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Checcoli A, Pol JG, Naldi A, Noel V, Barillot E, Kroemer G, Thieffry D, Calzone L, Stoll G. Dynamical Boolean Modeling of Immunogenic Cell Death. Front Physiol 2020; 11:590479. [PMID: 33281620 PMCID: PMC7690454 DOI: 10.3389/fphys.2020.590479] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2020] [Accepted: 10/24/2020] [Indexed: 11/13/2022] Open
Abstract
As opposed to the standard tolerogenic apoptosis, immunogenic cell death (ICD) constitutes a type of cellular demise that elicits an adaptive immune response. ICD has been characterized in malignant cells following cytotoxic interventions, such as chemotherapy or radiotherapy. Briefly, ICD of cancer cells releases some stress/danger signals that attract and activate dendritic cells (DCs). The latter can then engulf and cross-present tumor antigens to T lymphocytes, thus priming a cancer-specific immunity. This series of reactions works as a positive feedback loop where the antitumor immunity further improves the therapeutic efficacy by targeting cancer cells spared by the cytotoxic agent. However, not all chemotherapeutic drugs currently approved for cancer treatment are able to stimulate bona fide ICD: some commonly used agents, such as cisplatin or 5-fluorouracil, are unable to activate all features of ICD. Therefore, a better characterization of the process could help identify some gene or protein candidates to target pharmacologically and suggest combinations of drugs that would favor/increase antitumor immune response. To this end, we have built a mathematical model of the major cell types that intervene in ICD, namely cancer cells, DCs, CD8+ and CD4+ T cells. Our model not only integrates intracellular mechanisms within each individual cell entity, but also incorporates intercellular communications between them. The resulting cell population model recapitulates key features of the dynamics of ICD after an initial treatment, in particular the time-dependent size of the different cell types. The model is based on a discrete Boolean formalism and is simulated by means of a software tool, UPMaBoSS, which performs stochastic simulations with continuous time, considering the dynamics of the system at the cell population level with appropriate timing of events, and accounting for death and division of each cell type. With this model, the time scales of some of the processes involved in ICD, which are challenging to measure experimentally, have been predicted. In addition, our model analysis led to the identification of actionable targets for boosting ICD-induced antitumor response. All computational analyses and results are compiled in interactive notebooks which cover the presentation of the network structure, model simulations, and parameter sensitivity analyses.
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Affiliation(s)
- Andrea Checcoli
- Institut de Biologie de l'ENS (IBENS), Département de Biologie, École Normale Supérieure, CNRS, INSERM, Université PSL, Paris, France
| | - Jonathan G. Pol
- Equipe 11 labellisée par la Ligue Nationale contre le Cancer, Centre de Recherche des Cordeliers, INSERM U1138, Université de Paris, Sorbonne Université, Institut Universitaire de France, Paris, France
- Metabolomics and Cell Biology Platforms, Gustave Roussy Cancer Campus, Villejuif, France
| | - Aurelien Naldi
- Institut de Biologie de l'ENS (IBENS), Département de Biologie, École Normale Supérieure, CNRS, INSERM, Université PSL, Paris, France
| | - Vincent Noel
- Institut Curie, PSL Research University, Paris, France
- INSERM, U900, Paris, France
- MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, Paris, France
| | - Emmanuel Barillot
- Institut Curie, PSL Research University, Paris, France
- INSERM, U900, Paris, France
- MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, Paris, France
| | - Guido Kroemer
- Equipe 11 labellisée par la Ligue Nationale contre le Cancer, Centre de Recherche des Cordeliers, INSERM U1138, Université de Paris, Sorbonne Université, Institut Universitaire de France, Paris, France
- Metabolomics and Cell Biology Platforms, Gustave Roussy Cancer Campus, Villejuif, France
- Pôle de Biologie, Hôpital Europeen Georges Pompidou, AP-HP, Paris, France
- Suzhou Institute for Systems Biology, Chinese Academy of Sciences, Suzhou, China
- Department of Women's and Children's Health, Karolinska University Hospital, Stockholm, Sweden
| | - Denis Thieffry
- Institut de Biologie de l'ENS (IBENS), Département de Biologie, École Normale Supérieure, CNRS, INSERM, Université PSL, Paris, France
| | - Laurence Calzone
- Institut Curie, PSL Research University, Paris, France
- INSERM, U900, Paris, France
- MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, Paris, France
| | - Gautier Stoll
- Equipe 11 labellisée par la Ligue Nationale contre le Cancer, Centre de Recherche des Cordeliers, INSERM U1138, Université de Paris, Sorbonne Université, Institut Universitaire de France, Paris, France
- Metabolomics and Cell Biology Platforms, Gustave Roussy Cancer Campus, Villejuif, France
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Grasselly C, Denis M, Bourguignon A, Talhi N, Mathe D, Tourette A, Serre L, Jordheim LP, Matera EL, Dumontet C. The Antitumor Activity of Combinations of Cytotoxic Chemotherapy and Immune Checkpoint Inhibitors Is Model-Dependent. Front Immunol 2018; 9:2100. [PMID: 30356816 PMCID: PMC6190749 DOI: 10.3389/fimmu.2018.02100] [Citation(s) in RCA: 84] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Accepted: 08/24/2018] [Indexed: 12/14/2022] Open
Abstract
In spite of impressive response rates in multiple cancer types, immune checkpoint inhibitors (ICIs) are active in only a minority of patients. Alternative strategies currently aim to combine immunotherapies with conventional agents such as cytotoxic chemotherapies. Here, we performed a study of PD-1 or PDL-1 blockade in combination with reference chemotherapies in four fully immunocompetent mouse models of cancer. We analyzed both the in vivo antitumor response, and the tumor immune infiltrate 4 days after the first treatment. in vivo tumor growth experiments revealed variable responsiveness to ICIs between models. We observed enhanced antitumor effects of the combination of immunotherapy with chemotherapy in the MC38 colon and MB49 bladder models, a lack of response in the 4T1 breast model, and an inhibition of ICIs activity in the MBT-2 bladder model. Flow cytometry analysis of tumor samples showed significant differences in all models between untreated and treated mice. At baseline, all the tumor models studied were predominantly infiltrated with cells harboring an immunosuppressive phenotype. Early alterations of the tumor immune infiltrate after treatment were found to be highly variable. We found that the balance between effector cells and immunosuppressive cells in the tumor microenvironment could be altered with some treatment combinations, but this effect was not always correlated with an impact on in vivo tumor growth. These results show that the combination of cytotoxic chemotherapy with ICIs may result in enhanced, similar or reduced antitumor activity, in a model- and regimen-dependent fashion. The present investigations should help to select appropriate combination regimens for ICIs.
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Affiliation(s)
- Chloé Grasselly
- Anticancer Antibodies, CRCL, INSERM U1052, CNRS UMR 5286, CLB, UCBL, Lyon, France.,ANTINEO, Lyon, France
| | - Morgane Denis
- Anticancer Antibodies, CRCL, INSERM U1052, CNRS UMR 5286, CLB, UCBL, Lyon, France.,ANTINEO, Lyon, France
| | - Aurore Bourguignon
- Anticancer Antibodies, CRCL, INSERM U1052, CNRS UMR 5286, CLB, UCBL, Lyon, France.,ANTINEO, Lyon, France
| | | | | | | | - Laurent Serre
- Univ Lyon, Université Claude Bernard Lyon 1, INSERM 1052, CNRS 5286, Centre Léon Bérard, Cancer Research Center of Lyon, Lyon, France
| | - Lars Petter Jordheim
- Anticancer Antibodies, CRCL, INSERM U1052, CNRS UMR 5286, CLB, UCBL, Lyon, France
| | - Eva Laure Matera
- Anticancer Antibodies, CRCL, INSERM U1052, CNRS UMR 5286, CLB, UCBL, Lyon, France
| | - Charles Dumontet
- Anticancer Antibodies, CRCL, INSERM U1052, CNRS UMR 5286, CLB, UCBL, Lyon, France.,Hospices Civils de Lyon, Lyon, France
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