Treatment options for intrahepatic cholangiocarcinoma (iCCA), a highly malignant tumor with poor prognosis, are limited. Recent developments in immunotherapy and immune checkpoint inhibitors (ICIs) have offered new hope for treating iCCA. However, several issues remain, including the identification of reliable biomarkers of response to ICIs and immune-based combinations. Tumor immune microenvironment (TIME) of these hepatobiliary tumors has been evaluated and is under assessment in this setting in order to boost the efficacy of ICIs and to convert these immunologically "cold" tumors to "hot" tumors. Herein, the review TIME of ICCA and its critical function in immunotherapy. Moreover, this paper also discusses potential avenues for future research, including novel targets for immunotherapy and emerging treatment plans aimed to increase the effectiveness of immunotherapy and survival rates for iCCA patients.

This study aims to determine the predictive role of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) derived radiomic model in tumor immune profiling and immunotherapy for cholangiocarcinoma. To perform radiomic analysis, immune related subgroup clustering was first performed by single sample gene set enrichment analysis (ssGSEA). Second, a total of 806 radiomic features for each phase of DCE-MRI were extracted by utilizing the Python package Pyradiomics. Then, a predictive radiomic signature model was constructed after a three-step features reduction and selection, and receiver operating characteristic (ROC) curve was employed to evaluate the performance of this model. In the end, an independent testing cohort involving cholangiocarcinoma patients with anti-PD-1 Sintilimab treatment after surgery was used to verify the potential application of the established radiomic model in immunotherapy for cholangiocarcinoma. Two distinct immune related subgroups were classified using ssGSEA based on transcriptome sequencing. For radiomic analysis, a total of 10 predictive radiomic features were finally identified to establish a radiomic signature model for immune landscape classification. Regarding to the predictive performance, the mean AUC of ROC curves was 0.80 in the training/validation cohort. For the independent testing cohort, the individual predictive probability by radiomic model and the corresponding immune score derived from ssGSEA was significantly correlated. In conclusion, radiomic signature model based on DCE-MRI was capable of predicting the immune landscape of chalangiocarcinoma. Consequently, a potentially clinical application of this developed radiomic model to guide immunotherapy for cholangiocarcinoma was suggested.

Centromere protein F (CENPF), a protein related to the cell cycle, is a key part of the kinetochore-centromere complex involved in cell division, differentiation, and proliferation. CENPF expression is upregulated in various types of cancer and plays a role in oncogenesis and tumor progression. However, the expression pattern, prognostic significance, and biological role of CENPF in these cancer types are poorly understood. Therefore, in this study, we conducted a pan-cancer analysis of the role of CENPF, which we considered a cut point, to investigate its utility as a prognostic and immunological indicator for malignancies, especially cholangiocarcinoma (CCA). Using systematic bioinformatics analysis, we investigated the expression patterns, prognostic relevance, molecular function, signaling pathways, and immune infiltration patterns of CENPF in the pan-cancer analysis. Western blot and immunohistochemistry staining assays were performed to evaluate the expression profiles of CENPF in CCA tissues and cell lines. Furthermore, Cell Counting Kit-8, colony formation, wound healing, and Transwell assays, as well as CCA xenograft mouse models, were employed to determine the role and function of CENPF in CCA. The results showed that CENPF expression was upregulated and strongly linked to a worse prognosis in most cancer types. CENPF expression was substantially associated with immune cell infiltration, tumor microenvironment, genes related to immune checkpoints, tumor mutational burden, microsatellite instability, and immunotherapy response in diverse malignancies. CENPF was considerably overexpressed in CCA tissues and cells. Functionally, inhibiting CENPF expression significantly reduced the proliferating, migrating, and invading abilities of CCA cells. CENPF expression also affects the prognosis of multiple malignancies, which is highly associated with immunotherapy response and tumor immune cell infiltration. In conclusion, CENPF may act as an oncogene and an immune infiltration-related biomarker and can accelerate tumor development in CCA.

To identify the gene subtypes related to immune cells of cholangiocarcinoma and construct an immune score model to predict the immunotherapy efficacy and prognosis for cholangiocarcinoma.

Based on principal component analysis (PCA) algorithm, The Cancer Genome Atlas (TCGA)-cholangiocarcinoma, GSE107943 and E-MTAB-6389 datasets were combined as Joint data. Immune genes were downloaded from ImmPort. Univariate Cox survival analysis filtered prognostically associated immune genes, which would identify immune-related subtypes of cholangiocarcinoma. Least absolute shrinkage and selection operator (LASSO) further screened immune genes with prognosis values, and tumor immune score was calculated for patients with cholangiocarcinoma after the combination of the three datasets. Kaplan-Meier curve analysis determined the optimal cut-off value, which was applied for dividing cholangiocarcinoma patients into low and high immune score group. To explore the differences in tumor microenvironment and immunotherapy between immune cell-related subtypes and immune score groups of cholangiocarcinoma.

34 prognostic immune genes and three immunocell-related subtypes with statistically significant prognosis (IC1, IC2 and IC3) were identified. Among them, IC1 and IC3 showed higher immune cell infiltration, and IC3 may be more suitable for immunotherapy and chemotherapy. 10 immune genes with prognostic significance were screened by LASSO regression analysis, and a tumor immune score model was constructed. Kaplan-Meier (KM) and receiver operating characteristic (ROC) analysis showed that RiskScore had excellent prognostic prediction ability. Immunohistochemical analysis showed that 6 gene (NLRX1, AKT1, CSRP1, LEP, MUC4 and SEMA4B) of 10 genes were abnormal expressions between cancer and paracancer tissue. Immune cells infiltration in high immune score group was generally increased, and it was more suitable for chemotherapy. In GSE112366-Crohn's disease dataset, 6 of 10 immune genes had expression differences between Crohn's disease and healthy control. The area under ROC obtained 0.671 based on 10-immune gene signature. Moreover, the model had a sound performance in Crohn's disease.

The prediction of tumor immune score model in predicting immune microenvironment, immunotherapy and chemotherapy in patients with cholangiocarcinoma has shown its potential for indicating the effect of immunotherapy on patients with cholangiocarcinoma.

Biliary tract cancers (BTCs) are a heterogenous group of cancers arising from the biliary tract. The hallmark of these cancers is the advanced stage of presentation and a paucity of durable treatment options. Despite the advances in targeted therapy and immunotherapy in solid tumors, systemic cytotoxic chemotherapy has remained the mainstay for cholangiocarcinomas.

With advances in the understanding of the tumor microenvironment, genetic features, and inflammatory milieu, have led to the identification of tumor-infiltrating immune cells as indicators of prognosis and response to treatment in BTC. Through an improved comprehension of immunology, immuno-oncology is becoming another pillar of treatment along with traditional radiation, surgery, cytotoxic chemotherapy, and targeted therapies. This article reviews the evidence for immunotherapy use in cholangiocarcinoma, which still being in infancy, and offers promising new novel options for the management of biliary tract cancers.

Unprecedented advances have been achieved in hepatobiliary cancer treatment with immune checkpoint blockade (ICB). However, the efficacy of ICB in patients with hepatobiliary malignancies is still limited. Resistance to immunotherapies is often orchestrated by complicated tumor-host-microenvironment interactions but could also occur after initial efficacy, mostly when only partial responses are obtained. Clarification of cancer-resistance mechanisms will be beneficial to provide the rationale for the administration of personalized drugs. Here, we review the factors related to resistance to immune-targeted therapies in hepatobiliary malignancies and discuss the potential strategies for overcoming resistance and future directions of immunotherapy development.