Identification of cuproptosis-related gene signature to predict prognosis in lung adenocarcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36313444", "kind": "science-record", "revision": 3, "content_hash": "sha256:70863f79a54e126708f2056d63d7eca59b6ab516604461ee6b6e7f601f8d22fc", "created_at": "2026-11-01T18:15:44Z", "updated_at": "2026-11-01T21:29:21Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of cuproptosis-related gene signature to predict prognosis in lung adenocarcinoma.", "doi": "10.3389/fgene.2022.1016871", "pmid": "36313444", "authors": ["Yanju Lv", "Yajie Xiao", "Xiaoli Cui", "Haitao Luo", "Long Xu"], "journal": "Frontiers in genetics", "year": 2022, "abstract": "Background: Studies have reported that coppers are involved in the tumorigenesis and development of tumor. In herein, we aimed to construct a prognostic classification system for lung adenocarcinoma (LUAD) associated with cuproptosis. Methods: Samples information of LUAD were acquired from The Cancer Genome Atlas (TCGA) and GSE31210 dataset. Cuproptosis-related genes were screened from previous research. ConsensusClusterPlus was applied to determine molecular subtypes, which evaluated by genome analysis, tumor immune microenvironment analysis, immunotherapy, functional enrichment analysis. Furthermore, univariate Cox analysis combined with Lasso analysis were employed to construct a cuproptosis-related risk model for LUAD. Results: 14 genes related to cuproptosis phenotype were identified, and 2 clusters (C1 and C2) were determined. Among which, C1 had better survival outcome, less advanced stages, enhanced immune infiltration and enriched in TCA related pathways. A 7 cuproptosis-associated genes risk model was constructed, and the performance was verified in the GSE31210 dataset. A higher RiskScore was significantly correlated with worse overall survival, advanced stages. Cox survival analysis showed that RiskScore was an independent predictor. High-risk group patients had weakened immune infiltration, less likely to benefit from immunotherapy and was more sensitived to immunotherapy. Conclusion: The cuproptosis-related gene signature could serve as potential prognostic predictors for LUAD patients and may provide clues for the intervention of cuproptosis induced harm and targeted anti-tumor application.", "claims": [{"id": "claim-method", "statement": "Univariate and multivariate COX regression were used to examine the independent prognostic power of RiskScore.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36313444", "locator": "sections[12] \"Independent prognostic power of RiskScore\" paragraph 2", "quote": "Univariate and multivariate COX regression were used to examine the independent prognostic power of RiskScore."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. 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This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE31210"], "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:GSE31210"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36313444", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fgene.2022.1016871", "sha256": "sha256:605e96a4058fc955bc66e27775ccbf9d292bd9119789e9df76e886b070b68e2c", "bytes": 25264, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fgene.2022.1016871", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9614324", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE31210", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE31210", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE31210", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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