Development and validation of an oxidative stress-associated prognostic risk model for melanoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33976978", "kind": "science-record", "revision": 6, "content_hash": "sha256:a05e01cc985ebefc1a36ed5d6824a666882ff2d3046bc1da504ee1559cdfc70a", "created_at": "2026-11-01T15:41:35Z", "updated_at": "2026-11-01T21:25:18Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Development and validation of an oxidative stress-associated prognostic risk model for melanoma.", "doi": "10.7717/peerj.11258", "pmid": "33976978", "authors": ["Yu Yang", "Xuan Long", "Kun Li", "Guiyun Li", "Xiaohong Yu", "Ping Wen", "Jun Luo", "Xiaobin Tian", "Jinmin Zhao"], "journal": "PeerJ", "year": 2021, "abstract": "BACKGROUND: Oxidative stress (OS) is key to various diseases and is implicated in cancer progression and oncogenesis. However, the potential diagnostic value of OS-related genes in skin cutaneous melanoma (SKCM) remains unclear.\nMETHODS: We used data of RNA sequencing from 471 tumor tissues and one healthy tissue acquired from The Cancer Genome Atlas (TCGA)-SKCM cohort. The Genome Tissue Expression database was used to acquire transcriptome data from 812 healthy samples. OS-related genes that were differentially expressed between SKCM and healthy samples were investigated and 16 prognosis-associated OS genes were identified. The prognostic risk model was built using univariate and Cox multivariate regressions. The prognostic value of the hub genes was validated in the GSE65904 cohort, which included 214 SKCM patients.\nRESULTS: The overall survival rate of SKCM patients in the high-risk group was decreased compared to the low-risk group. In both TCGA and GSE65904 cohorts, the ROC curves suggested that our prognostic risk model was more accurate than other clinicopathological characteristics to diagnose SKCM. Moreover, risk score and nomograms associated with the expression of hub genes were developed. These presented reiterated our prognostic risk model. Altogether, this study provides novel insights with regards to the pathogenesis of SKCM. 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE65904"], "resolved_accessions": ["GSE65904"], "statements": ["The following information was supplied regarding data availability:All gene expression profiles are available from the TCGA (https://portal.gdc.cancer.gov; search term: cases.primary_site in [“skin”] and cases.project.program.name in [“TCGA”] and cases.project.project_id in [“TCGA-SKCM”] and files.analysis.workflow_type in [“HTSeq-FPKM”] and files.data_category in [“transcriptome profiling”] and files.data_type in [“Gene Expression Quantification”] and files.experimental_strategy in [“RNA-Seq”]), UCSC Xena, (https://xenabrowser.net/datapages/?dataset=TCGA-SKCM.htseq_fpkm.tsv&host=https%3A%2F%2Fgdc.xenahubs.net&removeHub=https%3A%2F%2Fxena.treehouse.gi.ucsc.edu%3A443), GTEx (https://xenabrowser.net/datapages/?dataset=gtex_RSEM_gene_fpkm&host=https%3A%2F%2Ftoil.xenahubs.net&removeHub=https%3A%2F%2Fxena.treehouse.gi.ucsc.edu%3A443) and GSE65904."], "basis": "The paper names GSE65904 in National Center for Biotechnology Information-Gene Expression Omnibus 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:33976978", "data:geo:GSE65904", "asset:table:pmid:33976978:1", "asset:table:pmid:33976978:2"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE65904"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:30:10Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 3, "usage": {"prompt_tokens": 32558, "completion_tokens": 3849, "cached_tokens": 11008}}, "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:33976978", "type": "paper", "label": "pmid:33976978"}, {"id": "source:pmid:33976978", "type": "manuscript", "label": "PMID 33976978 full text"}, {"id": "data:geo:GSE65904", "type": "dataset", "label": "GEO GSE65904"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:33976978", "type": "paper", "label": "pmid:33976978"}, {"id": "source:pmid:33976978", "type": "manuscript", "label": "PMID 33976978 full text"}, {"id": "data:geo:GSE65904", "type": "dataset", "label": "GEO GSE65904"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-33976978", "type": "extraction", "used": ["source:pmid:33976978"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE65904", "type": "accession_resolution", "used": ["data:geo:GSE65904"], "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:33976978", "parent_hash": "sha256:cfba94fc9397c24e96ba51d792d5b449a25bd14915afe2a0f62b158d8634ac16", "fork_of": null, "generation": 5}, "gaps": ["asset:data:geo:GSE65904 licence not read", "asset:data:geo:GSE65904 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "rna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["M) remains unclear. METHODS: We used data of RNA sequencing from 471 tumor tissues and one healthy tissu", "ssue Expression database was used to acquire transcriptome data from 812 healthy samples. OS-related ge"], "order_basis": "paper_text_order:306", "id": "assay:1"}, {"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": ["Multivariate Cox proportional hazards regression model was constructed based on the identified prognostic-related OS genes."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}