Highly Expressed CYBRD1 Associated with Glioma Recurrence Regulates the Immune Response of Glioma Cells to Interferon

Integrated Analysis of Multiomics Data Identified Molecular Subtypes and Oxidative Stress-Related Prognostic Biomarkers in Glioblastoma Multiforme

Glioblastoma multiforme (GBM) is a glioma in IV stage, which is one of the most common primary malignant brain tumors in adults. GBM has the characters of high invasiveness, high recurrence rate, and low survival rate and with a poor prognosis. GBM implicates various genetic changes and epigenetic and gene transcription disorders, which are crucial in developing GBM. With the progression and enhancement of high-throughput sequencing technologies, the acquirement and administering approaches of diverse biological omics data on distinctive levels are developing more advanced. However, the research of GBM with multiomics remains largely unknown. We identified GBM-related molecular subtypes by integrated multiomics data and exploring the connections of gene copy number variation (CNV) and methylation gene (MET) change data. The expression of CNV and MET genes was examined through cluster integration analysis. The present study confirmed three clusters (iC1, iC2, and iC3) with distinctive prognosis and molecule peculiarities. We also recognized three oxidative stress protecting molecules (OSMR, IGFBP6, and MYBPH) by contrasting gene expression, MET, and CNV in the three subtypes. OSMR, IGFBP6, and MYBPH were differentially expressed in the clusters, suggesting they might be recognized as characteristic markers for the three clusters in GBM. Through integrative investigation of genomics, epigenomics, and transcriptomics, we offer novel visions into the multilayered molecules of GBM and facilitate the accuracy remedy for GBM sufferers.

Identification of Novel Key Genes and Pathways in Multiple Sclerosis Based on Weighted Gene Coexpression Network Analysis and Long Noncoding RNA-Associated Competing Endogenous RNA Network

Objective

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system characterized by chronic inflammation and demyelination. This study is aimed at identifying crucial genes and molecular pathways involved in MS pathogenesis.

Methods

Raw data in GSE52139 were collected from the Gene Expression Omnibus. The top 50% expression variants were subjected to weighted gene coexpression network analysis (WGCNA), and the key module associated with MS occurrence was identified. A long noncoding RNA- (lncRNA-) associated competing endogenous RNA (ceRNA) network was constructed in the key module. The hub gene candidates were subsequently verified in an individual database.

Results

Of the 18 modules obtained, the cyan module was designated as the key module. The established ceRNA network was composed of seven lncRNAs, 45 mRNAs, and 21 microRNAs (miRNAs), and the FAM13A-AS1 was the lncRNA with the highest centrality. Functional assessments indicated that the genes in the cyan module primarily gathered in ribosome-related functional terms. Interestingly, the targeted mRNAs of the ceRNA network enriched in diverse categories. Moreover, highly expressed CYBRD1, GNG12, and SMAD1, which were identified as hub genes, may be associated with “valine leucine and isoleucine degradation,” “base excision repair,” and “fatty acid metabolism,” respectively, according to the results of single gene-based genomes and gene set enrichment analysis (GSEA).

Conclusions

Combined with the WGCNA and ceRNA network, our findings provide novel insights into the pathogenesis of MS. The hub genes discovered herein might also serve as novel biomarkers that correlate with the development and management of MS.