肝细胞癌免疫微环境全景剖析，引领免疫治疗前沿探索新方向
Merged summary
TL;DR - A review maps the heterogeneous immune microenvironment of hepatocellular carcinoma (HCC), connecting its cellular mechanisms with research tools, biomarkers, and emerging immunotherapies. It highlights how multi-omics and AI may improve treatment-response prediction and personalized therapy.
- Fibroblasts, the gut–liver axis, myeloid cells, T cells, B cells, and NK/NKT cells collectively shape HCC immune suppression and treatment resistance.
- Single-cell sequencing, spatial omics, multiplex immunofluorescence, organoids, and animal models enable detailed study of HCC immune heterogeneity.
- Phase III evidence supports checkpoint-inhibitor combinations, including atezolizumab–bevacizumab and tremelimumab–durvalumab, for advanced HCC.
- Candidate response markers include TMB, MSI, TP53 mutations, PD-L1, and ctDNA; AI models may integrate these signals for patient stratification.
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肝细胞癌免疫微环境全景剖析，引领免疫治疗前沿探索新方向
TL;DR - A review maps the heterogeneous immune microenvironment of hepatocellular carcinoma (HCC), connecting its cellular mechanisms with research tools, biomarkers, and emerging immunotherapies. It highlights how multi-omics and AI may improve treatment-response prediction and personalized therapy.
- Fibroblasts, the gut–liver axis, myeloid cells, T cells, B cells, and NK/NKT cells collectively shape HCC immune suppression and treatment resistance.
- Single-cell sequencing, spatial omics, multiplex immunofluorescence, organoids, and animal models enable detailed study of HCC immune heterogeneity.
- Phase III evidence supports checkpoint-inhibitor combinations, including atezolizumab–bevacizumab and tremelimumab–durvalumab, for advanced HCC.
- Candidate response markers include TMB, MSI, TP53 mutations, PD-L1, and ctDNA; AI models may integrate these signals for patient stratification.