The activity of cuproptosis pathway calculated by AUCell algorithm was employed to construct cuproptosis landscape in lung adenocarcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37481739", "kind": "science-record", "revision": 3, "content_hash": "sha256:11f41a731d0aeeeb5d0c6e1c488adabc1d7335140b2dcd3ca9b56123750991d7", "created_at": "2026-11-01T19:02:15Z", "updated_at": "2026-11-01T22:09:56Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "The activity of cuproptosis pathway calculated by AUCell algorithm was employed to construct cuproptosis landscape in lung adenocarcinoma.", "doi": "10.1007/s12672-023-00755-7", "pmid": "37481739", "authors": ["Weixian Lin", "Jiaren Wang", "Jing Ge", "Rui Zhou", "Yahui Hu", "Lushan Xiao", "Quanzhou Peng", "Zemao Zheng"], "journal": "Discover oncology", "year": 2023, "abstract": "Cuproptosis is a recently described copper-dependent cell death pathway. Consequently, there are still few studies on lung adenocarcinoma (LUAD)-related cuproptosis, and we aimed to deepen in this matter. In this study, data from 503 patients with lung cancer from the TCGA-LUAD cohort data collection and 11 LUAD single-cells from GSE131907 as well as from 10 genes associated with cuproptosis were analyzed. The AUCell R package was used to determine the copper-dependent cell death pathway activity for each cell subpopulation, calculate the CellChat score, and display cell communication for each cell subpopulation. The PROGENy score was calculated to show the scores of tumor-related pathways in different cell populations. GO and KEGG analyses were used to calculate pathway activity. Univariate COX and random forest analyses were used to screen prognosis-associated genes and construct models. The ssGSEA and xCell algorithms were used to calculate the immunocyte infiltration score. Based on data from the GDSC database, the drug sensitivity score was calculated using oncoPredict. Finally, in vitro experiments were performed to determine the role of TLE1, the most important gene in the prognostic model. The 11 LUAD single-cell samples were classified into 8 different cell populations, from which epithelial cells showed the highest copper-dependent cell death pathway activity. Epithelial cell subsets were significantly positively correlated with MAKP, hypoxia, and other pathways. In addition, cell subgroup communication showed highly active collagen and APP pathways. Using the Findmark algorithm, differentially expressed genes (DEGs) between epithelial and other cell types were identified. Combined with the bulk data in the TCGA-LUAD database, DEGs were enriched in pathways such as EGFR tyrosine kinase inhibitor resistance, Hippo signaling pathway, and tight junction. Subsequently, we selected 4 genes (out of 112) with prognostic significance, ANKRD29, RHOV, TLE1, and NPAS2, and used them to construct a prognostic model. The high- and low-risk groups, distinguished by the median risk score, showed significantly different prognoses. Finally, we chose TLE1 as a biomarker based on the relative importance score in the prognostic model. In vitro experiments showed that TLE1 promotes tumor proliferation and migration and inhibits apoptosis.", "claims": [{"id": "claim-method", "statement": "Subsequently, univariate COX survival analysis was performed on DEGs using the tinyarray package (p < 0.01), and 112 genes were selected (Fig. 4D).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37481739", "locator": "sections[20] \"Construction of a prognostic model\" paragraph 4", "quote": "Subsequently, univariate COX survival analysis was performed on DEGs using the tinyarray package (p < 0.01), and 112 genes were selected (Fig. 4D)."}], "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 author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37481739", "locator": "sections[31] \"notes\" paragraph 1", "quote": "The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Univariate COX and random forest analyses were used to screen prognosis-associated genes and construct models.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37481739", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Univariate COX and random forest analyses were used to screen prognosis-associated genes and construct models."}, {"asset": "source:pmid:37481739", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "In this study, data from 503 patients with lung cancer from the TCGA-LUAD cohort data collection and 11 LUAD single-cells from GSE131907 as well as from 10 genes associated with cuproptosis were analyzed."}, {"asset": "source:pmid:37481739", "locator": "sections[20] \"Construction of a prognostic model\" paragraph 4", "quote": "Then, 4 prognostic genes, ANKRD29, RHOV, TLE1, and NPAS2, were selected from the 112 genes in the TCGA-LUAD cohort according to the random forest analysis results, and a prognostic model was constructed using them (Fig. 4E)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "Univariate COX and random forest analyses were used to screen prognosis-associated genes and construct models.", "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:37481739"], "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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In addition, TLE1 knockdown significantly i"], "order_basis": "paper_text_order:2453", "id": "assay:1"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["re Collection (ATCC, Rockville, MD, USA) and cultured in KM and DMEM high glucose media supplemented", "lial cells HBE135-E6E7 and lung cancer cells A549, NCI-H2073 were purchased from the American", "ls and lung cancer cell lines. We found that A549 non-small cell lung cancer cells were signif", "howing expression of TLE1 in HBE135-E6E7 and A549 cells. E Western blot showing TLE1 knockdown"], "order_basis": "paper_text_order:2553", "id": "assay:2"}, {"role": "data_generation", "definition_id": "scrna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "unsupported", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["osstalk of LUAD in multicellular ecosystems, scRNA-seq analysis was performed on 11 LUAD samples af"], "order_basis": "paper_text_order:3036", "id": "assay:3"}, {"role": "data_generation", "definition_id": "western_blot", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ession of TLE1 associated with cell cycle. D Western blot showing expression of TLE1 in HBE135-E6E7 an", "ion of TLE1 in HBE135-E6E7 and A549 cells. E Western blot showing TLE1 knockdown efficiency in A549 ce", "iency in NCI-H2073 cell line was verified by Western blot. H Colony formation was measured in cells tr", "ciency of the TLE1 knockdown was verified by western blot analysis (Fig. 9E). TLE1 knockdown significa"], "order_basis": "paper_text_order:5650", "id": "assay:4"}, {"role": "data_generation", "definition_id": "transfection", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["NA. F Colony formation was measured in cells transfected with control or si-TLE1. Transwell assay sho", "ot. H Colony formation was measured in cells transfected with control or overexpressing TLE1. Transwe", "and A549 cells. E Western blot showing TLE1 knockdown efficiency in A549 cells by independent siRN", "l transfer in control cells compared to TLE1 knockdown cells. G TLE1 overexpression efficiency in N"], "order_basis": "paper_text_order:5750", "id": "assay:5"}, {"role": "analysis", "definition_id": "machine_learning", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Subsequently, univariate COX survival analysis was performed on DEGs using the tinyarray package (p < 0.01), and 112 genes were selected (Fig. 4D)."], "order_basis": "consumes_earlier_output", "id": "assay:6"}]}