Glioblastoma (GBM) is one of the most common and fatal malignancies worldwide, while its prognostic biomarkers are still being explored. This study aims to identify potential genes with clinical and prognostic significance by integrating bioinformatics analysis and investigating their function in HNSCC. Based on the Single-cell RNA sequencing (scRNA-seq) results of H3K27M-glioma cells, computational bioinformatics methods were employed for selecting prognostic biomarker for GBM. The protein NPC2 (NPC Intracellular Cholesterol Transporter 2), which has been shown to be related to lipoprotein metabolism and innate immune system, was identified to be upregulated in GBM. NPC2 showed a relatively higher expression in GBM samples, and a negative correlation with tumor purity and tumor infiltrating immune cells. Additionally, NPC2 was knocked down in U87-MG and U251 cells line, and cell proliferation and migration capability were evaluated with CCK-8, scratch and transwell assay, respectively. Cytological experiments has shown that NPC2 overexpression inhibited GBM cells proliferation and migration, indicating its important role in GBM progression. This is the first investigation into the prognostic value of NPC2 interact with GBM. The potential molecular factor NPC2 have been identified as a prognostic biomarker for GBM.

Contributions: (I) Conception and design: F Lu; (II) Administrative support: SH Shen; (III) Provision of study materials or patients: S Wu; (IV)

Background: Glioblastoma multiforme (GBM) is the most common type of glioma, and the most aggressive brain malignancy in adults. This study sought to identify novel survival-status related markers, and examine their function in glioma. Methods:The gene expression, survival heatmaps, and Kaplan-Meier survival plots of the genes were analyzed by using gene expression profiling interactive analysis (GEPIA) dataset, Linked Omics. The singlecell data analysis and tumor immune infiltration analysis was conducted by Tumor Immune Estimation Resource (TIMER) dataset. DBTRG and U251 cells with silenced Deltex E3 ubiquitin ligase 2 (DTX2) expression were constructed and used for Cell Counting Kit 8 (CCK-8), and wound healing assay in vitro.Chromatin immunoprecipitation sequencing (ChIP-seq) analysis was used to explore the histone activation marks and transcription factors DTX2 promoter. Dual-luciferase assays were carried out to detect the luciferase activities of bromodomain containing 4 (BRD4) binding to DTX2. Results:We first conducted a survival-status analysis to identify survival status-related genes in The Cancer Genome Atlas GBM and low-grade glioma data sets. A subsequent analysis identified 3 novel prognostic biomarkers; that is, DTX2, cytochrome P450 oxidoreductase, and Williams-Beuren syndrome chromosomal region 16 protein. In the validation Chinese Glioma Genome Atlas data sets, DTX2 showed the best performance, and was examined in a further analysis. Next, 3 short-hairpin ribonucleic acids were designed to silence DTX2 expression, and CCK-8 and wound-healing assays were applied to study the function of DTX2. We found that DTX2-silenced glioma cells exhibited a significant decrease in their growth and migration capabilities. Finally, the molecular basis for increased DTX2 in glioma was investigated via ChIP-Seq analysis and luciferase assays. The analysis revealed that DTX2 was transcriptionally activated by BRD4. Conclusions:In conclusion, BRD4 transcriptionally activates DTX2, contributes to glioma progression, predicts an unfavorable prognosis, and could provide new options for glioma prognosis prediction and treatment.

Glioblastoma (GBM) is the most common and aggressive malignant primary brain tumor. E3 ligases play important functions in glioma pathogenesis. CRISPR system offers a powerful platform for genome manipulation, while the screen of E3 ligases in GBM still remains to be explored. Here, we first constructed an E3 ligase small guide RNA (sgRNAs) library for glioma cells growth screening. After four passages, 299 significantly enriched or lost genes (SELGs) were compared with the initial state. Then the clinical significance of SELGs were validated and analyzed with TCGA glioblastoma and CGGA datasets. As RNF185 showed lost signal, decreased expression and favorable prognostic significance, we chose RNF185 for functional analysis. In vitro overexpressed cellular phenotype showed that RNF185 was a tumor suppressor in two glioma cell lines. Finally, the molecular mechanism of decreased RNF185 expression was investigated and increased miR-587 expression and DNA hypermethylation was evaluated. This study would provide a link between the molecular basis and glioblastoma pathogenesis, and a novel perspective for glioblastoma treatment.