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Deciphering the Multifaceted Immune Landscape of Unresectable Primary Liver Cancer to Predict Immunotherapy Response
Jun Xue1,2, Shuai Yang3, Si-Si Zhang1,4
1Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|October 28, 2024
Summary
Predicting immunotherapy response in liver cancer is crucial. This study identifies key immune cell changes in blood and tumors to distinguish responders from non-responders, enabling better treatment strategies.
Area of Science:
- Immunology
- Oncology
- Biomarker Discovery
Background:
- Immune checkpoint inhibitors (ICIs) targeting PD-1/PD-L1 are critical for primary liver cancer (PLC) treatment.
- However, predicting patient response to ICIs remains a significant clinical challenge.
Purpose of the Study:
- To identify predictive immune cell signatures in peripheral blood and tumor microenvironment for ICI responders versus non-responders in PLC.
- To develop a model for early discrimination of treatment response.
Main Methods:
- Single-cell mass cytometry on sequential peripheral blood mononuclear cells (PBMCs) from ICI-treated PLC patients.
- Multiplex immunohistochemistry to assess immune cell distribution in tumor tissues.
- Generalized linear model for predictive model development.
Main Results:
- Responders showed distinct baseline proportions of B cells, HLA-DR+CD8+T cells, and classical monocytes (CMs).
- Dynamic changes in CMs and HLA-DR+CD8+T cells were observed post-ICI treatment in responders.
- Higher enrichment of B cells and tertiary lymphoid structures in tumors correlated with response.
- A predictive model achieved AUC > 0.9 for early responder discrimination across cohorts.
Conclusions:
- Dynamic immune cell profiling in peripheral blood and tumor tissue can differentiate ICI responders from non-responders in PLC.
- These findings support improved patient stratification and novel strategies for monitoring ICI treatment efficacy in liver cancer.
