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<p>Emerging evidence indicates that aberrant cholesterol metabolism in macrophages plays a role in tumorigenesis, however, how specific metabolites released by macrophages influence immunosurveillance and along with their potential as therapeutic targets and prognostic biomarkers, remain unclear. We integrated 465 single-cell multi-omics and 1,318 bulk RNA-seq samples of colorectal cancer (CRC) using bioinformatics, single-cell metabolic flux modeling and machine learning to decipher cholesterol metabolic rewiring specific to tumor-associated macrophages (TAM), along with associated druggable targets and prognostic potential. We uncover that CYP27A1-mediated 26-hydroxycholesterol metabolism drives the formation of immunosuppressive SPP1 + APOE + TAM in CRC. Multi-omics and analysis (scATAC-seq, gene regulatory network, and spatial transcriptomics data) reveals that this subset activates SPI1, establishing a macrophage–Treg co-infiltration niche that inhibits CD8 + T-cell infiltration in large amounts of spatial transcriptomics data. Finally, we constructed a cholesterol metabolism-based gene signature derived from SPP1 + APOE + TAM and applied machine learning methods, achieving robust prognostic accuracy across four independent CRC cohorts. Collectively, our findings reveal CYP27A1 as a central regulator linking cholesterol metabolism to immune suppression, highlighting its therapeutic potential in tumor microenvironment–driven cancers and lipid-associated disorders.</p> Graphical Abstract <p></p>

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Multi-omics and metabolic flux modeling reveal that macrophage CYP27A1-derived 26-hydroxycholesterol drives immunosuppression and cancer malignancy

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月3日

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  • Jinfen Wei,
  • Bin Yu,
  • Na Wang,
  • Xinyao Huang,
  • Shuna Su,
  • Zixi Chen,
  • Meiling Hu,
  • Xiaoling Wen,
  • Jiangying Liang,
  • Lingbo Shao,
  • Hongjiu Wang,
  • Hongli Du,
  • Zhenzhen Wang

摘要

Emerging evidence indicates that aberrant cholesterol metabolism in macrophages plays a role in tumorigenesis, however, how specific metabolites released by macrophages influence immunosurveillance and along with their potential as therapeutic targets and prognostic biomarkers, remain unclear. We integrated 465 single-cell multi-omics and 1,318 bulk RNA-seq samples of colorectal cancer (CRC) using bioinformatics, single-cell metabolic flux modeling and machine learning to decipher cholesterol metabolic rewiring specific to tumor-associated macrophages (TAM), along with associated druggable targets and prognostic potential. We uncover that CYP27A1-mediated 26-hydroxycholesterol metabolism drives the formation of immunosuppressive SPP1 + APOE + TAM in CRC. Multi-omics and analysis (scATAC-seq, gene regulatory network, and spatial transcriptomics data) reveals that this subset activates SPI1, establishing a macrophage–Treg co-infiltration niche that inhibits CD8 + T-cell infiltration in large amounts of spatial transcriptomics data. Finally, we constructed a cholesterol metabolism-based gene signature derived from SPP1 + APOE + TAM and applied machine learning methods, achieving robust prognostic accuracy across four independent CRC cohorts. Collectively, our findings reveal CYP27A1 as a central regulator linking cholesterol metabolism to immune suppression, highlighting its therapeutic potential in tumor microenvironment–driven cancers and lipid-associated disorders.

Graphical Abstract