Construction and validation of a novel prognostic signature for cutaneous melanoma based on ferroptosis-related genes.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37159694", "kind": "science-record", "revision": 3, "content_hash": "sha256:31ddc2f3fd8f82b339fb3c5a51ece7d8a12929b53ac38363f49ba71b955bee39", "created_at": "2026-11-01T19:01:49Z", "updated_at": "2026-11-01T22:09:25Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Construction and validation of a novel prognostic signature for cutaneous melanoma based on ferroptosis-related genes.", "doi": "10.1016/j.heliyon.2023.e15725", "pmid": "37159694", "authors": ["Wenna Guo", "Xue Wang", "Yanting Zhang", "Hongtao Liu", "Shanshan Ma", "Fangxia Guan"], "journal": "Heliyon", "year": 2023, "abstract": "Ferroptosis, a recently uncovered iron-dependent, non-apoptotic cell death process, has been increasingly linked to cancer development. In this study, our objective was to develop a prognostic model centered on ferroptosis-related genes (FRGs) and assess its efficacy as an overall survival (OS) prediction biomarker. We conducted a systematic analysis of cutaneous melanoma (CM) and devised a novel ferroptosis-related prognostic signature (FRGSig) using the TCGA database. An independent dataset from GSE65904 was employed to corroborate the validity of the FRGSig. Both univariate and multivariate Cox proportional hazard regression analyses were utilized to construct a FRGSig composed of five FRGs. mRNA expression and immunohistochemistry (IHC) analysis demonstrated that the expression of FRGSig genes varied between tumor and normal tissues. According to Kaplan-Meier analysis, patients with elevated FRGsig scores faced a worse prognosis. The predictive accuracy of FRGSig was evaluated using the time-dependent receiver operating characteristic curve (ROC), with the area under the curve (AUC) values for 1, 3, and 5 OS at 0.682, 0.711, 0.735 in the TCGA cohort, and 0.662, 0.695, 0.712 in the validation dataset, respectively. Univariate and multivariate Cox regression analyses demonstrated that FRGSig served as an independent prognostic factor. Further analysis revealed a significant relationship between FRGSig and Tumor Mutational Burden (TMB) as well as immune infiltration levels. Gene set enrichment analysis (GSEA) disclosed functional disparities between high- and low-risk groups, suggesting that immune checkpoint-related pathways could be instrumental in the improved prognosis of the low-risk group. Taken together, the FRGSig has potential guidance for prognosis prediction and clinical treatment of CM.", "claims": [{"id": "claim-method", "statement": "Cox proportional hazards regression was applied to identify crucial gene related to patient survival [17]. Univariate analysis was used for determining the prognostic-related FRGs (P < 0.05), while multivariate analysis was applied to search for prognostic factors, and calculate the regression coefficients of each gene.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37159694", "locator": "sections[4] \"Development and evaluation of FRG prognostic signature (FRGSig)\" paragraph 2", "quote": "Cox proportional hazards regression was applied to identify crucial gene related to patient survival [17]. Univariate analysis was used for determining the prognostic-related FRGs (P < 0.05), while multivariate analysis was applied to search for prognostic factors, and calculate the regression coefficients of each gene."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The results shown in this manuscript are based upon the data generated by the TCGA Research Network: http://cancergenome.nih.gov/, NCBI GEO database: https://www.ncbi.nlm.nih.gov/geo, (GEPIA) database (http://gepia.cancer-pku.cn/), The Human Protein Atlas (http://www.proteinatlas.org/), FerrDb database (http://www.zhounan.org/ferrdb/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37159694", "locator": "sections[19] \"Data availability statement\" paragraph 2", "quote": "The results shown in this manuscript are based upon the data generated by the TCGA Research Network: http://cancergenome.nih.gov/, NCBI GEO database: https://www.ncbi.nlm.nih.gov/geo, (GEPIA) database (http://gepia.cancer-pku.cn/), The Human Protein Atlas (http://www.proteinatlas.org/), FerrDb database (http://www.zhounan.org/ferrdb/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The FRGSig predicted overall survival in cutaneous melanoma with 1-, 3-, and 5-year AUC values of 0.682, 0.711, and 0.735 in the TCGA cohort and 0.662, 0.695, and 0.712 in the validation dataset, respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37159694", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The predictive accuracy of FRGSig was evaluated using the time-dependent receiver operating characteristic curve (ROC), with the area under the curve (AUC) values for 1, 3, and 5 OS at 0.682, 0.711, 0.735 in the TCGA cohort, and 0.662, 0.695, 0.712 in the validation dataset, respectively."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The FRGSig predicted overall survival in cutaneous melanoma with 1-, 3-, and 5-year AUC values of 0.682, 0.711, and 0.735 in the TCGA cohort and 0.662, 0.695, and 0.712 in the validation dataset, respectively.", "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:37159694"], "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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