Lipid metabolism gene-wide profile and survival signature of lung adenocarcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33050938", "kind": "science-record", "revision": 8, "content_hash": "sha256:bff264ae21825dc96439147e1911f663925d00206092c29c34ac573cce965ca4", "created_at": "2026-11-01T15:41:13Z", "updated_at": "2026-11-01T22:45:27Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Lipid metabolism gene-wide profile and survival signature of lung adenocarcinoma.", "doi": "10.1186/s12944-020-01390-9", "pmid": "33050938", "authors": ["Jinyou Li", "Qiang Li", "Zhenyu Su", "Qi Sun", "Yong Zhao", "Tienan Feng", "Jiayuan Jiang", "Feng Zhang", "Haitao Ma"], "journal": "Lipids in health and disease", "year": 2020, "abstract": "BACKGROUND: Lung cancer has high morbidity and mortality across the globe, and lung adenocarcinoma (LUAD) is the most common histologic subtype. Disordered lipid metabolism is related to the development of cancer. Analysis of lipid-related transcriptome helps shed light on the diagnosis and prognostic biomarkers of LUAD.\nMETHODS: In this study, expression analysis of 1045 lipid metabolism-related genes was performed between LUAD tumors and normal tissues derived from the Cancer Genome Atlas Lung Adenocarcinoma (TCGA-LUAD) cohort. The interaction network of differentially expressed genes (DEGs) was constructed to identify the hub genes. The association between hub genes and overall survival (OS) was evaluated and formed a model to predict the prognosis of LUAD using a nomogram. The model was validated by another cohort, GSE13213.\nRESULTS: A total of 217 lipid metabolism-related DEGs were detected in LUAD. Genes were significantly enriched in glycerophospholipid metabolism, fatty acid metabolic process, and eicosanoid signaling. Through network analysis and cytoHubba, 6 hub genes were identified, including INS, LPL, HPGDS, DGAT1, UGT1A6, and CYP2C9. High expression of CYP2C9, UGT1A6, and INS, and low expressions of DGAT1, HPGDS, and LPL, were associated with worse overall survival for 1925 LUAD patients. The model showed that the high-risk score group had a worse OS, and the validated cohort showed the same result.\nCONCLUSIONS: In this study, a signature of 6 lipid metabolism genes was constructed, which was significantly associated with the diagnosis and prognosis of LUAD patients. Thus, the gene signature can be used as a biomarker for LUAD.", "claims": [{"id": "claim-method", "statement": "Lipid metabolism-related differentially expressed genes (DEGs) between LUAD tissues and normal tissues were screened through R package edgeR [26].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33050938", "locator": "sections[4] \"Identification of lipid metabolism-related differentially-expressed genes\" paragraph 2", "quote": "Lipid metabolism-related differentially expressed genes (DEGs) between LUAD tissues and normal tissues were screened through R package edgeR [26]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated and/or analyzed during the current study are available in the TCGA & GEO databases, [https://cancergenome.nih.gov/] & [https://www.ncbi.nlm.nih.gov/geo/].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33050938", "locator": "sections[27] \"notes\" paragraph 1", "quote": "The datasets generated and/or analyzed during the current study are available in the TCGA & GEO databases, [https://cancergenome.nih.gov/] & [https://www.ncbi.nlm.nih.gov/geo/]."}], "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:33050938"], "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:GSE13213"], "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:GSE13213"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33050938", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12944-020-01390-9", "sha256": 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