Glioma Subtypes Based on the Activity Changes of Immunologic and Hallmark Gene Sets in Cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35774141", "kind": "science-record", "revision": 4, "content_hash": "sha256:73266f14ee260896a9741332c0bfd869e0666b639e2609d2089d06f67c40cf5d", "created_at": "2026-11-01T18:14:48Z", "updated_at": "2026-11-01T22:06:55Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Glioma Subtypes Based on the Activity Changes of Immunologic and Hallmark Gene Sets in Cancer.", "doi": "10.3389/fendo.2022.879233", "pmid": "35774141", "authors": ["Sihan Chen"], "journal": "Frontiers in endocrinology", "year": 2022, "abstract": "Purpose: Glioma is the most common primary cranial brain tumor that arises from the cancelation of glial cells (which can be in the brain or spinal cord). It is due to innate genetic risk factors or induced by a carcinogenic environment. If left untreated, the disease has a poor prognosis.\nMethods: In this study, we downloaded glioma data from TCGA database and GEO (GSE4412). The GSEA database was used to screen tumor microenvironment-related gene sets. Cancer subtypes were classified by GSVA enrichment method.\nResults: By GSVA enrichment analysis, we obtain three Gliomas cancer subtypes. After further survival prognosis analysis and biological function analysis, we obtained 13 tumor microenvironment gene sets and 14 core genes that affect patients' survival prognosis, and these genes have the potential to become targets for targeted therapies and disease detection.\nConclusion: We screened a total of 13 gene sets through a series of enrichment analyses, statistical and prognostic analyses, etc. Among them, 14 core genes were identified, namely: TOP2A, TPX2, BUB1, AURKB, AURKA, CDK1, BUB1B, CCNA2, CCNB2, CDCA8, CDC20, KIF11, KIF20A and KIF2C.", "claims": [{"id": "claim-method", "statement": "least absolute shrinkage and selection operator (LASSO) were used to screen for sets of genes that potentially affect patient survival prognosis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35774141", "locator": "sections[5] \"Statistical Analysis\" paragraph 2", "quote": "least absolute shrinkage and selection operator (LASSO) were used to screen for sets of genes that potentially affect patient survival prognosis."}], "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:35774141", "locator": "sections[13] \"Data Availability Statement\" paragraph 2", "quote": "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."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Among them, 14 core genes were identified, namely: TOP2A, TPX2, BUB1, AURKB, AURKA, CDK1, BUB1B, CCNA2, CCNB2, CDCA8, CDC20, KIF11, KIF20A and KIF2C.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35774141", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Among them, 14 core genes were identified, namely: TOP2A, TPX2, BUB1, AURKB, AURKA, CDK1, BUB1B, CCNA2, CCNB2, CDCA8, CDC20, KIF11, KIF20A and KIF2C."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "Among them, 14 core genes were identified, namely: TOP2A, TPX2, BUB1, AURKB, AURKA, CDK1, BUB1B, CCNA2, CCNB2, CDCA8, CDC20, KIF11, KIF20A and KIF2C.", "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:35774141"], "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:GSE4412"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:group_comparison_wilcoxon", "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:GSE4412"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:group_comparison_wilcoxon"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35774141", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fendo.2022.879233", "sha256": "sha256:01de37ddc444b900ca0d6f51c9899479d836b592da90defb701e3b0a92873090", "bytes": 21956, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fendo.2022.879233", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9236851", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE4412", "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=GSE4412", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE4412", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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