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Integrative analysis and validation of necroptosis-related molecular signature for evaluating diagnosis and immune features in Rheumatoid arthritis.
Wan, Wei; Qian, Xinyu; Zhou, Bole; Gao, Jie; Deng, Jiewen; Zhao, Dongbao.
Afiliación
  • Wan W; Department of Rheumatology and Immunology, Shanghai Changhai Hospital, the first affiliated Hospital of Naval Medical University, Shanghai 200433, People's Republic of China.
  • Qian X; Department of Rheumatology and Immunology, Shanghai Changhai Hospital, the first affiliated Hospital of Naval Medical University, Shanghai 200433, People's Republic of China.
  • Zhou B; Department of Joint Bone Disease Surgery, Shanghai Changhai Hospital, the first affiliated Hospital of Naval Medical University, Shanghai 200433, People's Republic of China.
  • Gao J; Department of Rheumatology and Immunology, Shanghai Changhai Hospital, the first affiliated Hospital of Naval Medical University, Shanghai 200433, People's Republic of China.
  • Deng J; Department of Cardiovascular Diseases, Shanghai Changhai Hospital, the first affiliated Hospital of Naval Medical University, Shanghai 200433, People's Republic of China. Electronic address: dengjiewen@zju.edu.cn.
  • Zhao D; Department of Rheumatology and Immunology, Shanghai Changhai Hospital, the first affiliated Hospital of Naval Medical University, Shanghai 200433, People's Republic of China. Electronic address: dongbaozhao@163.com.
Int Immunopharmacol ; 131: 111809, 2024 Apr 20.
Article en En | MEDLINE | ID: mdl-38484666
ABSTRACT

OBJECTIVES:

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease that is characterized by persistent morning stiffness, joint pain, and swelling. However, there is a lack of reliable diagnostic markers and therapeutic targets that are both effective and trustworthy.

METHODS:

In this study, gene expression profiles (GSE89408, GSE55235, GSE55457, and GSE77298) were obtained from the Gene Expression Omnibus database. Differentially expressed necroptosis-related genes were attained from intersection of necroptosis-related gene set, differentially expressed genes, and weighted gene co-expression network analysis. The LASSO, random forest, and SVM-RFE machine learning algorithms were utilized to further screen potential diagnostic genes for RA. Immune cell infiltration was analyzed using the CIBERSORT method. The expressions of diagnostic genes were validated through quantitative real-time PCR, western blotting, immunohistochemistry, and immunofluorescence staining in synovial tissues collected from three trauma controls and three RA patients.

RESULTS:

Five core necroptosis-related genes (FAS, CYBB, TNFSF10, EIF2AK2, and BIRC2) were identified as potential biomarkers for RA. Two different necroptosis patterns based on these five genes were confirmed to significantly correlated with immune cells (especially macrophages). In vitro experiments showed significantly higher mRNA and protein expression levels of CYBB and EIF2AK2 in RA patients compared to normal controls, consistent with the bioinformatics analysis results.

CONCLUSION:

Our study identified a novel necroptosis-related subtype and five diagnostic biomarkers of RA, revealed vital roles in the development and occurrence of RA, and offered potential targets for clinical diagnosis and immunotherapy.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Artritis Reumatoide / Necroptosis Límite: Humans Idioma: En Revista: Int Immunopharmacol Asunto de la revista: ALERGIA E IMUNOLOGIA / FARMACOLOGIA Año: 2024 Tipo del documento: Article Pais de publicación: Países Bajos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Artritis Reumatoide / Necroptosis Límite: Humans Idioma: En Revista: Int Immunopharmacol Asunto de la revista: ALERGIA E IMUNOLOGIA / FARMACOLOGIA Año: 2024 Tipo del documento: Article Pais de publicación: Países Bajos