Integrated Analysis to Evaluate the Prognostic Value of Signature mRNAs in Glioblastoma Multiforme.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32296458", "kind": "science-record", "revision": 8, "content_hash": "sha256:d94f710b97c0dbbd854ef6646fe2a7cdc780fa7aabdaaf53ab6cc94509443548", "created_at": "2026-11-01T15:40:59Z", "updated_at": "2026-11-01T22:44:45Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integrated Analysis to Evaluate the Prognostic Value of Signature mRNAs in Glioblastoma Multiforme.", "doi": "10.3389/fgene.2020.00253", "pmid": "32296458", "authors": ["Ji'an Yang", "Long Wang", "Zhou Xu", "Liquan Wu", "Baohui Liu", "Junmin Wang", "Daofeng Tian", "Xiaoxing Xiong", "Qianxue Chen"], "journal": "Frontiers in genetics", "year": 2020, "abstract": "BACKGROUND: Gliomas are the most common intracranial tumors and are classified as I-IV. Among them, glioblastoma multiforme (GBM) is the most common invasive glioma with a poor prognosis. New molecular biomarkers that can predict clinical outcomes in GBM patients must be identified, which will help comprehend their pathogenesis and supply personalized treatment. Our research revealed four powerful survival indicators in GBM by reanalyzing microarray data and genetic sequencing data in public databases. Moreover, it unraveled new potential therapeutic targets which could help improve the survival time and quality of life of GBM patients.\nMATERIALS AND METHODS: To identify prognostic signatures in GBMs, we analyzed the gene profiling data of GBM and standard brain samples from the Gene Expression Omnibus, including four datasets and RNA sequencing data from The Cancer Genome Atlas (TCGA) containing 152 glioblastoma tissues. We performed the differential analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, weighted gene co-expression network analysis (WGCNA) and Cox regression analysis.\nRESULTS: After differential analysis in GSE12657, GSE15824, GSE42656 and GSE50161, overlapping differentially expressed genes were identified. We identified 110 up-regulated DEGs and 75 down-regulated DEGs in the GBM samples. Significantly enriched subclasses of the GO classification of these genes included mitotic sister chromatid separation, mitotic nuclear division and so on. In KEGG pathway analysis, the most abundant terms were ECM-receptor interaction and protein digestion and absorption. WGCNA analysis was performed on these 185 DEGs in 152 glioblastoma samples obtained from TCGA, and gene co-expression networks were constructed. We then performed a multivariate Cox analysis and established a Cox proportional hazards regression model using the top 20 genes significantly correlated with survival time. We identified a four-protein prognostic signature that could divide patients into high-risk and low-risk groups. Increased expression of SLC12A5, CCL2, IGFBP2, and PDPN was associated with increased risk scores. Finally, the K-M curves confirmed that these genes could be used as independent predictors of survival in patients with glioblastoma.\nCONCLUSION: Our analytical study identified a set of potential biomarkers that could predict survival and may contribute to successful treatment of GBM patients.", "claims": [{"id": "claim-method", "statement": "In our research, we identified 185 DEGs for GBM derived from independent profiling datasets by applying “limma” algorithm and “RRA” method.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32296458", "locator": "sections[16] \"Discussion\" paragraph 2", "quote": "In our research, we identified 185 DEGs for GBM derived from independent profiling datasets by applying “limma” algorithm and “RRA” method."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Microarray data were retrieved from the GEO data repository (http://www.ncbi.nlm.nih.gov/geo/) with the accession numbers: GSE12657, GSE50161, GSE42656, and GSE15824. The RNA sequencing data of human glioblastoma samples were obtained from the TCGA data portal (https://portal.gdc.cancer.gov).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32296458", "locator": "sections[17] \"Data Availability Statement\" paragraph 2", "quote": "Microarray data were retrieved from the GEO data repository (http://www.ncbi.nlm.nih.gov/geo/) with the accession numbers: GSE12657, GSE50161, GSE42656, and GSE15824. The RNA sequencing data of human glioblastoma samples were obtained from the TCGA data portal (https://portal.gdc.cancer.gov)."}], "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:32296458"], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE12657"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE12657"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:32296458", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fgene.2020.00253", "sha256": "sha256:081fece6aba69b630551715518669d0c76351b95684c5b96e81cfed9d509b963", "bytes": 23200, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fgene.2020.00253", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC7136556", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE12657", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE12657", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE12657", "version": null, "note": "Microarray data were retrieved from the GEO data repository (http://www.ncbi.nlm.nih.gov/geo/) with the accession numbers: GSE12657, GSE50161, GSE42656, and GSE15824. The RNA sequencing data of human glioblastoma samples were obtained from the TCGA data portal (https://portal.gdc.cancer.gov).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Microarray data were retrieved from the GEO data repository (http://www.ncbi.nlm.nih.gov/geo/) with the accession numbers: GSE12657, GSE50161, GSE42656, and GSE15824. 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