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Background <p>Clear cell renal cell carcinoma (ccRCC) exhibits marked metabolic reprogramming, and the unfolded protein response (UPR) plays a crucial role in stress adaptation and immune regulation; however, its underlying mechanisms remain unclear.</p> Methods <p>Multi-omics data from The Cancer Genome Atlas (TCGA) program, Gene Expression Omnibus (GEO), and ArrayExpress were integrated, and UPR key genes were identified using an autoencoder combined with XGBoost. ConsensusClusterPlus and Weighted Gene Co-expression Network Analysis (WGCNA) were applied to determine the intersection genes of UPR–WGCNA–macrophage (UWMG). A prognostic model was then constructed using least absolute shrinkage and selection operator–Cox regression and validated across multiple cohorts. Single-cell transcriptome analysis was used to map UPR activity, trace myeloid differentiation paths, and examine CellChat-based communication patterns, aiming to clarify how UPR signaling connects to immune polarization.</p> Results <p>In the metabolic model, the UPR pathway showed the strongest contribution, and its activity was mainly observed in macrophages. From 17 UWMGs, a five-gene prognostic model (CEBPB, PLAUR, ARHGAP24, SNHG8, and ZBTB16) was developed and performed consistently across multiple independent cohorts. The high-risk group exhibited concurrent features of immune activation and suppression. Communication analysis revealed that tumor cells with high CEBPB expression exhibited enhanced MIF–CXCR4 signaling and were associated with macrophage M2-like polarization and an immunosuppressive microenvironment.</p> Conclusions <p>The UPR–CEBPB–MIF signaling axis is associated with macrophage polarization and an immunosuppressive immune microenvironment in ccRCC. The proposed multi-omics model demonstrates stable prognostic value and provides potential targets for optimizing immunotherapy.</p>

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UPR–CEBPB–MIF Signaling Links to Macrophage Polarization and an Immunosuppressive Tumor Microenvironment in Clear Cell Renal Cell Carcinoma

  • 期刊论文

  • 发表日期：

    2026年4月5日

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  • Tingxuan Lv,
  • Renfeng Jia,
  • Kexin Li,
  • Jinhui Yang,
  • Xiao Liu,
  • Wei Hu

摘要

Background

Clear cell renal cell carcinoma (ccRCC) exhibits marked metabolic reprogramming, and the unfolded protein response (UPR) plays a crucial role in stress adaptation and immune regulation; however, its underlying mechanisms remain unclear.

Methods

Multi-omics data from The Cancer Genome Atlas (TCGA) program, Gene Expression Omnibus (GEO), and ArrayExpress were integrated, and UPR key genes were identified using an autoencoder combined with XGBoost. ConsensusClusterPlus and Weighted Gene Co-expression Network Analysis (WGCNA) were applied to determine the intersection genes of UPR–WGCNA–macrophage (UWMG). A prognostic model was then constructed using least absolute shrinkage and selection operator–Cox regression and validated across multiple cohorts. Single-cell transcriptome analysis was used to map UPR activity, trace myeloid differentiation paths, and examine CellChat-based communication patterns, aiming to clarify how UPR signaling connects to immune polarization.

Results

In the metabolic model, the UPR pathway showed the strongest contribution, and its activity was mainly observed in macrophages. From 17 UWMGs, a five-gene prognostic model (CEBPB, PLAUR, ARHGAP24, SNHG8, and ZBTB16) was developed and performed consistently across multiple independent cohorts. The high-risk group exhibited concurrent features of immune activation and suppression. Communication analysis revealed that tumor cells with high CEBPB expression exhibited enhanced MIF–CXCR4 signaling and were associated with macrophage M2-like polarization and an immunosuppressive microenvironment.

Conclusions

The UPR–CEBPB–MIF signaling axis is associated with macrophage polarization and an immunosuppressive immune microenvironment in ccRCC. The proposed multi-omics model demonstrates stable prognostic value and provides potential targets for optimizing immunotherapy.