Article Information

Wentao Li, Jinghui Xiu, Liang Yao, Qiuliang Li, Guannan Li, Xiaodong Li, Lu Zhang, Chunhong Ning, Wei Yun, Shizong Hu, Jingqi Huang^*

Department of Pharmacology, Pharmaron Beijing, Co. Ltd., No. 6, TaiHe Road, BDA, Beijing, 100176, People'sRepublic of China

*Corresponding author: Jingqi Huang, SVP. Pharmacology; IACUC, Chair, Pharmaron Beijing, Co. Ltd. Beijing, China.

Received: 22 May 2024; Accepted: 29 May 2024; Published: 05 June 2024

Citation: Wentao Li, Jinghui Xiu, Liang Yao, Qiuliang Li, Guannan Li, Xiaodong Li, Lu Zhang, Chunhong Ning, Wei Yun, Shizong Hu, Jingqi Huang. Comprehensive Profiling of The Immune Status of A Broad Range of in vivo Syngeneic Models to Support IO Development and to Accurately Predict Clinical Benefit of Therapy. Fortune Journal of Health Sciences. 7 (2024): 288-298.

Abstract

Keywords

syngeneic model, tumor, immunotherapy, tumor microenvironment

Article Details

Introduction

Recent clinical successes in treating tumors with immunotherapies, including the application of anti-PD1, anti-PD-L1, and anti-CTLA-4 antibodies, demonstrate the potential to transform treatment methods and improve patient outcomes [1-3]. In particular, PD-1 blockade in PD-L1-expressing tumor cells can overcome immunosuppressive mechanisms present in the tumor microenvironment and reactivate tumor-specific T cells. Priming of naïve T cells into antigen-specific effector T cells requires the participation of the T cell receptor (TCR), antigen recognition, and the proper balance between expression of co-stimulatory molecules that activate T cell proliferation, and co-inhibitory molecules that attenuate T cell activation. Therefore, a promising strategy involves the manipulation of co-stimulatory and co-inhibitory molecules to change the balance within the tumor microenvironment from an immunosuppressive state to an immunostimulatory state. These treatments represent a shift in the approach to cancer therapy as they do not target tumor cells but instead target the immune system to escape inhibitory pathways that attenuate effective antitumor immune responses. However, despite these improvements, clinical responses are still limited. A major factor hindering these novel therapies is the complicated tumor microenvironment, and most likely, the establishment of an immunosuppressive tumor microenvironment due to the existence of Tregs and MDSCs. In many experimental models, Tregs locally regulate the interactions between cytotoxic T lymphocytes (CTLs) and antigen presenting cells (APCs) to induce CTL dysfunction by altering the balance of costimulatory and coinhibitory signals [4]. Tregs can also negatively modulate the activity of other immune cells through the action of soluble molecules, such as IL-10, IL-35, and TGF-β. Thus, it is advantageous for tumors to express membrane bound T cell inhibitory molecules and promote the expansion of Tregs against tumor antigens to evade the immune system.

Currently, murine syngeneic tumor models are the first choice for the development of immune therapeutic agents in the oncology field. Therefore, fully understanding and selecting appropriate preclinical models for target validation, and providing preclinical proof of concept for candidate immunotherapeutic drugs, is crucial to developing new therapeutic approaches for cancer treatment [5]. However, to date, the majority of studies have been performed in a small number of models (compared to xenografts) and, despite their widespread use, little is known about the genotypes and phenotypes of these syngeneic murine tumor models [6]. Consequently, a better understanding of these models is required to select appropriate models and permit both data interpretation and extrapolation to the clinic [6,7]. Here, we describe a comprehensive characterization of gene expression and immunological composition of several murine syngeneic tumor models. We found that immunosuppressive cell types predominated in syngeneic murine tumor models, and further investigation showed differences in both the composition and magnitude of tumor immune infiltrates. In conclusion, this study conducted an extensive immune status profiling of a panel of murine tumor cell lines and of commonly used syngeneic tumor models using RT-PCR and flow cytometer (FACS). Both immune-related genes and the activation of immune infiltration cells were analyzed on all validated in vivo syngeneic models. These data can be readily applied to expedite the discovery and development of novel immunotherapies by increasing the efficiency of preclinical drug development.

Materials and Methods

Cell lines and reagents

Forty-nine murine tumor cell lines were purchased from ATCC, ECACC, Shanghai Zishi, Shanghai huiying biological technology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences or COBIOER for oncology research purposes (Table 1). Cells were cultured in their respective mediums at 37^oC in an incubator with humidified atmosphere of 5% CO₂. Antibodies used for FACS analysis were purchased from Bio-Legend and Ebioscience, and RT-PCR primers and reagents were purchased from QIAGEN and Thermo Fisher. The cell culture medium RPMI 1640, DMEM, Waymouth's MB 752/1, L-15, IMDM, MEM, Fischer's, f12K are from Gibco. Anti PD-1 antibody (CD279, clone RMP1-14) was purchased from Bio-X-Cell.

Table 1: Cell lines and culture conditions

RT-PCR

Tumor tissues were collected and homogenized, and total RNA was extracted with the RNA easy kit (QIAGEN). cDNA was synthesized by using a reverse transcriptase kit (Invitrogen). The data were calculated with 2-ΔCt method.

Animals

At the end of study, all the animals were terminated by carbon dioxide (CO2) euthanasia, animals were put in a 12-liter chamber with 50% volume displacement per minute for 3 minutes, CO2 flow was maintained for 1 minute after respiratory arrest to confirm the death of animal. All animal studies were performed according to the guidelines approved by the IACUC and the guidance of the Association for AAALAC. The Animal Use Protocol (AUP) ON-SYN-06012023 was approved by Pharmaron IACUC members.

The General procedures for animal care and housing were in accordance with the standard of Commission on Life Sciences, National Research Council, SOPs. Female mice aged 7 to 9 weeks with body weight between 18-22 g were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd (joint venture with Charles River Laboratories) and / or Animal Research Center of Nanjing University. Mice used for these studies were quarantined for 3 days initially, and complete health checks were performed by an experienced veterinarian. The mice were housed under specific pathogen-free conditions on a 12/12 light/dark cycle, with ad libitum UV-treated water and rodent diet. For the experimental mouse tumor model, MC38 (1 x 10^8cells/ml) or EMT6 (2 x 10^5cell/ml) were inoculated subcutaneously onto the right flank of the mice. Twice a week (BIW), 2.5 mg/kg or 10 mg/kg anti-PD-1 antibody (Bio-X-Cell) or vehicle PBS were injected intraperitoneally. Tumor volume was measured via caliper and calculated using the formula (a^2 width × b length)/2. Tumor volume was used to calculate tumor growth inhibition (TGI), an indicator of antitumor effectiveness, using the formula: TGI = (1-T/C) × 100%, where “T” and “C” were the mean relative volumes (% tumor growth) of the tumors in the treated and the control groups, respectively.

Tissue dissociation and cytometric analysis

After the tumor volumes reached ~100mm³ and ~500mm³, tumor tissues were harvested and processed using a tumor dissociation enzyme mix. The cell suspensions were passed through 70 μm and 40 μm cell strainers and resuspended FACS buffer (PBS supplemented with 2% FBS). Cells were transferred into FACS tubes and blocked with anti-CD16/32 mAb, then stained with an antibody cocktail including anti-mouse CD45 (PerCP-Cy5.5, Biolegend), CD4 (PE/CY7, Biolegend), CD3 (APC, Biolegend), CD8 (BV510, Biolegend), CD11b (FITC, ebioscience), Gr-1 (BV510, Biolegend), F4/80 (BV421, Biolegend), and CD11c (PE, ebioscience) antibodies for 20 min at 4^oC. Cells were then resuspended in 2 ml of fixation buffer and 1× permeabilization buffer was added along with add 2 ul of FOXP3 Abs, and incubated at 4°C for 30 mins in the dark. Next, fixed cells were washed with 1× intracellular buffer, centrifuged at 600 rpm at 4^oC, and incubated with anti-mouse FoxP3 antibodies (PE, ebioscience). For each sample, 100,000 live events were collected using a BD Canto Cytometer. The data were analyzed with BD FACSDiva™ software.

Statistical analyses

Flow cytometry data was analyzed in GraphPad Prism using one-way ANOVA with Tukey’s correction for multiple comparisons. For tumor growth studies, group sizes were determined using power analyses based on the variability of the models in pilot studies. Tumor growth data were log10 transformed [8, 9]. Models were defined as having statistical significance if the growth kinetics P value between the treated group and the control group was <0.05.

Results

Cell line and culture condition

Expression levels and correlation of PD-L1 and MHCI

Tumors often exploit immune-checkpoint pathways, such as the PD-1 pathway, to protect themselves from the antitumor immune response. PD-L1, the ligand of PD-1, is frequently upregulated on various types of tumor cells, where it inhibits local antitumor T cell responses. To explore the expression levels and correlation of PD-L1 and MHCI on the murine cancer cell lines, we used flow cytometry. The results showed heterogeneity in PD-L1 and MHCI expression across different murine tumor cell lines (Fig. 1A and 1B) and a positive correlation was found between PD-L1 and MHCI expression in cancer cell lines (R² square=0.6157, ***P<0.0001) (Fig. 1C). To determine whether differences in tumor immune infiltration cells could affect responsiveness to immune-checkpoint blockade, we analyzed the expression level of immune-related pathway factors by RT-PCR in various tumor models. We found heterogeneity in tumor immune infiltrates across different tumor cell lines and across murine syngeneic models (Fig. 1 and Fig. 2).

Figure 1: FACS analysis of PD-L1 and MHCI levels in multiple murine tumor cell lines

Murine tumor cell lines (total 44 cell lines) were analyzed by flow-cytometer for PD-L1 (A) and MHCI (B) expression, and the correlation between PD-L1 and MHCI levels was reported (R²=0.6157, ***P<0.0001) (C).

Immune marker expression as readout of immune pathway activity

In a second study, we examined the activity of immune-related pathways in tumor immune infiltrates. To this end, we used RT-PCR to analyze the expression level of immune-relevant proteins, such as regulatory T cell-related proteins, proteins relevant to tumor associated macrophages (TAM), co-stimulator receptors of T cells, co-inhibitory receptors of T cells, and co-inhibitory ligands of tumor cells. The results showed a large variety in the expression of immune markers (Fig. 2). The expressions of TAM-related markers were relatively high, which indicated that the tumor microenvironment was immunosuppressive. Immunological diversity broadly uncovers the diversity of tumor models and therefore provides a powerful resource to evaluate different immunotherapies in the context of these distinct microenvironments for preclinical application.

Figure 2: Gene expression of immune-related pathways in murine syngeneic models

The expression of immune-related genes was analyzed by RT-PCR (Fig. 2) on 37 different tumor models covering 17 tumor types. A total of 23 immune-related genes corresponding to co-stimulatory receptors, co-inhibitory receptors, TAM markers, and Tregs markers were evaluated, with high amplification shown as light red colors, middle amplification as yellow colors, and low amplification as dark green colors.

FACS analysis of immune cell populations in tumor tissues reveals heterogeneity across murine syngeneic models

A complicated immune microenvironment within a tumor often leads to a poor prognosis. Interactions between cancer cells and other immune cell populations contribute to the establishment of an immunosuppressive system that promotes the growth of the tumor. To explore the immune status of tumors, we used flow cytometry to analyze the tumor immune cell infiltration across murine models. Tumors were collected at an average volume of 100 mm³ and 500 mm³ approximately, as this often corresponds to the tumor volume at initiation of dosing in efficacy studies. Immune phenotyping profiling revealed profound differences in the tumor microenvironment across different tumor cell lines in multiple tumor syngeneic models. With the growth of tumor volume, the population of immune cells in tumor tissues showed definite heterogeneity. The ratio of CD4 ⁺T/CD8 ⁺T cells was reduced in general with tumor growth, and Tregs and MDSCs were increased in most tumor cell lines (Fig. 3), demonstrating that the reduction of tumor-infiltrating lymphocytes and the increase of immunosuppressive cells in the tumor microenvironment might have contributed to tumor growth.

Figure 3: Population of immune cell populations in tumor tissues (tumor volume: 100 mm³ and 500 mm³)

Flow cytometry analysis was used to determine the percentages of immune cells in different volumes of tumor tissues of multiple tumor cell lines (Fig. 3), including the percentages of CD45⁺ cells (Fig. 3A), Tregs (Fig. 3B), CD4⁺T cells (Fig. 3C), MDSCs (Fig. 3D), CD8⁺ T (Fig. 3E), and macrophages (Fig. 3F).

Efficacy of PD-1 mAb and CTLA-4 mAb treatment in murine syngeneic models

Table 2 shows TGI of anti-PD-1 antibody treatment in different syngeneic models. We observed various therapeutic effects of anti-PD-1 antibody in different tumor models. Some tumor models showed a high response to anti-PD-1 antibody, while other tumor models showed a mild response or no response. These results serve to identify reference models that can be used for anti-PD-1 applications or to identify possible models for the development of combination therapy in research and development, and clinical treatment.

Table 2: TGI of PD-1 check point inhibitors

Immune-modulating effects of PD-1 inhibition on the MC38 murine colon cancer and EMT6 murine breast cancer models

Immune checkpoint blocking therapy is currently approved by the FDA to treat multiple cancer types. PD-1 is overexpressed on TILs and the PD-1 ligand is highly up-regulated in most cancer cells. Therefore, we chose the relatively highly responsive colon model MC38 and the moderately responsive breast cancer model EMT6 for further study. We assessed the antitumor activity of PD-1 antibody in MC38 tumor models. The results showed that TGI followed anti-PD-1 (2.5 mg/kg) treatment in the MC38 model with a TGI of 54% (Fig. 4), with no significant change in mean body weight during the treatment period. We detected immune cell populations (CD45⁺, CD3⁺, CD4⁺, CD8⁺, Tregs, MDSCs) via flow cytometry on Day 0 (with the vehicle control mean tumor volume approximately 100 mm³) and Day 7 (mean tumor volume approximately 500-600 mm³) of treatment. We also analyzed the expressions of immune pathway-related genes on Day 0 and Day 7. Expression levels of immune pathway-related genes identified through flow cytometry were investigated using RT-PCR as described above. Flow cytometry results revealed that CD4⁺ T cells were significantly increased on Day 7 with anti-PD-1 treatment compared to the control group (P<0.05). Levels of other immune cells (CD45⁺, CD8⁺, Tregs) were decreased, and immunosuppressive MDSCs had no obvious changes compared to the control group. The TAM- and Tregs-related gene expression levels were decreased in general, and gene expression levels of co-stimulator receptors, co-inhibitory receptors of T cells, and co-inhibitory ligands of tumor cells, were increased in the anti-PD-1 treated group compared to the control group.

TGI by anti-PD-1 (10 mg/kg) treatment in the EMT6 model was 23% (Fig. 5), with no remarkable changes in the mean body weight of mice during the treatment period. Flow cytometry results showed that the percentage of CD4⁺ T cells/CD8⁺ T cells was significantly increased following anti-PD-1 treatment compared to the control group (*P<0.05), MDSCs and Tregs were significantly decreased, and CD45⁺, CD3⁺ T cells were increased compared to the control groups on Day 8. The expression of gene for TAM markers, Tregs markers, co-stimulator receptors, co-inhibitory receptors of T cells, and co-inhibitory ligands of tumor cells were all increased. These results showed that immunosuppression in the tumor microenvironment improved through anti-PD-1 treatment. At the same time, our data illustrated the remarkable differences of tumor microenvironments in different tumor models, which depends on the tumor type and the progression of tumor growth. Multiple tumors showed infiltrated immune cells which reflected the composition and magnitude of phenotypes of infiltrates and might have contributed to the alteration of differential gene expression related to immune pathways. In addition, these data highlight the need for extensive characterization of models used for preclinical immunotherapy research, and provides data that will, based on the proposed mechanism of action of the therapy being evaluated, support investigators in selecting appropriate models using hypothesis-driven rationales.

Figure 4: The antitumor activity of anti-PD-1 treatment varies for the MC38 murine colon cancer model

Tumor growth curves for MC38 subcutaneous murine syngeneic tumor model treated with PD-1 antibody 2.5 mg/kg (CD279, clone RMP1-14). Treatment was given by intraperitoneal injection on the days marked with ticks on the x axis of the graphs (Fig. 4A). MC38 tumors were collected on Day 7 post treatment for FACS analysis for immune cell profiling (Fig 4B). Gene profiling of the tumor was conducted (Fig 4C). n ≥ 6 mice per group. *P <0.05, ns: non-significant P ≥0.05.

Figure 5: Anti-tumor effect of PD-1 antibody on EMT6 murine breast cancer model

Tumor growth curves for EMT6 subcutaneous murine syngeneic tumor model treated with (A) PD-1 antibody 10 mg/kg (CD279, clone RMP1-14). Treatment was also given by intraperitoneal injection on the days marked with ticks on the x axis of the graphs (Fig 5A). EMT6 tumors were collected on Day 8 of treatment for FACS analysis for immune cell profiling (Fig 5B). Gene profiling of the tumor was conducted (Fig 5C). n ≥ 6 mice per group. *P <0.05, ns: non-significant P ≥0.05

Discussion

Tumors not only contain cancer cells, but also comprise a rich microenvironment composed of blood vessels, APCs, neutrophils, myeloid-derived suppressor cells, tumor-associated macrophages, fibroblasts, components of the extracellular matrix, and soluble factors (such as cytokines and growth factors), all of which may assist or hinder anti-tumor immune responses. The lack of clinical efficacy of cancer therapy can be mostly attributed to an immunosuppressive tumor microenvironment, and the presence of Tregs or MDSCs, which can inhibit anti-tumor immune responses and is associated with decreased survival [10-12]. Alternatively, the expression of inhibitory molecules on the surface of tumor cells could promote the expansion and accumulation of nonresponsive anergic T cells or Tregs within the tumor microenvironment [13-16]. Murine syngeneic tumor models play a central role in the development of novel immunotherapies. Considering the limited understanding of preclinical trial models, there is a need to extensively elucidate their immunological characteristics in the tumor microenvironment. In this study, a total of 44 tumor cell lines were analyzed for the expression of PD-L1 and MHCI at the cellular level, with the highest expression on RENCA, WEHI-164, P388D, and EMT6 cells, and the lowest expression levels on EL4, LL-2, and WEHI-231 cells. The correlation of PD-L1 expression vs. MHCI expression was R²=0.62 (Fig. 1). Immune-related genes were analyzed by RT-PCR (Fig. 2). Furthermore, 50 models were profiled for immune status when the tumor volume was ~100 mm³ and ~500 mm³ (Fig. 3). Herein, we provide a guide for the selection of syngeneic models to test drug therapeutic effect and to evaluate immunotherapy, which not only increases the value of such studies but also reduces the numbers of animals used in scientific research. PD-1 antibody was tested, and the response of this checkpoint inhibitor was reported with TGI values.

Immune checkpoint plays an important regulatory role in adaptive immunity and determines the fate of the immune cell towards activation or suppression, which has been extensively studied in recent years [17-19]. It was divided into two categories: forward signaling towards TC, and both forward and reverse signaling towards TC and APC. Each category can be further divided into stimulatory and inhibitory immune checkpoints. The stimulatory immune checkpoint turns up the immune system leading to immune cell proliferation or activation, while the inhibitory immune checkpoint turns down the immune system leading to immune cell suppression or death. For instance, costimulatory molecules will enhance T cell expansion and differentiation either because of increased rates of T cell proliferation or increased survival of the activated T cells [20-24]. Elucidation of the complex web of stimulatory and inhibitory signals in different models will ultimately contribute to guiding treatment strategies and enhancing therapeutic responses. In this study, we tested various costimulatory receptor and coinhibitory ligand markers in MC38 and EMT tumor syngeneic models, and also detected immunosuppressive MDSCs and Tregs, and multiple TILs in multiple syngeneic models. We observed that the composition of immune-infiltrate cells in the tumor microenvironment across the models was strikingly varied. Previous studies have shown that different syngeneic tumor models can respond differently to treatment [25, 26], so it was necessary that the differences between an extensive array of syngeneic models were characterized. A complicated immune microenvironment with tumor development leads to an unsatisfactory prognosis. This immunological variety of immune infiltration cells observed in this study broadly demonstrated the diversity of tumors observed clinically, and therefore may provide suitable settings to evaluate experimental immunotherapies in the context of these distinct microenvironments. Our data also illustrated the remarkable differences between tumor microenvironments which were influenced by the tumor type and the progression of tumor growth. Infiltrated immune cells in the tumor tissues reflected the composition and magnitude of phenotypes of infiltrates and contributed to the alteration of differential gene expression related to immune pathways. Hopefully, this profiling data with in vivo treatment of PD-1 antibody will help scientists to select appropriate models to support research and development, and to better understand how immunotherapy agents act on the immune system.

In summary, we provide an extensive range of commonly used murine syngeneic models that allow for the selection of a model based on the biology of the tumor cells and the tumor microenvironment. The integration of such data sets will inform optimal therapeutic strategies, which will contribute to a better understanding of human cancer subtypes and, in turn, may ultimately improve the efficiency of drug development for oncology.

Acknowledgements

Thanks to Dr. Chune Liu, Project Manager, Pharmacology of Pharmaron Inc., for providing valuable comments and suggestions for this manuscript. Thanks to Dr. Erich Grimm, the Vice President, BD of Pharmaron Inc., for proof reading.

Statements & Declarations

This work was supported by Pharmaron Beijing, Co. Ltd. Author Jingqi Huang has received research support from Pharmacology Pharmaron Beijing, Co. Ltd.

Author Contributions

Jingqi Huang is fully responsible to the study design and data quality.

Jinghui Xiu and Shizong Hu managed ex vivo section including FACS and gene analysis.

Wentao Li, Lu Zhang, Liang Yao, Guannan Li, Qiuliang Li, Xiaodong Li and Wei Yun performed in vivo studies.

Chunhong Ning composed the manuscript.

All authors read and approved the final manuscript.

Availability of data and materials

The data generated during and analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Conflict of interest

All authors are employed by Pharmaron Beijing, Co. Ltd. This study was sponsored by Pharmacology Pharmaron Corporation.

Consent for publication

Not applicable.

Ethics approval

All in vivo experiments were conducted in Pharmaron Pharmacology with approved animal protocols.  In vivo experiments were done according to the guidelines approved by the Institutional Animal Care and Use Committee (IACUC) of Pharmaron Pharmacology in accordance with all standards of the Association for Assessment and Accreditation of Laboratory Animal Care (AAALAC).

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