Single-cell pancancer analysis reveals epithelial–immune crosstalk in shaping the premetastatic niche of liver metastasis

Liver metastasis is a frequent and clinically important event across multiple solid tumors, yet a cross-cancer single-cell description of the metastatic immune ecosystem remains incomplete. Here, we integrated single-cell RNA-sequencing data from primary tumors and liver metastases across 12 cancer types and combined cell-state annotation, pseudotime ordering, ligand–receptor inference, and multiplex immunofluorescence as orthogonal tissue-level support. We identified a hepatocyte-like malignant epithelial state enriched in liver metastases, characterized by coexpression of hepatic genes, epithelial markers, oncogenic transcripts such as MYC and KRAS, and inferred copy-number-variation signals. CellChat analysis suggested that this epithelial state may engage RGS1-high and LILRB5-high macrophage states through a CCL3–CCR1-associated signaling axis. Reprocessed tissue imaging supported spatial proximity between TAT+/EPCAM+ epithelial cells and these macrophage populations across several tumor types. In addition, macrophage and T-cell composition differed between primary tumors and liver metastases, and sample-level associations linked RGS1-high macrophages to selected CD4 + T-cell states and LILRB5-high resident-like macrophages to selected CD8 + T-cell states. Overall, this study provides a pancancer descriptive atlas of epithelial–immune programs associated with liver metastasis and nominates candidate cellular associations for future functional testing.

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Publication Details

Journal
Scientific Reports
Published
2026-07-30
DOI
https://doi.org/10.1038/s41598-026-60900-4
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00

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article

Single-cell pancancer analysis reveals epithelial–immune crosstalk in shaping the premetastatic niche of liver metastasis

Shi-Lei Liu, Ziyi Yang, Kezhou Wang, Wenting Dai et al.
Scientific Reports
Single-cell and spatial transcriptomics
article

Single-cell pancancer analysis reveals epithelial–immune crosstalk in shaping the premetastatic niche of liver metastasis

Shi-Lei Liu, Ziyi Yang, Kezhou Wang, Wenting Dai, Qiu‐Yi Tang, Yi‐Jian Zhang, Zi-you Wu, Hua-Kai Wang, Honggang Xiang, Yidi Zhu, Yu Zhang, Yue Yang, Wei Gong, Yu Zhang
article en

Abstract

Liver metastasis is a frequent and clinically important event across multiple solid tumors, yet a cross-cancer single-cell description of the metastatic immune ecosystem remains incomplete. Here, we integrated single-cell RNA-sequencing data from primary tumors and liver metastases across 12 cancer types and combined cell-state annotation, pseudotime ordering, ligand–receptor inference, and multiplex immunofluorescence as orthogonal tissue-level support. We identified a hepatocyte-like malignant epithelial state enriched in liver metastases, characterized by coexpression of hepatic genes, epithelial markers, oncogenic transcripts such as MYC and KRAS, and inferred copy-number-variation signals. CellChat analysis suggested that this epithelial state may engage RGS1-high and LILRB5-high macrophage states through a CCL3–CCR1-associated signaling axis. Reprocessed tissue imaging supported spatial proximity between TAT+/EPCAM+ epithelial cells and these macrophage populations across several tumor types. In addition, macrophage and T-cell composition differed between primary tumors and liver metastases, and sample-level associations linked RGS1-high macrophages to selected CD4 + T-cell states and LILRB5-high resident-like macrophages to selected CD8 + T-cell states. Overall, this study provides a pancancer descriptive atlas of epithelial–immune programs associated with liver metastasis and nominates candidate cellular associations for future functional testing.

Scientific Reports
Army Medical University (CN), Shanghai Jiao Tong University (CN), XinHua Hospital (CN), Southwest Hospital (CN), Pudong New Area People's Hospital (CN)
Shanghai Municipal Health Commission, National Natural Science Foundation of China, Southwest Hospital
Zero hunger
Openalex Percentile: Top 15%
Single-cell and spatial transcriptomics
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