Knockdown of long non-coding RNA Taurine up-regulated 1 inhibited doxorubicin resistance of bladder urothelial carcinoma via Wnt/β-catenin pathway Knockdown of long non-coding RNA Taurine up-regulated 1 inhibited doxorubicin resistance of bladder urothelial carcinoma via Wnt/β-catenin pathway

Objective: Human brain glioma is the most malignant primary intracranial tumor, which has poor prognosis and high mortality. Long noncoding RNAs are considered to take part in cellular phenotypes and are emerging as diagnostic and prognostic biomarkers of glioma. This study will research the effects of Small Nucleolar RNA Host Gene 5 (SNHG5) gene on malignant cellular phenotypes in glioma and explore the possible mechanisms.

Objective: To investigate the clinical significance of long noncoding RNA (lncRNA) CDKN2B antisense RNA 1 (CDKN2B-AS) gene and its effects on Gemcitabine sensitivity in BUC.

Mitochondria, known as the “energy factory” of cells, are essential organelles with a double membrane structure and genetic material found in most eukaryotic cells. They play a crucial role in tumorigenesis and development, with alterations in mitochondrial structure and function in tumor cells leading to characteristics such as rapid proliferation, invasion, and drug resistance. Glioma, the most common brain tumor with a high recurrence rate and limited treatment options, has been linked to changes in mitochondrial structure and function. This review focuses on the bioenergetics, dynamics, metastasis, and autophagy of mitochondria in relation to glioma proliferation, as well as the potential use of mitochondria‐targeting drugs in glioma treatment.

The function of glutamate ionotropic receptor NMDA type subunit 1 (GRIN1) in neurodegenerative diseases has been widely reported; however, its role in the occurrence of glioma remains less explored. We obtained clinical data and transcriptome data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Hub gene’s expression differential analysis and survival analysis were conducted by browsing the Gene Expression Profiling Interactive Analysis (GEPIA) database, Human Protein Atlas database, and LOGpc database. We conducted a variation analysis of datasets obtained from GEO and TCGA and performed a weighted gene coexpression network analysis (WGCNA) using the R programming language (3.6.3). Kaplan‐Meier (KM) analysis was used to calculate the prognostic value of GRIN1. Finally, we conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Using STRING, we constructed a protein–protein interaction (PPI) network. Cytoscape software, a prerequisite of visualizing core genes, was installed, and CytoHubba detected the 10 most tumor‐related core genes. We identified 185 differentially expressed genes (DEGs). GO and KEGG enrichment analyses illustrated that the identified DEGs are imperative in different biological functions and ascertained the potential pathways in which the DEGs may be enriched. The overall survival calculated by KM analysis showed that patients with lower expression of GRIN1 had worse prognoses than patients with higher expression of GRIN1 (p = 0.004). The GEPIA and LOGpc databases were used to verify the expression difference of GRIN1 among GBM, LGG, and normal brain tissues. Ultimately, immunohistochemical assay results showed that GRIN1 was detected in normal tissue and not in the tumor specimens. Our results highlight a potential target for glioma treatment and will further our understanding of the molecular mechanisms underlying the treatment of glioma.