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Decoding the cholangiocarcinoma tumor microenvironment: from single-cell and spatial atlases to translational
Longhao Zhang1, Kai Zhang1, Jingnan Xue2
1Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100010, China.
Background:
Cholangiocarcinoma is a heterogeneous biliary malignancy characterized by late diagnosis, stromal desmoplasia, immune exclusion, and frequent resistance to chemotherapy, immunotherapy, and molecularly targeted therapy. Although genomic stratification has enabled biomarker-directed treatment for selected patients, cancer cell-intrinsic alterations alone do not fully explain disease progression or therapeutic failure.
Main Body:
Recent advances in single-cell RNA sequencing, single-cell multi-omics, spatial transcriptomics, spatial proteomics, multiplex imaging, and pathomics have redefined the CCA tumor microenvironment as an active ecosystem composed of malignant cholangiocytes, cancer-associated fibroblasts, tumor-associated macrophages, regulatory T cells, exhausted CD8 + T cells, natural killer cells, B cells/plasma cells, endothelial cells, extracellular matrix, and tertiary lymphoid structures. These approaches have identified clinically relevant cellular states and spatial niches, including CD146 + vascular cancer-associated fibroblasts, LGALS1 + fibroblasts, SPP1 + macrophages, MEOX1 + regulatory T cells, POSTN+ fibroblast-rich invasive fronts, and CAF-TAM-vascular interaction units. Major communication axes such as IL-6/IL-6R, TGF-β/TGFBR, SPP1/CD44, CXCL12/CXCR4, PD-1/PD-L1, VEGF/VEGFR, and POSTN/integrins connect cellular heterogeneity with immune escape, invasion, angiogenesis, and therapy resistance.
Conclusions:
This review synthesizes current single-cell and spatial atlases of CCA and proposes a conceptual translational framework in which TME-derived cellular states, spatial biomarkers, and druggable communication axes may inform patient stratification and rational combination therapy. Because many proposed TME phenotypes and composite biomarkers remain atlas-derived, correlative, or preclinical, this framework should be viewed as a roadmap for prospective validation rather than as a clinically established classification.