Metabolism‐related biomarkers, molecular classification, and immune infiltration in diabetic ulcers with validation.
Diabetes mellitus (DM) can lead to diabetic ulcers (DUs), which are the most severe complications. Due to the need for more accurate patient classifications and diagnostic models, treatment and management strategies for DU patients still need improvement. The difficulty of diabetic wound healing is...
| Publicado en: | International Wound Journal Vol. 20; no. 9; pp. 3498 - 3514 |
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| Autores principales: | , , , , , , , , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Nov2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=173114876&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 173114876 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 17424801 1725 jtl: International Wound Journal issn: 17424801 maglogo: Y pubinfo: dt: Nov2023 vid: 20 iid: 9 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 173114876 163935520 173114876 173114876 10.1111/iwj.14223 173114876 ppf: 3498 ppct: 16 formats: tig: atl: Metabolism‐related biomarkers, molecular classification, and immune infiltration in diabetic ulcers with validation. aug: au: Ma, Xiao‐Xuan Zhang, Ying Jiang, Jing‐Si Ru, Yi Luo, Ying Luo, Yue Fei, Xiao‐Ya Song, Jian‐Kun Ma, Xin Li, Bin Tan, Yi‐Mei Kuai, Le affil: Department of Dermatology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China sug: subj: Biological Markers Metabolism Diabetic Foot Classification Diabetes Mellitus Complications Validation Studies Immune System Physiology Human RNA Sequence Analysis Gene Expression Profiling Random Forest Algorithms ROC Curve Consensus Cluster Analysis Factor Analysis Correlational Studies Reverse Transcriptase Polymerase Chain Reaction Funding Source Diabetic Patients ab: Diabetes mellitus (DM) can lead to diabetic ulcers (DUs), which are the most severe complications. Due to the need for more accurate patient classifications and diagnostic models, treatment and management strategies for DU patients still need improvement. The difficulty of diabetic wound healing is caused closely related to biological metabolism and immune chemotaxis reaction dysfunction. Therefore, the purpose of our study is to identify metabolic biomarkers in patients with DU and construct a molecular subtype‐specific prognostic model that is highly accurate and robust. RNA‐sequencing data for DU samples were obtained from the Gene Expression Omnibus (GEO) database. DU patients and normal individuals were compared regarding the expression of metabolism‐related genes (MRGs). Then, a novel diagnostic model based on MRGs was constructed with the random forest algorithm, and classification performance was evaluated utilizing receiver operating characteristic (ROC) analysis. The biological functions of MRGs‐based subtypes were investigated using consensus clustering analysis. A principal component analysis (PCA) was conducted to determine whether MRGs could distinguish between subtypes. We also examined the correlation between MRGs and immune infiltration. Lastly, qRT‐PCR was utilized to validate the expression of the hub MRGs with clinical validations and animal experimentations. Firstly, 8 metabolism‐related hub genes were obtained by random forest algorithm, which could distinguish the DUs from normal samples validated by the ROC curves. Secondly, DU samples could be consensus clustered into three molecular classifications by MRGs, verified by PCA analysis. Thirdly, associations between MRGs and immune infiltration were confirmed, with LYN and Type 1 helper cell significantly positively correlated; RHOH and TGF‐β family remarkably negatively correlated. Finally, clinical validations and animal experiments of DU skin tissue samples showed that the expressions of metabolic hub genes in the DU groups were considerably upregulated, including GLDC, GALNT6, RHOH, XDH, MMP12, KLK6, LYN, and CFB. The current study proposed an auxiliary MRGs‐based DUs model while proposing MRGs‐based molecular clustering and confirmed the association with immune infiltration, facilitating the diagnosis and management of DU patients and designing individualized treatment plans. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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