ArticleMolecular medicine reports2015
Identification of differential splicing genes in gliomas using exon expression profiling.
Article in Molecular medicine reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 24 citations in OpenAlex.
- Identification and characterisation of calcitonin receptor isoforms expressed in glioblastoma derived glioma stem and U-87 MG cells.FEBS open bio · 2026Article
- ATRT-SHH comprises three molecular subgroups with characteristic clinical and histopathological features and prognostic significance.Acta neuropathologica · 2022Article
- OKN-007 Alters Protein Expression Profiles in High-Grade Gliomas: Mass Spectral Analysis of Blood Sera.Brain sciences · 2022Article
- A comprehensive characterization of the transcriptome in enzalutamide resistance prostate cancer.Annals of translational medicine · 2021Article
- Genome-wide profiling of alternative splicing in glioblastoma and their clinical value.BMC cancer · 2021Article
- Review
- Article
- Prognostic alternative splicing signature reveals the landscape of immune infiltration in Pancreatic Cancer.Journal of Cancer · 2020Article
- RNA processing genes characterize RNA splicing and further stratify lower-grade glioma.JCI insight · 2019Article
- Current Challenges and Opportunities in Treating Glioblastoma.Pharmacological reviews · 2018Article
- Computer Analysis of Glioma Transcriptome Profiling: Alternative Splicing Events.Journal of integrative bioinformatics · 2017Article
- Contactin-2/TAG-1, active on the front line for three decades.Cell adhesion & migration · 2017Article
- RNA processing as an alternative route to attack glioblastoma.Human genetics · 2017Review
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diffuse gliomas are the most common type of malignant primary brain tumor, and their initiation and/or progression are often associated with alternative splicing. They produce an enormous economic burden on society and greatly impair the quality of life of those affected. The aim of the current study was to explore the differentially expressed genes (DEGs) observed in glioblastoma (GBM) and oligodendroglioma (OD) at the splicing level, and to analyze their functions in order to identify the underlying molecular mechanisms of gliomas. The exon‑level expression profile data GSE9385 was downloaded from the Gene Expression Omnibus database, and included 26 GBM samples, 22 OD samples and 6 control brain samples. The differentially expressed exon‑level probes were analyzed using the microarray detection of alternative splicing algorithm combined with the splicing index method, and the corresponding DEGs were identified. Next, a Gene Ontology enrichment analysis of the DEGs was performed. Additionally, the protein‑protein interaction (PPI) networks were constructed based on the depth‑first search algorithm. A total of 300 DEGs were identified to be shared by GBM and OD, including 97 upregulated and 203 downregulated DEGs. Furthermore, screening with a defined threshold identified 6 genes that were highly expressed in GBM, including AFF2, CACNA2D3 and ARPP21, while the 6 highly expressed genes in OD notably included CNTN2. The TP53 and HIST1H3A genes were the hub nodes in the PPI network of DEGs from GBM, while CNTN2 was linked to the highest degree in the OD PPI network. The present study provides a comprehensive bioinformatics analysis of DEGs in GBM and OD, which may provide a basis for understanding the initiation and/or progression of glioma development.
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