Cuproptosis-Related LncRNA Signature for Predicting Prognosis of Hepatocellular Carcinoma: A Comprehensive Analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36452343", "kind": "science-record", "revision": 3, "content_hash": "sha256:e8bd788a351a2e6123ea0c297ddbe7e7f7b112e656c83c56e9f18278a55f1d9b", "created_at": "2026-11-01T19:00:56Z", "updated_at": "2026-11-01T22:08:12Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Cuproptosis-Related LncRNA Signature for Predicting Prognosis of Hepatocellular Carcinoma: A Comprehensive Analysis.", "doi": "10.1155/2022/3265212", "pmid": "36452343", "authors": ["Qiqi Chen", "Tong Sun", "Guorong Wang", "Mengyu Zhang", "Yitian Zhu", "Xiaonan Shi", "Zhishan Ding"], "journal": "Disease markers", "year": 2022, "abstract": "Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide and has a poor prognosis. Cuproptosis is a novel mode of cell death that has only recently been discovered. Considering the critical role of lncRNAs in liver cancer development, the aim of this study was to construct a prognostic signature based on cuproptosis-related lncRNAs (CRlncRNAs). We downloaded RNA-sequencing data and corresponding clinical information of patients with HCC from The Cancer Genome Atlas (TCGA) database. To verify the robustness of the model, we added an external validation set obtained from the Gene Expression Omnibus (GEO): GSE40144. In addition, we identified the cuproptosis-related genes (CRGs) based on previous reports. Pearson correlation analysis, univariate Cox regression, and least absolute shrinkage and selection operator (LASSO) Cox regression analysis were utilized to screen for genes associated with prognosis. On this basis, multivariate Cox regression and stepAIC were used to further construct and optimize the prognostic model. The simplified signature with the lowest Akaike information criterion (AIC) value was considered the prognostic signature. Seven different algorithms were used to perform immune infiltration analysis. The single-sample Gene Set Enrichment Analysis (ssGSEA) algorithm was utilized to find the difference in immune function between the high- and low-risk groups. Finally, in vitro experiments were performed by quantitative real-time PCR (qRT-PCR) analysis using HCC cell lines to validate the expression of prognostic genes. We identified 3 lncRNAs (CYTOR, LINC00205, and LINC01184) as independent risk factors for HCC. The receiver operating characteristic (ROC) curves calculated that the AUC at 1, 3, and 5 years reached 0.717, 0.633, and 0.607, respectively. The expression levels of 41 immune checkpoints differed significantly between the high- and low-risk groups, and there were significant differences in sensitivity to immunotherapy between the high- and low-risk groups. The risk model could also serve as a promising predictor of immunotherapeutic response, which has been verified by the TIDE algorithm (p < 0.001). Overall, we propose a signature related to CRlncRNAs that can be used to predict the prognosis of HCC patients, which was validated in external cohort and in vitro experiments.", "claims": [{"id": "claim-method", "statement": "Pearson correlation analysis, univariate Cox regression, and least absolute shrinkage and selection operator (LASSO) Cox regression analysis were utilized to screen for genes associated with prognosis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36452343", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Pearson correlation analysis, univariate Cox regression, and least absolute shrinkage and selection operator (LASSO) Cox regression analysis were utilized to screen for genes associated with prognosis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories, further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36452343", "locator": "sections[24] \"Data Availability\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories, further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "CYTOR, LINC00205, and LINC01184 were identified as independent risk factors for HCC.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36452343", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "We identified 3 lncRNAs (CYTOR, LINC00205, and LINC01184) as independent risk factors for HCC."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "CYTOR, LINC00205, and LINC01184 were identified as independent risk factors for HCC.", "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:36452343"], "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:GSE40144"], "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:GSE40144"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36452343", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2022/3265212", "sha256": "sha256:8fdf3083d2f90174acbec9e4586489ed9839114ee45ef333a1c8abe01b091ac8", "bytes": 35854, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/2022/3265212", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9705118", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE40144", "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=GSE40144", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE40144", "version": null, "note": "The datasets presented in this study can be found in online repositories, further inquiries can be directed to the corresponding author.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets presented in this study can be found in online repositories, further inquiries can be directed to the corresponding author.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM986208", "GSM986209", "GSM986210", "GSM986211", "GSM986212", "GSM986213", "GSM986214", "GSM986215", "GSM986216", "GSM986217", "GSM986218", "GSM986219", "GSM986220", "GSM986221", "GSM986222", "GSM986223", "GSM986224", "GSM986225", "GSM986226", "GSM986227", "GSM986228", "GSM986229", "GSM986230", "GSM986231", "GSM986232", "GSM986233", "GSM986234", "GSM986235", "GSM986236", "GSM986237", "GSM986238", "GSM986239", "GSM986240", "GSM986241", "GSM986242", "GSM986243", "GSM986244", "GSM986245", "GSM986246", "GSM986247", "GSM986248", "GSM986249", "GSM986250", "GSM986251", "GSM986252", "GSM986253", "GSM986254", "GSM986255", "GSM986256", "GSM986257", "GSM986258", "GSM986259", "GSM986260", "GSM986261", "GSM986262", "GSM986263", "GSM986264", "GSM986265", "GSM986266"], "sample_count": 59, "group_sizes": null, "group_sizes_basis": null, "platform": "11269", "taxon": "Homo sapiens", "title": "LncRNA expression profiles of 59 tumorous liver tissues derived from patients with hepatocellular carcinoma (HCC)", "resolution_checked_at": "2026-11-01T18:46:34Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE40144 not downloaded", "asset:data:geo:GSE40144 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Pearson correlation analysis, univariate Cox regression, and least absolute shrinkage and selection operator (LASSO) Cox regression analysis were utilized to screen for genes associated with prognosis."}}, {"id": "method-2", "family": "group_comparison", "specific": "student_t_test", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["student_t"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Student's t test"}}, {"id": "method-3", "family": "principal_component_analysis", "specific": "pca", "label": "Principal component analysis", "dsl_operations": ["pca_fit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["wide_numeric_matrix"], "evidence": {"score": 0.8, "band": "high", "quote": "Principal component analysis"}}, {"id": "method-4", "family": "correlation_analysis", "specific": "pearson", "label": "Correlation analysis", "dsl_operations": ["pearson_r"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["paired_numeric_columns"], "evidence": {"score": 0.7, "band": "medium", "quote": "Pearson correlation"}}], "targets": [], "gaps": ["method.reader_differs_from_extractor"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["cox_ph"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE40144"], "resolved_accessions": ["GSE40144"], "statements": ["The datasets presented in this study can be found in online repositories, further inquiries can be directed to the corresponding author."], "basis": "The paper names GSE40144 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["cox_ph"], "assets": ["source:pmid:36452343", "data:geo:GSE40144"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE40144"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T18:17:40Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 11677, "completion_tokens": 1304, "cached_tokens": 0}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:36452343", "type": "paper", "label": "pmid:36452343"}, {"id": "source:pmid:36452343", "type": "manuscript", "label": "PMID 36452343 full text"}, {"id": "data:geo:GSE40144", "type": "dataset", "label": "GEO GSE40144"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:36452343", "type": "paper", "label": "pmid:36452343"}, {"id": "source:pmid:36452343", "type": "manuscript", "label": "PMID 36452343 full text"}, {"id": "data:geo:GSE40144", "type": "dataset", "label": "GEO GSE40144"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-36452343", "type": "extraction", "used": ["source:pmid:36452343"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE40144", "type": "accession_resolution", "used": ["data:geo:GSE40144"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:36452343", "parent_hash": "sha256:6493460a5a1c165904eab95d62033e7182e164305814655ac3c19c76cc6b950e", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE40144 licence not read", "asset:data:geo:GSE40144 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["o experiments were performed by quantitative real-time PCR (qRT-PCR) analysis using HCC cell lines to v"], "order_basis": "paper_text_order:1556", "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": ["ture Collection Center (Shanghai, China) and cultured in high-glucose DMEM containing 10% fetal bovin", "ted. 2.7. Cell Culture Human HCC cell lines (HepG2) and human hepatic epithelial cells (LO2) we"], "order_basis": "paper_text_order:3713", "id": "assay:2"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Pearson correlation analysis, univariate Cox regression, and least absolute shrinkage and selection operator (LASSO) Cox regression analysis were utilized to screen for genes associated with prognosis."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}