to elucidate the underlying mechanisms. H19 was found to be upregulated in GC tissues and cells compared with the para‑cancerous tissues, and an elevated expression of H19 was associated with lymph node metastasis and TNM stage. Furthermore, the downregulation of H19 suppressed the proliferation, invasion, migration and epithelial‑mesenchymal transition of GC cells in vitro and suppressed tumor growth in vivo. H19 was also found to be able to bind with miR‑22‑3p, and H19‑induced cell growth and metastasis were shown to be reversed by the upregulation of miR‑22‑3p; the miR‑22‑3p level was found to inversely correlate with H19 expression in GC tissues. Furthermore, the overexpression of miR‑22‑3p notably suppressed the proliferation, migration and invasion of GC cells, and these effects were enhanced by the downregulation of Snail1. In addition, cell growth and metastasis induced by miR‑22‑3p downregulation were partially reversed by the knockdown of Snail1. Furthermore, a negative correlation was observed between the mRNA expression levels of miR‑22‑3p and Snail1 in GC tissues. On the whole, the findings of the present study revealed that H19 was upregulated in GC tissues, which promoted tumor growth and metastasis via the miR‑22‑3p/Snail1 signaling pathway. In summary, these findings provide novel insight into the potential regulatory roles of H19 in GC, and suggest that the H19/miR‑22‑3p/Snail1 axis may prove to be a promising therapeutic target for the treatment of patients with GC.

A prognostic signature based on three non-coding RNAs for prediction of the overall survival of glioma patients

Recent studies have identified certain non‐coding RNAs (ncRNAs) as biomarkers of disease progression. Glioma is the most common primary intracranial cancer, with high mortality. Here, we developed a prognostic signature for prediction of overall survival (OS) of glioma patients by analyzing ncRNA expression profiles. We downloaded gene expression profiles of glioma patients along with their clinical information from the Gene Expression Omnibus and extracted ncRNA expression profiles via a microarray annotation file. Correlations between ncRNAs and glioma patients’ OS were first evaluated through univariate Cox regression analysis and a permutation test, followed by random survival forest analysis for further screening of valuable ncRNA signatures. Prognostic signatures could be established as a risk score formula by including ncRNA signature expression values weighted by their estimated regression coefficients. Patients could be divided into high risk and low risk subgroups by using the median risk score as cutoff. As a result, glioma patients with a high risk score tended to have shorter OS than those with low risk scores, which was confirmed by analyzing another set of glioma patients in an independent dataset. Additionally, gene set enrichment analysis showed significant enrichment of cancer development‐related biological processes and pathways. Our study may provide further insights into the evaluation of glioma patients’ prognosis.

Long noncoding RNAs in cancer cells

Long noncoding RNA (lncRNA) has recently been investigated as key modulators that regulate many biological processes in human cancers via diverse mechanisms. LncRNAs can interact with macromolecules such as DNA, RNA, or protein to exert cellular effects and to act as either tumor promoters or tumor suppressors in various malignancies. Moreover, the aberrant expression of lncRNAs may be detected in multiple cancer phenotypes by employing the rapidly developing modern gene chip technology and bioinformatics analysis. Herein, we highlight the mechanisms of action of lncRNAs, their functional cellular roles and their involvement in cancer progression. Finally, we provide an overview of recent progress in the lncRNA field and future potential for lncRNAs as cancer diagnostic markers and therapeutics.

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.

Long non-coding RNAs in brain tumours: Focus on recent epigenetic findings in glioma

Glioma biology is a major focus in tumour research, primarily due to the aggressiveness and high mortality rate of its most aggressive form, glioblastoma. Progress in understanding the molecular mechanisms behind poor prognosis of glioblastoma, regardless of treatment approaches, has changed the classification of brain tumours after nearly 100 years of relying on anatomopathological criteria. Expanding knowledge in genetic, epigenetic and translational medicine is also beginning to contribute to further elucidating molecular dysregulation in glioma. Long non‐coding RNAs (lncRNAs) and their main representatives, large intergenic non‐coding RNAs (lincRNAs), have recently been under scrutiny in glioma research, revealing novel mechanisms of pathogenesis and reinforcing others. Among those confirmed was the reactivation of events significant for foetal brain development and neuronal commitment. Novel mechanisms of tumour suppression and activation of stem‐like behaviour in tumour cells have also been examined. Interestingly, these processes involve lncRNAs that are present both during normal brain development and in brain malignancies and their reactivation might be explained by epigenetic mechanisms, which we discuss in detail in the present review. In addition, the review discusses the lncRNAs‐induced changes, as well as epigenetic changes that are consequential for tumour formation, affecting, in turn, the expression of various types of lncRNAs.

Long noncoding RNA SNHG7 promotes the progression and growth of glioblastoma via inhibition of miR-5095

The long non-coding RNA SNHG7 (small nucleolar RNA host gene 7) has been reported to be involved in various cancers as a potential oncogene. However, the functions and molecular mechanisms of SNHG7 in glioblastoma (GBM) are largely unknown. In the present study, we showed that the expression of SNHG7 was significantly upregulated in GBM tissues and cell lines compared with non-cancerous brain tissues. Furthermore, we found that SNHG7 knockdown remarkably suppressed the proliferation, migration and invasion of A172 and U87 cells while inducing their apoptosis. Subsequently, we showed that SNHG7 knockdown significantly inhibited tumor growth and metastasis in vivo by using xenograft experiments in nude mice. In terms of mechanism, we found that SNHG7 directly inhibited miR-5095, which targeted the 3' UTR of CTNNB1 mRNA and subsequently downregulated the Wnt/β-catenin signaling pathway in GBM. Using rescue experiments, we demonstrated that SNHG7 promoted the proliferation, migration and invasion of GBM cells through the inhibition of miR-5095 and concomitant activation of Wnt/β-catenin signaling pathway. Taken together, the SNHG7/miR-5095 axis might be a potential target for the development of effective GBM therapy.

The long non-coding RNA uc.4 influences cell differentiation through the TGF-beta signaling pathway

In a previous study, we screened thousands of long non-coding RNAs (lncRNAs) to assess their potential relationship with congenital heart disease (CHD). In this study, uc.4 attracted our attention because of its high level of evolutionary conservation and its antisense orientation to the CASZ1 gene, which is vital for heart development. We explored the function of uc.4 in cells and in zebrafish, and describe a potential mechanism of action. P19 cells were used to investigate the function of uc.4. We studied the effect of uc.4 overexpression on heart development in zebrafish. The overexpression of uc.4 influenced cell differentiation by inhibiting the TGF-beta signaling pathway and suppressed heart development in zebrafish, resulting in cardiac malformation. Taken together, our findings show that uc.4 is involved in heart development, thus providing a potential therapeutic target for CHD.