Cancer-associated fibroblasts shape features of lymphocyte aggregation and collagen deposition in hepatocellular carcinoma

The progression of hepatocellular carcinoma (HCC) is significantly influenced by the tumor microenvironment, in which cancer-associated fibroblasts (CAFs), collagen fibers (CFs), and tumor-infiltrating lymphocytes (TILs) interact to regulate tumor growth and immune infiltration. Understanding the spatial and functional coordination among these components is essential for prognostic assessment. This retrospective study included 335 patients from two tertiary hospitals. Early-stage HCC tissue samples were analyzed using artificial intelligence-based algorithms to quantify TIL fraction and aggregation, while collagen architecture was characterized using multiphoton microscopy (MPM). Moreover, single-cell RNA sequencing was used for functional profiling of CAFs, and multiplex immunofluorescence was applied for spatial validation. The relationship between TILs and collagen features was associated with clinical outcomes. Prognostic models were developed using Cox regression and validated internally and externally. MPM demonstrated strong co-localization of CFs and TILs, with lymphocytes spatially aligned following collagen orientation within the tumor core. CAF subtypes exhibited heterogeneous expression of extracellular matrix (ECM)-related and lymphocyte-modulatory genes, with ECM-mediated signaling dominating CAF–T/B cell communication. TIL aggregation and CF orientation independently predicted disease-free and overall survival. The multifactorial Fiber-TIL-Clinical model (FTC model) achieved superior predictive performance (area under the curve = 0.902 for early recurrence) by integrating these features with clinical variables. The FTC model integrates CF features and TIL characteristics, demonstrating strong performance in predicting HCC recurrence.

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Publication Details

Journal
Journal of Translational Medicine
Published
2026-07-30
DOI
https://doi.org/10.1186/s12967-026-08686-x
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

Cancer-associated fibroblasts shape features of lymphocyte aggregation and collagen deposition in hepatocellular carcinoma

Siqin Zhang, Lianhuang Li, 连渊娥, Jiaying Ye et al.
Journal of Translational Medicine
Single-cell and spatial transcriptomics
article

Cancer-associated fibroblasts shape features of lymphocyte aggregation and collagen deposition in hepatocellular carcinoma

Siqin Zhang, Lianhuang Li, 连渊娥, Jiaying Ye, Zehong Zhang, 周松强, Yannan Bai, Zhongchang Weng, Dongsheng Xia, Shi Chen, Xingxing Huang, Jie Lin
article en

Abstract

The progression of hepatocellular carcinoma (HCC) is significantly influenced by the tumor microenvironment, in which cancer-associated fibroblasts (CAFs), collagen fibers (CFs), and tumor-infiltrating lymphocytes (TILs) interact to regulate tumor growth and immune infiltration. Understanding the spatial and functional coordination among these components is essential for prognostic assessment. This retrospective study included 335 patients from two tertiary hospitals. Early-stage HCC tissue samples were analyzed using artificial intelligence-based algorithms to quantify TIL fraction and aggregation, while collagen architecture was characterized using multiphoton microscopy (MPM). Moreover, single-cell RNA sequencing was used for functional profiling of CAFs, and multiplex immunofluorescence was applied for spatial validation. The relationship between TILs and collagen features was associated with clinical outcomes. Prognostic models were developed using Cox regression and validated internally and externally. MPM demonstrated strong co-localization of CFs and TILs, with lymphocytes spatially aligned following collagen orientation within the tumor core. CAF subtypes exhibited heterogeneous expression of extracellular matrix (ECM)-related and lymphocyte-modulatory genes, with ECM-mediated signaling dominating CAF–T/B cell communication. TIL aggregation and CF orientation independently predicted disease-free and overall survival. The multifactorial Fiber-TIL-Clinical model (FTC model) achieved superior predictive performance (area under the curve = 0.902 for early recurrence) by integrating these features with clinical variables. The FTC model integrates CF features and TIL characteristics, demonstrating strong performance in predicting HCC recurrence.

Journal of Translational Medicine
Fujian Normal University (CN), Fujian Medical University (CN), Fujian Provincial Hospital (CN), Union Hospital (CN)
Openalex Percentile: Top 15%
Single-cell and spatial transcriptomics
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