RPP30, a transcriptional regulator, is a potential pathogenic factor in glioblastoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32702667", "kind": "science-record", "revision": 6, "content_hash": "sha256:c4b170aed335bb679dfeb470781cb71fb26cdf7d0866558c7b0c5c5109e5b1da", "created_at": "2026-11-01T15:41:06Z", "updated_at": "2026-11-01T21:23:33Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "RPP30, a transcriptional regulator, is a potential pathogenic factor in glioblastoma.", "doi": "10.18632/aging.103596", "pmid": "32702667", "authors": ["Guanzhang Li", "You Zhai", "Hanjie Liu", "Zhiliang Wang", "Ruoyu Huang", "Haoyu Jiang", "Yuemei Feng", "Yuanhao Chang", "Fan Wu", "Fan Zeng", "Tao Jiang", "Wei Zhang"], "journal": "Aging", "year": 2020, "abstract": "BACKGROUND: Old age has been demonstrated to be a risk factor for GBM, but the underlying biological mechanism is still unclear. We designed this study intending to determine a mechanistic explanation for the link between age and pathogenesis in GBM.\nRESULTS: The expression of RPP30, an independent prognostic factor in GBM, was negatively correlated with age in both tumor and non-tumor brain samples. However, the post-transcriptional modifications carried out by RPP30 were different in primary GBM and non-tumor brain samples. RPP30 affected protein expression of cancer pathways by performing RNA modifications. Further, we found that RPP30 was related to drug metabolism pathways important in GBM. The decreased expression of RPP30 in older patients might be a pathogenic factor for GBM.\nCONCLUSION: This study revealed the role of RPP30 in gliomagenesis and provided the theoretical foundation for targeted therapy.\nMETHODS: In total, 616 primary GBM samples and 41 non-tumor brain samples were enrolled in this study. Transcriptome data and clinical information were obtained from the CGGA, TCGA, and GSE53890 databases. Gene Set Variation Analysis and Gene Ontology analyses were the primary analytical methods used in this study. All statistical analyses were performed using R.", "claims": [{"id": "claim-method", "statement": "Age-related genes were screened out by pearson correlation analysis in primary GBM (from CGGA and TCGA databases) and non-tumor brain samples (from GSE53890).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32702667", "locator": "sections[15] \"Screening of candidate genes\" paragraph 2", "quote": "Age-related genes were screened out by pearson correlation analysis in primary GBM (from CGGA and TCGA databases) and non-tumor brain samples (from GSE53890)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The sequencing data of the CGGA database has been published on the CGGA portal website (http://www.cgga.org.cn/). 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We downloaded transcriptome microarray data from 507 samples of primary GBM from th", "https://cancergenome.nih.gov). Transcriptome microarray data from non-tumor brain samples were obtai"], "order_basis": "paper_text_order:5245", "id": "assay:1"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["re cultured in Astrocyte Medium (Gibco). All cell lines were cultured at 37 °C and 5% CO2. Statistical analysis St", ", Chinese Academy of Science. U87 cells were cultured in DMEM (Gibco) supplemented with 10% fetal bov", "0% fetal bovine serum (Gibco). HA cells were cultured in Astrocyte Medium (Gibco). 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