Syngeneic murine models with distinct immune microenvironments represent subsets of human intrahepatic cholangiocarcinoma

Abstract

Background & aims: Cholangiocarcinoma (CCA) is a poorly immunogenic malignancy associated with limited survival. Syngeneic immunocompetent mouse models of CCA are an essential tool to elucidate the tumor immune microenvironment (TIME), understand mechanisms of tumor immune evasion, and test novel immunotherapeutic strategies. The scope of this study was to develop and characterize immunocompetent CCA models with distinct genetic drivers, and correlate tumor genomics, immunobiology, and therapeutic response.

Methods: A multifaceted approach including scRNA-seq, CITE-seq, whole exome and bulk RNA sequencing was employed. FDA-approved PD-1/PD-L1 antibodies were tested in humanized PD-1/PD-L1 mice (HuPD-H1).

Results: A genetic mouse model of intrahepatic CCA (iCCA) driven by intrabiliary transduction of Fbxw7ΔF/Akt that mimics human iCCA was generated. From the Fbxw7ΔF/Akt tumors, a murine cell line (FAC) and syngeneic model with genetic and phenotypic characteristics of human iCCA were developed. Established SB1 (YAP^S127A/Akt) and KPPC (Kras^G12Dp53^L/L) models were compared to the FAC model. Although the models had transcriptomic similarities, they had substantial differences as well. Mutation patterns of FAC, SB1, and KPPC cells matched different mutational signatures in Western and Japanese CCA patient cohorts. KPPC tumors had a high tumor mutation burden. FAC tumors had a T cell-infiltrated TIME, while SB1 tumors had a preponderance of suppressive myeloid cells. FAC, SB1, and KPPC tumors matched different immune signatures in human iCCA cohorts. Moreover, FAC, SB1, and KPPC tumor-bearing HuPD-H1 mice displayed differential responses to nivolumab or durvalumab.

Conclusions: Syngeneic iCCA models display a correlation between tumor genotype and TIME phenotype, with differential responses to FDA-approved immunotherapies. This study underscores the importance of leveraging multiple preclinical models to understand responses to immunotherapy in different genetic subsets of human CCA.

Impact and implications: Understanding the relationship between tumor genotype and the phenotype of the immune microenvironment is an unmet need in cholangiocarcinoma (CCA). Herein, we use syngeneic murine models of intrahepatic CCA with different genetic drivers to demonstrate a correlation between tumor genotype and immune microenvironment phenotype in murine models, which is associated with differential responses to FDA-approved immunotherapies. This information will help guide other preclinical studies. Additionally, it emphasizes that immune checkpoint inhibition in patients with CCA is not a "one-size-fits-all" approach. Our observations suggest that, as for targeted therapies, patients should be stratified and selected for treatment according to their tumor genetics.

Keywords: Tumor immune microenvironment; immunotherapy; preclinical models.

Fig. 1.. Characterization of murine CCA tumors following biliary transduction of Fbxw7ΔF/Akt.

(A) Schematic depicting a genetic mouse model of CCA driven by Sleeping Beauty transposase-mediated intrabiliary transduction of Fbxw7ΔF and myr-Akt. (B) Gross images of murine livers following biliary transduction at 8, 12, and 16 weeks with increasing tumor burden. Approximately 60% of the animals had tumors at 16 weeks. (C-D) H&E staining and immunohistochemistry of KRT19, HepPar1, α-SMA, and CD45 in murine CCA tumor at 8, 12, and 16 weeks. Scale bar 200 μm. CCA, cholangiocarcinoma. (This figure appears in color on the web.)

Fig. 2.. Implantation of FAC cells results in a syngeneic orthotopic murine model of CCA.

(A) Representative phase contrast microscopy image of FAC cells derived from distinct Fbxw7ΔF/Akt biliary transduction tumor nodules; scale bar 300 μm. (B) Growth curve of FAC cells at 0, 24, 48, and 72 h after plating. (C) Lysates prepared from FAC and Huh7 cells and mouse small intestine tissue were subjected to immunoblot analysis of KRT19, HNF4α, and Sox9. β-actin and GAPDH used as loading controls. (D) Schematic depicting orthotopic implantation model of FAC cells and subsequent tumor development. (E) Tumor weight following orthotopic implantation of FAC cells at 2 and 4 weeks (F) Gross images of murine livers following orthotopic implantation of FAC cells at 2 and 4 weeks. (G-H) H&E staining and immunohistochemistry of KRT19, HepPar1, α-SMA, and CD45 in murine FAC tumor at 2 and 4 weeks. Scale bar 100 μm. CCA, cholangiocarcinoma. (This figure appears in color on the web.)

Fig. 3.. Bulk RNA sequencing and whole exome sequencing of FAC, SB1, and KPPC cells.

(A) Principal component analysis plot of transcriptomes from FAC, SB1, KPPC cells and normal mouse cholangiocyte organoids. (B) Heatmap illustrating variations in gene expression among CCA cell lines and mouse organoids. The colors indicate the level of expression. The intensity of colors is scaled within each row, providing a visual representation of differential gene expression across the samples. (C) Bar plot illustrating pathways unique to each CCA cell line, ranked among the top five upregulated pathways when compared to mouse organoids, analyzed using gene set-enrichment analysis. (D) Summary of mutation type and number based on whole exome sequencing of FAC, SB1, and KPPC cells. (E) Mutational burden of two human CCA patient cohorts (ICGC and TCGA-CHOL) and mouse cell line (left panel). Tumor mutation burden in FAC, SB1 and KPPC cells in mutations per megabase (mut/Mb) (right panel). (F) The top 10 mutated genes in FAC, SB1 and KPPC cells. (G) For the top mutated genes identified from the human cohorts comprising of 468 patients (51 from TCGA-CHOL cohort and 417 patients from ICGC cohort), the bar plot shows filtered tumor mutation rates of these genes in human cohorts and unfiltered tumor mutation rates in mouse cell lines (n = 9) (left two panels). Variant types are indicated for each gene in each mouse sample (right panel). (H) Relative contributions of the identified known COSMIC mutation signatures to each human and mouse cohort. CCA, cholangiocarcinoma; ICGC, International Cancer Genome Consortium; TCGA-CHOL, The Cancer Genome Atlas-cholangiocarcinoma. (This figure appears in color on the web.)

Fig. 4.. The tumor immune microenvironment of syngeneic mouse models.

(A) Schematic of FAC, SB1, and KPPC syngeneic mouse models. (B) Average tumor weight of FAC, SB1, and KPPC tumors. (C) UMAP plot of the unsupervised cell clusters identified from scRNA-seq data. (D) Stacked bar graph representing the relative cell type abundance in tumor and adjacent liver from FAC model. (E) Heatmap depicting the relative abundance of myeloid cell subsets in FAC, SB1, and KPPC tumors. (F) Heatmap depicting the relative abundance of lymphocyte subsets in FAC, SB1, and KPPC tumors. (G) Percentage of TAMs of CD45⁺ cells in FAC, SB1, and KPPC tumors (n ≥10). (H–I) Percentage of G-MDSCs (H) and M-MDSCs (I) of CD45⁺ cells in FAC, SB1, and KPPC tumors (n ≥10). (J) Percentage of CTLs of CD45⁺ cells in FAC, SB1, and KPPC tumors (n ≥4). (K) Percentage of granzyme B⁺ reactive CTLs of CD45⁺ cells in FAC, SB1, and KPPC tumors (n ≥10). (L) Percentage of NK cells of CD45⁺ cells in FAC, SB1, and KPPC tumors (n ≥10). (M) Heatmap depicting differential upregulation of genes encoding cytokines and chemokines in the CCA cell lines with fold change >2 and p value <0.05. (N) Heatmaps illustrating the expression of genes comprising the five STIM classes in FAC, SB1, and KPPC CCA cell lines using bulk RNA-seq data obtained from CCA cell lines. Color representation corresponds to the Z score of the expression data scaled across all genes within each sample. All flow cytometry data are represented as mean ± SD. Unpaired Student’s t test was used. *p <0.05; **p <0.01; ***p <0.001; ****p <0.0001; n.s. = not significant. CCA, cholangiocarcinoma; CTLs, cytotoxic T lymphocytes; G-MDSCs, granulocytic-MDSCs; MDSCs, myeloid-derived suppressor cells; M-MDSCs, monocytic-MDSCs; NK, natural killer; scRNA-seq, single-cell RNA sequencing; STIM, Stroma, Tumor and Immune Microenvironment; TAMs, tumor-associated macrophages; UMAP, uniform manifold approximation and projection. (This figure appears in color on the web.)

Fig. 5.. Syngeneic models of CCA have different responses to immune checkpoint inhibition.

(A) Schematic of FAC syngeneic mouse models and the treatment plan. (B) Average tumor weight in mg and representative images of FAC tumors (n ≥7). (C-E) Percentage of CD8⁺ T cells (CTLs), granzyme B-expressing reactive CTLs, and TAMs of CD45⁺ cells in tumors analyzed by flow cytometry (n ≥4). (F) Schematic of KPPC syngeneic mouse models and the treatment plan. (G) Representative images and average tumor weight of KPPC tumors (n ≥7). (H-J) Percentage of CTLs, reactive CTLs, and granzyme B -expressing reactive CTLs of CD45⁺ in tumors (n ≥3). Data are represented as mean ± SD. Unpaired Student’s t test was used. *p <0.05; **p <0.01; ***p <0.001; ns = not significant. CCA, cholangiocarcinoma; CTLs, cytotoxic T lymphocytes; TAMs, tumor-associated macrophages. (This figure appears in color on the web.)

Fig. 6.. Response to durvalumab and nivolumab monotherapy varies in FAC, KPPC, and SB1 tumor-bearing humanized mice.

(A) Schematic of FAC syngeneic humanized PD-1/PD-L1 mouse models (HuPD-H1) and treatment plan. (B) Average tumor weights in mg and representative images of FAC tumors in HuPD-H1 mice with or without nivolumab or durvalumab treatment (n ≥13). (C) Ultrasound images depict representative tumor cross-sectional areas in FAC tumor-bearing mice before and after treatment with nivolumab. Total volumetric area was quantified after 3D reconstruction using Prospect software. (D) Average tumor weights of KPPC tumors in HuPD-H1 mice with or without nivolumab treatment (n ≥7). (E) Average tumor weights of SB1 tumors in HuPD-H1 mice with or without durvalumab treatment (n ≥4). Data are represented as mean ± SD. Unpaired Student’s t test was used. *p <0.05; n.s. = not significant. (This figure appears in color on the web.)