Screening and identification of LMNB1 and DLGAP5, two key biomarkers in gliomas.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33956061", "kind": "science-record", "revision": 7, "content_hash": "sha256:3415c5e592106492175fc857ed0e2240ebe1ab876b62e9b4fd5b6a2c316bf06e", "created_at": "2026-11-01T15:41:34Z", "updated_at": "2026-11-01T22:03:42Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Screening and identification of LMNB1 and DLGAP5, two key biomarkers in gliomas.", "doi": "10.1042/BSR20210231", "pmid": "33956061", "authors": ["Ding Zhou", "Mengmeng Wang", "Yu Zhang", "Kai Wang", "Min Zhao", "Yan Wang", "Xu Wang", "Rutong Yu", "Xiuping Zhou"], "journal": "Bioscience reports", "year": 2021, "abstract": "Glioma is the most common primary cancer in the central nervous system. Despite advances in surgery, radiotherapy and chemotherapy over the past decades, the prognosis of glioblastoma patients remains poor. We aim to identify robust gene signatures to better understand the complex molecular mechanisms and to discover potential novel molecular biomarkers for glioma. By exploring GSE16011, GSE4290 and GSE50161 data in Gene Expression Omnibus (GEO) database, we screened out 380 differentially expressed genes between non-tumor and glioma tissues, and further selected 30 hub genes through the Molecular Complex Detection (MCODE) plug-in in Cytoscape. In addition, LMNB1 and DLGAP5 were selected for further analyses due to their high expression in gliomas and were verified by using our cohort. Our study confirmed that LMNB1 and DLGAP5 were up-regulated in gliomas, and patients with high expression of LMNB1 or DLGAP5 had poor survival rate. Furthermore, silence of LMNB1 and DLGAP5 inhibited the proliferation of glioma cells. Together, LMNB1 and DLGAP5 were two potentially novel molecular biomarkers for diagnosis and prognosis of glioma.", "claims": [{"id": "claim-method", "statement": "Kaplan–Meier survival analyses was used to estimate the survival distribution, followed by a log‐rank test evaluating the difference between stratified groups, using the median value as the cutoff.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33956061", "locator": "sections[13] \"Statistical analysis\" paragraph 2", "quote": "Kaplan–Meier survival analyses was used to estimate the survival distribution, followed by a log‐rank test evaluating the difference between stratified groups, using the median value as the cutoff."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data underlying this study are freely available from GEO database (https://www.ncbi.nlm.nih.gov/geo/), UCSC-TCGA (http://genome-cancer.ucsc.edu) and CGGA (http://www.cgga.org.cn/index.jsp). 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