Identification of a metabolic-related gene signature predicting the overall survival for patients with stomach adenocarcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33614297", "kind": "science-record", "revision": 7, "content_hash": "sha256:3e9a3d20f2db75fb2e6671610dcd418b199b5a35bf49694e64b1be2ef10c8a94", "created_at": "2026-11-01T15:41:26Z", "updated_at": "2026-11-01T22:03:10Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of a metabolic-related gene signature predicting the overall survival for patients with stomach adenocarcinoma.", "doi": "10.7717/peerj.10908", "pmid": "33614297", "authors": ["Yuan Nie", "Linxiang Liu", "Qi Liu", "Xuan Zhu"], "journal": "PeerJ", "year": 2021, "abstract": "BACKGROUND: The reprogramming of energy metabolism and consistently altered metabolic genes are new features of cancer, and their prognostic roles remain to be further studied in stomach adenocarcinoma (STAD).\nMETHODS: Messenger RNA (mRNA) expression profiles and clinicopathological data were downloaded from The Cancer Genome Atlas (TCGA) and the GSE84437 databases from the Gene Expression Omnibus (GEO) database. A univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression model established a novel metabolic signature based on TCGA. The area under the receiver operating characteristic (ROC) curve (AUROC) and a nomogram were calculated to assess the predictive accuracy.\nRESULTS: A novel metabolic-related signature (including acylphosphatase 1, RNA polymerase I subunit A, retinol dehydrogenase 12, 5-oxoprolinase, ATP-hydrolyzing, malic enzyme 1, nicotinamide N-methyltransferase, gamma-glutamyl transferase 5, deoxycytidine kinase, galactosidase alpha, DNA polymerase delta 3, glutathione S-transferase alpha 2, N-acyl sphingosine amidohydrolase 1, and N-acyl sphingosine amidohydrolase 1) was identified. In both TCGA and GSE84437, patients in the high-risk group showed significantly poorersurvival than the patients in the low-risk group. A good predictive value was shown by the AUROC and nomogram. Furthermore, gene set enrichment analyses (GSEAs) revealed several significantly enriched pathways, which may help in explaining the underlying mechanisms.\nCONCLUSIONS: A novel robust metabolic-related signature for STAD prognosis prediction was conducted. The signature may reflect the dysregulated metabolic microenvironment and can provided potential biomarkers for metabolic therapy in STAD.", "claims": [{"id": "claim-method", "statement": "The prognosis-related metabolic genes were confirmed by combining the univariate Cox regression and LASSO penalized Cox regression analysis and to set up a new prognostic gene signature.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33614297", "locator": "sections[5] \"Construction of the prognostic metabolic gene signature\" paragraph 2", "quote": "The prognosis-related metabolic genes were confirmed by combining the univariate Cox regression and LASSO penalized Cox regression analysis and to set up a new prognostic gene signature."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The following information was supplied regarding data availability:The source codes and collected data are available in the Supplemental Files.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33614297", "locator": "sections[15] \"Additional Information and Declarations\" paragraph 4", "quote": "The following information was supplied regarding data availability:The source codes and collected data are available in the Supplemental Files."}], "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:33614297"], "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:GSE84437"], "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:GSE84437"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33614297", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.7717/peerj.10908", "sha256": 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