Verification of biological markers of subacute cutaneous lupus erythematosus via TMT labelling proteomics combined with transcriptome data.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40323689", "kind": "science-record", "revision": 3, "content_hash": "sha256:8eaaed176b2a531d124668f12a032532388b7529ffc002136d26880022b6e526", "created_at": "2026-11-01T20:30:29Z", "updated_at": "2026-11-01T22:14:01Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Verification of biological markers of subacute cutaneous lupus erythematosus via TMT labelling proteomics combined with transcriptome data.", "doi": "10.1080/07853890.2025.2500696", "pmid": "40323689", "authors": ["Yuan Tao", "Guo Hua", "Sun Min", "Lu Xiao-Hong", "Jiang Jia-Hui", "Tang Biao", "He Cai-Feng", "Zhang Cheng", "Ci Chao", "Wu Jian-Ping"], "journal": "Annals of medicine", "year": 2025, "abstract": "OBJECTIVE: This study aimed to investigate biological markers in subacute cutaneous lupus erythematosus (SCLE).\nMETHODS: The tandem mass tag (TMT)-labelling proteomics method was used to explore differentially expressed proteins between SCLE lesions and normal skin tissues. The differences in transcriptomic data between SCLE tissues and normal skin tissues were analysed from the GEO database (GSE81071, GSE109248 and GSE112943). The differences in transcriptomic data from peripheral blood mononuclear cells (PBMCs) of patients with systemic lupus erythematosus (SLE) and normal controls were analysed (GSE81622 and GSE154851). The 35 healthy controls, 30 SCLE patients, 35 SLE patients and 30 lupus nephritis (LN) patients were diagnosed and enrolled. The serum expression levels of IFI44 and EPSTI1 were detected. Data were presented as the mean ± standard deviation or frequency and were analysed using Student's t-test, Chi-square test and one-way ANOVA between the groups. Receiver operating characteristic (ROC) curves were used to analyse the clinical efficacy of IFI44 and EPSTI1 in distinguishing SCLE from SLE.\nRESULTS: In a comparative analysis of SCLE lesions and normal skin tissues, proteomics studies identified 376 proteins that exhibited significant differential expression. In GO and KEGG analyses, the enriched terms mainly included the interferon-gamma-mediated signalling pathway (p < .001), immune receptor activity (p < .001) and cell adhesion molecules (p < .001). The top 10 hub genes were screened in SCLE as follows: CD8A, CXCL10, IFI44, CD7, CCL5, TLR4, EPSTI1, ISG15, KLRD1 and SELL using Cytoscape (3.10.1) software. The 15 common proteins/genes between proteomics and three datasets results were found, including CXCL10, OAS1, DDX60L, CFB, IFI6, HERC6, IFI44L, GBP1, EPSTI1, OAS2, CXCL11, TYMP, IFI44, ISG15 and IFIT3. The 61 differentially expressed genes in GSE81622 and the top 100 differentially expressed genes in GSE154851, alongside the 15 identified genes described above through Venn diagram analysis. Four common genes, IFI44L, IFI44, EPSTI1 and OAS1, were identified. Two common genes, IFI44 and EPSTI1, were found in hub genes from the proteomics results. The serum levels of IFI44 and EPSTI1 in LN were significantly higher than those in SLE patients (p < .05). ROC curve analysis demonstrated that serum levels of IFI44 and EPSTI1 could differentiate SCLE from SLE with an area under the curve (AUC) of 0.898 and 0.847, respectively.\nCONCLUSIONS: The IFI44 and EPSTI1 proved to be closely involved in the progression from SCLE to SLE, and can represent new candidate diagnostic molecular markers of occurrence and progression of SCLE.", "claims": [{"id": "claim-method", "statement": "Receiver operating characteristic (ROC) curves were used to analyse the clinical efficacy of IFI44 and EPSTI1 in distinguishing SCLE from SLE.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40323689", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Receiver operating characteristic (ROC) curves were used to analyse the clinical efficacy of IFI44 and EPSTI1 in distinguishing SCLE from SLE."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The raw proteomics data in this study were obtained by contacting the corresponding authors Ci Chao and Wu Jian-ping with a reasonable request (Email: cichao8911@126.com, wujp0526@163.com).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40323689", "locator": "sections[24] \"Data availability statement\" paragraph 2", "quote": "The raw proteomics data in this study were obtained by contacting the corresponding authors Ci Chao and Wu Jian-ping with a reasonable request (Email: cichao8911@126.com, wujp0526@163.com)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Receiver operating characteristic curve analysis demonstrated that serum IFI44 and EPSTI1 could differentiate SCLE from SLE with AUC values of 0.898 and 0.847, respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40323689", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "ROC curve analysis demonstrated that serum levels of IFI44 and EPSTI1 could differentiate SCLE from SLE with an area under the curve (AUC) of 0.898 and 0.847, respectively."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "Receiver operating characteristic curve analysis demonstrated that serum IFI44 and EPSTI1 could differentiate SCLE from SLE with AUC values of 0.898 and 0.847, 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:40323689"], "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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