Comprehensive analysis of a TNF family based-signature in diffuse gliomas with regard to prognosis and immune significance.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35000592", "kind": "science-record", "revision": 4, "content_hash": "sha256:3e0daef507432c5c21090a745fba2d8bc98c494ee52e95e45f6d0c88f2752b43", "created_at": "2026-11-01T17:36:43Z", "updated_at": "2026-11-01T22:05:32Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Comprehensive analysis of a TNF family based-signature in diffuse gliomas with regard to prognosis and immune significance.", "doi": "10.1186/s12964-021-00814-y", "pmid": "35000592", "authors": ["Qiang-Wei Wang", "Wei-Wei Lin", "Yong-Jian Zhu"], "journal": "Cell communication and signaling : CCS", "year": 2022, "abstract": "BACKGROUND: Several studies have shown that members of the tumor necrosis factor (TNF) family play an important role in cancer immunoregulation, and trials targeting these molecules are already underway. Our study aimed to integrate and analyze the expression patterns and clinical significance of TNF family-related genes in gliomas.\nMETHODS: A total of 1749 gliomas from 4 datasets were enrolled in our study, including the Cancer Genome Atlas (TCGA) dataset as the training cohort and the other three datasets (CGGA, GSE16011, and Rembrandt) as validation cohorts. Clinical information, RNA expression data, and genomic profile were collected for analysis. We screened the signature gene set by Cox proportional hazards modelling. We evaluated the prognostic value of the signature by Kaplan-Meier analysis and timeROC curve. Gene Ontology (GO) and Gene set enrichment analysis (GSEA) analysis were performed for functional annotation. CIBERSORT algorithm and inflammatory metagenes were used to reveal immune characteristics.\nRESULTS: In gliomas, the expression of most TNF family members was positively correlated. Univariate analysis showed that most TNF family members were related to the overall survival of patients. Then through the LASSO regression model, we developed a TNF family-based signature, which was related to clinical, molecular, and genetic characteristics of patients with glioma. Moreover, the signature was found to be an independent prognostic marker through survival curve analysis and Cox regression analysis. Furthermore, a nomogram prognostic model was constructed to predict individual survival rates at 1, 3 and 5 years. Functional annotation analysis revealed that the immune and inflammatory response pathways were enriched in the high-risk group. Immunological analysis showed the immunosuppressive status in the high-risk group.\nCONCLUSIONS: We developed a TNF family-based signature to predict the prognosis of patients with glioma. Video abstract.", "claims": [{"id": "claim-method", "statement": "By LASSO regression algorithm, we screened eight genes as covariates to evaluate prognostic value (Fig. 1a).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35000592", "locator": "sections[10] \"Identification of a TNF family based-signature in gliomas\" paragraph 2", "quote": "By LASSO regression algorithm, we screened eight genes as covariates to evaluate prognostic value (Fig. 1a)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The authors confirm the data that has been used in this work is available on reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35000592", "locator": "sections[26] \"notes\" paragraph 1", "quote": "The authors confirm the data that has been used in this work is available on reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We developed a TNF family-based signature to predict the prognosis of patients with glioma.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35000592", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "We developed a TNF family-based signature to predict the prognosis of patients with glioma."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "We developed a TNF family-based signature to predict the prognosis of patients with glioma.", "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:35000592"], "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:GSE108474"], "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:GSE108474"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35000592", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12964-021-00814-y", "sha256": 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