Construction and comprehensive analysis of a competitive endogenous RNA network to reveal potential biomarkers for the malignant differentiation of glioma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34596120", "kind": "science-record", "revision": 7, "content_hash": "sha256:21281ca36361b84d345f5068908ae3c1da261d7cca47fce935fc443a1cd51113", "created_at": "2026-11-01T15:41:55Z", "updated_at": "2026-11-01T21:26:21Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Construction and comprehensive analysis of a competitive endogenous RNA network to reveal potential biomarkers for the malignant differentiation of glioma.", "doi": "10.1097/MD.0000000000027248", "pmid": "34596120", "authors": ["Xin Li", "Jingwen Zhang", "Min Zhang", "Xianghua Qi", "Shiyuan Wang", "Jing Teng"], "journal": "Medicine", "year": 2021, "abstract": "BACKGROUND: Long noncoding RNAs (lncRNAs) can act as microRNA (miRNA) sponges to regulate protein-coding gene expression; therefore, lncRNAs are considered major components of the competitive endogenous RNA (ceRNA) network and have attracted growing attention. This study explored the regulatory mechanisms and functional roles of lncRNAs as ceRNAs in the malignant differentiation of low-grade glioma (LGG) to glioblastoma (GBM) and their potential impact on the prognosis of patients with GBM.\nMETHODS: LncRNA and messenger RNA (mRNA) data were extracted from the Cancer Genome Atlas (TCGA) database from 156 GBM samples and 529 LGG samples. Separately, the miRNA expression data were downloaded from the Gene Expression Omnibus database, with the GSE112009 dataset containing miRNA expression data from 10 GBM samples and 15 LGG samples. Weighted gene coexpression network analysis was performed to screen the glioma grade-related lncRNAs. Then, a ceRNA network was established. The database for annotation, visualization, and integrated discovery was adopted to conduct functional enrichment analysis based on 57 upregulated differentially expressed mRNAs in the ceRNA network. Finally, Kaplan-Meier curves were created for the survival analysis of 13 hub lncRNA by combining the clinical data of GBM patients in TCGA.\nRESULTS: A ceRNA network including 16 lncRNAs, 18 miRNAs, and 78 mRNAs specific to the malignant differentiation of LGG to GBM was established. The 57 upregulated differentially expressed mRNAs in the ceRNA network were significantly enriched in 35 gene ontology terms and 5 pathways. The survival analysis showed that 2 lncRNAs (LINC00261 and HOXA10-AS) were prognostic biomarkers for patients with GBM in TCGA.\nCONCLUSION: The proposed ceRNA network may help elucidate the regulatory mechanism by which lncRNAs function as ceRNAs and contribute to the malignant differentiation of LGG to GBM. Importantly, the candidate lncRNAs, miRNAs, and mRNAs involved in the ceRNA network can be further evaluated as potential therapeutic targets and prognostic biomarkers for GBM.", "claims": [{"id": "claim-data-access", "statement": "Available lncRNA-seq and mRNA-seq data from 529 LGG samples (of WHO grades I, II, and III) and 156 GBM samples were collected from the Cancer Genome Atlas (TCGA) database (https://tcga-data.nci.nih.gov/) on February 1, 2020.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34596120", "locator": "sections[3] \"Data collection and preprocessing\" paragraph 2", "quote": "Available lncRNA-seq and mRNA-seq data from 529 LGG samples (of WHO grades I, II, and III) and 156 GBM samples were collected from the Cancer Genome Atlas (TCGA) database (https://tcga-data.nci.nih.gov/) on February 1, 2020."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:34596120"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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