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pmid:40109870

A novel prognostic scoring model based on cuproptosis identifies COMMD1 as a novel therapy target for liver hepatocellular carcinoma.

Oncology research · 2025 doi:10.32604/or.2024.049772

Paper

partial

Experiment

partial

Data

partial

Analysis

absent

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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A novel prognostic scoring model based on cuproptosis identifies COMMD1 as a novel therapy target for liver hepatocellular carcinoma.
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10.32604/or.2024.049772
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40109870
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Oncology research
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Does source perhaps number 1 million cases by 2025, 14 genes, k=2, six selected genes; but none is headline finding. Thus false.\n\nNeed comply \"headline number only\" but false says what text states instead. target_result should state text does state instead, perhaps \"COMMD1 is identified as a potential prognostic marker for HCC, with deletion impacting disease progression.\" Need no evidence because empty per instruction. JSON valid. parent_value 0, unit \"\", evidence \"\", target_result concise. Ensure no unsupported number in target_result perhaps \"COMMD1 is identified as a potential prognostic marker for HCC, with deletion of this gene impacting disease progression.\" That's paraphrase okay in target_result? They say say what text states instead. Fine. Could quote exact wording perhaps better. No number. number_stated false.\n\nLet's answer only JSON.</think>\n\n{\"parent_value\":0,\"unit\":\"\",\"evidence\":\"\",\"target_result\":\"COMMD1 is identified as a potential prognostic marker for HCC, with deletion of this gene impacting disease progression.\",\"number_stated\":false}", "reading": {"parent_value": 0, "unit": "", "evidence": "", "target_result": "COMMD1 is identified as a potential prognostic marker for HCC, with deletion of this gene impacting disease progression.", "number_stated": false, "source_locator": null}, "recorded_at": "2026-10-31T15:35:58.686107+00:00"}], "agreement": false, "disagreements": [], "agreement_basis": {"policy": "decisive_fields", "decisive_fields": ["work_type", "number_stated", "parent_value", "unit"]}, "blinded": true}, "human_critique": {"status": "not_run", "reviewer": null, "signed_at": null, "conflict_checked": false, "commentary": null}, "stages": [{"key": "target_materials", "status": "pending", "reason": null, "evidence": null}, {"key": "independent_readings", "status": "blocked", "reason": "The independent readings are incomplete or disagree; the source evidence must resolve the difference.", "evidence": {"provider_errors": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "reason": "a quoted statement is absent from the supplied text", "raw_response": "{\"target_result\":\"unclear\",\"work_type\":\"analysis_plus_physical_validation\",\"physical_methods\":[\"Deletion of COMMD1\",\"Cellular functional experiments\"],\"analysis_methods\":[\"Lasso Cox regression\",\"Univariate Cox analysis\",\"Multivariate Cox analysis\",\"Correlation analysis\",\"Consensus matrix cluster analysis\",\"ssGSEA\",\"CIBERSORT analysis\",\"Spearman correlation analysis\",\"GO enrichment analysis\",\"KEGG enrichment analysis\",\"oncoPredict\",\"t-test\",\"One-way ANOVA\",\"LSD post hoc analysis\"],\"statistical_method\":\"\",\"method_evidence\":\"\",\"repositories\":[{\"repository\":\"The Cancer Genome Atlas (TCGA)\",\"accession\":\"unknown\",\"data_description\":\"Clinical features and gene expression data for hepatocellular carcinoma patients\",\"evidence\":\"This study aimed to develop a prognostic model for HCC based on cuproptosis-related genes, utilizing clinical data and gene expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases.\",\"publicly_downloadable\":true},{\"repository\":\"Gene Expression Omnibus (GEO)\",\"accession\":\"unknown\",\"data_description\":\"Clinical features and gene expression data for hepatocellular carcinoma patients\",\"evidence\":\"This study aimed to develop a prognostic model for HCC based on cuproptosis-related genes, utilizing clinical data and gene expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases.\",\"publicly_downloadable\":true}],\"availability_statement\":\"Clinical features and gene expression data of HCC patients were collected from publicly available databases. All study data are in this article and additional files.\",\"data_on_request\":false,\"source_claims\":[\"The analysis identified Copper Metabolism Domain Containing 1 (COMMD1) as a potential prognostic marker for HCC, with deletion of this gene impacting disease progression.\",\"Cellular functional experiments validated the role of COMMD1 in HCC.\",\"COMMD1 emerges as a promising candidate for HCC treatment, with implications for prognosis prediction and therapeutic targeting.\"],\"missing_information\":[\"No headline numerical result is stated in the supplied source text.\",\"No statistical method can be unambiguously assigned to the unavailable headline numerical result.\",\"No accession is printed for the TCGA data.\",\"No accession is printed for the GEO data.\",\"The supplied text does not state that the underlying TCGA or GEO data are available on request.\"],\"evidence_spans\":[\"This study aimed to develop a prognostic model for HCC based on cuproptosis-related genes, utilizing clinical data and gene expression profiles from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases.\",\"Clinical features and gene expression data of HCC patients were collected from publicly available databases. Patients from TCGA were randomly divided into training and testing sets, and Lasso Cox regression was applied to develop a predictive model using cuproptosis-related genes.\",\"The analysis identified Copper Metabolism Domain Containing 1 (COMMD1) as a potential prognostic marker for HCC, with deletion of this gene impacting disease progression. Cellular functional experiments validated the role of COMMD1 in HCC.\",\"COMMD1 emerges as a promising candidate for HCC treatment, with implications for prognosis prediction and therapeutic targeting.\",\"Cox analyses, both univariate and multivariate, were conducted using the R programming language (version 4.2.1). Survival data for patients was displayed using the forest plot tool along with calibration curves for survival rates at 1-, 3-, and 5-year.\",\"Statistical analysis was performed using SPSS 17.0 (IBM, Chicago, IL, USA) and GraphPad Prism 8.0 (GraphPad Software, San Diego, CA, USA). Data are presented as means ± standard deviations (SD). Group comparisons were made using both the t-test and one-way ANOVA. Additionally, comparisons among the three groups were assessed using ANOVA and t-tests with LSD for post hoc analysis.\",\"All study data are in this article and additional files.\"]}"}]}}, {"key": "source_resolution", "status": "pending", "reason": null, "evidence": null}, {"key": "protocol_reconstruction", "status": "pending", "reason": null, "evidence": null}, {"key": "control_execution", "status": "pending", "reason": null, "evidence": null}, {"key": "control_comparison", "status": "pending", "reason": null, "evidence": null}, {"key": "publication", "status": "pending", "reason": null, "evidence": null}], "gaps": ["review.human_critique", "review.machine_critique.blocked"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "package:1e733df6566f5474fd18fbae9b30b930a5977fb632c0caed743c401e42402d95", "type": "sep_package", "label": "SEP v1 package for pmid:40109870"}], "activities": [{"id": "activity:conversion:pmid:40109870", "type": "conversion", "used": ["package:1e733df6566f5474fd18fbae9b30b930a5977fb632c0caed743c401e42402d95"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:minimax", "type": "model", "label": "minimax"}, {"id": "agent:minimax_alt", "type": "model", "label": "minimax_alt"}, {"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}], "source_run_id": "run-20261023T122449232913", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "b5fc6906-cf06-4f94-866f-2e9d201fb908", "parent_hash": "1e733df6566f5474fd18fbae9b30b930a5977fb632c0caed743c401e42402d95", "fork_of": null, "generation": 1}, "gaps": ["abstract", "asset:source:pmid:40109870 not verified", "authors", "capability", "corpus_record_absent", "execution.not_run", "method", "review.human_critique", "review.machine_critique.blocked", "step:obtain_source_data blocked on data:not_downloaded", "step:run_analysis blocked on no owned computational capability is bound to this experiment", "step:run_analysis input 'materials:the source data behind the published result in pmid:40109870' does not resolve to a declared asset", "targets"]}