Long Noncoding RNA LINC00173 Promotes NUTF2 Expression Through Sponging miR-765 and Facilitates Tumorigenesis in Glioma

Biomarker potential of competing endogenous RNA networks in Polycystic Ovary Syndrome (PCOS)

Polycystic ovary syndrome (PCOS) is the most common condition affecting women of reproductive age globally. PCOS continues to be the largest contributing factor to female infertility despite significant progress in our knowledge of the molecular underpinnings and treatment of the condition. The fact that PCOS is a very diverse condition makes it one of the key reasons why we haven't been able to overcome it. Non-coding RNAs (ncRNAs) are implicated in the development of PCOS, according to growing evidence. However, it is unclear how the complex regulatory relationships between the many ncRNA types contribute to the growth of this malignancy. Competing endogenous RNA (ceRNA), a recently identified mechanism in the RNA world, suggests regulatory interactions between various RNAs, including long non-coding RNAs (lncRNAs), microRNAs (miRNAs), transcribed pseudogenes, and circular RNAs (circRNAs). Recent studies on PCOS have shown that dysregulation of multiple ceRNA networks (ceRNETs) between these ncRNAs plays crucial roles in developing the defining characteristics of PCOS development. And it is believed that such a finding may open a new door for a deeper comprehension of PCOS's unexplored facets. In addition, it may be able to provide fresh biomarkers and effective therapy targets for PCOS. This review will go over the body of information that exists about the primary roles of ceRNETs before highlighting the developing involvement of several newly found ceRNETs in a number of PCOS characteristics.

LncRNA Linc00173 may be a potential prognostic biomarker in human solid tumors: a meta-analysis and bioinformatics analysis

Despite advances in diagnostic techniques and treatments, cancer remains one of the leading causes of death worldwide.Therefore, finding new biomarkers and therapeutic targets is crucial for improving the diagnosis and treatment of human cancer.LncRNA Linc00173 is a newly identified tumor marker, and in this study, we aimed to explore the relationship between Linc00173 and clinicopathological features and patient prognosis. By using The Cochrane Library, EMbase, Web of Science, PubMed, OVID, we conducted a complete and thorough literature search from its inception to November 10, 2022.Meta-analysis was performed using Stata SE16.0 software. Nine studies involving 1102 patients were included.Meta-analysis showed that the overexpression of Linc00173 was significantly associated with poorer OS (HR = 1.76,95%CI:1.36-2.26, P < 0.001) and shorter DFS (HR = 1.89, 95%CI:1.49-2.40,P < 0.001),and was significantly associated with gender (male) (OR = 1.31,95% CI:1.01-1.69, P = 0.042), tumor size (large) (OR = 1.34,95% CI:1.01-1.78, P = 0.045), and lymph node metastasis (positive) (OR = 1.72,95% CI:1.03-2.88, P = 0.038). Overexpression of Linc00173 is associated with poor prognosis in cancer patients and is a potential prognostic biomarker and therapeutic target.

Identification of immune and Toll-like receptor signaling pathway related feature lncRNAs to construct diagnostic nomograms for acute ischemic stroke

We aimed to identify the immune and Toll-like receptor (TLR) signaling pathway related feature lncRNAs to construct the diagnostic nomograms for acute ischemic stroke (AIS). Two AIS-associated expression profiles GSE16561 and GSE22255 were downloaded from NCBI Gene Expression Omnibus, the former was the training set and the latter was the validation set. The differential expression genes (DEGs) and lncRNAs (DElncRNAs) related to TLR signaling pathway were identified between AIS and control groups. The single sample gene set enrichment analysis (ssGSEA) was applied to evaluate the immune infiltration. The immune and TLR signaling pathway related DElncRNAs were determined. Three optimization algorithms were utilized to select the immune and TLR signaling pathway related feature lncRNAs to construct the diagnostic nomograms of AIS. Based on the lncRNA signature, a ceRNA network was constructed. 37 DEGs and 28 DElncRNAs related to TLR signaling pathway were identified in GSE16561. 16 immune cell types exhibited significant differences in distribution between AIS and control groups. 28 immune and TLR signaling pathway related DElncRNAs were determined. 8 immune and TLR signaling pathway related feature lncRNAs were selected. The diagnostic nomograms of AIS performed well in both datasets. A ceRNA network was constructed consisting of 7 immune and TLR signaling pathway related feature lncRNAs as well as 19 AIS related miRNAs and 21 TLR signaling pathway related genes. LINC00173, LINC01089, LINC02210, MIR600HG, SNHG14, TP73-AS1, LINC00680 and CASC2 may be the potential biomarkers of AIS diagnosis, and TLR signaling pathway may be a promising immune related therapeutic target for AIS.

A review on the role of LINC00173 in human cancers

Long intergenic non-protein coding RNA 173 (LINC00173) is a long non-coding RNA with especial function in the tumorigenic process. Studies in different types of cancers support an oncogenic role for LINC00173 except for studies in B-cell precursor acute lymphoblastic leukemia, cervical cancer, pancreatic cancer and gastric cancer. In breast and lung cancers, both oncogenic and tumor suppressor roles have been reported for LINC00173. LINC00173 can serve as a molecular sponge for miRNAs. miR-218/Etk, miR-511-5p/VEGFA, miR-182-5p/AGER, miR-765/NUTF2, miR-765/PLP2, miR-182-5p/FBXW7, miR-338-3p/Rab25, miR‑641/RAB14 and miR-1275/BCL2 are examples of the miRNA/mRNA axes being regulated by LINC00173 in the context of cancer. The current review provides a summary of different studies on the role of LINC00173 in these cancers.

Long noncoding RNA long intergenic non-protein-coding RNA 173 contributes to nasopharyngeal carcinoma progression by regulating microRNA-765/Gremlin 1 pathway

BACKGROUND

Long intergenic non-protein-coding RNA 173 (LINC00173) executes vital functions in various cancers. Nevertheless, its role and expression in nasopharyngeal carcinoma (NPC) have yet to be investigated. Here, we investigated its effects on the malignancy characteristics of NPC and elucidated the potential molecular mechanism of LINC00173 in NPC progression.

METHODS

Quantitative real-time reverse transcription-PCR (qRT-PCR) and immunoblotting were conducted to estimate the LINC00173, microRNA-765 (miR-765), and Gremlin 1 (GREM1) expressions in NPC cells and tissues. Cell counting kit-8 (CCK8), colony formation, and wound healing experiments were done to evaluate the proliferation, growth, and migration of NPC cells, respectively. The tumorous growth of NPC cells in vivo was assessed through the xenograft tumor experiment. Furthermore, the interactions among miR-765, LINC00173, and GREM1 were investigated through bioinformatics analyses, luciferase reporter and RNA immunoprecipitation chip assays.

RESULTS

An upregulated LINC00173 expression was found in NPC cell lines and tissues. The functional experiments uncovered that its downregulation repressed NPC cell proliferation, growth, and migration. In addition, LINC00173 knockdown hampered the NPC cells' tumorous growth in vivo. These effects could partially be reversed by downregulating miR-765. GREM1 is a downstream target of miR-765. GREM1 knockdown could repress the proliferation, growth, and migration of NPC cells. Nonetheless, these anti-tumor effects could be abolished by miR-765 downregulation. Mechanistically, LINC00173 increased the expression of GREM1 by binding with miR-765.

CONCLUSIONS

LINC00173 functions as an oncogenic factor by binding with miR-765 to promote the progression of NPC via GREM1 upregulation. This study provides a novel insight into the molecular mechanisms involved in NPC progression.

L-RAPiT: A Cloud-Based Computing Pipeline for the Analysis of Long-Read RNA Sequencing Data

Long-read sequencing (LRS) has been adopted to meet a wide variety of research needs, ranging from the construction of novel transcriptome annotations to the rapid identification of emerging virus variants. Amongst other advantages, LRS preserves more information about RNA at the transcript level than conventional high-throughput sequencing, including far more accurate and quantitative records of splicing patterns. New studies with LRS datasets are being published at an exponential rate, generating a vast reservoir of information that can be leveraged to address a host of different research questions. However, mining such publicly available data in a tailored fashion is currently not easy, as the available software tools typically require familiarity with the command-line interface, which constitutes a significant obstacle to many researchers. Additionally, different research groups utilize different software packages to perform LRS analysis, which often prevents a direct comparison of published results across different studies. To address these challenges, we have developed the Long-Read Analysis Pipeline for Transcriptomics (L-RAPiT), a user-friendly, free pipeline requiring no dedicated computational resources or bioinformatics expertise. L-RAPiT can be implemented directly through Google Colaboratory, a system based on the open-source Jupyter notebook environment, and allows for the direct analysis of transcriptomic reads from Oxford Nanopore and PacBio LRS machines. This new pipeline enables the rapid, convenient, and standardized analysis of publicly available or newly generated LRS datasets.

NUTF2 as a Prognostic Indicator and Potential Therapeutic Target in Head and Neck Squamous Cell Carcinoma

Aim: To identify genes associated with the prognosis of head and neck squamous cell carcinoma (HNSC) and potential molecular targets for therapy. Materials and Methods: Gene Expression Profiling Interactive Analysis, Human Protein Atlas, University of ALabama at Birmingham CANcer, LinkedOmics, cBioPortal, Cell Counting Kit 8, and polymerase chain reaction were used in this study. Results: The expression level of nuclear transport factor 2 (NUTF2) was elevated in HNSC tissues and was associated with poor prognosis in HNSC patients. NUTF2-targeted intervention inhibited the proliferation of HNSC cells. SEC61G, which was positively correlated with NUTF2, was decreased in HNSC cells with NUTF2 suppression. Conclusions: NUTF2 may be correlated with the prognosis and development of HNSC, laying the foundation for future studies on the potential role of NUTF2 in HNSC.

Long Intergenic Non-Protein Coding RNA 173 in Human Cancers

Long non-coding RNAs belong to non-coding RNAs (ncRNAs) with a length of more than 200 nucleotides and limited protein-coding ability. Growing research has clarified that dysregulated lncRNAs are correlated with the development of various complex diseases, including cancer. LINC00173 has drawn researchers' attention as one of the recently discovered lncRNAs. Aberrant expression of LINC00173 affects the initiation and progression of human cancers. In the present review, we summarize the recent considerable research on LINC00173 in 11 human cancers. Through the summary of the abnormal expression of LINC00173 and its potential molecular regulation mechanism in cancers, this article indicates that LINC00173 may serve as a potential diagnostic biomarker and a target for drug therapy, thus providing novel clues for future related research.

Construction and Characterization of n6-Methyladenosine-Related lncRNA Prognostic Signature and Immune Cell Infiltration in Kidney Renal Clear Cell Carcinoma

Background. Kidney renal clear cell carcinoma (KIRC) lacks effective prognostic biomarkers and the role and mechanism of N6-methyladenosine (m6A) modification of long noncoding RNAs (lncRNAs) in KIRC remain unclear. Methods. We extracted standard mRNA-sequencing and clinical data from the TCGA database. The prognostic risk model was obtained by Lasso regression and Cox regression. We randomly divided the samples into training and test sets, each taking half of the cases. Based on Lasso regression and Cox regression for training set, the prognostic risk signature was constructed; risk scores were calculated with the R package “glmnet.” Based on the median value of the prognostic risk score, risk scores were calculated for each patient and we divided all KIRC samples into high-risk and low-risk groups. Then, high- and low-risk subtypes were established and their prognosis, clinical features, and immune infiltration microenvironment were evaluated in test set and the entire sampled data set. The reliability of the prognostic model was confirmed by receiver operating characteristic curve analysis. Results. We found 28 prognostic m6A-related lncRNAs and established a m6A-related lncRNAs prognostic signature. $\text{Risk\hspace{0.17em}score}=AC015813.1\ast \left(0.0086\right)+EMX2OS\ast \left(-0.0101\right)+LINC00173\ast \left(0.0309\right)+PWAR5\ast \left(-0.0146\right)+SNHG1\ast \left(0.0043\right).$ The signature showed a better predictive ability than other clinical indicators, including tumor node metastasis classification (TNM), histological, and pathological stages. In the high-risk group, M0 macrophages, CD8+ T cells, and regulatory T cells had significantly higher scores. Contrarily, in the low-risk group, activated dendritic cells, M1 macrophages, mast resting cells, and monocytes had significantly higher scores. In the high-risk group, LSECtin was overexpressed. In the low-risk group, PD-L1 was overexpressed. Moreover, high-risk patients may benefit more from AZ628. Conclusions. In conclusion, prognosis prediction of patients with KIRC and new insights for immunotherapy are provided by the m6A-related lncRNA prognostic signature.

Underexpression of LINC00173 in TCF3/PBX1-Positive Cases Is Associated With Poor Prognosis in Children With B-Cell Precursor Acute Lymphoblastic Leukemia

Background

B-cell precursor acute lymphoblastic leukemia (BCP-ALL) is the most frequent pediatric cancer worldwide. Despite improvements in treatment regimens, approximately 20% of the cases cannot be cured, highlighting the necessity for identifying new biomarkers to improve the current clinical and molecular risk stratification schemes. We aimed to investigate whether LINC00173 is a biomarker in ALL and to explore its expression level in other human cancer types.

Methods

A nested case-control study including Mexican children with BCP-ALL was conducted. LINC00173 expression was evaluated by qRT-PCR using hydrolysis probes. To validate our findings, RNA-seq expression data from BCP-ALL and normal tissues were retrieved from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Genotype-Tissue Expression (GTEx) repositories, respectively. LINC00173 expression was also evaluated in solid tumors by downloading available data from The Cancer Genome Atlas (TCGA).

Results

A lower expression of LINC00173 in BCP-ALL cases compared to normal subjects was observed (p < 0.05). ALL patients who carry the TCF3/PBX1 fusion gene displayed lower expression of LINC00173 in contrast to other BCP-ALL molecular subtypes (p < 0.04). LINC00173 underexpression was associated with a high risk to relapse (HR = 1.946, 95% CI = 1.213-3.120) and die (HR = 2.073, 95% CI = 1.211-3.547). Patients with TCF3/PBX1 and underexpression of LINC00173 had the worst prognosis (DFS: HR = 12.24, 95% CI = 5.04-29.71; OS: HR = 11.19, 95% CI = 26-32). TCGA data analysis revealed that underexpression of LINC00173 is also associated with poor clinical outcomes in six new reported tumor types.

Conclusion

Our findings suggest that LINC00173 is a biomarker of poor prognosis in BCP-ALL and other types of cancer. We observed an association between the expression of LINC00173 and TCF3/PBX1 and the risk to relapse and die in BCP-ALL, which is worse in TCF3/PBX1-positive cases displaying underexpression of LINC00173. Experimental studies are needed to provide insight into the LINC00173 and TCF3/PBX relationship.

NTF2 Upregulation in HNSCC: a Predictive Marker and Potential Therapeutic Target Associated With Immune Infiltration

Background

Head and neck squamous cell carcinoma (HNSCC) is a type of malignant tumor with an increasing incidence worldwide and a meager 5-year survival rate. It is known that nuclear transporter factor 2 (NTF2) transports related proteins into the nucleus physiologically. However, the role of NTF2 in HNSCC remains unclear.

Methods

In this study, RNA-Seq data of HNSCC samples with corresponding clinical information were obtained from The Cancer Genome Atlas (TCGA) database. In addition, other expression profiling data were downloaded from the Gene Expression Omnibus (GEO) database. The differential expressions of NTF2, along with the overall survival (OS) rates were identified and analyzed. Then, the clinical features and expression levels of NTF2 were utilized to develop a prognostic model. The study also utilized the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) methods to determine the related pathways of NTF2. Furthermore, the Tumor Immune Estimation Resource (TIMER) database was referenced to discover the immune correlation of NTF2. In this research investigation, RT-qPCR, western blotting, Cell Counting Kit-8 (CCK-8) assay, wound-healing assay, and immunohistochemical (IHC) staining methods were adopted to perform experimental verifications.

Results

This study’s results confirmed that the NTF2 expressions were significantly increased in HNSCC tissue when compared with normal tissue. In addition, the high expression levels of NTF2 were found to be associated with poor prognoses, which was confirmed via the IHC validations of HNSCC samples with survival data. The results of functional enrichment analysis showed that the NTF2 was associated with epithelial cell growth, skin differentiation, keratosis, and estrogen metabolism. Furthermore, the expressions of NTF2 were determined to be negatively involved with immune infiltrations and correlated with immune checkpoint blockade (ICB) responses following various ICB therapy strategies. The results of the CCK-8 assay and wound-healing assay confirmed the NTF2’s promoting effects on the proliferation and migration of tumor cells.

Conclusions

This study defined a novel prognostic model associated with the expressions of NTF2, which was shown to be independently related to the OS of HNSCC. It was concluded in this study that NTF2 might be a potential diagnostic and prognostic biomarker for HNSCC.

Integrated Analysis of Competitive Endogenous RNA Networks in Acute Ischemic Stroke

Background: Acute ischemic stroke (AIS) is a severe neurological disease with complex pathophysiology, resulting in the disability and death. The goal of this study is to explore the underlying molecular mechanisms of AIS and search for new potential biomarkers and therapeutic targets.

Methods: Integrative analysis of mRNA and miRNA profiles downloaded from Gene Expression Omnibus (GEO) was performed. We explored differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMirs) after AIS. Target mRNAs of DEMirs and target miRNAs of DEGs were predicted with target prediction tools, and the intersections between DEGs and target genes were determined. Subsequently, Gene Ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses, Gene set enrichment analysis (GSEA), Gene set variation analysis (GSVA), competitive endogenous RNA (ceRNA) (lncRNA-miRNA-mRNA) network, protein–protein interaction (PPI) network, and gene transcription factors (TFs) network analyses were performed to identify hub genes and associated pathways. Furthermore, we obtained AIS samples with evaluation of immune cell infiltration and used CIBERSORT to determine the relationship between the expression of hub genes and infiltrating immune cells. Finally, we used the Genomics of Drug Sensitivity in Cancer (GDSC) database to predict the effect of the identified targets on drug sensitivity.

Result: We identified 293 DEGs and 26 DEMirs associated with AIS. DEGs were found to be mainly enriched in inflammation and immune-related signaling pathways through enrichment analysis. The ceRNA network included nine lncRNAs, 13 miRNAs, and 21 mRNAs. We used the criterion AUC >0.8, to screen a 3-gene signature (FBL, RPS3, and RPS15) and the aberrantly expressed miRNAs (hsa-miR-125a-5p, hsa-miR-125b-5p, hsa-miR-148b-3p, and hsa-miR-143-3p) in AIS, which were verified by a method of quantitative PCR (qPCR) in HT22 cells. T cells CD8, B cells naïve, and activated NK cells had statistical increased in number compared with the acute cerebral infarction group. By predicting the IC50 of the patient to the drug, AZD0530, Z.LLNle.CHO and NSC-87877 with significant differences between the groups were screened out. AIS demonstrated heterogeneity in immune infiltrates that correlated with the occurrence and development of diseases.

Conclusion: These findings may contribute to a better understanding of the molecular mechanisms of AIS and provide the basis for the development of novel treatment targets in AIS.

A Pan-Cancer Analysis of the Oncogenic Role of Nuclear Transport Factor 2 in Human Cancers

Nuclear transport factor 2 (NUTF2) is a GDP-binding protein that participates in the nucleocytoplasmic transport process. The role of NUTF2 in cancer development is largely unknown and lacks systemic assessment across human cancers. In this study, we performed a pan-cancer analysis of NUTF2 in human cancers. Out of 33 types of cancers, 19 types had significantly different expression of NUTF2 between tumor and normal tissues. Meanwhile, survival analysis showed that NUTF2 could be an independent prognostic factor in several tumor types. Further analysis suggested that the expression of NUTF2 expression was correlated with the infiltration of immune cells, such as CD8⁺ T cells, effector memory CD4⁺ T cells, and cancer-associated fibroblasts in kidney renal clear cell carcinoma. Moreover, co-expression analysis showed the positive association between NUTF2 and cell proliferation biomarkers (MKI67and PCNA) and epithelial–mesenchymal transition markers (VIM, TWIST1, SNAI1, SNAI2, FN1, and CDH2), suggesting that NUTF2 plays important roles in regulating cancer proliferation and metastasis. This pan-cancer analysis of NUTF2 provides a systemic understanding of its oncogenic role across different types of cancers.

Nuclear Transporting Factor 2 as a Novel Biomarker of Head and Neck Squamous Cell Carcinoma and Associated with T/B Cell Receptor Signaling Pathway

Objective

This study is aimed at exploring the role of nuclear transporting factor 2 (NUTF2) in head and neck squamous cell carcinoma (HNSCC) based on The Cancer Genome Atlas (TCGA) database.

Methods

We obtained 528 HNSCC patients' clinical data from TCGA and performed expression level analysis of NUTF2. Gene Sets Enrichment Analysis (GSEA) was conducted to identify NUTF2-associated regulatory mechanisms in HNSCC. In addition, several other tools were used to enrich the regulatory network.

Results

We found that NUTF2 was significantly upregulated (P < 0.001) in HNSCC. We then observed that higher NUTF2 is associated with poorer overall survival and disease-free survival. Further, by using Cox analyses, we determined high NUTF2 as an independent risk factor of predicting poorer overall survival. Tumor immune infiltration analysis revealed a significantly negative correlation between NUTF2 expression and the level of tumor infiltrated CD8⁺ T cell and B cell, suggesting that NUTF2 may be involved in the immune regulation of HNSCC. Gene sets related to T/B cell receptor signaling pathways were differentially enriched based on the NUTF2 expression phenotype. KEGG pathways were used to show that NUTF2 may affect proliferation, differentiation, and immune response of T/B cell through regulating PI3K/AKT, NFκB, MAPK, and Calcium signaling pathways.

Conclusion

NUTF2 might be a valuable biomarker for HNSCC and correlated with T/B cell receptor signaling pathway.

Identification of NUTF2 as a Candidate Diagnostic and Prognostic Biomarker Associated with Immune Infiltration in Head and Neck Squamous Cell Carcinoma

Background

Head and neck squamous cell carcinoma (HNSC) is one of the most common tumors worldwide. Nuclear transport factor 2 (NUTF2) plays a key role in cell death and immune processes. However, few reports have studied correlations between NUTF2 gene expression and the occurrence and development of HNSC.

Methods

The expression of NUTF2 was analyzed using publicly available databases, including the Cancer Genome Atlas and Human Protein Atlas and Gene Expression Omnibus (GEO) database, which was validated by RT-PCR. We evaluated the functions of NUTF2 with Kaplan–Meier curve, logistic regression were used to study the relationship between clinicopathological features and the expression of NUTF2. Cox regression analyses were used to identify the effects of NUTF2 expression on survival. Gene Ontology and Gene Set Enrichment Analysis were used to explore relevant biological pathways. The relationship between NUTF2 and tumor-infiltrating immune cells was investigated with on-line bioinformatic tools.

Results

NUTF2 was significantly upregulated in HNSC lesions and is associated with tumor size (P < 0.01). Increased expression of NUTF2 was linked to shorter overall and progress-free survival in HNSC. Cox regression analyses revealed that NUTF2 is an independent prognostic factor in HNSC. GSEA analysis demonstrated that NUTF2 negatively regulates several immune pathways. NUTF2 was correlated with the infiltrating levels of B cells and CD8+ T cells and was negatively correlated with diverse immune marker sets in HNSC.

Conclusion

NUTF2 is highly expressed in HNSC and correlates with poor prognosis. Correlation with immune functions suggests that NUTF2 may serve as a biomarker and therapeutic target for HNSC.

Identification of LINC00173 in Myasthenia Gravis by Integration Analysis of Aberrantly Methylated- Differentially Expressed Genes and ceRNA Networks

Myasthenia gravis (MG) is an autoimmune disease associated with autoantibody production that leads to skeletal muscle weakness. The molecular mechanisms underlying MG are not fully understood. We analyzed the gene expression profile (GSE85452) and methylation profile (GSE85647) of MG samples from the GEO database to identify aberrantly methylated-differentially expressed genes. By integrating the datasets, we identified 143 hypermethylation-low expression genes and 91 hypomethylation-high expression genes. Then we constructed PPI network and ceRNA networks by these genes. Phosphatase and tensin homolog (PTEN) and Abelson tyrosine-protein kinase (ABL)1 were critical genes in both PPI networks and ceRNA networks. And potential MG associated lncRNAs were selected by comprehensive analysis of the critical genes and ceRNA networks. In the hypermethylation-low expression genes associated ceRNA network, sirtuin (SIRT)1 was the most important gene and the lncRNA HLA complex (HC) P5 had the highest connection degree. Meanwhile, PTEN was the most important gene and the lncRNA LINC00173 had the highest connection degree in the hypomethylation-high expression genes associated ceRNA network. LINC00173 was validated to be upregulated in MG patients by qRT-PCR (P = 0.005), which indicated LINC00173 might be a potential biomarker for MG. These results provide a basis for future studies on the molecular pathogenesis of MG.

miR-56a Mediates the Wnt/β-Catenin Pathway to Promote the Efficacy of Radiation on Glioma

Clarification of the miR-56a-mediated effect of Wnt/β-catenin pathway in glioma cells on radiosensitization. miRNA arrays were used to analyze the differential expression of miRNAs in biopsies from glioma patients. qRT-PCR to detect the levels of miR-56a and Wnt/β-catenin expressed in glioma cells and tissues. Evaluation of the impact of miR-56a on cell growth, invasion, and migrationforming ability by MTT assay and colony formation experiments. To analyze the involvement of miR-56a-mediated Wnt/β-catenin pathway in glioma biological processes and to examine the impact of miR-56a in glioma cell radiosensitivity. After miRNA array analysis, we found that miR-56a expression was significantly increased, and further studies showed that ectopic miR-56a expression in glial cells was sensitive to radiotherapy. miR-56a induction of Wnt/β-catenin promotes the upregulation of Parp in glioma cells. miR-56a can promote glioma cell migration and invasion in vitro as an important potential target for glioma disease.