Comprehensive analysis of a long non-coding RNA-mediated competitive endogenous RNA network in glioblastoma multiforme

Increased Expression of Homeobox 5 Predicts Poor Prognosis: A Potential Prognostic Biomarker for Glioma

Background

The homeobox gene 5 (HOXB5) encodes a transcription factor that regulates the embryonic development of the central nervous system. Notably, its expression pattern and prognostic role in glioma remain unelucidated.

Methods

This study identified the relationship between HOXB5 and glioma by investigating HOXB5 expression data from The Cancer Genome Atlas and the Genotype Tissue Expression databases and validating the obtained data using the Chinese Glioma Genome Atlas database. Western blots were used to identify HOXB5 expression levels in glioma cells and clinical samples. Kaplan-Meier and multivariate Cox regression analyses were performed to assess the prognostic value of HOXB5. The key functions and signaling pathways related to HOXB5 were analyzed using GO, KEGG, and GSEA. Immune infiltration was calculated using the microenvironment cell populations-counter, estimate the proportion of immune and cancer, and ESTIMATE algorithms.

Results

The expression of HOXB5 was upregulated in glioma and generally increased with malignancy. HOXB5 was an independent prognostic factor for glioma patients. A nomogram was further built that integrated HOXB5, and it showed stratifying prediction accuracy and efficiency. HOXB5 was associated with the regulation of cell growth, endothelial cell growth, and the IL-6/JAK-STAT3 pathway, and was determined to possibly promote stomatal specimen enrichment and angiogenesis.

Conclusion

HOXB5 protein is overexpressed in glioma and might serve as a good predictive factor of this disease.

Identification of LncRNA Prognostic Signature Associated With Genomic Instability in Pancreatic Adenocarcinoma

Background

Genomic instability (GI) is a critical feature of cancer which plays a key role in the occurrence and development of pancreatic adenocarcinoma (PAAD). Long non-coding RNA (LncRNA) is an emerging prognostic biomarker because it is involved in regulating GI. Recently, researchers used such GI-related LncRNAs (GILncRNAs) to establish a prognostic signature for patients with cancer and helped in predicting the overall prognosis of the patients. However, it is evident that patients with PAAD still lack such prognostic signature constructed with GILncRNA.

Methods

The present study screened GILncRNAs from 83 patients with PAAD. Prognosis-related GILncRNAs were identified by univariate Cox regression analysis. The correlation coefficients of these GILncRNAs were obtained by multivariate Cox regression analysis and used to construct a signature. The signature in the present study was then assessed through survival analysis, mutation correlation analysis, independent prognostic analysis, and clinical stratification analysis in the training set and validated in the testing as well as all TCGA set. The current study performed external clinical relevance validation of the signature and validated the effect of AC108134.2 in GILncSig on PAAD using in vitro experiments. Finally, the function of GILncRNA signature (GILncSig) dependent on Gene Ontology enrichment analysis was explored and chemotherapeutic drug sensitivity analysis was also performed.

Results

Results of the present study found that a total of 409 GILncRNAs were identified, 5 of which constituted the prognostic risk signature in this study, namely, AC095057.3, AC108134.2, AC124798.1, AL606834.1, and AC104695.4. It was found that the signature of the present study was better than others in predicting the overall survival and applied to patients with PAAD of all ages, genders, and tumor grades. Further, it was noted that the signature of the current study in the GSE102238, was correlated with tumor length, and tumor stage of patients with PAAD. In vitro, functional experiments were used in the present study to validate that AC108134.2 is associated with PAAD genomic instability and progression. Notably, results of the pRRophetic analysis in the current study showed that the high-risk group possessed reverse characteristics and was sensitive to chemotherapy.

Conclusions

In conclusion, it was evident that the GILncSig used in the present study has good prognostic performance. Therefore, the signature may become a potential sensitive biological indicator of PAAD chemotherapy, which may help in clinical decision-making and management of patients with cancer.

Comprehensive analysis of the LncRNAs, MiRNAs, and MRNAs acting within the competing endogenous RNA network of LGG

Messenger RNA (mRNA) and long noncoding RNA (lncRNA) targets interact via competitive microRNA (miRNA) binding. However, the roles of cancer-specific lncRNAs in the competing endogenous RNA (ceRNA) networks of low-grade glioma (LGG) remain unclear. This study obtained RNA sequencing data for normal solid tissue and LGG primary tumour tissue from The Cancer Genome Atlas database. We used a computational method to analyse the relationships among the mRNAs, lncRNAs, and miRNAs in these samples. Gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was used to predict the biological processes (BPs) and pathways associated with these genes. Kaplan-Meier survival analysis was used to evaluate the association between the expression levels of specific mRNAs, lncRNAs, and miRNAs and overall survival. Finally, we created a ceRNA network describing the relationships among these mRNAs, lncRNAs, and miRNAs using Cytoscape 3.5.1. A total of 2555 differentially expressed (DE) mRNAs, 218 DElncRNAs, and 192 DEmiRNAs were identified using R. In addition, GO and KEGG pathway analysis of the mRNAs and lncRNAs in the ceRNA network identified 10 BPs, 10 cell components, 10 molecular functions, and 48 KEGG pathways as selectively enriched. A total of 55 lncRNAs, 50 miRNAs, and 10 mRNAs from this network were shown to be closely associated with overall survival in LGG. Finally, 59 miRNAs, 235 mRNAs, and 17 lncRNAs were used to develop a ceRNA network comprising 313 nodes and 1046 edges. This study helps expand our understanding of ceRNA networks and serves to clarify the underlying pathogenesis mechanism of LGG.

Identification of biomarkers and ceRNA network in glioblastoma through bioinformatic analysis and evaluation of potential prognostic values

Background

Glioblastoma (GBM) is one of the most common and malignant primary brain tumors in adults, with high mortality rates and limited treatment. Based on bioinformatic analyses, this study aimed to identify biomarkers and relevant molecular pathways that may serve as potential targets for the treatment of GBM.

Methods

Expression profiles were downloaded from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database; nine GBM samples and three normal samples were extracted from the GSE104267 dataset. Differentially-expressed messenger RNA (mRNA) and long non-coding RNA (lncRNA) were screened from the preprocessed dataset. The clusterProfiler package in R was used to perform a biological process (BP) analysis of gene ontology (GO), and a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed separately in upregulated and downregulated groups. A competing endogenous RNA (ceRNA) network was constructed using Cytoscape. Based on data downloaded from The Cancer Genome Atlas (TCGA), Kaplan-Meier (K-M) survival curves were established. Real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to evaluate IL10RB antisense RNA 1 (IL10RB-AS1) expression in GBM tissue compared with that in normal brain tissue.

Results

A total of 253 differentially-expressed genes (DEGs) were obtained. Based on BP and KEGG enrichment annotation analyses, 11 lncRNA-related pathways were identified through function prediction analysis. A competing endogenous RNA (ceRNA) subnetwork, including 21 nodes and 29 regulatory pairs, was then constructed. Based on the clinical data of GBM in TCGA, one survival-related DEG, IL10RB-AS1, was identified using the log-rank statistical test. K-M survival curves of IL10RB-AS1 and expression levels of IL10RB-AS1 in both GBM and normal brain tissue were obtained.

Conclusions

Through the combination of bioinformatic analyses, one survival-related differentially-expressed lncRNA, IL10RB-AS1, was identified. This, along with several related signaling pathways and ceRNA systems that were elucidated in GBM have potential prognostic value and might offer new possibilities for the treatment of GBM.

Reboot: a straightforward approach to identify genes and splicing isoforms associated with cancer patient prognosis

Nowadays, the massive amount of data generated by modern sequencing technologies provides an unprecedented opportunity to find genes associated with cancer patient prognosis, connecting basic and translational research. However, treating high dimensionality of gene expression data and integrating it with clinical variables are major challenges to perform these analyses. Here, we present Reboot, an integrative approach to find and validate genes and transcripts (splicing isoforms) associated with cancer patient prognosis from high dimensional expression datasets. Reboot innovates by using a multivariate strategy with penalized Cox regression (LASSO method) combined with a bootstrap approach, in addition to statistical tests and plots to support the findings. Applying Reboot on data from 154 glioblastoma patients, we identified a three-gene signature (IKBIP, OSMR, PODNL1) whose increased derived risk score was significantly associated with worse patients' prognosis. Similarly, Reboot was able to find a seven-splicing isoforms signature related to worse overall survival in 177 pancreatic adenocarcinoma patients with elevated risk scores after uni- and multivariate analyses. In summary, Reboot is an efficient, intuitive and straightforward way of finding genes or splicing isoforms signatures relevant to patient prognosis, which can democratize this kind of analysis and shed light on still under-investigated cancer-related genes and splicing isoforms.

Comprehensive In Silico Analysis of a Novel Serum Exosome-Derived Competitive Endogenous RNA Network for Constructing a Prognostic Model for Glioblastoma

Purpose

Glioblastoma (GBM) is one of the most aggressive brain tumors with high mortality, and tumor-derived exosomes provide new insight into the mechanisms of GBM tumorigenesis, metastasis and therapeutic resistance. We aimed to establish an exosome-derived competitive endogenous RNA (ceRNA) network for constructing a prognostic model for GBM.

Methods

We obtained the expression profiles of long noncoding RNAs (lncRNAs), miRNAs, and mRNAs from the GEO and TCGA databases and identified differentially expressed RNAs in GBM to construct a ceRNA network. By performing lasso and multivariate Cox regression analyses, we identified optimal prognosis-related differentially expressed lncRNAs (DElncRNAs) and generated a risk score model termed the exosomal lncRNA (exo-lncRNA) signature. The exo-lncRNA signature was subsequently validated in the CGGA GBM cohort. Finally, a novel prognostic nomogram was constructed based on the exo-lncRNA signature and clinicopathological parameters and validated in the CGGA external cohort. Based on the ceRNA hypothesis, oncocers were identified based on highly positive correlations between lncRNAs and mRNAs mediated by the same miRNAs. Furthermore, regression analyses were performed to assess correlations between the expression abundances of lncRNAs in tumors and exosomes.

Results

A total of 45 DElncRNAs, six DEmiRNAs, and 38 DEmRNAs were identified, and an exosome-derived ceRNA network was built. Three optimal prognostic-related DElncRNAs, HOTAIR (HR=0.341, P<0.001), SOX21-AS1 (HR=0.30, P<0.001), and STEAP3-AS1 (HR=2.47, P<0.001), were included to construct the exo-lncRNA signature, which was further proven to be an independent prognostic factor. The novel prognostic nomogram was constructed based on the exo-lncRNA signature, patient age, pharmacotherapy, radiotherapy, IDH mutation status, and MGMT promoter status, with a concordance index of 0.878. ROC and calibration plots both suggested that the nomogram had beneficial discrimination and predictive abilities. A total of 11 pairs of prognostic oncocers were identified. Regression analysis suggested excellent consistency of the expression abundance of the three exosomal lncRNAs between exosomes and tumor tissues.

Conclusions

Exosomal lncRNAs may serve as promising prognostic predictors and therapeutic targets. The prognostic nomogram based on the exo-lncRNA signature might provide an intuitive method for individualized survival prediction and facilitate better treatment strategies.

Linc00475 promotes the progression of glioma by regulating the miR-141-3p/YAP1 axis

Glioma is the most prevalent and lethal primary brain tumour. Abundant long non‐coding RNAs ( lncRNAs) are aberrant and play crucial roles in the oncogenesis of glioma. The exact functions of linc00475 in glioma remain blurred. Here, we analysed the expression levels of linc00475 by qRT‐PCR and discovered that linc00475 was up‐regulated in glioma and predicted a poor prognosis in patients with glioma. Besides, inhibiting linc00475 restrained the progression of glioma in vitro and in vivo. Further experiments confirmed that linc00475 regulated the progression of glioma by acting as a sponge for miR‐141‐3p. Moreover, we detected the binding sites of linc00475 and miR‐141‐3p, the YAP1‐ 3′UTR and miR‐141‐3p by luciferase reporters. The rescue assays confirmed that inhibiting linc00475 restrained the progression of glioma through the miR‐141‐3p/YAP1 pathway. Collectively, our research demonstrates the key roles of linc00475 in glioma, which could be a promising therapeutic target.

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.

Hsa_circ_0043278 functions as competitive endogenous RNA to enhance glioblastoma multiforme progression by sponging miR-638

Circular RNAs have a critical function in the pathogenesis of many diseases and can function as competing endogenous RNA or miRNA sponges to inhibit miRNA and therefore upregulate the expression of target genes. However, little is known about the role of has_circRNA_0043278 (circ_0043278) in glioblastoma multiforme (GBM) and its potential downstream miRNA targets. This work validated that circ_0043278 is highly expressed in GMB cell lines and tissues, while knockdown circ_0043278 inhibited GBM cell migration, proliferation, and invasion invitro and tumorigenesis invivo. Dual-luciferase reporter assay determined that circ_0043278 directly sponged miR-638 to upregulate the expression of HOXA9, which can activate downstream Wnt/β-catenin signaling in GBM. Moreover, miR-638 inhibition reversed circ_0043278 silencing-induced impairment of malignant tumor behavior. These results showed that circ-0043278/miRNA-638/ Homeobox A9 (HOXA9) axis had a vital function in promoting GBM progression. Our findings may provide potential new targets for the diagnosis and therapy of GBM.

Long intergenic non-protein coding RNA 00475 silencing acts as a tumor suppressor in glioma under hypoxic condition by impairing microRNA-449b-5p-dependent AGAP2 up-regulation

Objective

Long non-coding RNAs have been demonstrated to be involved in the progression of a variety of cancers, including glioma. Through microarray analyses, long intergenic non-protein coding RNA 00475 (LINC00475) was identified in the glioma development. However, its potential role remains incompletely understood. This study aimed to elucidate the effect of LINC00475 on the development of glioma under hypoxic conditions.

Methods

Glioma cells underwent hypoxic treatment and were collected. The functional role of LINC00475 and AGAP2 in glioma was determined using ectopic expression, depletion, and reporter assay experiments. Then, the expression of LINC00475, microRNA (miR)-449b-5p, AGAP2, FAK, and HIF-1α was determined. In addition, cell migration and invasion were examined. Finally, a tumor xenograft was carried out in nude mice to explore the role of LINC00475 on oxidation in vivo.

Results

LINC00475 was identified to be overexpressed in hypoxic glioma samples, which was further observed to bind to and down-regulate miR-449b-5p, and negatively targeted AGAP2. Moreover, we also revealed a positive correlation between LINC00475 and AGAP2 expression in glioma. In addition, silencing of LINC00475 decreased the extent of FAK phosphorylation and reduced the expression of HIF-1α and AGAP2. It was also observed that LINC00475 silencing suppressed glioma cell proliferation, migration, and invasion, and promoted cell apoptosis. Moreover, oxidation of nude mice was promoted by LINC00475 silencing.

Conclusion

Taken together, LINC00475 silencing exerted an inhibitory effect on glioma under hypoxic conditions by down-regulating AGAP2 via up-regulation of miR-449b-5p.

Noncoding RNAs as potential biomarkers for DIPG diagnosis and prognosis: XIST and XIST-210 involvement

PURPOSE

Diffuse intrinsic pontine gliomas (DIPGs) are the most fatal primary brainstem tumors in pediatric patients. The identification of new molecular features, mediating their formation and progression, as non-coding RNAs (ncRNAs), would be of great importance for the development of effective treatments.

METHODS

We analyzed the DIPGs transcriptome with the HTA2.0 array and it was compared with pediatric non-brainstem astrocytoma expression profiles (GSE72269).

RESULTS

More than 50% of the differentially expressed transcripts were ncRNAs and based on this, we proposed a DIPGs ncRNA signature. LncRNAs XIST and XIST-210, and the HBII-52 and HBII-85 snoRNA clusters were markedly downregulated in DIPGs. qPCR assays demonstrated XIST downregulation in all non-brainstem astrocytomas, in a gender, age, and brain location-independent manner, as well as in DIPGs affecting boys; however, DIPGs affecting girls showed both downregulation and upregulation of XIST. Girls' with longer survival positively correlated with XIST expression.

CONCLUSIONS

The involvement of ncRNAs in DIPGs is imminent and their expression profile is useful to differentiate them from non-neoplastic tissues and non-brain stem astrocytomas, which suggests their potential use as DIPG biomarkers. In fact, XIST and XIST-210 are potential DIPG prognostic biomarkers.

Long Noncoding RNA PVT1 Promotes Prostate Cancer Metastasis by Increasing NOP2 Expression via Targeting Tumor Suppressor MicroRNAs

BACKGROUND

Metastatic disease caused by prostate cancer (PCa) is the principal cause of PCa-related mortality. Long non-protein-coding RNAs may possess significant cellular functions. Plasmacytoma variant translocation 1 (PVT1), a long non-coding RNA encoded by the human PVT1 gene, is an oncogene, which can regulate several tumor-related genes. In PCa, the function and mechanism of PVT1 are unclear. NOP2 is being pursued as a prognostic marker for cancer aggressiveness, which promotes mouse fibroblast growth and tumor formation. Essentially, nothing is known about the specific interactions between the PVT1 and NOP2.

METHODS

 190 pairs of PCa tissues and adjacent normal tissues were collected and RNA sequencing was used to identify the differential lncRNAs. Real-time quantitative real-time PCR (RT-qPCR) confirmed these results and gene regulatory relationship. Lentiviral vectors were used to alter PVT1 and genes to analyze their effects on PCa progression. Transwell migration and invasion assays were performed to test the metastasis ability. Biofunction of PVT1 and NOP2 were confirmed in vitro and in vivo.

RESULTS

In this study, we reported that the long noncoding RNA-PVT1 was upregulated in PCa metastasis tissues and promoted migration of PCa cells in vitro and their metastasis in vivo. High levels of PVT1 significantly downregulated tumor suppressor microRNAs (miRNAs), such as miR-15b-5p, miR-27a-3p, miR-143-3p, and miR-627-5p, whose levels in metastasis tissues were low compared to those in non-metastasis tissues. In vitro and in vivo, PVT1 promotes PCa metastasis via targeting miRNAs. Furthermore, the expression level of PVT1 was positively associated with the expression of NOP2, a cancer metastasis-related protein. We demonstrated that NOP2 promoted invasion and migration of PCa. For specific mechanism, correlation analysis showed that PVT1 promoted metastasis by up-regulating NOP2.

CONCLUSION

Taken together, our results show that PVT1 acts as an inducer of PCa metastasis via targeting miRNAs, thereby promoting NOP2. This axis may have diagnostic and therapeutic potential for advanced PCa.

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

Purpose

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

Materials and Methods

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

Results

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

Conclusion

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