Abstract 5276: Comprehensive spatial mapping uncovers immune ecotypes linked to tumor heterogeneity in HCC lung metastasis

Abstract Tumor immune microenvironment (TME) heterogeneity, shaped by diverse immune and stromal cells, significantly influences tumor metastasis, yet the specific immune ecotypes involved and their relationship to intra-tumor heterogeneity remain unclear. In this study, we present a comprehensive spatial and cellular multi-omics analysis of 44 primary and 54 lung metastatic lesions from 34 HCC patients. By integrating public single-cell RNA sequencing data from 187, 290 tumor cells across 146 HCC cases, we define HCC cellular states and uncover their organization in high-dimensional spatial expression profiles from paired HCC primary and metastatic lung lesions. Our integrated analysis, incorporating data with three independent cohorts, uncovers three pro-metastatic modules—Cell cycle(G2/M), Cellular Stress and Hypoxia —that contribute to early HCC lung metastasis. Notably, the first two modules are specific to lung metastasis, while the latter one is common across all extrahepatic organs. We show how tumor cells with distinct modules interact with various immune cell types, facilitating metastasis through different mechanisms. Additionally, these tumor cells form multi-layered structures of varying sizes, with specific state pairs preferentially clustering across multiple scales, all within a 55 µm limit. In vivo studies further reveal that interactions between G2/M-high tumor cells and Angio-macrophages and T3-neutrophils accelerate lung dissemination. Treatment with the G2/M inhibitor paclitaxel effectively disrupts this process, reducing metastasis. These findings provide critical insights into how tumor cell heterogeneity reshapes the TME to drive metastasis, underscoring the importance of spatially informed features for personalized cancer therapies. Our work emphasizes the potential of tailored strategies to prevent and manage metastasis based on tumor-immune interactions. Citation Format: Jinghan Zhu, Guangzhen Cai, Bin Guo, Xiaoping Chen, Huilan Zhang, Hong Zhu, Wanguang Zhang. Comprehensive spatial mapping uncovers immune ecotypes linked to tumor heterogeneity in HCC lung metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5276.

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Journal
Cancer Research
Published
2025-04-21
DOI
https://doi.org/10.1158/1538-7445.am2025-5276
Primary Topic
Radiomics and Machine Learning in Medical Imaging
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article
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article

Abstract 5276: Comprehensive spatial mapping uncovers immune ecotypes linked to tumor heterogeneity in HCC lung metastasis

Huilan Zhang, Wanguang Zhang, Guangzhen Cai, Jinghan Zhu et al.
Cancer Research
Radiomics and Machine Learning in Medical Imaging
article

Abstract 5276: Comprehensive spatial mapping uncovers immune ecotypes linked to tumor heterogeneity in HCC lung metastasis

Huilan Zhang, Wanguang Zhang, Guangzhen Cai, Jinghan Zhu, Xiaoping Chen, Bin Guo, Hong Zhu
article en

Abstract

Abstract Tumor immune microenvironment (TME) heterogeneity, shaped by diverse immune and stromal cells, significantly influences tumor metastasis, yet the specific immune ecotypes involved and their relationship to intra-tumor heterogeneity remain unclear. In this study, we present a comprehensive spatial and cellular multi-omics analysis of 44 primary and 54 lung metastatic lesions from 34 HCC patients. By integrating public single-cell RNA sequencing data from 187, 290 tumor cells across 146 HCC cases, we define HCC cellular states and uncover their organization in high-dimensional spatial expression profiles from paired HCC primary and metastatic lung lesions. Our integrated analysis, incorporating data with three independent cohorts, uncovers three pro-metastatic modules—Cell cycle(G2/M), Cellular Stress and Hypoxia —that contribute to early HCC lung metastasis. Notably, the first two modules are specific to lung metastasis, while the latter one is common across all extrahepatic organs. We show how tumor cells with distinct modules interact with various immune cell types, facilitating metastasis through different mechanisms. Additionally, these tumor cells form multi-layered structures of varying sizes, with specific state pairs preferentially clustering across multiple scales, all within a 55 µm limit. In vivo studies further reveal that interactions between G2/M-high tumor cells and Angio-macrophages and T3-neutrophils accelerate lung dissemination. Treatment with the G2/M inhibitor paclitaxel effectively disrupts this process, reducing metastasis. These findings provide critical insights into how tumor cell heterogeneity reshapes the TME to drive metastasis, underscoring the importance of spatially informed features for personalized cancer therapies. Our work emphasizes the potential of tailored strategies to prevent and manage metastasis based on tumor-immune interactions. Citation Format: Jinghan Zhu, Guangzhen Cai, Bin Guo, Xiaoping Chen, Huilan Zhang, Hong Zhu, Wanguang Zhang. Comprehensive spatial mapping uncovers immune ecotypes linked to tumor heterogeneity in HCC lung metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 5276.

Cancer ResearchVol. 85(8_Supplement_1)
Huazhong University of Science and Technology (CN)
Life in Land
Openalex Percentile: Top 88%
Radiomics and Machine Learning in Medical Imaging
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