免疫系统
肝病学
肿瘤微环境
外科肿瘤学
癌症研究
淋巴上皮瘤样癌
医学
免疫疗法
淋巴上皮瘤
爱泼斯坦-巴尔病毒
结直肠外科
免疫学
内科学
病毒
腹部外科
作者
Nai‐Jung Chiang,Ya‐Chin Hou,Kien Thiam Tan,Hung‐Wen Tsai,Yih‐Jyh Lin,Yi‐Chen Yeh,Li‐Tzong Chen,Ya-Fu Hou,Ming‐Huang Chen,Yan-Shen Shan
标识
DOI:10.1007/s12072-022-10346-3
摘要
Limited data are available for tumor immune microenvironment (TIME) in Epstein–Barr virus (EBV)-associated lymphoepithelioma-like cholangiocarcinoma (EBV-LELCC), a rare subtype of intrahepatic cholangiocarcinoma (IHCC). We aimed to investigate TIME features in EBV-LELCC and the correlation between the components of TIME and the clinical outcomes. Tumor tissues from five EBV-LELCC cases confirmed through EBER in situ hybridization and five stage-matched conventional IHCC (non-EBV IHCC) cases were collected. These samples were used to evaluate genetic alterations, TIME composition, and PD-L1 expression through ion AmpliSeq comprehensive cancer panel, PanCancer immune profiling panel, immunohistochemistry, and immunofluorescence staining. The correlation between clinical outcomes and TIME components was analyzed in the two EBV-LELCC cases receiving anti-PD-1 treatment. The genetic mutations identified in EBV-LELCC were BARD1, CD19, CD79B, EPHA5, KDM5A, MUC6, MUC16, PTEN, RECQL4, TET1, and TNFAIP3. Both CD79B and TNFAIP3 mutations were involved in the NF-κB signaling pathway. PD-L1 was highly expressed in tumor-infiltrating immune cells, especially the T cells and macrophages. The TIME of EBV-LELCC displayed abundant immune cell infiltration with a stronger adaptive immune response. Increased Th1 cells, NK CD56dim cells, and M1 macrophages, decreased M2 macrophages, exhausted CD8 T cell infiltration, and increased T cell activation signatures in TIME were associated with longer survival. Two patients with metastatic EBV-LELCC had good disease control after anti-PD-1 antibody treatment. A significantly larger TIME component made EBV-LELCCs more sensitive to immune checkpoint blockade (ICB). A better understanding of the composition of TIME in EBV-LELCC is critical for predicting the clinical outcomes of ICB treatment.
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