Cuproptosis-related lncRNAs potentially predict prognosis and therapy sensitivity of breast cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37529698", "kind": "science-record", "revision": 3, "content_hash": "sha256:0ecf3c8b6e2cb9c04281ec03c0123042d780754b373c97a54978f09ac24aadab", "created_at": "2026-11-01T19:02:18Z", "updated_at": "2026-11-01T22:10:00Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Cuproptosis-related lncRNAs potentially predict prognosis and therapy sensitivity of breast cancer.", "doi": "10.3389/fphar.2023.1199883", "pmid": "37529698", "authors": ["Xiwen Wu", "Ying Zhang", "Gehao Liang", "Huizhen Ye"], "journal": "Frontiers in pharmacology", "year": 2023, "abstract": "Background: Cuproptosis-related lncRNAs regulate the biological functions of various cancers. However, the role of cuproptosis-related lncRNAs in breast cancer remains unclear. In this study, we investigated the biological functions and clinical applications of cuproptosis-related lncRNAs in breast cancer. Methods: The Cancer Genome Atlas (TCGA) database and the GSE20685 dataset were used for screening cuproptosis-related lncRNAs. Colony formation and CCK-8 kit assays were performed for detecting the proliferative function of cuproptosis-related lncRNAs, whereas wound healing, migration, and invasion assays were performed for detecting the metastatic regulation of cuproptosis-related lncRNAs in breast cancer. Finally, a prognostic cuproptosis-related lncRNA model was constructed using LASSO Cox regression analysis for detecting survival and sensitivity to conventional treatment (endocrine therapy, chemotherapy, and radiotherapy) and novel therapy (PARP and CDK4/6 inhibitors). Results: In this study, we screened six cuproptosis-related lncRNAs associated with the survival of patients with breast cancer. Biofunctional experiments indicated that cuproptosis-related lncRNAs play essential roles in regulating the proliferation and metastasis of breast cancer cells. Finally, we applied a model of six cuproptosis-related lncRNAs to classify the patients into high- and low-risk groups. High-risk group patients exhibited worse survival rates (p < 0.001) and lower sensitivity to chemotherapy, endocrine therapy, and radiation therapy. Compared with high-risk patients, low-risk patients exhibited a lower expression of CDK4/6 inhibitor-resistant biomarkers (CCNE1, E2F1, and E2F2) and PARP inhibitor-resistant biomarkers (BRCA1/BRCA2), indicating that patients in the low-risk group were more suitable for PARP inhibitor and CDK4/6 inhibitor application. Conclusion: Cuproptosis-related lncRNAs are essential for regulating the biological functions of breast cancer, and they have the potential to predict prognosis and sensitivity of breast cancer to various therapies.", "claims": [{"id": "claim-method", "statement": "Univariate Cox regression analysis and LASSO Cox regression analysis were used to calculate predictive cuproptosis-related lncRNAs and establish the cuproptosis-related lncRNA signature.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37529698", "locator": "sections[5] \"2.3 Cuproptosis-related lncRNA signature and model construction\" paragraph 2", "quote": "Univariate Cox regression analysis and LASSO Cox regression analysis were used to calculate predictive cuproptosis-related lncRNAs and establish the cuproptosis-related lncRNA signature."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37529698", "locator": "sections[25] \"Data availability statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Finally, we applied a model of six cuproptosis-related lncRNAs to classify the patients into high- and low-risk groups.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37529698", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Finally, we applied a model of six cuproptosis-related lncRNAs to classify the patients into high- and low-risk groups."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Finally, we applied a model of six cuproptosis-related lncRNAs to classify the patients into high- and low-risk groups.", "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:37529698"], "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:GSE20685"], "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:GSE20685"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:37529698", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fphar.2023.1199883", "sha256": "sha256:2f2a6a6becbce87d49e0b13cb461df1b59ad46af3b7a4ced03574fff48f839c8", "bytes": 52157, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fphar.2023.1199883", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10390311", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE20685", "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=GSE20685", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE20685", "version": null, "note": "The datasets presented in this study can be found in online repositories. 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