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pmid:40860944
Machine Learning-Based Identification and Experimental Validation of Hub Ferroptosis-Related Cuproptosis Genes in Lupus Nephritis.
Su Zhang · Weitao Hu · Yifang Zhang · Chunyan Huang · Ziqiong He · Jing Xu · Shihong Lin · Baoya Yang · Xiaoqing Chen
Journal of inflammation research · 2025 doi:10.2147/JIR.S526572
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Experiment
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Complete file
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The aim of this study was to explore the expression and effects of ferroptosis-related cuproptosis genes (FRCGs) in LN using bioinformatics and experimental validation.\nMethods: The LN-related datasets GSE112943 and GSE32591 were downloaded from the GEO database. We collected 834 ferroptosis-related genes and 1046 cuproptosis-related genes. Weighted gene co-expression network analysis (WGCNA) and machine learning algorithms identified hub FRCGs in the LN. We then analyzed the relationship of hub FRCGs with immune infiltration and clinical traits. Finally, we validated the expression of the hub FRCGs in vivo and in vitro.\nResults: A total of 31 differentially expressed FRCGs (DE-FRCGs) in the LN were screened, which were mainly involved in the response to metal ions and oxidative stress. And they were engaged in autophagy-animal signaling pathway. Machine learning identified two hub FRCGs (JUN and ZFP36). Public datasets, clinical samples, in vivo and in vitro experiments confirmed that hub FRCGs expression was reduced in the LN group compared to control group. Immune infiltration analysis displayed that monocytes and macrophages were the major infiltrating cells in LN kidneys. In LN, hub genes were negatively correlated with macrophages and monocytes.\nConclusion: This study elucidates the contribution of ferroptosis-related cuproptosis genes to the onset and progression of LN. JUN and ZFP36 were potentially effective biomarkers of LN and may be potential targets for LN therapy in the future.", "claims": [{"id": "claim-method", "statement": "The training cohort was then screened for differentially expressed genes (DEGs) with the “limma” package of R.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40860944", "locator": "sections[3] \"Acquisition of Datasets and Screening of Differentially Expressed Genes\" paragraph 2", "quote": "The training cohort was then screened for differentially expressed genes (DEGs) with the “limma” package of R."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated and/or analysed during the current study are available in the [GEO] repository, [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE112943].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40860944", "locator": "sections[41] \"Data Availability Statement\" paragraph 2", "quote": "The datasets generated and/or analysed during the current study are available in the [GEO] repository, [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE112943]."}], "state": "complete"}, {"id": "claim-target-result", "statement": "In GSE112943, limma screening identified 12,520 DEGs, and their intersection with WGCNA modules, ferroptosis-related genes, and cuproptosis-related genes yielded 31 DE-FRCGs.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40860944", "locator": "sections[29] \"Identification of DEGs\" paragraph 2", "quote": "A total of 12520 DEGs (Supplementary material) were screened in the LN and NC groups, including 7151 up-regulated genes and 5369 down-regulated genes (Figure 2C and D)."}, {"asset": "source:pmid:40860944", "locator": "sections[31] \"Acquisition and Functional Enrichment Analysis of DE-FRCGs\" paragraph 2", "quote": "The DEGs, WGCNAs, FRGs and CRGs were taken to intersect to obtain the 31 DE-FRCGs in the LN (Figure 3A)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "In GSE112943, limma screening identified 12,520 DEGs, and their intersection with WGCNA modules, ferroptosis-related genes, and cuproptosis-related genes yielded 31 DE-FRCGs.", "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:40860944"], "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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