lncRNA LINC01494 Promotes Proliferation, Migration And Invasion In Glioma Through miR-122-5p/CCNG1 Axis.

Background: Long noncoding RNAs (lncRNAs) are recognized as key effectors in tumor, including glioma. LINC01494 is an uncharacterized novel lncRNA. In this research, we aimed to investigate the function of LINC01494 in glioma.

A 6-Gene Risk Signature Predicts Survival of Glioblastoma Multiforme.

Background: This study aims to develop novel signatures for glioblastoma multiforme (GBM).

Methods: GBM expression profiles from The Cancer Genome Atlas (TCGA) were downloaded and DEGs between tumor and normal samples were identified by differential expression analysis (DEA). A risk signature was developed by applying weighted gene coexpression network analysis (WGCNA) and Cox regression analysis.

Construction of Novel DNA Methylation-Based Prognostic Model to Predict Survival in Glioblastoma.

Glioblastoma (GBM) is a most aggressive primary cancer in brain with poor prognosis. This study aimed to identify novel tumor biomarkers with independent prognostic values in GBMs. The DNA methylation profiles were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus database.

Prognostic Markers Identification in Glioma by Gene Expression Profile Analysis.

This study aimed to explore more gene markers associated with glioma or its prognosis. The glioma-related RNAseq data from the Gene Expression Omnibus database and The Cancer Genome Atlas dataset in UCSC Xena database were downloaded. There was a total of 971 tumor samples and 102 normal samples in the 2 datasets.

Gene and microRNA Signatures Are Associated with the Development and Survival of Glioblastoma Patients.

This study was aimed to identify hub genes associated with the development of glioblastoma (GBM) by conducting a bioinformatic analysis. The raw gene expression data were downloaded from the Gene Expression Omnibus database and The Cancer Genome Atlas project. After the differentially expressed genes (DEGs) were identified, the functional enrichment analysis of DEGs was conducted.

Ampelopsin inhibits human glioma through inducing apoptosis and autophagy dependent on ROS generation and JNK pathway.

Glioma is the most common form of malignant brain cancer with high mortality rate in human. Therefore, finding effective therapeutic strategy and revealing the underlying molecular mechanism is necessary. Ampelopsin (Amp), an effective component of the traditional Chinese herb of Ampelopsis grossedentata, is reported to have important biological properties, including anti-inflammatory, anti-cancer, and anti-oxidant activity; however, its effects on human glioma are poorly understood.

LncRNA BLACAT1 regulates VASP expression via binding to miR-605-3p and promotes giloma development.

Glioma, an aggressive tumor in brain, presents a very poor prognosis. Emerging evidence has demonstrated that dysfunction of long noncoding RNAs (lncRNAs) is closely related to giloma development. However, the roles of lncRNA BLACAT1 in glioma are not unknown.

LncRNA LINC01857 promotes growth, migration, and invasion of glioma by modulating miR-1281/TRIM65 axis.

The great importance of long noncoding RNAs (lncRNAs) has been acknowledged in tumorigenesis gradually. LncRNA LINC01857 is a novel lncRNA and has been reported to promote breast cancer progression. However, the biological roles of LINC01857 in glioma are not explored.

Effects of mir-128a on the invasion and proliferation of glioma U251 cells.

Effects of mir-128a on the proliferation and migration of human glioma U251 cells were explored. The constructed mir-128a-shRNA lentivirus vector (infection group) and scramble shRNA (interference group) were transfected into glioma U251 cells, and uninfected U251 cells as control group. The expression level of mir-128a, the ability of proliferation, invasion, apoptosis and migration of cells in each group were detected by RT-qPCR, MTT assay, Transwell migration , cell wound scratch assay and TUNEL cell apoptosis assay.

Candidate Biomarkers and Molecular Mechanism Investigation for Glioblastoma Multiforme Utilizing WGCNA.

To reveal the potential molecular mechanism of glioblastoma multiforme (GBM) and provide the candidate biomarkers for GBM gene therapy. Microarray dataset GSE50161 was obtained from GEO database. The differentially expressed genes (DEGs) were identified between GBM samples and control samples, followed by the module partition analysis based on WGCNA.

PLK1 inhibitor facilitates the suppressing effect of temozolomide on human brain glioma stem cells.

Glioblastoma is the most frequent and most aggressive brain tumour in adults. Temozolomide is an oral chemotherapy drug and one of the major components of chemotherapy regimens used as a treatment of some brain cancers. We examined the tolerance of stem cells isolated from glioma cell line U87 and U251 to temozolomide (TMZ) and explored the effect of PLK1 (Polo like kinase 1) protein expression on TMZ sensibility.

Identification of gene markers associated with metastasis in clear cell renal cell carcinoma.

The present study aimed to screen potential target genes for the early diagnosis and treatment of early metastatic clear cell renal cell carcinoma (ccRCC) using the microarray data of early metastatic and non-metastatic ccRCC samples. The DNA microarray dataset GSE47352 was downloaded from Gene Expression Omnibus and included 4 early metastatic and 5 non-metastatic ccRCC samples. Differentially expressed genes (DEGs) were screened using the limma package.

Screening of differentially expressed genes associated with human glioblastoma and functional analysis using a DNA microarray.

Glioblastoma multiforme (GBM) is the most malignant type of human glioma, and has a poor prognosis. Screening differentially expressed genes (DEGs) in brain tumor samples and normal brain samples is of importance for identifying GBM and to design specific-targeting drugs. The transcriptional profile of GSE30563, containing three genechips of brain tumor samples and three genechips of normal brain samples, was downloaded from Gene Expression Omnibus to identify the DEGs.

Analysis of gene expression profiles associated with glioma progression.

The present study aimed to investigate changes at the transcript level that are associated with spontaneous astrocytoma progression, and further, to discover novel targets for glioma diagnosis and therapy. GSE4290 microarray data downloaded from Gene Expression Omnibus were used to identify the differentially expressed genes (DGEs) by significant analysis of microarray (SAM). The Short Time Series Expression Miner (STEM) method was then applied to class these DEGs based on their degrees of differentiation in the process of tumor progression.

Identification of differentially expressed genes regulated by transcription factors in glioblastomas by bioinformatics analysis.

The present study aimed to identify differentially expressed genes (DEGs) regulated by transcription factors (TFs) in glioblastoma, by conducting a bioinformatics analysis. The results of the present study may provide potential therapeutic targets that are involved in the development of glioblastoma. The GSE4290 raw data set was downloaded from the Gene Expression Omnibus database, and consisted of 23 non‑tumor samples and 77 glioblastoma (grade 4) tumor samples.

Gene expression analyses to explore the biomarkers and therapeutic targets for gliomas.

To improve treatment strategies of glioma, microarray data were applied to screen target molecules that were regulated by microRNAs (miRNAs). GSE31262 was downloaded from Gene Expression Omnibus, including five neural stem cells samples from normal human and nine stem cells samples from glioma patients. Differentially expressed genes (DEGs) were identified with Multtest package and Limma package of R language, and false discovery rate < 0.