Autologous humanized mouse models of iPSC-derived tumors enable characterization and modulation of cancer-immune cell interactions

Abstract

Modeling the tumor-immune cell interactions in humanized mice is complex and limits drug development. Here, we generated easily accessible tumor models by transforming either primary skin fibroblasts or induced pluripotent stem cell-derived cell lines injected in immune-deficient mice reconstituted with human autologous immune cells. Our results showed that fibroblastic, hepatic, or neural tumors were all efficiently infiltrated and partially or totally rejected by autologous immune cells in humanized mice. Characterization of tumor-immune infiltrates revealed high expression levels of the dysfunction markers Tim3 and PD-1 in T cells and an enrichment in regulatory T cells, suggesting rapid establishment of immunomodulatory phenotypes. Inhibition of PD-1 by Nivolumab in humanized mice resulted in increased immune cell infiltration and a slight decrease in tumor growth. We expect that these versatile and accessible cancer models will facilitate preclinical studies and the evaluation of autologous cancer immunotherapies across a range of different tumor cell types.

Keywords: PD-1; autologous tumors; cancer immunotherapy; humanized mouse models; iPSC.

Graphical abstract

Figure 1

Engineered human skin fibroblast-derived tumors are recognized by autologous immune cells in Auto-AT mice (A) Growth curves for 4T transformed adult dermal skin fibroblasts (left) and individual growth for all tumors without immune humanization (middle, no-AT, blue) and with autologous Hu-AT (right, Auto-AT, green) expressed in radiance integrated density. Shown is the mean ± SEM. (B) End point tumor volume assessment in no-AT (n = 24 tumors) and Auto-AT (n = 10 tumors) conditions. (C) Characterization of the human immune infiltrate by flow cytometry. tSNE dimensional reduction visualization with unsupervised clustering using FlowSOM module for FlowJo and manual labeling of subtypes (left). Differential clustering between hTIIC and blood human CD45⁺ cells shows little overlap, signifying differential marker expression levels (right). (D) Manual quantification of differentially represented human immune populations between blood and tumor samples. (E) Exhaustion/dysfunction gating strategy (left) and quantification (right) showing no significant change in total CD3, CD8+, and CD4⁺ T cell population dysfunction frequency between blood and tumor. (F) Differential expression levels of dysfunction markers Tim3 and PD-1 on human T cell populations in blood vs. tumor samples shown by mean fluorescence intensity quantification. In (C, right), (D), (E), and (F), red indicates blood human immune cells, and light blue indicates hTIIC; n = number of tumors, two tumors per mouse.

Figure 2

Human skin fibroblast-derived tumors are recognized by autologous immune cells in Hu-BLT mice (A) Growth curves for repeated experiments showing fetal skin fibroblast-derived tumors from two different donors exposed to allogeneic (top and bottom) and autologous (middle) Hu-BLT immune reconstitution. Shown as mean ± SEM; n = number of tumors, two tumors per mouse. (B) Endpoint tumor volume assessment in BLT mice for each condition presented in (A) showing Auto-BLT to be less proficient at rejecting tumors than Allo-BLT. (C) tSNE dimensional-reduction plots of human blood (left) or tumor-infiltrating immune cells (hTIIC, right) for Allo-BLT (top) and Auto-BLT (bottom) flow cytometry samples. All immune cells are from the same donor. (D) Population annotation of human immune populations in BLT-humanized mice. Combined results and population annotation from (C) (top) and expression of exhaustion markers PD-1 and Tim3 (bottom left and middle) and Treg-associated marker CD25 (bottom right). All these markers are enriched in the hTIIC samples. (E) quantification of effector populations (top row) in blood and hTIIC samples of Auto-BLT (gray bars, filled circles) and Allo-BLT (empty bars and circles) samples. Enrichment of CD8⁺ cells and concomitant decrease in hCD4⁺ T cells in Auto-BLT was observed. Quantification of immunosuppressive Treg (bottom far left) and dysfunctional T cells (bottom center-left), and expression levels of PD-1 (bottom center-right) and Tim3 (bottom far right). No significant variation between immunosuppressive and dysfunction markers between Auto- and Allo-BLT samples was observed.

Figure 3

iPSC-derived hepatic tumors are recognized in Auto-AT mice (A) Schematic of the iPSC differentiation protocol used to generate hepatocyte-like cells (HLC). Red arrows indicate time points for initiation of cellular transformation by SV40ER transduction. (B) Histology of a HLC 4T tumor at low and high magnifications of hematoxylin-eosin-saffron (HES) staining. High magnification (left) shows border of well-circumscribed tumor with entrapped liver parenchyma (blue arrowheads) and varying tumor density. High magnification photomicrograph (right) again shows parenchymal entrapment (blue arrowheads), polynucleated cells (red arrowheads), numerous mitoses, hyperchromatic nuclei, and generally highly pleomorphic cells and nuclei. (C) Mean ± SEM of in vivo HCT 4T tumor elimination by Auto-AT. Integrated density of intrahepatic tumor-associated luciferase signal for two independent donors (left and right) and representative longitudinal in vivo bioluminescence from donor A Scale bar in C: left, 1 mm; right, 100 μm.

Figure 4

iPSC-derived neural tumors are rejected in Auto-AT mice (A) Schematic of iPSC differentiation approach for the generation of neural stem cells (NSCs) and astrocytic cell populations. Red arrows indicate populations transformed using the 4T approach. (B) Histology of one iNSC 4T tumor (top) and two representative iAstro-derived tumors (middle and bottom). High-magnification photomicrographs on right show poorly differentiated tumor cells with brisk mitotic activity with little (top) or more conspicuous (middle) diffuse infiltration or epithelioid/giant cell differentiation (bottom). (C) Representative images of longitudinal in vivo luciferase imaging in no-AT (top) and Auto-AT (bottom) mice. (D) Mean ± SEM graph of in vivo luciferase signal quantification of iAstro 4T tumors with (Auto-AT) and without (no-AT) adoptive transfer in two different donors. (E) Immunofluorescent staining images for human immune cells infiltrate detection within samples of iAstro 4T tumors at day 29 post-tumor-cell injection and Auto-AT showing human immune infiltrate specifically within tumors. Red, SV40 Large T; green, hCD45; blue, DAPI. Scale bar in B: left, 2 mm; all other scale bars, 100 μm.

Figure 5

Injection of Nivolumab in Hu-AT mice leads to increased immune infiltration and clearance of autologous tumors (A-B) Tumor microphotograph of HLA-ABC and PD-L1-stained fibroblastic (top) and HLC 4T (bottom) tumors. Fibroblastic tumors show strong PD-L1 staining, and HLC 4T tumors show tumor-specific (T) staining compared with surrounding mouse liver (L). Effect of Nivolumab administration in Auto-AT fibroblastic (C) and HLC 4T (D) tumor-bearing mice. (C) Shown are the results of two independent experiments showing tumor growth (left, mean ± SEM) and tumor weight at sacrifice (right, mean ± SD) for each experiment; n = number of tumors, two tumors per mouse. (D) Tumor growth curve (mean ± SEM) of HLC 4T tumors as measured by luciferase-associated radiance in Auto-AT (green), and Auto-AT treated with Nivolumab (orange) ; n = number of mice, one intrahepatic tumor injection per mouse. (E) Representative images of human immune infiltrate within s.c. fibroblastic tumor samples for NSG-SGM3 control (left), Auto-AT alone (middle) and Auto-AT + Nivolumab (right). Red, large T; green human CD45. Scale bars, 200 μm.