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Background <p>Rheumatoid arthritis (RA) is a chronic autoimmune disease marked by joint inflammation and destruction. Current treatments often have side effects and resistance. Cucurbitacin E (CuE), a natural compound with anti-inflammatory properties, shows therapeutic potential but its role in RA is unclear. This study explores CuE’s mechanisms in RA, focusing on M1 macrophage polarization.</p> Methods <p>We used a multi-omics approach, integrating transcriptomics, single-cell sequencing, and network pharmacology. Key steps included immune infiltration analysis, WGCNA, machine learning-based biomarker discovery, and flow cytometry validation. Pseudotime trajectory and cell communication analyses were also employed.</p> Results <p>Immune infiltration analysis revealed increased M1 macrophage infiltration in RA patients. WGCNA identified gene modules related to macrophage polarization. Machine learning identified five key biomarkers (CCR2, NFKB1, NT5E, PIK3R1, TYRO3). A diagnostic model based on these biomarkers achieved high accuracy (AUC = 0.94). Pseudotime and cell communication analyses suggested CuE may regulate M1 polarization and signaling networks. Flow cytometry showed high CuE concentrations inhibited M1 macrophage polarization.</p> Conclusion <p>CuE inhibits M1 macrophage polarization and related pathways, offering a promising RA treatment strategy. The identified biomarkers may serve as diagnostic and therapeutic targets. Future research should validate CuE’s clinical effects.</p>

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Cucurbitacin E inhibits M1 macrophage polarization and attenuates rheumatoid arthritis: a multi-omics analysis and experimental validation

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月7日

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  • Haolan Xiong,
  • Shenglu Cao,
  • Lin Yang,
  • Xiaofang Hu,
  • Gang Wang,
  • Fuming Wang

摘要

Background

Rheumatoid arthritis (RA) is a chronic autoimmune disease marked by joint inflammation and destruction. Current treatments often have side effects and resistance. Cucurbitacin E (CuE), a natural compound with anti-inflammatory properties, shows therapeutic potential but its role in RA is unclear. This study explores CuE’s mechanisms in RA, focusing on M1 macrophage polarization.

Methods

We used a multi-omics approach, integrating transcriptomics, single-cell sequencing, and network pharmacology. Key steps included immune infiltration analysis, WGCNA, machine learning-based biomarker discovery, and flow cytometry validation. Pseudotime trajectory and cell communication analyses were also employed.

Results

Immune infiltration analysis revealed increased M1 macrophage infiltration in RA patients. WGCNA identified gene modules related to macrophage polarization. Machine learning identified five key biomarkers (CCR2, NFKB1, NT5E, PIK3R1, TYRO3). A diagnostic model based on these biomarkers achieved high accuracy (AUC = 0.94). Pseudotime and cell communication analyses suggested CuE may regulate M1 polarization and signaling networks. Flow cytometry showed high CuE concentrations inhibited M1 macrophage polarization.

Conclusion

CuE inhibits M1 macrophage polarization and related pathways, offering a promising RA treatment strategy. The identified biomarkers may serve as diagnostic and therapeutic targets. Future research should validate CuE’s clinical effects.