Cancer Immunotherapy: A promising platform for predicting toxicity
Organ-on-chip approaches could help researchers to better predict the toxicity of cancer immunotherapy drugs.
- Lausanne University Hospital, Switzerland
Killing cancer cells can be done directly or by harnessing the immune system through an approach called cancer immunotherapy (Robert, 2020). Indeed, over the past decade, most of the advances in oncology have involved boosting immune cells to destroy tumor cells. Some of these treatments have resulted in impressive improvements in survival, bringing the possibility of a cure closer for some patients (Robert et al., 2018). This is a big milestone in oncology.
Despite these advances, immunotherapies can be associated with toxicity, which forces the treatment to be stopped: if immune cells become too activated, they can mistakenly recognize and destroy healthy tissues. This can lead, for example, to rashes, hepatitis or colitis depending on whether the skin, liver or gut are attacked (Marin-Acevedo et al., 2019).
A big challenge in oncology is therefore to predict which new immunotherapy drugs are going to be too harmful for patients. This is usually examined in animal models, but since their immune systems differ from the human immune system, it can be difficult to reliably predict toxicity (Zschaler et al., 2014). Now, in eLife, Nikolce Gjorevski (Roche), Lauriane Cabon (Roche) and colleagues – including Jordan Kerns and Chaitra Belgur of Emulate Inc in Boston as joint first authors – report how an in vitro model can help bypass this problem for T cell bispecific antibodies immunotherapy (Kerns et al., 2021).
T cell bispecific antibodies (or TCBs) can recognise and bind to ‘antigen’ proteins present on the surface of tumors, as well as receptors displayed by immune ‘T cells’: by bringing the two types of cells closer, this process helps to activate T cells and allows them to kill their targets. However, the antigens that TCBs bind to are not always exclusive to cancer cells. Recognition of non-cancer cells which share antigens with tumors – known as the on-target, off-tumor effect – can lead to normal cells being damaged (Labrijn et al., 2019; Figure 1). Predicting which TCBs under clinical development will cause such undesired toxicity represents an important challenge in oncology.
Figure 1
Testing drug toxicity using an organ-on-chip platform.
Administering TCBs to an organ-on-chip platform (such as a model of the lung or intestine) allows the antibodies (Y-shaped structures) to recognize antigens (shown in yellow and blue) present in both healthy epithelial and cancerous cells. This brings T cells close to their targets and also activates them, which can lead to healthy cells being damaged (as assessed by measuring cell death and inflammation levels). This model is able to partially reproduce toxicity observed in animals and humans.
Image credit: Image was prepared with Servier Medical Art (CC BY 3.0).
To address this issue, Kerns et al. first took advantage of a lung-on-chip model (Huh et al., 2010) – a system grown under conditions mimicking those found in the body – to predict toxicity to TCBs. This ‘mini-organ’ was exposed to a TCB that recognises an antigen present in ovarian, lung and breast cancer cells, but which can also be expressed, at lower levels, in healthy lung cells. This manipulation led to healthy cells being damaged in the lung-on-chip model, which was then used to determine which TCB dose could kill tumors while sparing normal lung cells. This dose was then administered to mouse models, whose lungs remained undamaged. This demonstrates that the lung-on-chip was able to efficiently predict toxicity in these animals.
Kerns et al. then used an intestine-on-chip model to test a TCB which targets an antigen present on both colon cancer and normal intestine cells. Healthy cells survived the treatment but signs of toxicity emerged that could mimick side-effects that commonly occur in patients, such as increased inflammation.
Using an organ-on-chip model to test TCBs therefore has two main advantages. First, it reproduces toxicity observed in vivo, and can help to determine which doses are effective while remaining safe for normal cells. Second, it serves to predict toxicity before patients are administered with newly-developed TCBs, filling the gap between animal and human studies for drugs that are yet to be clinically tested. Organ-on-chip models could therefore make drug development more efficient by helping to screen out toxic TCBs before they reach cancer patients.
References
-
Bispecific antibodies: a mechanistic review of the pipelineNature Reviews Drug Discovery 18:585–608.https://doi.org/10.1038/s41573-019-0028-1
-
Immune checkpoint inhibitor toxicitiesMayo Clinic Proceedings 94:1321–1329.https://doi.org/10.1016/j.mayocp.2019.03.012
-
Durable complete response after discontinuation of pembrolizumab in patients with metastatic melanomaJournal of Clinical Oncology 36:1668–1674.https://doi.org/10.1200/JCO.2017.75.6270
-
A decade of immune-checkpoint inhibitors in cancer therapyNature Communications 11:3801.https://doi.org/10.1038/s41467-020-17670-y
-
Differences in innate immune response between man and mouseCritical Reviews in Immunology 34:433–454.https://doi.org/10.1615/CritRevImmunol.2014011600
Article and author information
Author details
Maria Ochoa de Olza
Publication history
- Version of Record published: September 24, 2021 (version 1)
Copyright
© 2021, Ochoa de Olza
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 864
- views
-
- 63
- downloads
-
- 2
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Cancer Immunotherapy: A promising platform for predicting toxicity
eLife 10:e73191.
https://doi.org/10.7554/eLife.73191
Further reading
-
- Cancer Biology
Diffuse midline gliomas (DMGs) are aggressive and fatal pediatric tumors of the central nervous system that are highly resistant to treatments. Lysine to methionine substitution of residue 27 on histone H3 (H3-K27M) is a driver mutation in DMGs, reshaping the epigenetic landscape of these cells to promote tumorigenesis. H3-K27M gliomas are characterized by deregulation of histone acetylation and methylation pathways, as well as the oncogenic MYC pathway. In search of effective treatment, we examined the therapeutic potential of dual targeting of histone deacetylases (HDACs) and MYC in these tumors. Treatment of H3-K27M patient-derived cells with Sulfopin, an inhibitor shown to block MYC-driven tumors in vivo, in combination with the HDAC inhibitor Vorinostat, resulted in substantial decrease in cell viability. Moreover, transcriptome and epigenome profiling revealed synergistic effect of this drug combination in downregulation of prominent oncogenic pathways such as mTOR. Finally, in vivo studies of patient-derived orthotopic xenograft models showed significant tumor growth reduction in mice treated with the drug combination. These results highlight the combined treatment with PIN1 and HDAC inhibitors as a promising therapeutic approach for these aggressive tumors.
-
- Cancer Biology
- Cell Biology
High-throughput vertebrate animal model systems for the study of patient-specific biology and new therapeutic approaches for aggressive brain tumors are currently lacking, and new approaches are urgently needed. Therefore, to build a patient-relevant in vivo model of human glioblastoma, we expressed common oncogenic variants including activated human EGFRvIII and PI3KCAH1047R under the control of the radial glial-specific promoter her4.1 in syngeneic tp53 loss-of-function mutant zebrafish. Robust tumor formation was observed prior to 45 days of life, and tumors had a gene expression signature similar to human glioblastoma of the mesenchymal subtype, with a strong inflammatory component. Within early stage tumor lesions, and in an in vivo and endogenous tumor microenvironment, we visualized infiltration of phagocytic cells, as well as internalization of tumor cells by mpeg1.1:EGFP+ microglia/macrophages, suggesting negative regulatory pressure by pro-inflammatory cell types on tumor growth at early stages of glioblastoma initiation. Furthermore, CRISPR/Cas9-mediated gene targeting of master inflammatory transcription factors irf7 or irf8 led to increased tumor formation in the primary context, while suppression of phagocyte activity led to enhanced tumor cell engraftment following transplantation into otherwise immune-competent zebrafish hosts. Altogether, we developed a genetically relevant model of aggressive human glioblastoma and harnessed the unique advantages of zebrafish including live imaging, high-throughput genetic and chemical manipulations to highlight important tumor-suppressive roles for the innate immune system on glioblastoma initiation, with important future opportunities for therapeutic discovery and optimizations.
