ArticleInternational journal of clinical and experimental pathology2026
TMEM161B-AS1: a pivotal long non-coding RNA in the pathogenesis of glioblastoma revealed by Mendelian randomization analysis.
Article in International journal of clinical and experimental pathology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesThe significance of long non-coding RNAs (lncRNAs) in glioblastoma multiforme (GBM) has been acknowledged, but their specific role in the pathogenesis of GBM has not been thoroughly investigatedr. This study aimed to investigate the involvement of lncRNAs in the pathogenesis of GBM.
methodsWe collected GBM tissues from four patients and corresponding para-carcinoma controls samples, and used HiSeq sequencing to generate lncRNA expression profiles in GBM. To identify lncRNAs associated with GBM, we employed Mendelian randomization (MR), leveraging the comprehensive extensive expression data obtained from HiSeq sequencing to infer causal relationships. Expression quantitative trait loci (eQTLs) for brain tissues were accessed from the Genotype-Tissue Expression (GTEx) Portal. Subsequently, we conducted an integrative analysis combining brain cancer genome-wide association study (GWAS) summary data (finn-b-C3_GBM) with eQTL data using MR. Differentially expressed lncRNAs were intersected with MR results to identify lncRNA candidates. Subsequently, the ENCORI database was used to identify genes regulated by the candidate lncRNAs, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed.
resultA protein-protein interaction (PPI) network was constructed to identify hub genes associated with GBM, and these findings were validated using the Gene Expression Profiling Interactive Analysis 2 (GEPIA2) tool. A total of 106 lncRNAs exhibited significant alterations in expression levels (|log
conclusionsThese findings suggest pathways for the development of more precise and sensitive biomarkers for the diagnosis and management of GBM, which may ultimately enhance patient outcomes.
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