Apoptosis-related genes-based prognostic signature for osteosarcoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35504036", "kind": "science-record", "revision": 5, "content_hash": "sha256:e5542f0441a9aa58b257cf84b457dfa2828cc06db984010be82c143757d945d3", "created_at": "2026-11-01T18:14:23Z", "updated_at": "2026-11-01T22:48:59Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Apoptosis-related genes-based prognostic signature for osteosarcoma.", "doi": "10.18632/aging.204042", "pmid": "35504036", "authors": ["Fei Yang", "Yi Zhang"], "journal": "Aging", "year": 2022, "abstract": "Osteosarcoma (OS) is a common malignant primary tumor of skeleton, especially in children and adolescents, characterized by high lung metastasis rate. Apoptosis has been studied in various tumors, while the prognostic role of apoptosis-related genes in OS has been seldom studied. Three OS related datasets were downloaded from Gene Expression Omnibus (GEO) database. Univariate Cox and LASSO Cox regression analysis identified optimal genes, which were used for building prognostic Risk score. Subsequent multivariate Cox regression analysis and Kaplan-Meier survival analysis determined the independent prognostic factors for OS. The immune cell infiltration was analyzed in CIBERSORT. Basing on 680 apoptosis-related genes, the OS patients could be divided into 2 clusters with significantly different overall survival. Among which, 6 optimal genes were identified to construct Risk score. In both training set (GSE21257) and validation set (meta-GEO dataset), high risk OS patients had significantly worse overall survival compared with the low risk patients. Besides, high Risk score was an independent poor prognostic factor for OS with various ages or genders. Three immune cells were differentially infiltrated between high and low risk OS patients. In conclusion, a six-gene (TERT, TRAP1, DNM1L, BAG5, PLEKHF1 and PPP3CB) based prognostic Risk score signature is probably conducive to distinguish different prognosis of OS patients.", "claims": [{"id": "claim-method", "statement": "The overall survival rate was estimated basing on Kaplan-Meier method in survival and survminer package of R. The significance of difference among various groups was tested by log-rank test. Multivariate Cox regression analysis was used to find all independent prognostic factors for OS patients.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35504036", "locator": "sections[6] \"Survival analysis\" paragraph 2", "quote": "The overall survival rate was estimated basing on Kaplan-Meier method in survival and survminer package of R. The significance of difference among various groups was tested by log-rank test. Multivariate Cox regression analysis was used to find all independent prognostic factors for OS patients."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data generated and analyzed in this study are available from the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/) database.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35504036", "locator": "sections[10] \"Availability of data\" paragraph 2", "quote": "All data generated and analyzed in this study are available from the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/) database."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A six-gene prognostic Risk score signature comprising TERT, TRAP1, DNM1L, BAG5, PLEKHF1 and PPP3CB can distinguish prognosis in osteosarcoma patients.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35504036", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "In conclusion, a six-gene (TERT, TRAP1, DNM1L, BAG5, PLEKHF1 and PPP3CB) based prognostic Risk score signature is probably conducive to distinguish different prognosis of OS patients."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A six-gene prognostic Risk score signature comprising TERT, TRAP1, DNM1L, BAG5, PLEKHF1 and PPP3CB can distinguish prognosis in osteosarcoma patients.", "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:35504036"], "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:GSE16091"], "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:GSE16091"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35504036", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.18632/aging.204042", "sha256": 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