Progression to fibrosis and hepatocellular carcinoma in DEN CCl4 liver mice, is associated with macrophage and striking regulatory T cells infiltration

Abstract

Background and aim: Hepatocellular carcinoma (HCC) is a classic inflammation related cancer with most cases arising from chronic liver disease (CLD). This study investigates immune dysregulation that occurs during the progression of CLD to HCC by delineating changes in immune cell composition and distribution within the liver microenvironment.

Methods: Mice were injected with Diethylnitrosamine (DEN) at 4 weeks of age, followed by continuous tri-weekly injections of carbon tetrachloride (CCl₄) for 6 and 21 weeks to induce liver fibrosis and HCC. Naïve and Phosphate-buffered saline (PBS) corn oil treated mice were used as controls. Immune cell profiling was performed using multiplex immunofluorescence and flow cytometry analyses.

Results: The spatial analysis of immune cell populations in HCC reveals stable leukocytes overall, with notable increases in myeloid cells, particularly infiltrating macrophages (Inf mph). Indeed, Inf mph show a progressive enrichment from control to tumor, reaching a 5-fold and 10-fold increase in the invasive margin (IM) and surrounding non-tumor tissue (NTT) regions, respectively. T lymphocytes, especially CD4+ T cells but not CD8+ T cells, significantly expand, with CD4+ cells increasing up to 10-fold in the IM and NTT regions of HCC livers. Regulatory T cells (Tregs) population exhibits an extraordinary 125-fold and 80-fold surge in the IM and NTT regions, respectively.

Conclusions: The DEN-CCl₄ induced HCC mouse model replicates key immunosuppressive features of human HCC, notably increased Tregs and macrophages, which provides a robust platform for testing immunotherapies. The prominence of immune cells in the IM region underscores its importance as a critical interface modulating tumor-immune interactions, while the elevated immune presence in the NTT region reflects broader immune dysregulation associated with advanced CLD, and potentially facilitating tumor progression.

Keywords: flow cytometry; hepatocellular carcinoma; immune cells; liver; liver fibrosis; multiplex immunofluorescence.

Figure 1

DEN and CCl4 induced liver fibrosis and HCC in mice. (A) Single injection of 100mg/kg DEN at 4 weeks of age, followed by CCl4 injections of 0.5ml/kg, 3 times a week for 6 weeks to induce liver fibrosis and for 21 weeks to induce the development of HCC tumors in the background of CLD. (B) Representative macroscopic liver images of control, fibrosis and HCC livers. (C) Change in the liver weight and liver to body weight ratios between control (n=5), fibrosis (n=6), HCC (n=7). (D) Representative images of Sirius red and Hematoxylin-eosin staining on control, fibrosis and HCC livers. Collagen encapsulated tumor in HCC liver by the Sirius red staining. (E) Percentage of Sirius red-stained area in control (n=5), fibrosis (n=5) and HCC-NTT (n=6). (F) Ki67⁺ proliferating cells in tumor. (G) Percentage of proliferating cells to total Hoechst detection and percentage of proliferating hepatocytes to total hepatocyte population in control (n=4), fibrosis (n=4), tumor, IM and RT regions of HCC livers (n=4). Error bars represent mean ± SD. One-way ANOVA followed by Tukey’s multiple comparison test was performed. *p<0.05, **p<0.01, ***p<0.001.

Figure 2

Altered spatial localization of immune cells during CLD progression from fibrosis to HCC. (A) Quantification of the number of leukocytes, myeloid cells, granulocytes per mm² tissue in control, fibrosis and HCC livers (combined all 3 regions). (B) Representative staining images of CD45 leukocytes, CD11b myeloid cells and Ly6G granulocytes in control, fibrosis and HCC (tumor, IM and RT regions) groups. (C) Quantification of the number of leukocytes, myeloid cells and granulocytes per mm² tissue in control (n=5), fibrosis (n=6), tumor, IM and NTT of the HCC (n=7) group. (D) Representative immunostaining image of Ki67⁺ proliferating CD45 leukocytes in the tumor region of HCC liver. (E) Percentage of proliferating CD45 leukocytes to total leukocyte population. Error bars represent mean ± SD. One-way ANOVA followed by Tukey’s multiple comparison test for each individual immune cell population was performed. *p<0.05, **p<0.01, ***p<0.001.

Figure 3

Increased numbers of infiltrating macrophages during CLD progression from fibrosis to HCC. (A) Quantification of the number of macrophages, Kupffer cells, Inf macrophages per mm² tissue in control, fibrosis and HCC livers (combined all 3 regions). (B) Representative immunostaining images of IBA1⁺ macrophages and CLEC4F⁺ KCs in control, fibrosis and HCC (tumor, IM and RT regions) groups. (C) Quantification of the number of hepatic macrophages, KCs and Inf mph per mm² tissue in control, fibrosis groups and tumor, IM and RT of the HCC group (n=4). (D) Ratio of KCs and Inf Mphs in total hepatic macrophage populations in all 5 regions. (E) Representative immunostaining images of Ki67⁺ proliferating KCs and Inf Mphs. (F) Percentages of proliferating KCs and Inf Mphs to total KC and Inf mphs populations, respectively. Error bars represent mean ± SD. One-way ANOVA followed by Tukey’s multiple comparison test was performed. *p<0.05, **p<0.01, ***p<0.001.

Figure 4

Increased infiltration of T lymphocytes during CLD progression from fibrosis to HCC. (A) Quantification of the number of CD3 T, CD8 T, CD4 T cells and Tregs per mm² tissue in control, fibrosis and HCC livers (combined all 3 regions). (B) Representative immunostaining images of T lymphocytes like, CD3 T, CD8 T, CD4 T cells and Tregs in control, fibrosis and HCC (tumor, IM and RT regions) groups. (C) Quantification of number of CD3 T, CD8 T, CD4 T cells and Tregs per mm² tissue in control, fibrosis groups and tumor, IM and NTT of HCC group (n=4). Error bars represent mean ± SD. One-way ANOVA followed by Tukey’s multiple comparison test was performed. *p<0.05, **p<0.01, ***p<0.001.

Figure 5

Infiltration and interaction among different immune cell types differs in healthy, fibrosis and HCC livers. (A) Heatmap showing the fold change (against the control group) of immune cell populations in the studied groups. (B) The densities of various immune cells analyzed through multiplex IF are presented as a heatmap in HCC liver tissue. Red hues indicate high cell density while blue ones indicate low cell density. Tumor areas are depicted by black dash circles and tumor regions are depicted by purple oval. (C) Spearman’s correlation matrix and respective p-values of the different parameters stained on HCC liver (tumor, IM, NTT). *p<0.05, **p<0.01, ***p<0.001.

Figure 6

Altered infiltration of immune cells in fibrosis livers. Quantification of the absolute cell numbers of several immune cell populations per g of liver by flow cytometry. (A) Leukocytes, (B), Myeloid cell lineage, (C), Lymphoid cell lineages in naïve (n=4), fibrosis (n=8) groups. Error bars represent mean ± SD. One-way ANOVA followed by Tukey’s multiple comparison test was performed. *p<0.05, **p<0.01, ***p<0.001.