A long non-coding RNA signature in glioblastoma multiforme predicts survival

Innovative perspectives on glioblastoma: the emerging role of long non-coding RNAs

Glioblastoma (GBM) is a highly aggressive and treatment-resistant brain tumor. Recent advancements have highlighted the crucial role of long noncoding RNAs (lncRNAs) in GBM's molecular biology. Unlike protein-coding RNAs, lncRNAs regulate gene expression through transcription, post-transcriptional modifications, and chromatin remodeling. Some lncRNAs, like HOTAIR, CCAT2, CRNDE, and MALAT1, promote GBM development by affecting tumor suppressors and various signaling pathways like PI3K/Akt, mTOR, EGFR, NF-κB, and Wnt/β-catenin. Conversely, certain lncRNAs such as TUG1, MEG3, and GAS8-AS1 act as tumor suppressors and are associated with better prognosis. The study presented in the manuscript aims to explore the involvement of lncRNAs in GBM, focusing on their roles in tumor progression, proliferation, invasion, and potential implications for early detection and immunotherapy. The research seeks to elucidate the mechanisms by which specific lncRNAs influence GBM characteristics and highlight their potential as therapeutic targets or biomarkers in managing this aggressive form of brain cancer.

Expression and clinical significance of lncRNA PART1 in patients with unexplained recurrent pregnancy loss

PURPOSE

Previous studies have reported the involvement of long noncoding RNAs (lncRNAs) in reproductive diseases via the regulation of target genes. This study aimed to determine whether lnc-prostate androgen-regulated transcript 1 (lnc-PART1)could be used as a biomarker of unexplained recurrent pregnancy loss (URPL) and a possible predictor of poor pregnancy outcomes in women with URPL.

MATERIALS AND METHODS

Sixty patients with URPL and 15 healthy women were included in this study. PART1 expression was detected in plasma and endometrial tissues using a quantitative reverse transcription polymerase chain reaction. Logistic regression and receiver operating characteristic curve analyses were performed to analyze the association between PART1 expression and pregnancy outcomes in women with URPL.

RESULTS

The expression of PART1transcript variant 2 was significantly up-regulated in the endometrial specimens from patients with URPL compared to control tissues. High tissue expression levels of PART1transcript variant 2 were associated with poor pregnancy outcomes in women with URPL, indicating that it could serve as a potential risk factor. Additionally, PART1 could serve as a potential risk factor for adverse pregnancy outcomes in patients with URPL (OR = 4.374; 95% CI = 1.052-18.189; p = .042).

CONCLUSION

lncRNA PART1 transcript variant 2 was highly expressed in patients with URPL. Therefore, it is important to conduct in-depth studies on the relationship between PART1 expression and URPL.

MIAT promotes myofibroblastic activities and transformation in oral submucous fibrosis through sponging the miR-342-3p/SOX6 axis

Oral submucous fibrosis (OSF) is an oral potentially malignant disorder that is closely related to the habit of areca nut chewing. Long non-coding RNA (lncRNA) myocardial infarction-associated transcript (MIAT) has been identified as an essential regulator in the fibrosis progression. However, the role of MIAT in the development of OSF remains unknown. The transcriptomic profile showed that MIAT is significantly overexpressed in the OSF cohort, with a positive correlation to fibrotic markers. The silencing of MIAT expression in primary buccal mucosal fibroblasts (BMFs) markedly inhibited arecoline-induced myofibroblast transformation. Mechanistically, MIAT functioned as a miR-342-3p sponge and suppressed the inhibitory effect of miR-342-3p on SOX6 mRNA, thereby reinstating SOX6 expression. Subsequent RNA expression rescue experiments confirmed that MIAT enhanced resistance to apoptosis and facilitated myofibroblastic properties such as cell mobility and collagen gel contraction by regulating the miR-342-3p/SOX6 axis. Taken together, these results suggest that the abnormal upregulation of MIAT is important in contributing persistent activation of myofibroblasts in fibrotic tissue, which may result from prolonged exposure to the constituents of areca nut. Furthermore, our findings demonstrated that therapeutic avenues that target the MIAT/miR-342-3p/SOX6 axis may be a promising approach for OSF treatments.

Exploring the prognostic value and biological pathways of transcriptomics and radiomics patterns in glioblastoma multiforme

OBJECTIVES

To develop a multi-omics prognostic model integrating transcriptomics and radiomics for predicting overall survival in patients with glioblastoma multiforme (GBM), and investigate the biological pathways of radiomics patterns.

MATERIALS AND METHODS

Transcription profiles of GBM patients and normal controls were used to obtain differentially expressed mRNAs and long non-coding RNAs (lncRNAs). Radiomics features were extracted from magnetic resonance imaging (MRI). Least absolute shrinkage and selection operator (LASSO) Cox regression was employed to select survival-associated features for the construction of transcriptomics and radiomics signatures. Genes associated with GBM prognosis were identified through the analysis of lncRNA-mRNA co-expression networks and Weighted Gene Co-expression Network Analysis (WGCNA), and their biological pathways were investigated using Genomes enrichment analysis. Transcriptomics, radiomics, and clinical data were integrated to evaluate the multi-omics prognostic model's performance.

RESULTS

LASSO Cox regression yielded 21 survival-related features, including 19 transcriptomics features and 2 radiomics features. Based on transcriptomics and radiomics signature, GBM patients were classified as high-risk or low-risk. The genes obtained from the co-expression network screen were associated with microtubule binding, while those from the WGCNA screen were associated with growth factor receptor binding. In the training set, the AUC values for the multi-omics model and clinical model were 0.964 and 0.830, respectively, while in the validation set, they were 0.907 and 0.787. The multi-omics prognostic model outperformed the clinical prognostic model.

CONCLUSIONS

The co-expression network and WGCNA methods revealed genes associated with multiple biological pathways in GBM. The multi-omics prognostic model demonstrated excellent performance and indicated significant potential for clinical application.

LncRNA PART1 promotes malignant biological behaviours associated with head and neck cancer cells via synergistic action with FUT6

The aim of this study was to determine the role of lncRNA PART1 and downstream FUT6 in tumorigenesis and progression of head and neck cancer (HNC). Bioinformatics analysis and qRT-PCR revealed that lncRNA PART1 was expressed at low levels in HNC patients. The proliferation, apoptosis, migration and flow cytometry results showed that low expression of lncRNA PART1 inhibited apoptosis and promoted HNC cell migration and proliferation. In addition, animal experiments have also shown that low expression of lncRNA PART1 can promote tumor growth. LncRNA PART1 overexpression promoted apoptosis and inhibited HNC cell migration and proliferation. Through bioinformatics analysis, FUT6 was found to be expressed at low levels in HNC and to be correlated with patient survival. Immunohistochemical and qRT-PCR results revealed that FUT6 was underexpressed in tumour tissues and HNC cells. Cell and animal experiments showed that overexpression of FUT6 could inhibit tumour proliferation and migration. Bioinformatics analysis revealed that lncRNA PART1 was positively correlated with FUT6. By qRT-PCR and western blot, we observed that after knockdown of lncRNA PART1, both the mRNA and protein expression levels of FUT6 were reduced. The above results indicated that lncRNA PART1 and FUT6 play an important role in HNC, and that lncRNA PART1 affected the development of tumor by downstream FUT6.

Long noncoding RNA UNC5B-AS1 suppresses cell proliferation by sponging miR-24-3p in glioblastoma multiforme

BACKGROUND

Glioblastoma multiforme (GBM) is the most common primary CNS tumor, characterized by high mortality and heterogeneity. However, the related lncRNA signatures and their target microRNA (miRNA) for GBM are still mostly unknown. Therefore, it is critical that we discover lncRNA markers in GBM and their biological activities.

MATERIALS AND METHODS

GBM-related RNA-seq data were obtained from the Cancer Genome Atlas (TCGA) database. The "edger" R package was used for differently expressed lncRNAs (DELs) identification. Then, we forecasted prospective miRNAs that might bind to lncRNAs by Cytoscape software. Survival analysis of those miRNAs was examined by the starBase database, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the miRNAs' target genes was conducted by the Gene Set Enrichment Analysis (GSEA) database and R software. Moreover, the proliferative ability of unc-5 netrin receptor B antisense RNA 1 (UNC5B-AS1) cells was evaluated by Cell Counting Kit-8 (CCK-8) analysis. Mechanistically, the regulatory interaction between UNC5B-AS1 and miRNA in GBM biological processes was studied using CCK-8 analysis.

RESULTS

Our results indicated that overexpression of UNC5B-AS1 has been shown to suppress GBM cell growth. Mechanistically, miR-24-3p in GBM was able to alleviate the anti-oncogenic effects of UNC5B-AS1 on cell proliferation.

CONCLUSION

The discovery of the novel UNC5B-AS1-miR-24-3p network suggests possible lncRNA and miRNA roles in the development of GBM, which may have significant ramifications for the analysis of clinical prognosis and the development of GBM medications.

Immune-related lncRNAs signature and radiomics signature predict the prognosis and immune microenvironment of glioblastoma multiforme

BACKGROUND

Glioblastoma multiforme (GBM) is the most common primary malignant brain tumor in adults. This study aimed to construct immune-related long non-coding RNAs (lncRNAs) signature and radiomics signature to probe the prognosis and immune infiltration of GBM patients.

METHODS

We downloaded GBM RNA-seq data and clinical information from The Cancer Genome Atlas (TCGA) project database, and MRI data were obtained from The Cancer Imaging Archive (TCIA). Then, we conducted a cox regression analysis to establish the immune-related lncRNAs signature and radiomics signature. Afterward, we employed a gene set enrichment analysis (GSEA) to explore the biological processes and pathways. Besides, we used CIBERSORT to estimate the abundance of tumor-infiltrating immune cells (TIICs). Furthermore, we investigated the relationship between the immune-related lncRNAs signature, radiomics signature and immune checkpoint genes. Finally, we constructed a multifactors prognostic model and compared it with the clinical prognostic model.

RESULTS

We identified four immune-related lncRNAs and two radiomics features, which show the ability to stratify patients into high-risk and low-risk groups with significantly different survival rates. The risk score curves and Kaplan-Meier curves confirmed that the immune-related lncRNAs signature and radiomics signature were a novel independent prognostic factor in GBM patients. The GSEA suggested that the immune-related lncRNAs signature were involved in L1 cell adhesion molecular (L1CAM) interactions and the radiomics signature were involved signaling by Robo receptors. Besides, the two signatures was associated with the infiltration of immune cells. Furthermore, they were linked with the expression of critical immune genes and could predict immunotherapy's clinical response. Finally, the area under the curve (AUC) (0.890,0.887) and C-index (0.737,0.817) of the multifactors prognostic model were greater than those of the clinical prognostic model in both the training and validation sets, indicated significantly improved discrimination.

CONCLUSIONS

We identified the immune-related lncRNAs signature and tradiomics signature that can predict the outcomes, immune cell infiltration, and immunotherapy response in patients with GBM.

The role and clinical relevance of long non-coding RNAs in glioma

Glioma represents a complex and heterogeneous disease, posing significant challenges to both clinicians and researchers. Despite notable advancements in glioma treatment, the overall survival rate for most glioma patients remains dishearteningly low. Hence, there is an urgent necessity to discover novel biomarkers and therapeutic targets specifically tailored for glioma. In recent years, long non-coding RNAs (lncRNAs) have emerged as pivotal regulators of gene expression and have garnered attention for their involvement in the development and progression of various cancers, including glioma. The dysregulation of lncRNAs plays a critical role in glioma pathogenesis and influences clinical outcomes. Consequently, there is growing interest in exploring the potential of lncRNAs as diagnostic and prognostic biomarkers, as well as therapeutic targets. By understanding the functions and dysregulation of lncRNAs in glioma, researchers aim to unlock new avenues for the development of innovative treatment strategies catered to glioma patients. The identification and thorough characterization of lncRNAs hold the promise of novel therapeutic approaches that could potentially improve patient outcomes and enhance the management of glioma, ultimately striving for better prospects and enhanced quality of life for those affected by this challenging disease. The primary objective of this paper is to comprehensively review the current state of knowledge regarding lncRNA biology and their intricate roles in glioma. It also delves into the potential of lncRNAs as valuable diagnostic and prognostic indicators and explores their feasibility as promising targets for therapeutic interventions.

Non-coding RNAs and glioma: Focus on cancer stem cells

Glioblastoma and gliomas can have a wide range of histopathologic subtypes. These heterogeneous histologic phenotypes originate from tumor cells with the distinct functions of tumorigenesis and self-renewal, called glioma stem cells (GSCs). GSCs are characterized based on multi-layered epigenetic mechanisms, which control the expression of many genes. This epigenetic regulatory mechanism is often based on functional non-coding RNAs (ncRNAs). ncRNAs have become increasingly important in the pathogenesis of human cancer and work as oncogenes or tumor suppressors to regulate carcinogenesis and progression. These RNAs by being involved in chromatin remodeling and modification, transcriptional regulation, and alternative splicing of pre-mRNA, as well as mRNA stability and protein translation, play a key role in tumor development and progression. Numerous studies have been performed to try to understand the dysregulation pattern of these ncRNAs in tumors and cancer stem cells (CSCs), which show robust differentiation and self-regeneration capacity. This review provides recent findings on the role of ncRNAs in glioma development and progression, particularly their effects on CSCs, thus accelerating the clinical implementation of ncRNAs as promising tumor biomarkers and therapeutic targets.

Prognostic utility of lncRNAs (LINC00565 and LINC00641) as molecular markers in glioblastoma multiforme (GBM)

Background and aim

Glioblastoma multiforme (GBM) is primary brain tumor grade IV characterized by fast cell proliferation, high mortality and morbidity and most lethal gliomas. Molecular approaches underlying its pathogenesis and progression with diagnostic and prognostic value have been an area of interest. Long-non coding RNAs (lncRNAs) aberrantly expressed in GBM have been recently studied. The aim is to investigate the clinical role of lncRNA565 and lncRNA641 in GBM patients.

Patients and methods

Blood samples were withdrawn from 35 newly diagnosed GBM cases with 15 healthy individuals, then lncRNA565 and lncRNA641 expression were evaluated using real time-PCR. Their diagnostic efficacy was detected using receiver operating characteristic curve. Progression free survival (PFS) and overall survival (OS) were studied using Kaplan–Meier curves.

Results

lncRNAs expressions were increased significantly among GBM as compared to control group. Their expressions were correlated with clinico-pathological data and survival pattern for the studied GBM patients. Higher levels of both lncRNAs were correlated to worse performance status. Expression of lncRNA565 was increased with large tumor size (≥ 5 cm). Survival analysis showed that both investigated lncRNA were increased with worse PFS and OS.

Conclusion

Expression of lncRNA565 and lncRNA641 in a liquid biopsy sample can be used as prognostic biomarker for GBM patients.

Crosstalk between lncRNAs in the apoptotic pathway and therapeutic targets in cancer

The assertion that a significant portion of the mammalian genome has not been translated and that non-coding RNA accounts for over half of polyadenylate RNA have received much attention. In recent years, increasing evidence proposes non-coding RNAs (ncRNAs) as new regulators of various cellular processes, including cancer progression and nerve damage. Apoptosis is a type of programmed cell death critical for homeostasis and tissue development. Cancer cells often have inhibited apoptotic pathways. It has recently been demonstrated that up/down-regulation of various lncRNAs in certain types of tumors shapes cancer cells' response to apoptotic stimuli. This review discusses the most recent studies on lncRNAs and apoptosis in healthy and cancer cells. In addition, the role of lncRNAs as novel targets for cancer therapy is reviewed here. Finally, since it has been shown that lncRNA expression is associated with specific types of cancer, the potential for using lncRNAs as biomarkers is also discussed.

PART1 destabilized by NOVA2 regulates blood-brain barrier permeability in endothelial cells via STAU1-mediated mRNA degradation

Blood-brain barrier dysfunction is recognized as a precursor of Alzheimer's disease development. Endothelial cells as structural basis of blood-brain barrier were observed tight junction failure in amyloid-β(1-42)-stimulated environment. In this study, we found NOVA2, PPP2R3A were down-regulated while PART1, p-NFκB-p65 were up-regulated in amyloid-β(1-42)-incubated endothelial cells. Knockdown of either NOVA2 or PPP2R3A and overexpression of PART1 all increased blood-brain barrier permeability. Lower blood-brain barrier permeability was observed in overexpression of NOVA2 and PPP2R3A and knockdown of PART1 and NFκB-p65. Same tendencies were found in the tight junction-related proteins expressions. Furthermore, overexpression and knockdown of NOVA2 and PART1 had no effect on cell viability. Mechanistically, NOVA2 overexpression was confirmed to reduce half-life of PART1. PART1 could destabilize PPP2R3A messenger RNA (mRNA) by interacting with STAU1. In addition, p-NFκB-p65 functioning as transcription factor reduced the expression of tight junction-related proteins, which was prompted by low protein level of PPP2R3A. Our study highlights the crucial role of NOVA2/PART1/PPP2R3A/p-NFκB-p65 pathway in amyloid-β(1-42)-incubated endothelial cells to modulating blood-brain barrier permeability through STAU1-mediated messenger RNA degradation, implying a potential mechanism of lncRNA and protein interaction in pathogenesis of Alzheimer's disease.

A seven-lncRNA signature for predicting prognosis in breast carcinoma

Background

Long non-coding RNAs (lncRNAs) play an important part in tumorigenesis and cancer metastasis and can serve as a potential biosignature for cancer prognosis. However, the use of lncRNA signatures to predict survival in breast carcinoma is yet unreported.

Methods

The lncRNA expression profiles and homologous clinical data of 913 breast carcinoma samples from the Cancer Genome Atlas (TCGA), were analyzed to obtain 2,547 differentially expressed lncRNAs. Univariate Cox proportional risk regression was applied to both the training and testing datasets to screen the common prognostic lncRNAs. Potential prognostic LncRNAs were screened by multivariate Cox proportional risk regression in the training data set of the selected LncRNAs.

Results

Seven lncRNAs (LINC02037, MAPT-AS1, RP1-37C10.3, RP11-344E13.4, RP11-454P21.1, RP11-616M22.1, SPACA6P-AS) were prominently associated with overall survival. Kaplan-Meier analysis and receiver operating characteristic (ROC) curves indicated that these indicators were sensitive and specific for survival prediction. The areas under the ROC curve of the seven-lncRNA signature in predicting 3- and 5-year survival rates were 0.771 and 0.780 respectively in the combined cohort. Furthermore, enrichment analysis revealed that these seven lncRNAs might participate multiple pathways related to tumorigenesis and prognosis.

Conclusions

The proposed seven-lncRNA signature could serve as a latent prognostic biomarker for survival prediction in patients with breast carcinoma.

Long non-coding RNA FAM66C regulates glioma growth via the miRNA/LATS1 signaling pathway

Glioma is one of the most common primary intracranial carcinomas and typically associated with a dismal prognosis and poor quality of life. The identification of novel oncogenes is clinically valuable for early screening and prevention. Recently, the studies have revealed that long non-coding RNAs (lncRNAs) play important roles in the development and progression of cancers including glioma. The expression of lncRNA FAM66C is reduced in glioma cell lines and clinical samples compared to non-tumor samples. Knockdown of FAM66C in U87 and U251 cells significantly promoted cell proliferation and migration, respectively. Furthermore, the correlation between FAM66C and Hippo pathway regulators YAP1 and LATS1, along with the alteration of their protein expression level indicated that FAM66C regulated cell growth through this pathway. Moreover, luciferase assay demonstrated that another two noncoding RNAs, miR15a/miR15b, directly bonded to the 3'UTR of LATS1 to facilitated its transcriptional expression and inhibited cell growth. In addition, the luciferase activity of FAM66C was block by miR15a/miR15b, and the promotion of cell growth effects caused by FAM66C deficiency was attenuated by miR15a/miR15b mimics, further proved that FAM66C functioned as a competing endogenous RNA to regulate glioma growth via the miRNA/LATS1 signaling pathway.

A Novel Prognostic Prediction Model for Colorectal Cancer Based on Nine Autophagy-Related Long Noncoding RNAs

Introduction

Colorectal cancer (CRC) is the most common gastrointestinal cancer and has a low overall survival rate. Tumor–node–metastasis staging alone is insufficient to predict patient prognosis. Autophagy and long noncoding RNAs play important roles in regulating the biological behavior of CRC. Therefore, establishing an autophagy-related lncRNA (ARlncRNA)-based bioinformatics model is important for predicting survival and facilitating clinical treatment.

Methods

CRC data were retrieved from The Cancer Genome Atlas. The database was randomly divided into train set and validation set; then, univariate and multivariate Cox regression analyses were performed to screen prognosis-related ARlncRNAs for prediction model construction. Interactive network and Sankey diagrams of ARlncRNAs and messenger RNAs were plotted. We analyzed the survival rate of high- and low-risk patients and plotted survival curves and determined whether the risk score was an independent predictor of CRC. Receiver operating characteristic curves were used to evaluate model sensitivity and specificity. Then, the expression level of lncRNA was detected by quantitative real-time polymerase chain reaction, and the location of lncRNA was observed by fluorescence in situ hybridization. Additionally, the protein expression was detected by Western blot.

Results

A prognostic prediction model of CRC was built based on nine ARlncRNAs (NKILA, LINC00174, AC008760.1, LINC02041, PCAT6, AC156455.1, LINC01503, LINC00957, and CD27-AS1). The 5-year overall survival rate was significantly lower in the high-risk group than in the low-risk group among train set, validation set, and all patients (all p < 0.001). The model had high sensitivity and accuracy in predicting the 1-year overall survival rate (area under the curve = 0.717). The prediction model risk score was an independent predictor of CRC. LINC00174 and NKILA were expressed in the nucleus and cytoplasm of normal colonic epithelial cell line NCM460 and colorectal cancer cell lines HT29. Additionally, LINC00174 and NKILA were overexpressed in HT29 compared with NCM460. After autophagy activation, LINCC00174 expression was significantly downregulated both in NCM460 and HT29, while NKILA expression was significantly increased.

Conclusion

The new ARlncRNA-based model predicts CRC patient prognosis and provides new research ideas regarding potential mechanisms regulating the biological behavior of CRC. ARlncRNAs may play important roles in personalized cancer treatment.

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.

Exosomal noncoding RNAs: key players in glioblastoma drug resistance

Glioma, as one of the most severe human malignancies, is defined as the Central Nervous System's (CNS) tumors. Glioblastoma (GBM) in this regard, is the most malignant type of gliomas. There are multiple therapeutic strategies to cure GBM, for which chemotherapy is often the first-line treatment. Still, various cellular processes, such as uncontrolled proliferation, invasion and metastasis, may disturb the treatment efficacy. Drug resistance is another process in this way, which can also cause undesirable effects. Thereupon, identifying the mechanisms, involved in developing drug resistance and the relevant mechanisms can be very helpful in GBM management. The discovery of exosomal non-coding RNAs (ncRNAs), RNA molecules that can be transferred between the cells and different tissues using the exosomes, was a milestone in this regard. It has been revealed that the key exosomal ncRNAs, including circular RNAs, microRNAs, and long ncRNAs, are able to modulate GBM drug resistance through different signaling pathways or by affecting regulatory proteins and their corresponding genes. Nowadays, researchers are trying to overcome the limitations of chemotherapy by targeting these RNA molecules. Accordingly, this review aims to clarify the substantial roles of exosomal ncRNAs in GBM drug resistance and involved mechanisms.

Large-Scale Transcriptomics-Driven Approach Revealed Overexpression of CRNDE as a Poor Survival Prognosis Biomarker in Glioblastoma

Glioblastoma is the most common and malignant brain malignancy worldwide, with a 10-year survival of only 0.7%. Aggressive multimodal treatment is not enough to increase life expectancy and provide good quality of life for glioblastoma patients. In addition, despite decades of research, there are no established biomarkers for early disease diagnosis and monitoring of patient response to treatment. High throughput sequencing technologies allow for the identification of unique molecules from large clinically annotated datasets. Thus, the aim of our study was to identify significant molecular changes between short- and long-term glioblastoma survivors by transcriptome RNA sequencing profiling, followed by differential pathway-activation-level analysis. We used data from the publicly available repositories The Cancer Genome Atlas (TCGA; number of annotated cases = 135) and Chinese Glioma Genome Atlas (CGGA; number of annotated cases = 218), and experimental clinically annotated glioblastoma tissue samples from the Institute of Pathology, Faculty of Medicine in Ljubljana corresponding to 2-58 months overall survival (n = 16). We found one differential gene for long noncoding RNA CRNDE whose overexpression showed correlation to poor patient OS. Moreover, we identified overlapping sets of congruently regulated differential genes involved in cell growth, division, and migration, structure and dynamics of extracellular matrix, DNA methylation, and regulation through noncoding RNAs. Gene ontology analysis can provide additional information about the function of protein- and nonprotein-coding genes of interest and the processes in which they are involved. In the future, this can shape the design of more targeted therapeutic approaches.

GLIDR promotes the progression of glioma by regulating the miR-4677-3p/MAGI2 axis

Gliomas are the most common and fatal primary brain tumors. Growing evidence suggests that long non-coding RNAs (lncRNAs) constitute novel and potential therapeutic targets for glioma. However, the biological role of glioblastoma down-regulated RNA (GLIDR) in glioma remains largely elusive. In the current study, we used quantitative real-time polymerase chain reaction (qRT-PCR) to detect GLIDR expression in glioma cells. Cell counting kit 8 (CCK-8) assay, colony formation assay, JC-1 staining, and flow cytometry were used to evaluate the role of GLIDR in proliferation and apoptosis of glioma cells. Western blotting was performed to assess the effect of GLIDR on the level of apoptosis-related proteins. In addition, bioinformatics prediction, RNA immunoprecipitation (RIP), RNA pull-down, and luciferase reporter gene assays were used to study the regulatory mechanisms of GLIDR in glioma. GLIDR was found to be highly expressed in glioma cells and silencing of GLIDR inhibited cell proliferation and promoted apoptosis. Functionally, GLIDR bound to miR-4677-3p that directly targeted membrane-associated guanylate kinase, WW, and PDZ domain-containing protein 2 (MAGI2). Our data showed that GLIDR affects the proliferation and apoptosis of glioma cells by targeting miR-4677-3p to regulate the expression of MAGI2. In conclusion, our study determined the oncogenic role of GLIDR in glioma, which may provide a new perspective for the treatment of glioma.

The Roles Played by Long Non-Coding RNAs in Glioma Resistance

Glioma originates in the central nervous system and is classified based on both histological features and molecular genetic characteristics. Long non-coding RNAs (lncRNAs) are longer than 200 nucleotides and are known to regulate tumorigenesis and tumor progression, and even confer therapeutic resistance to glioma cells. Since oncogenic lncRNAs have been frequently upregulated to promote cell proliferation, migration, and invasion in glioma cells, while tumor-suppressive lncRNAs responsible for the inhibition of apoptosis and decrease in therapeutic sensitivity in glioma cells have been generally downregulated, the dysregulation of lncRNAs affects many features of glioma patients, and the expression profiles associated with these lncRNAs are needed to diagnose the disease stage and to determine suitable therapeutic strategies. Accumulating studies show that the orchestrations of oncogenic lncRNAs and tumor-suppressive lncRNAs in glioma cells result in signaling pathways that influence the pathogenesis and progression of glioma. Furthermore, several lncRNAs are related to the regulation of therapeutic sensitivity in existing anticancer therapies, including radiotherapy, chemotherapy and immunotherapy. Consequently, we undertook this review to improve the understanding of signaling pathways influenced by lncRNAs in glioma and how lncRNAs affect therapeutic resistance.

LncRNA PART1 Promotes Proliferation and Migration, Is Associated with Cancer Stem Cells, and Alters the miRNA Landscape in Triple-Negative Breast Cancer

Triple-negative breast cancers (TNBCs) are aggressive, lack targeted therapies and are enriched in cancer stem cells (CSCs). Novel therapies which target CSCs within these tumors would likely lead to improved outcomes for TNBC patients. Long non-coding RNAs (lncRNAs) are potential therapeutic targets for TNBC and CSCs. We demonstrate that lncRNA prostate androgen regulated transcript 1 (PART1) is enriched in TNBCs and in Aldefluor^high CSCs, and is associated with worse outcomes among basal-like breast cancer patients. Although PART1 is androgen inducible in breast cancer cells, analysis of patient tumors indicates its androgen regulation has minimal clinical impact. Knockdown of PART1 in TNBC cell lines and a patient-derived xenograft decreased cell proliferation, migration, tumor growth, and mammosphere formation potential. Transcriptome analyses revealed that the lncRNA affects expression of hundreds of genes (e.g., myosin-Va, MYO5A; zinc fingers and homeoboxes protein 2, ZHX2). MiRNA 4.0 GeneChip and TaqMan assays identified multiple miRNAs that are regulated by cytoplasmic PART1, including miR-190a-3p, miR-937-5p, miR-22-5p, miR-30b-3p, and miR-6870-5p. We confirmed the novel interaction between PART1 and miR-937-5p. In general, miRNAs altered by PART1 were less abundant than PART1, potentially leading to cell line-specific effects in terms miRNA-PART1 interactions and gene regulation. Together, the altered miRNA landscape induced by PART1 explains most of the protein-coding gene regulation changes (e.g., MYO5A) induced by PART1 in TNBC.

Construction and analysis of a ceRNA network and patterns of immune infiltration in bladder cancer

Background

Bladder cancer (BC) is the ninth most common malignant tumor, accounting for an estimate of 549,000 new BC cases and 200,000 BC-related deaths worldwide in 2018. The prognosis of BC has not substantially improved despite significant advances in the diagnosis and treatment of the disease.

Methods

The RNA sequencing (RNA-seq) data and clinical information of BC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) algorithm was used to assess immune infiltration. The survival analyses were performed using the selected components of a ceRNA network and selected immune cell types by least absolute shrinkage and selection operator (LASSO) Cox regression to calculate the risk score. The accuracy of prognosis prediction was determined by receiver operating characteristic (ROC) curves, survival curves, and nomograms. Finally, the correlation analysis was performed to investigate the relationships between the signature components of the ceRNA network and the immune cell signature.

Results

Two completed survival analyses included selected components of the ceRNA network (ELN, SREBF1, DSC2, TTLL7, DIP2C, SATB1, hsa-miR-20a-5p, and hsa-miR-29c-3p) and selected immune cell types (M0 macrophages, M2 macrophages, resting mast cells, and neutrophils). ROC curves, survival curves (all P values <0.05), nomograms, and calibration curves indicated that the accuracy of the two survival analyses was acceptable. Moreover, the correlations between TTLL7 and resting mast cells (R=0.24, P<0.001), DSC2 and resting mast cells (R=−0.23, P<0.001), ELN and resting mast cells (R=0.44, P<0.001), and hsa-miR-29c-3p and M0 macrophages (R=−0.29, P<0.001) were significant, indicating that interactions of these factors may play significant roles in the prognosis of BC.

Conclusions

TTLL7, DSC2, ELN, hsa-miR-29c-3p, resting mast cells, and M0 macrophages may play an important role in the development of BC. However, additional studies are needed to confirm this hypothesis.

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.

Exploration of Prognostic Biomarkers for Lung Adenocarcinoma Through Bioinformatics Analysis

With the development of computer technology, screening cancer biomarkers based on public databases has become a common research method. Here, an eight-gene prognostic model, which could be used to judge the prognosis of patients with lung adenocarcinoma (LUAD), was developed through bioinformatics methods. This study firstly used several gene datasets from GEO database to mine differentially expressed genes (DEGs) in LUAD tissue and healthy tissue via joint analysis. Later, enrichment analysis for the DEGs was performed, and it was found that the DEGs were mainly activated in pathways involved in extracellular matrix, cell adhesion, and leukocyte migration. Afterward, a TCGA cohort was used to perform univariate Cox, least absolute shrinkage and selection operator method, and multivariate Cox regression analyses for the DEGs, and a prognostic model consisting of eight genes (GPX3, TCN1, ASPM, PCP4, CAV2, S100P, COL1A1, and SPOK2) was established. Receiver operation characteristic (ROC) curve was then used to substantiate the diagnostic efficacy of the prognostic model. The survival significance of signature genes was verified through the GEPIA database, and the results exhibited that the risk coefficients of the eight genes were basically congruous with the effects of these genes on the prognosis in the GEPIA database, which suggested that the results were accurate. Finally, combined with clinical characteristics of patients, the diagnostic independence of the prognostic model was further validated through univariate and multivariate regression, and the results indicated that the model had independent prognostic value. The overall finding of the study manifested that the eight-gene prognostic model is closely related to the prognosis of LUAD patients, and can be used as an independent prognostic indicator. Additionally, the prognostic model in this study can help doctors make a better diagnosis in treatment and ultimately benefit LUAD patients.

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.

Immune-Related Long Non-coding RNA Signature and Clinical Nomogram to Evaluate Survival of Patients Suffering Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) turns out to be one of the most prevalent cancer types, leading to a relatively high mortality among worldwide sufferers. In this study, gene microarray data of ESCC patients were obtained from the GEO database, with the samples involved divided into a training set and a validation set. Based on the immune-related differential long non-coding RNAs (lncRNAs) we identified, a prognostic eight-lncRNA-based risk signature was constructed following regression analyses. Then, the predictive capacity of the model was evaluated in the training set and validation set using survival curves and receiver operation characteristic curves. In addition, univariate and multivariate regression analyses based on clinical information and the model-based risk score also demonstrated the ability of the risk score in independently determining the prognosis of patients. Besides, based on the CIBERSORT tool, the abundance of immune infiltrates in tumor samples was scored, and a significant difference was presented between the high- and low- risk groups. Correlation analysis with immune checkpoints (PD1, PDL1, and CTLA4) indicated that the eight-lncRNA signature–based risk score was negatively correlated with PD1 expression, suggesting that the eight-lncRNA signature may have an effect in immunotherapy for ESCC. Finally, GO annotation was performed for the differential mRNAs that were co-expressed with the eight lncRNAs, and it was uncovered that they were remarkably enriched in immune-related biological functions. These results suggested that the eight-lncRNA signature–based risk model could be employed as an independent biomarker for ESCC prognosis and might play a part in evaluating the response of ESCC to immunotherapy with immune checkpoint blockade.

A Five Immune-Related lncRNA Signature as a Prognostic Target for Glioblastoma

Background: A variety of regulatory approaches including immune modulation have been explored as approaches to either eradicate antitumor response or induce suppressive mechanism in the glioblastoma microenvironment. Thus, the study of immune-related long noncoding RNA (lncRNA) signature is of great value in the diagnosis, treatment, and prognosis of glioblastoma.

Methods: Glioblastoma samples with lncRNA sequencing and corresponding clinical data were acquired from the Cancer Genome Atlas (TCGA) database. Immune-lncRNAs co-expression networks were built to identify immune-related lncRNAs via Pearson correlation. Based on the median risk score acquired in the training set, we divided the samples into high- and low-risk groups and demonstrate the survival prediction ability of the immune-related lncRNA signature. Both principal component analysis (PCA) and gene set enrichment analysis (GSEA) were used for immune state analysis.

Results: A cohort of 151 glioblastoma samples and 730 immune-related genes were acquired in this study. A five immune-related lncRNA signature (AC046143.1, AC021054.1, AC080112.1, MIR222HG, and PRKCQ-AS1) was identified. Compared with patients in the high-risk group, patients in the low-risk group showed a longer overall survival (OS) in the training, validation, and entire TCGA set (p = 1.931e-05, p = 1.706e-02, and p = 3.397e-06, respectively). Additionally, the survival prediction ability of this lncRNA signature was independent of known clinical factors and molecular features. The area under the ROC curve (AUC) and stratified analyses were further performed to verify its optimal survival predictive potency. Of note, the high-and low-risk groups exhibited significantly distinct immune state according to the PCA and GSEA analyses.

Conclusions: Our study proposes that a five immune-related lncRNA signature can be utilized as a latent indicator of prognosis and potential therapeutic approach for glioblastoma.

Non-coding RNAs regulation of macrophage polarization in cancer

Noncoding RNA (ncRNA) transcripts that did not code proteins but regulate their functions were extensively studied for the last two decades and the plethora of discoveries have instigated scientists to investigate their dynamic roles in several diseases especially in cancer. However, there is much more to learn about the role of ncRNAs as drivers of malignant cell evolution in relation to macrophage polarization in the tumor microenvironment. At the initial stage of tumor development, macrophages have an important role in directing Go/No-go decisions to the promotion of tumor growth, immunosuppression, and angiogenesis. Tumor-associated macrophages behave differently as they are predominantly induced to be polarized into M2, a pro-tumorigenic type when recruited with the tumor tissue and thereby favoring the tumorigenesis. Polarization of macrophages into M1 or M2 subtypes plays a vital role in regulating tumor progression, metastasis, and clinical outcome, highlighting the importance of studying the factors driving this process. A substantial number of studies have demonstrated that ncRNAs are involved in the macrophage polarization based on their ability to drive M1 or M2 polarization and in this review we have described their functions and categorized them into oncogenes, tumor suppressors, Juggling tumor suppressors, and Juggling oncogenes.

Comprehensive Characterization of Alternative mRNA Splicing Events in Glioblastoma: Implications for Prognosis, Molecular Subtypes, and Immune Microenvironment Remodeling

Alternative splicing (AS) of pre-mRNA has been widely reported to be associated with the progression of malignant tumors. However, a systematic investigation into the prognostic value of AS events in glioblastoma (GBM) is urgently required. The gene expression profile and matched AS events data of GBM patients were obtained from The Cancer Genome Atlas Project (TCGA) and TCGA SpliceSeq database, respectively. 775 AS events were identified as prognostic factors using univariate Cox regression analysis. The least absolute shrinkage and selection operator (LASSO) cox model was performed to narrow down candidate AS events, and a risk score model based on several AS events were developed subsequently. The risk score-based signature was proved as an efficient predictor of overall survival and was closely related to the tumor purity and immunosuppression in GBM. Combined similarity network fusion and consensus clustering (SNF-CC) analysis revealed two distinct GBM subtypes based on the prognostic AS events, and the associations between this novel molecular classification and clinicopathological factors, immune cell infiltration, as well as immunogenic features were further explored. We also constructed a regulatory network to depict the potential mechanisms that how prognostic splicing factors (SFs) regulate splicing patterns in GBM. Finally, a nomogram incorporating AS events signature and other clinical-relevant covariates was built for clinical application. This comprehensive analysis highlights the potential implications for predicting prognosis and clinical management in GBM.

A 5-lncRNA Signature Associated with Smoking Predicts the Overall Survival of Patients with Muscle-Invasive Bladder Cancer

Increasing evidence demonstrated that noncoding RNA is abnormally expressed in cancer tissues and serves a vital role in tumorigenesis, tumor development, and metastasis. The aim of the present study was to determine an lncRNA signature in order to predict the overall survival (OS) of patients with muscle-invasive bladder cancer (MIBC). A total of 246 patients with pathologically confirmed MIBC in The Cancer Genome Atlas (TCGA) dataset were recruited and included in the present study. We choose patients who have smoked less (including never smoking) or more than 15 years. A total of 44 differentially expressed lncRNAs were identified with a fold change larger than 1.5 and a P value < 0.05 through the limma package. Subsequently, a comparison between patients with no tobacco smoke exposure for <15 years and patients who had been exposed to tobacco smoke for >15 years was performed by using the matchIt package. Among the 44 differentially expressed lncRNAs, 5 lncRNAs were identified to be significantly associated with OS. Based on the characteristic risk scores of these 5 lncRNAs, patients were divided into low-risk and high-risk groups and exhibited significant differences in OS. Multivariate Cox regression analysis demonstrated that the 5-lncRNA signature was independent of age, tumor-node metastasis (TNM) staging, lymphatic node status, and adjuvant postoperative radiotherapy. In the present study, a novel 5-lncRNA signature was developed and was demonstrated to be useful in predicting the survival of patients with MIBC. If validated, this lncRNA signature may assist in the selection of a high-risk subpopulation that requires more aggressive therapeutic intervention. The risk scores involved in several associated pathways were identified using gene set enrichment analysis (GSEA). However, the clinical implications and mechanism of these 5 lncRNAs require further investigation.

If Artificial In Vitro Microenvironment Can Influence Tumor Drug Resistance Network via Modulation of lncRNA Expression?-Comparative Analysis of Glioblastoma-Derived Cell Culture Models and Initial Tumors In Vivo

The tumor resistance of glioblastoma cells in vivo is thought to be enhanced by their heterogeneity and plasticity, which are extremely difficult to curb in vitro. The external microenvironment shapes the molecular profile of tumor culture models, thus influencing potential therapy response. Our study examines the expression profile of selected lncRNAs involved in tumor resistance network in three different glioblastoma-derived models commonly utilized for testing drug response in vitro. Differential expression analysis revealed significant divergence in lncRNA profile between parental tumors and tumor-derived cell cultures in vitro, including the following particles: MALAT1, CASC2, H19, TUSC7, XIST, RP11-838N2.4, DLX6-AS1, GLIDR, MIR210HG, SOX2-OT. The examined lncRNAs influence the phenomenon of tumor resistance via their downstream target genes through a variety of processes: multi-drug resistance, epithelial-mesenchymal transition, autophagy, cell proliferation and viability, and DNA repair. A comparison of in vivo and in vitro expression identified differences in the levels of potential lncRNA targets, with the highest discrepancies detected for the MDR1, LRP1, BCRP and MRP1 genes. Co-expression analyses confirmed the following interrelations: MALAT1-TYMS, MALAT1-MRP5, H19-ZEB1, CASC2-VIM, CASC2-N-CAD; they additionally suggest the possibility of MALAT1-BCRP, MALAT1-mTOR and TUSC7-PTEN interconnections in glioblastoma. Although our results clearly demonstrate that the artificial ex vivo microenvironment changes the profile of lncRNAs related to tumor resistance, it is difficult to anticipate the final phenotypic effect, since this phenomenon is a complex one that involves a network of molecular interactions underlying a variety of cellular processes.

Development of an Autophagy Score Signature for Predicting Overall Survival in Papillary Renal Cell Carcinoma

Background

Autophagy is considered to be closely associated with cancer, functioning as either an anticancer or procancer mechanism depending on the cancer stage. However, the prognostic value of autophagy on papillary renal cell carcinoma (pRCC) remains unclear. In this study, our purpose was to determine the autophagy-related mRNA signature to predict the overall survival of patients with pRCC.

Materials and Methods

A total of 284 patients with pathologic confirmed pRCC in The Cancer Genome Atlas (TCGA) dataset were recruited and included. We choose patients who have smoked less than 15 years but staging 3 or 4 (including nontobacco exposure) vs. more than 15 years but staging 1 or 2. Fourteen differentially expressed mRNAs were found with fold change > 2 and P value < 0.001 through limma package after making a pair between nontobacco exposure or less than 15 years and tobacco exposure more than 15 years by matchIt package.

Results

Six mRNAs were identified to be significantly associated with overall survival. Then, using a risk score based on the signature of these six mRNAs, we divided the patients into low-risk and high-risk groups with significantly different OS. Further multivariate Cox regression analyses revealed that the 6-mRNA signature was independent of age, TNM stage, and tumor type. In the present study, a novel 6-mRNA signature that is useful in survival prediction in pRCC patients was developed. If validated, this mRNA signature might assist in selecting high-risk subpopulation that needs more aggressive therapeutic intervention. The risk score involved in several cancer-related pathways was identified using gene set enrichment analysis.

Conclusion

We initially generated a six autophagy-related genes' signature, which correlates with AJCC N stage, tumor type, and pathological stage and independently predicts OS.

Novel Molecular Markers in Glioblastoma-Benefits of Liquid Biopsy

Glioblastoma is a primary Central Nervous System (CNS) malignancy with poor survival. Treatment options are scarce and despite the extremely heterogeneous nature of the disease, clinicians lack prognostic and predictive markers to characterize patients with different outcomes. Certain immunohistochemistry, FISH, or PCR-based molecular markers, including isocitrate dehydrogenase1/2 (IDH1/2) mutations, epidermal growth factor receptor variant III (EGFRvIII) mutation, vascular endothelial growth factor overexpression (VEGF) overexpression, or (O6-Methylguanine-DNA methyltransferase promoter) MGMT promoter methylation status, are well-described; however, their clinical usefulness and accuracy is limited, and tumor tissue samples are always necessary. Liquid biopsy is a developing field of diagnostics and patient follow up in multiple types of cancer. Fragments of circulating nucleic acids are collected in various forms from different bodily fluids, including serum, urine, or cerebrospinal fluid in order to measure the quality and quantity of these markers. Multiple types of nucleic acids can be analyzed using liquid biopsy. Circulating cell-free DNA, mitochondrial DNA, or the more stable long and small non-coding RNAs, circular RNAs, or microRNAs can be identified and measured by novel PCR and next-generation sequencing-based methods. These markers can be used to detect the previously described alterations in a minimally invasive method. These markers can be used to differentiate patients with poor or better prognosis, or to identify patients who do not respond to therapy. Liquid biopsy can be used to detect recurrent disease, often earlier than using imaging modalities. Liquid biopsy is a rapidly developing field, and similarly to other types of cancer, measuring circulating tumor-derived nucleic acids from biological fluid samples could be the future of differential diagnostics, patient stratification, and follow up in the future in glioblastoma as well.

LncRNA PART1 Exerts Tumor-Suppressive Functions in Tongue Squamous Cell Carcinoma via miR-503-5p

Background

Tongue squamous cell carcinoma (TSCC) accounts for one-third of oral cancers. Previous studies had reported that lncRNA/miRNA regulated the biological behaviors of different cancer cells. However, the mechanisms of PART1 in regulating tumorigenesis and TSCC development via targeting miR-503-5p had not been studied.

Methods

The expressions of PART1 and miR-503-5p in tissues and cultured cell lines were detected by qRT-PCR. StarBase 3.0 was used to predict the binding sites of PART1, then dual-luciferase assay and RNA pull-down assay were executed to confirm whether miR-503-5p was a target of PART1. TSCC cells were co-transfected with PART1-overexpressed plasmid or miR-503-5p mimics in vitro, and the transfection efficiency was evaluated through qRT-PCR. Western blot was performed to assess the expressions of EMT-related proteins. CCK-8 and clone formation assays were conducted to detect cell proliferation, TUNEL assay was used to detect apoptosis, and transwell assay was executed to test migration and invasion.

Results

The low PART1 expression and high miR-503-5p expression were found in TSCC tissues and cell lines (CAL-27 and SCC9). PART1 expression was positively correlated with patients’ prognosis. The targeting and binding relationship between PART1 and miR-503-5p was confirmed, and overexpressed PART1 diminished the expression of miR-503-5p as well. Moreover, PART1 facilitated apoptosis, inhibited proliferation, invasion and migration of TSCC cells, and these influences were impeded by miR-503-5p overexpression.

Conclusion

LncRNA PART1 played a cancer-suppressing role in TSCC by targeting miR-503-5p, which provided a potential target for TSCC treatment.

RNA Interference Nanotherapeutics for Treatment of Glioblastoma Multiforme

Nucleic acid therapeutics for RNA interference (RNAi) are gaining attention in the treatment and management of several kinds of the so-called "undruggable" tumors via targeting specific molecular pathways or oncogenes. Synthetic ribonucleic acid (RNAs) oligonucleotides like siRNA, miRNA, shRNA, and lncRNA have shown potential as novel therapeutics. However, the delivery of such oligonucleotides is significantly hampered by their physiochemical (such as hydrophilicity, negative charge, and instability) and biopharmaceutical features (in vivo serum stability, fast renal clearance, interaction with extracellular proteins, and hindrance in cellular internalization) that markedly reduce their biological activity. Recently, several nanocarriers have evolved as suitable non-viral vectors for oligonucleotide delivery, which are known to either complex or conjugate with these oligonucleotides efficiently and also overcome the extracellular and intracellular barriers, thereby allowing access to the tumoral micro-environment for the better and desired outcome in glioblastoma multiforme (GBM). This Review focuses on the up-to-date advancements in the field of RNAi nanotherapeutics utilized for GBM treatment.

A lncRNA prognostic signature associated with immune infiltration and tumour mutation burden in breast cancer

Current studies have shown that long non-coding RNAs (lncRNAs) may serve as prognostic biomarkers in multiple cancers. Therefore, we postulated that expression patterns of multiple lncRNAs combined into a single signature could improve clinicopathological risk stratification and prediction of overall survival rate for breast cancer patients. Two algorithms, Least Absolute Shrinkage and Selector Operation (LASSO) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE), were used to select candidate lncRNAs. Univariate and multivariate Cox regression analyses were employed to construct a seven-lncRNA signature for breast cancer. Stratified analysis revealed that the signature was significantly associated with multiple clinicopathological risk factors. For clinical use, we developed a nomogram model to predict overall survival and odds of death for breast cancer patients. Single-sample gene set enrichment analysis (ssGSEA), CIBERSORT algorithm and ESTIMATE method were employed to assess the relative immune cell infiltrations of each sample. Differentially infiltration of immune cells and diverse tumour mutation burden (TMB) scores might give rise to the efficacy of lncRNA signature for predicting the overall survival of patients. Correlation analysis implied that LINC01215 was associated with multiple immune-related signalling pathways. A seven-lncRNA prognostic signature is a reliable tool to predict the prognosis of breast cancer patients.

Long non-coding RNA LPP-AS2 promotes glioma tumorigenesis via miR-7-5p/EGFR/PI3K/AKT/c-MYC feedback loop

Background

Glioblastoma is the most common primary malignant intracranial tumor with poor clinical prognosis in adults. Accumulating evidence indicates that long non-coding RNAs (lncRNAs) function as important regulators in cancer progression, including glioblastoma. Here, we identified a new lncRNA LPP antisense RNA-2 (LPP-AS2) and investigated its function and mechanism in the development of glioma.

Methods

High-throughput RNA sequencing was performed to discriminate differentially expressed lncRNAs and mRNAs between glioma tissues and normal brain tissues. Expression of LPP-AS2, epidermal growth factor receptor (EGFR) and miR-7-5p in glioma tissues and cell lines was detected by real-time quantitative PCR (RT-qPCR), and the functions of lncRNA LPP-AS2 in glioma were assessed by in vivo and in vitro assays. Insight into the underlying mechanism of competitive endogenous RNAs (ceRNAs) was obtained via bioinformatic analysis, dual luciferase reporter assays, RNA pulldown assays, RNA immunoprecipitation (RIP) and rescue experiments.

Results

The results of high-throughput RNA-seq indicated lncRNA LPP-AS2 was upregulated in glioma tissues and further confirmed by RT-qPCR. Higher LPP-AS2 expression was related to a poor prognosis in glioma patients. Based on functional studies, LPP-AS2 depletion inhibited glioma cell proliferation, invasion and promoted apoptosis in vitro and restrained tumor growth in vivo, overexpression of LPP-AS2 resulted in the opposite effects. In addition, LPP-AS2 and EGFR were observed in co-expression networks. LPP-AS2 was found to function as a ceRNA to regulate EGFR expression by sponging miR-7-5p in glioma cells. The result of chromatin immunoprecipitation (ChIP) assays validated that c-MYC binds directly to the promoter region of LPP-AS2. As a downstream protein of EGFR, c-MYC was modulated by LPP-AS2 and in turn enhanced LPP-AS2 expression. Thus, lncRNA LPP-AS2 promoted glioma tumorigenesis via a miR-7-5p/EGFR/PI3K/AKT/c-MYC feedback loop.

Conclusions

Our study elucidated that LPP-AS2 acted as an oncogene through a novel molecular pathway in glioma and might be a potential therapeutic approach for glioma diagnosis, therapy and prognosis.

Long noncoding RNA PART1 restrains aggressive gastric cancer through the epigenetic silencing of PDGFB via the PLZF-mediated recruitment of EZH2

Current reports refer to the role of long noncoding RNA (lncRNA) prostate androgen-regulated transcript 1 (PART1) as a tumor suppressor in some types of cancer but as an oncogene in other kinds of cancer. In gastric cancer, it had been reported to be downregulated. However, the clinical significance and underlying mechanism of PART1 function in gastric cancer remains undefined. Here, seven differential expression levels of noncoding RNAs (DE-lncRNAs) were screened from gastric cancer through a probe reannotation of a human exon array. PART1 was selected for further study because of its high fold change number. In our cohort, PART1 was identified as a significant downregulated lncRNA in gastric cancer tissues by qPCR and in situ hybridization (ISH), and its low expression was significantly correlated with postoperative metastasis and short overall survival time after surgery. Through the results of gain-of-function experiments, PART1 was confirmed as a tumor suppressor that can decrease not only cell viability, migration, and invasion in vitro but also tumorigenesis and tumor metastasis in vivo. Mechanistically, RNA pull-down and RNA-binding protein immunoprecipitation (RIP) showed that PART1 interacts with androgen receptor (AR), and then, promyelocytic leukemia zinc finger (PLZF) is upregulated in an androgen-independent manner. In a chain reaction, chromatin immunoprecipitation (ChIP) assay additionally illustrated that PLZF upregulation increased the enrichment of EZH2 and H3K27 trimethylation in the platelet-derived growth factor (PDGFB) promotor, thereby inhibition of PDGFB and the subsequent PDGFRβ/PI3K/Akt signaling pathway. Based on these findings, we showed PART1 plays a tumor suppressor role by promoting PLZF expression followed by recruitment of EZH2 to mediate epigenetic PDGFB silencing and downstream PI3K/Akt inhibition, suggesting that PART1 has a key role in restraining the aggressive ability of GC cells and providing a novel perspective on lncRNAs in GC progression.

Analyzing the lncRNA, miRNA, and mRNA-associated ceRNA networks to reveal potential prognostic biomarkers for glioblastoma multiforme

Background

Glioblastoma multiforme (GBM) is the most seriously brain tumor with extremely poor prognosis. Recent research has demonstrated that competitive endogenous RNA (ceRNA) network which long noncoding RNAs (lncRNAs) act as microRNA (miRNA) sponges to regulate mRNA expression were closely related to tumor development. However, the regulatory mechanisms and functional roles of ceRNA network in the pathogenesis of GBM are remaining poorly understood.

Methods

In this study, we systematically analyzed the expression profiles of lncRNA and mRNA (GSE51146 dataset) and miRNA (GSE65626 dataset) from GEO database. Then, we constructed a ceRNA network with the dysregulated genes by bioinformatics methods. The TCGA and GSE4290 dataset were used to confirm the expression and prognostic value of candidate mRNAs.

Results

In total, 3413 differentially expressed lncRNAs and mRNAs, 305 differentially expressed miRNAs were indentified in GBM samples. Then a ceRNA network containing 3 lncRNAs, 5 miRNAs, and 60 mRNAs was constructed. The overall survival analysis of TCGA databases indicated that two mRNAs (C1s and HSD3B7) were remarkly related with the prognosis of GBM.

Conclusion

The ceRNA network may increase our understanding to the pathogenesis of GBM. In general, the candidate mRNAs from the ceRNA network can be predicted as new therapeutic targets and prognostic biomarkers for GBM.

Molecular mechanisms of long non-coding RNAs in anaplastic thyroid cancer: a systematic review

BACKGROUND

anaplastic thyroid cancer (ATC) is one of the most lethal and aggressive cancers. Evidence has shown that the tumorigenesis of ATC is a multistep process involving the accumulation of genetic and epigenetic changes. Several studies have suggested that long non-coding RNAs (lncRNAs) may play an important role in the development and progression of ATC. In this article, we have collected the published reports about the role of lncRNAs in ATC.

METHODS

"Scopus", "Web of Science", "PubMed", "Embase", etc. were systematically searched for articles published since 1990 to 2020 in English language, using the predefined keywords.

RESULTS

961 papers were reviewed and finally 33 papers which fulfilled the inclusion and exclusion criteria were selected. Based on this systematic review, among a lot of evidences on examining the function of lncRNAs in thyroid cancer, there are only a small number of studies about the role of lncRNAs and their molecular mechanisms in the pathogenesis of ATC.

CONCLUSIONS

lncRNAs play a crucial role in regulation of different processes involved in the development and progression of ATC. Currently, just a few lncRNAs have been identified in ATC that may serve as prognosis markers such as GAS5, MIR22HG, and CASC2. Also, because of the dysregulation of Klhl14-AS, HOTAIRM1, and PCA3 during ATC development and progression, they may act as therapeutic targets. However, for most lncRNAs, only a single experiment has evaluated the expression profile in ATC tissues/cells. Therefore, further functional studies and expression profiling is needed to resolve this limitation and identify novel and valid biomarkers.

Identification of a Six-lncRNA Signature With Prognostic Value for Breast Cancer Patients

Breast cancer (BRCA) is the most common cancer and a major cause of death in women. Long non-coding RNAs (lncRNAs) are emerging as key regulators and have been implicated in carcinogenesis and prognosis. In this study, we aimed to develop a lncRNA signature of BRCA patients to improve risk stratification. In the training cohort (GSE21653, n = 232), 17 lncRNAs were identified by univariate Cox proportional hazards regression, which were significantly associated with patients’ survival. The least absolute shrinkage and selection operator-penalized Cox proportional hazards regression analysis was used to identify a six-lncRNA signature. According to the median of the signature risk score, patients were divided into a high-risk group and a low-risk group with significant disease-free survival differences in the training cohort. A similar phenomenon was observed in validation cohorts (GSE42568, n = 101; GSE20711, n = 87). The six-lncRNA signature remained as independent prognostic factors after adjusting for clinical factors in these two cohorts. Furthermore, this signature significantly predicted the survival of grade III patients and estrogen receptor-positive patients. Furthermore, in another cohort (GSE19615, n = 115), the low-risk patients that were treated with tamoxifen therapy had longer disease-free survival than those who underwent no therapy. Overall, the six-lncRNA signature can be a potential prognostic tool used to predict disease-free survival of patients and to predict the benefits of tamoxifen treatment in BRCA, which will be helpful in guiding individualized treatments for BRCA patients.

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.

Long non-coding RNA LINC01426 facilitates glioblastoma progression via sponging miR-345-3p and upregulation of VAMP8

Background

Long non-coding RNAs (lncRNAs) has been extensively reported play important roles in regulating the development and progression of cancers, including Glioblastoma (GBM). LINC01426 is a novel lncRNA that has been identified as an oncogenic gene in GBM. Herein, we attempted to elucidate the detailed functions and underlying mechanisms of LINC01426 in GBM.

Methods

LINC01426 expression in GBM cell lines and tissues were detected by quantitative real-time PCR (qRT-PCR). Cell Counting Kit-8 (CCK8) assays, colony formation assays, subcutaneous tumor formation assays were utilized to investigate the biological functions of LINC01426 in GBM. Dual-luciferase reporter assays, RNA immunoprecipitation (RIP) and bioinformatic analysis were performed to determine the underlying mechanisms.

Results

LINC01426 is up-regulated in malignant GBM tissues and cell lines and it is capable to promote GBM cell proliferation and growth. Mechanistically, LINC01426 serves as a molecular sponge to sequester the miR345-3p and thus enhancing the level of VAMP8, an oncogenic coding gene, to promote GBM progression.

Conclusions

Our results revealed the detailed mechanisms of LINC01426 facilitated cell proliferation and growth in GBM and report the clinical value of LINC01426 for GBM prognosis and treatment.

Long non-coding RNA NBAT1 inhibits the progression of glioma through the miR-21/SOX7 axis

Glioma is one of the most prevalent types of malignancy in the central nervous system worldwide, and the prognosis of patients with late stage glioma remains poor. Thus, the development of promising therapeutic strategies against glioma is essential. Long non-coding RNAs (lncRNAs) are functional RNA molecules involved in the initiation and progression of tumors, including glioma. Investigation on the regulatory roles of lncRNAs may facilitate the development of effective treatments. lncRNA NBAT1 is associated with the growth and metastasis of cancer; however, its underlying molecular mechanisms remain unknown. Thus, the present study aimed to investigate the effects of NBAT1 in glioma. The expression levels of NBAT1, microRNA (miRNA/miR)-21 and SOX7 in patients with glioma, and healthy donors using reverse transcription-quantitative PCR analysis. Human glioma cells (A172 and AM138) and normal astrocytes were used to establish the NBAT1-knockdown and overexpression models. Cell Counting Kit-8 and Transwell assays were performed to determine whether NBAT1 exerted effects on cell proliferation, migration and invasion. The results demonstrated that NBAT1 expression decreased in glioma tissues compared to normal samples. Additionally, downregulation of NBAT1 was detected in human glioma cells compared with normal astrocytes. Overexpression of NBAT1 inhibited glioma cell proliferation, migration and invasion. In addition, miR-21 was identified as a potential target of NBAT1, and the effects of miR-21-induced cell proliferation and metastasis were reversed following overexpression of NBAT1. Furthermore, SOX7 was predicted as the potential target of miR-21, and its expression was upregulated in glioma cells by overexpression of NBAT1 compared with the vehicle only control. Taken together, the results of the present study provide novel insight into the functions of NBAT1 in glioma, suggesting that the NBAT1/miR-21/SOX7 axis may act as a potential therapeutic target for the treatment of patients with glioma.

Coding of Glioblastoma Progression and Therapy Resistance through Long Noncoding RNAs

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.

Long non-coding RNA GAS5 in human cancer

Long non-coding RNAs (lncRNAs) constitute a group of >200-nucleotide ncRNA molecules. lncRNAs regulate several cell functions, such as proliferation, apoptosis, invasion and metastasis. Meanwhile, lncRNAs are abnormally expressed in human malignancies, where they suppress or promote tumor growth. The present study focused on growth arrest-specific transcript 5 (GAS5), a well-known lncRNA that acts as a tumor suppressor but is suppressed in multiple types of cancer, including mammary carcinoma, prostate cancer, colorectal cancer, gastric cancer, melanoma, esophageal squamous cell carcinoma, lung cancer, ovarian cancer, cervical cancer, gliomas, osteosarcoma, pancreatic cancer, bladder cancer, kidney cancer, papillary thyroid carcinoma, neuroblastoma, endometrial cancer and liver cancer. Notably, GAS5 is overexpressed in liver cancer, potentially functioning as an oncogene. In the present study, the diagnostic and therapeutic roles of GAS5 in different tumors were reviewed, with a summary of the potential clinical application of the lncRNA, which may help identify novel study directions for GAS5.

PWRN1 Suppressed Cancer Cell Proliferation and Migration in Glioblastoma by Inversely Regulating hsa-miR-21-5p

Objective

To evaluate the expression and function of long noncoding RNA (lncRNA) Prader-Willi region non-protein coding RNA 1 (PWRN1) in human glioblastoma (GBM).

Materials and Methods

QRT-PCR was applied to assess PWRN1 expression in human GBM tumors and GBM cell lines. PWRN1 was overexpressed by lentiviral infection in LN-229 and U-251 cells to evaluate its effect on GBM cell proliferation and migration in vitro, and xenograft in vivo. The endogenously competing target of PWRN1, human microRNA-21-5p (hsa-miR-21-5p) was evaluated by dual-luciferase activity assay and qRT-PCR. Also, hsa-miR-21-5p was upregulated in PWRN1-overexpressed GBM cells to evaluate the functional involvement of hsa-miR-21-5p in PWRN1-mediated GBM cell proliferation and migration.

Results

PWRN1 was downregulated in both human GBM tumors and GBM cell lines. In LN-229 and U-251, PWRN1 overexpression suppressed cancer cell proliferation and migration in vitro, and xenograft growth in vivo. Hsa-miR-21-5p was demonstrated to be the downstream competing target of PWRN1 in GBM. Conversely, upregulating hsa-miR-21-5p in LN-229 and U-251 cells reversed the tumor-suppressing effects of PWRN1 overexpression.

Conclusion

PWRN1 is markedly downregulated in GBM. Overexpressing PWRN1 has tumor inhibitory effect on GBM cells, likely via reversely suppressing the expression of tumor oncogenic factor of hsa-miR-21-5p.

The Construction and Comprehensive Prognostic Analysis of the LncRNA-Associated Competitive Endogenous RNAs Network in Colorectal Cancer

Competing endogenous RNAs (ceRNAs) are a newly proposed RNA interaction mechanism that has been associated with the tumorigenesis, metastasis, diagnosis, and predicting survival of various cancers. In this study, we constructed a ceRNA network in colorectal cancer (CRC). Then, we sought to develop and validate a composite clinicopathologic–genomic nomogram using The Cancer Genome Atlas (TCGA) database. To construct the ceRNA network in CRC, we analyzed the mRNAseq, miRNAseq data, and clinical information from TCGA database. LncRNA, miRNA, and mRNA signatures were identified to construct risk score as independent indicators of the prognostic value in CRC patients. A composite clinicopathologic–genomic nomogram was developed to predict the overall survival (OS). One hundred sixty-one CRC-specific lncRNAs, 97 miRNAs, and 161 mRNAs were identified to construct the ceRNA network. Multivariate Cox proportional hazards regression analysis indicated that nine-lncRNA signatures, eight-miRNA signatures, and five-mRNA signatures showed a significant prognostic value for CRC. Furthermore, a clinicopathologic–genomic nomogram was constructed in the primary cohort, which performed well in both the primary and validation sets. This study presents a nomogram that incorporates the CRC-specific ceRNA expression profile, clinical features, and pathological factors, which demonstrate its excellent differentiation and risk stratification in predicting OS in CRC patients.