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Published on: June 12, 2021
Mitigating non-genetic resistance to checkpoint inhibition based on multiple states of immune exhaustion
Irina Kareva1,2, Jana L Gevertz3
1Quantitative Pharmacology Department, EMD Serono, Merck KGaA, Billerica, MA, USA. irina.kareva@emdserono.com.
Abstract:
Despite the revolutionary impact of immune checkpoint inhibition on cancer therapy, the lack of response in a subset of patients, as well as the emergence of resistance, remain significant challenges. Here we explore the theoretical consequences of the existence of multiple states of immune cell exhaustion on response to checkpoint inhibition therapy. In particular, we consider the emerging understanding that T cells can exist in various states: fully functioning cytotoxic cells, reversibly exhausted cells with minimal cytotoxicity, and terminally exhausted cells. We hypothesize that inflammation augmented by drug activity triggers transitions between these phenotypes, which can lead to non-genetic resistance to checkpoint inhibitors. We introduce a conceptual mathematical model, coupled with a standard 2-compartment pharmacometric (PK) model, that incorporates these mechanisms. Simulations of the model reveal that, within this framework, the emergence of resistance to checkpoint inhibitors can be mitigated through altering the dose and the frequency of administration. Our analysis also reveals that standard PK metrics do not correlate with treatment outcome. However, we do find that levels of inflammation that we assume trigger the transition from the reversibly to terminally exhausted states play a critical role in therapeutic outcome. A simulation of a population that has different values of this transition threshold reveals that while the standard high-dose, low-frequency dosing strategy can be an effective therapeutic design for some, it is likely to fail a significant fraction of the population. Conversely, a metronomic-like strategy that distributes a fixed amount of drug over many doses given close together is predicted to be effective across the entire simulated population, even at a relatively low cumulative drug dose. We also demonstrate that these predictions hold if the transitions between different states of immune cell exhaustion are triggered by prolonged antigen exposure, an alternative mechanism that has been implicated in this process. Our theoretical analyses demonstrate the potential of mitigating resistance to checkpoint inhibitors via dose modulation.
Insights
Understanding immune cell exhaustion states is key to improving cancer therapy. Modulating drug dosage and frequency, like with metronomic dosing, can overcome resistance to immune checkpoint inhibitors.
Area of Science:
- Immunology
- Pharmacology
- Mathematical Biology
Background:
- Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy but face challenges with non-response and acquired resistance.
- T cells exhibit diverse exhaustion states: functional, reversible, and terminal, impacting therapeutic efficacy.
- Non-genetic resistance mechanisms, influenced by inflammation or antigen exposure, contribute to ICI treatment failure.
Purpose of the Study:
- To explore the theoretical impact of immune cell exhaustion states on response to ICI therapy.
- To investigate how dose and administration frequency influence resistance to ICIs.
- To identify potential strategies for mitigating ICI resistance through dose modulation.
Main Methods:
- Development of a conceptual mathematical model integrating immune cell exhaustion phenotypes.
- Coupling the conceptual model with a standard 2-compartment pharmacokinetic (PK) model.
- Simulations to analyze the effects of different dosing strategies (high-dose/low-frequency vs. metronomic) on therapeutic outcomes.
Main Results:
- Emergence of resistance to ICIs can be mitigated by altering drug dose and administration frequency.
- Standard PK metrics do not reliably correlate with treatment outcomes.
- Inflammation levels triggering transitions to terminally exhausted T cells critically influence therapeutic success.
- Metronomic-like dosing strategies are predicted to be effective across diverse patient populations, unlike standard high-dose regimens.
- Resistance mitigation holds true even when transitions are triggered by prolonged antigen exposure.
Conclusions:
- Immune cell exhaustion phenotypes significantly influence ICI therapy response and resistance.
- Dose modulation, particularly metronomic-like strategies, offers a promising approach to overcome ICI resistance.
- Future therapeutic designs should consider immune cell state dynamics beyond traditional PK parameters.
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