The value of a metabolic and immune-related gene signature and adjuvant therapeutic response in pancreatic cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39867576", "kind": "science-record", "revision": 3, "content_hash": "sha256:4de656aee3fc44c2c2f20ac8dc815de821ab7fd4ecaa8a1f0c57ed2fd9693ba7", "created_at": "2026-11-01T20:30:09Z", "updated_at": "2026-11-01T22:13:34Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "The value of a metabolic and immune-related gene signature and adjuvant therapeutic response in pancreatic cancer.", "doi": "10.3389/fgene.2024.1475378", "pmid": "39867576", "authors": ["Danlei Ni", "Jiayi Wu", "Jingjing Pan", "Yajing Liang", "Zihui Xu", "Zhiying Yan", "Kequn Xu", "Feifei Wei"], "journal": "Frontiers in genetics", "year": 2024, "abstract": "Background: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy characterized by a dismal prognosis. Treatment outcomes exhibit substantial variability across patients, underscoring the urgent need for robust predictive models to effectively estimate survival probabilities and therapeutic responses in PDAC.\nMethods: Metabolic and immune-related genes exhibiting differential expression were identified using the TCGA-PDAC and GTEx datasets. A genetic prognostic model was developed via univariable Cox regression analysis on a training cohort. Predictive accuracy was assessed using Kaplan-Meier (K-M) curves, calibration plots, and ROC curves. Additional analyses, including GSAE and immune cell infiltration studies, were conducted to explore relevant biological mechanisms and predict therapeutic efficacy.\nResults: An 8-gene prognostic model (AK2, CXCL11, TYK2, ANGPT4, IL20RA, MET, ENPP6, and CA12) was established. Three genes (AK2, ENPP6, and CA12) were associated with metabolism, while the others were immune-related. Most genes correlated with poor prognosis. Validation in TCGA-PDAC and GSE57495 datasets demonstrated robust performance, with AUC values for 1-, 3-, and 5-year OS exceeding 0.7. The model also effectively predicted responses to adjuvant therapy.\nConclusion: This 8-gene signature enhances prognostic accuracy and therapeutic decision-making in PDAC, offering valuable insights for clinical applications and personalized treatment strategies.", "claims": [{"id": "claim-method", "statement": "Prognostic genes were identified using univariable Cox regression analysis (p < 0.001).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39867576", "locator": "sections[5] \"Establishment of the 8-gene signature\" paragraph 2", "quote": "Prognostic genes were identified using univariable Cox regression analysis (p < 0.001)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39867576", "locator": "sections[22] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Validation in TCGA-PDAC and GSE57495 datasets demonstrated robust performance, with AUC values for 1-, 3-, and 5-year OS exceeding 0.7.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39867576", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Validation in TCGA-PDAC and GSE57495 datasets demonstrated robust performance, with AUC values for 1-, 3-, and 5-year OS exceeding 0.7."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Validation in TCGA-PDAC and GSE57495 datasets demonstrated robust performance, with AUC values for 1-, 3-, and 5-year OS exceeding 0.7.", "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:39867576"], "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. 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