Modeling the effect of immunotherapies on human castration-resistant prostate cancer

Coletti, Roberta; Marchetti, Luca

doi:10.1016/j.jtbi.2020.110500

Cited by 8 publications

(7 citation statements)

References 63 publications

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“…In particular, the value of

, representing the maximal killing rate of tumor by CTL due to the drug ipilimumab , strongly affects the efficacy of the proposed administration protocols. The value of this parameter has been estimated in our previous work [ 15 ], by fitting experimental data referring to those prostate cancer patients having the greatest benefits from the ipilimumab therapy. Therefore, the value estimated for

is higher than what adequate for the average of the prostate cancer patient population, and all the model results represent the optimal case of well-responding patients.…”

Section: Resultsmentioning

confidence: 99%

“…We employ a mathematical model of tumor growth, interacting with the immune system, developed in our previous work [ 15 ]. The original model is composed by 8 ordinary differential equations (ODEs), describing the two forms of PCa, (castration sensitive and resistant, previously named androgen dependent and independent) and some key variables of the immune system, such as dendritic cells, Cytotoxic T cells (CTL), Regulatory T cells (Treg), the interleukin-2 (IL-2), as well as the evolution of the Prostate Specific Antigen (PSA) as linear combination of the PCa cells.…”

Section: Materials and Methodsmentioning

confidence: 99%

“…one infusion of 10 mg/kg every 3 weeks for four cycles. Simulating the system for a patient of

kg (average patient weight according to Coletti et al approximation [ 15 ]), we found the maximal concentration reached and set it as the threshold

mg.…”

Section: Materials and Methodsmentioning

confidence: 99%

“…These extensions allowed us to test a large variety of possible combination therapies, by considering both their efficacy in reducing the tumor and their synergy. We also developed a model of human castration-resistant PCa including dendritic cell vaccine sipuleucel-T and the anti-CTLA4 ipilimumab [ 15 ]. This work aimed at investigating the effect of the immunotherapies on the model steady-states, in order to evaluate if they could lead to tumor eradication.…”

Section: Introductionmentioning

confidence: 99%

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A Model-Based Framework to Identify Optimal Administration Protocols for Immunotherapies in Castration-Resistance Prostate Cancer

Coletti

Lunardi

Caffo

et al. 2021

Cancers

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Prostate cancer (PCa) is one of the most frequent cancer in male population. Androgen deprivation therapy is the first-line strategy for the metastatic stage of the disease, but, inevitably, PCa develops resistance to castration (CRPC), becoming incurable. In recent years, clinical trials are testing the efficacy of anti-CTLA4 on CRPC. However, this tumor seems to be resistant to immunotherapies that are very effective in other types of cancers, and, so far, only the dendritic cell vaccine sipuleucel-T has been approved. In this work, we employ a mathematical model of CRPC to determine the optimal administration protocol of ipilimumab, a particular anti-CTLA4, as single treatment or in combination with the sipuleucel-T, by considering both the effect on tumor population and the drug toxicity. To this end, we first introduce a dose-depending function of toxicity, estimated from experimental data, then we define two different optimization problems. We show the results obtained by imposing different constraints, and how these change by varying drug efficacy. Our results suggest administration of high-doses for a brief period, which is predicted to be more efficient than solutions with prolonged low-doses. The model also highlights a synergy between ipilimumab and sipuleucel-T, which leads to a better tumor control with lower doses of ipilimumab. Finally, tumor eradication is also conceivable, but it depends on patient-specific parameters.

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“…In particular, the value of

is higher than what adequate for the average of the prostate cancer patient population, and all the model results represent the optimal case of well-responding patients.…”

Section: Resultsmentioning

confidence: 99%

Section: Materials and Methodsmentioning

confidence: 99%

“…one infusion of 10 mg/kg every 3 weeks for four cycles. Simulating the system for a patient of

kg (average patient weight according to Coletti et al approximation [ 15 ]), we found the maximal concentration reached and set it as the threshold

mg.…”

Section: Materials and Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Model-Based Framework to Identify Optimal Administration Protocols for Immunotherapies in Castration-Resistance Prostate Cancer

Coletti

Lunardi

Caffo

et al. 2021

Cancers

Self Cite

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show abstract

“…In the early days of cancer immunotherapy, these modeling efforts focused -next to chemotherapy [37] -on cellular immunotherapy [38,39]. More recently, the field has addressed ICI therapy (e.g., [33,40,41]). Models of tumor-immune dynamics have been applied to study pharmacokinetic and therapy dynamics (PK/PD), treatment effects (including mechanism(s) of action, optimizing dosing regimens), treatment combinations, toxicity, biomarker prediction, drug resistance, and drug discovery (see reviews on these topics [38,[42][43][44][45][46][47]).…”

Section: Discussionmentioning

confidence: 99%

In silicocancer immunotherapy trials uncover the consequences of therapy-specific response patterns for clinical trial design and outcome

Creemers

Ankan²,

Roes

et al. 2021

Preprint

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Background Late-stage cancer immunotherapy trials strive to demonstrate the clinical efficacy of novel immunotherapies, which is leading to exceptional responses and long-term survival in subsets of patients. To establish the clinical efficacy of an immunotherapy, it is critical to adjust the trial's design to the expected immunotherapy-specific response patterns. Methods In silico cancer immunotherapy trials are virtual clinical trials that simulate the kinetics and outcome of immunotherapy depending on the type and treatment schedule. We used an ordinary differential equation model to simulate (1) cellular interactions within the tumor microenvironment, (2) translates these into disease courses in patients, and (3) assemble populations of virtual patients to simulate in silico late-stage immunotherapy, chemotherapy, or combination trials. We predict trial outcomes and investigate how therapy-specific response patterns affect the probability of their success. Results In silico cancer immunotherapy trials reveal that immunotherapy-derived survival kinetics — such as delayed curve separation and plateauing curve of the treatment arm — arise naturally due to biological interactions in the tumor microenvironment. In silico clinical trials are capable of translating these biological interactions into survival kinetics. Considering four aspects of clinical trial design — sample size calculations, endpoint and randomization rate selection, and interim analysis planning — we illustrate that failing to consider such distinctive response patterns can significantly reduce the power of novel immunotherapy trials. Conclusion In silico trials have three significant implications for immuno-oncology. First, they provide an economical approach to verify the robustness of biological assumptions underlying an immunotherapy trial and help to scrutinize its design. Second, the biological basis of these trials facilitates and encourages communication between biomedical researchers, doctors, and trialists. Third, its application as an educational tool can illustrate design principles to scientists in training, contributing to improved designs and higher success rates of future immunotherapy trials.

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Modeling the synergistic properties of drugs in hormonal treatment for prostate cancer

Reckell

Nguyen

Phan

et al. 2021

Journal of Theoretical Biology

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Modeling the effect of immunotherapies on human castration-resistant prostate cancer

Cited by 8 publications

References 63 publications

A Model-Based Framework to Identify Optimal Administration Protocols for Immunotherapies in Castration-Resistance Prostate Cancer

A Model-Based Framework to Identify Optimal Administration Protocols for Immunotherapies in Castration-Resistance Prostate Cancer

In silicocancer immunotherapy trials uncover the consequences of therapy-specific response patterns for clinical trial design and outcome

Modeling the synergistic properties of drugs in hormonal treatment for prostate cancer

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