Identification of core genes as potential biomarkers for predicting progression and prognosis in glioblastoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36238156", "kind": "science-record", "revision": 4, "content_hash": "sha256:7330972cdc769ec84ce1c3c9d8b6ddf9ba0d5ae5901a0ac7e664573b6d6dac13", "created_at": "2026-11-01T18:15:36Z", "updated_at": "2026-11-01T22:07:50Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of core genes as potential biomarkers for predicting progression and prognosis in glioblastoma.", "doi": "10.3389/fgene.2022.928407", "pmid": "36238156", "authors": ["Jianping Zeng", "Shushan Hua", "Jing Liu", "Rajneesh Mungur", "Yongsheng He", "Jiugeng Feng"], "journal": "Frontiers in genetics", "year": 2022, "abstract": "Background: Glioblastoma is a common malignant neuroepithelial neoplasm with poor clinical outcomes and limited treatment options. It is extremely important to search and confirm diverse hub genes that are effective in the advance and prediction of glioblastoma. Methods: We analyzed GSE50161, GSE4290, and GSE68848, the three microarray datasets retrieved from the GEO database. GO function and KEGG pathway enrichment analyses for differentially expressed genes (DEGs) were performed using DAVID. The PPI network of the DEGs was analyzed using the Search Tool for the Retrieval of Interacting Genes database and visualized by Cytoscape software. Hub genes were identified through the PPI network and a robust rank aggregation method. The Cancer Genome Atlas (TCGA) and the Oncomine database were used to validate the hub genes. In addition, a survival curve analysis was conducted to verify the correlation between the expression of hub genes and patient prognosis. Human glioblastoma cells and normal cells were collected, and then RT-PCR, Western blot, and immunofluorescence were conducted to validate the expression of the NDC80 gene. A cell proliferation assay was used to detect the proliferation of glioma cells. The effects of NDC80 expression on migration and invasion of GBM cell lines were evaluated by conducting scratch and transwell assays. Results: A total of 716 DEGs were common to all three microarray datasets, which included 188 upregulated DEGs and 528 downregulated DEGs. Furthermore, we found that among the common DEGs, 10 hub genes showed a high degree of connectivity. The expression of the 10 hub genes in TCGA and the Oncomine database was significantly overexpressed in glioblastoma compared with normal genes. Additionally, the survival analysis showed that the patients with low expression of six genes (BIR5C, CDC20, NDC80, CDK1, TOP2A, and MELK) had a significantly favorable prognosis (p < 0.01). We discovered that NDC80, which has been shown to be important in other cancers, also has an important role in malignant gliomas. The RT-PCR, Western blot, and immunofluorescence results showed that the expression level of NDC80 was significantly higher in human glioblastoma cells than in normal cells. Moreover, we identified that NDC80 increased the proliferation and invasion abilities of human glioblastoma cells. Conclusion: The six genes identified here may be utilized to form a panel of disease progression and predictive biomarkers of glioblastoma for clinical purposes. NDC80, one of the six genes, was discovered to have a potentially important role in GBM, a finding that needs to be further studied.", "claims": [{"id": "claim-method", "statement": "The DEGs between GBM and normal samples were identified by using the online analysis tool GEO2R (https://www.ncbi.nlm. nih.gov/geo/geo2r/) for the GEO database, based on the R language.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36238156", "locator": "sections[4] \"Data processing of DEGs\" paragraph 2", "quote": "The DEGs between GBM and normal samples were identified by using the online analysis tool GEO2R (https://www.ncbi.nlm. nih.gov/geo/geo2r/) for the GEO database, based on the R language."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36238156", "locator": "sections[27] \"Data availability statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. 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