ABSTRACT
BACKGROUND AND AIMS: 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. METHODS: 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. RESULTS: 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). CONCLUSION: A better understanding of the composition of TIME in EBV-LELCC is critical for predicting the clinical outcomes of ICB treatment.
Subject(s)
Bile Duct Neoplasms , Cholangiocarcinoma , Epstein-Barr Virus Infections , B7-H1 Antigen , Bile Duct Neoplasms/complications , Bile Ducts, Intrahepatic/pathology , Cholangiocarcinoma/complications , Cholangiocarcinoma/therapy , Epstein-Barr Virus Infections/complications , Herpesvirus 4, Human/genetics , Humans , Immune Checkpoint Inhibitors , Immunotherapy , Mixed Function Oxygenases , NF-kappa B , Proto-Oncogene Proteins , Retinoblastoma-Binding Protein 2 , Tumor MicroenvironmentABSTRACT
BACKGROUND: Liver fibrosis is thought to be associated with early recurrence of hepatocellular carcinoma (HCC) after resection. To recognize HCC patients with higher risk of early recurrence, we used a second harmonic generation and two-photon excitation fluorescence (SHG/TPEF) microscopy to create a fully quantitative fibrosis score which is able to predict early recurrence. METHODS: The study included 81 HCC patients receiving curative intent hepatectomy. Detailed fibrotic features of resected hepatic tissues were obtained by SHG/TPEF microscopy, and we used multi-dimensional artificial intelligence analysis to create a recurrence prediction model "combined index" according to the morphological collagen features of each patient's non-tumor hepatic tissues. RESULTS: Our results showed that the "combined index" can better predict early recurrence (area under the curve = 0.917, sensitivity = 81.8%, specificity = 90.5%), compared to alpha fetoprotein level (area under the curve = 0.595, sensitivity = 68.2%, specificity = 47.6%). Using a Cox proportional hazards analysis, a higher "combined index" is also a poor prognostic factor of disease-free survival and overall survival. CONCLUSIONS: By integrating multi-dimensional artificial intelligence and SHG/TPEF microscopy, we may locate patients with a higher risk of recurrence, follow these patients more carefully, and conduct further management if needed.
