Tisagenlecleucel Model‐Based Cellular Kinetic Analysis of Chimeric Antigen Receptor–T Cells

Stein, Andrew M.; Grupp, Stephan A.; Levine, John E.; Laetsch, Theodore W.; Pulsipher, Michael A.; Boyer, Michael W.; August, Keith J.; Levine, Bruce L.; Tomassian, Lori; Shah, Shruti; Leung, Mimi; Huang, Pai Hsi; Awasthi, Rakesh; Mueller, Karen Thudium; Wood, Patricia A.; June, Carl H.

doi:10.1002/psp4.12388

Cited by 96 publications

(197 citation statements)

References 22 publications

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“…S11c). We remark that the parameters 2 and 5 are on the order of (10 42h ), which appear to be activation and the T-cell proliferation is not dose dependent [18], the trend observed in 5 with dose is dominated by the exhaustion rate: the higher the dose, the lower the exhaustion rate, resulting in an increased value of 5 . The death rate of CAR T-cells was very small as compared to the cancer cell proliferation rate for all conditions.…”

Section: Carrgo Model Applied To In Vivo Human Datamentioning

confidence: 80%

“…As CAR T-cell therapy is a newly advanced treatment modality, relatively few studies have utilized computational modelling to understand and improve this cell-based therapy. Recently computational models have been developed to investigate cytokine release syndrome for toxicity management [15][16][17], effect of cytokine release syndrome on CAR T-cell proliferation [18], and mechanisms of CAR T-cell activation [19,20], dosing strategies [21]. However, it remains an open challenge how to use mathematical modeling to study and ultimately predict dynamics of CAR T-cell mediated cancer cell killing with respect to CAR T-cell dose, cancer cell proliferation, target antigen expression, and how these factors contribute to the overall effectiveness of CAR T-cell therapy.…”

Section: Introductionmentioning

confidence: 99%

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Mathematical deconvolution of CAR T-cell proliferation and exhaustion from real-time killing assay data

Sahoo¹,

Yang²,

Abler³

et al. 2019

Preprint

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Chimeric antigen receptor (CAR) T-cell therapy has shown promise in the treatment of hematological cancers and is currently being investigated for solid tumors including high-grade glioma brain tumors. There is a desperate need to quantitatively study the factors that contribute to the efficacy of CAR T-cell therapy in solid tumors. In this work we use a mathematical model of predator-prey dynamics to explore the kinetics of CAR T-cell killing in glioma: the Chimeric Antigen Receptor t-cell treatment Response in GliOma (CARRGO) model. The model includes rates of cancer cell proliferation, CAR T-cell killing, CAR T-cell proliferation and exhaustion, and CAR T-cell persistence. We use patient-derived and engineered cancer cell lines with an in vitro real-time cell analyzer to parameterize the CARRGO model. We observe that CAR T-cell dose correlates inversely with the killing rate and correlates directly with the net rate of proliferation and exhaustion. This suggests that at a lower dose of CAR T-cells, individual T-cells kill more cancer cells but become more exhausted as compared to higher doses. Furthermore, the exhaustion rate was observed to increase significantly with tumor growth rate and was dependent on level of antigen expression. The CARRGO model highlights nonlinear dynamics involved in CAR T-cell therapy and provides novel insights into the kinetics of CAR T-cell killing. The model suggests that CAR T-cell treatment may be tailored to individual tumor characteristics including tumor growth rate and antigen level to maximize therapeutic benefit.Statement of SignificanceWe utilize a mathematical model to deconvolute the nonlinear contributions of CAR T-cell proliferation and exhaustion to predict therapeutic efficacy and dependence on CAR T-cell dose and target antigen levels.

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Section: Carrgo Model Applied To In Vivo Human Datamentioning

confidence: 80%

Section: Introductionmentioning

confidence: 99%

Mathematical deconvolution of CAR T-cell proliferation and exhaustion from real-time killing assay data

Sahoo¹,

Yang²,

Abler³

et al. 2019

Preprint

View full text Add to dashboard Cite

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“…A previous model already considered CAR T cell proliferation in response to antigen burden, but memory CAR T were not considered, neither the effect of tumor inhibition of CAR T cells [53]. Another interesting mathematical model was made upon tisagenlecleucel-treated patient data [48]. This model was adapted from previous empirical model of immune response to bacterial/viral infections.…”

Section: Discussionmentioning

confidence: 99%

Three-Compartment Model of CAR T-cell Immunotherapy

Rodrigues

Barros

Almeida

2019

Preprint

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Immunotherapy has gained great momentum with CAR T (chimeric antigen receptor) cellular therapy, in which the patient's T lymphocytes are genetically manipulated to recognize tumor-specific antigens to increase elimination efficiency. Although recently approved by FDA to treat B cell malignancies, issues such as dose, administration protocol, toxicity, resistance to immunotherapy, among others, remain open and are the subject of intense research nowadays. Improved CAR T cell immunotherapy requires a better understanding of the interplay between CAR T cell doses and tumor burden. We developed a threecompartment mathematical model to describe tumor response to CAR T cell immunotherapy in immunodeficient mouse models (NSG and SCID/beige) based on two published articles from literature. We modeled different receptors as CART 19BBz or CART 123, and different tumor targets as HDML-2 and RAJI. We considered interactions between tumor cells, effector T cells, and T cell differentiation into memory T cells; tumor-induced immunosuppressive effects, conversion of memory T cells into effector T cells in the presence of tumor cells, and individual specificities considered as uncertainties in the parameters of the model. The model was able to represent the two considered immunotherapy scenarios. For the HDML-2 scenario, the tumor is eliminated after the immunotherapy with the CAR T cells even in case of a challenge due to the memory T cells long-term immune protection. For the Raji tumor, expressing indoleamine 2,3-dioxygenase (IDO) activity, the model represented tumor dynamics even when IDO inhibitors are introduced. Using in silico studies considering different dosing quantities and tumor burden, we showed that the proposed model can represent the three possible outcomes: tumor elimination, equilibrium, and escape. We found that therapy effectiveness may also depend on small variations in the parameters' values, regarded as intrinsic individual specificities, as T cell proliferation capacity, as well as immunosuppressive tumor microenvironment factors. These issues may significantly reduce the chance of tumor elimination. In this way, the developed model provides potential use for assessing different CAR T cell protocols and associated efficacy without further in vivo experiments.

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“…Values were calculated assuming that 10 8 T-cells are introduced; however, delivery rates due to any other desired number or blood concentration of cells could be calculated by multiplying results by the ratio of the desired number to 10 8 or multiplying blood concentration by the total blood volume in the target species. Although models to predict expansion of a T-cell population have been studied in the past [9,30], it is difficult to quantify cellular proliferation in or fractional recirculation from a given tissue. However, a maximum rate of delivery due to anatomy can be estimated with greater confidence, thus proliferation was not considered.…”

Section: Discussionmentioning

confidence: 99%

“…Despite efficacy seen in pre-clinical models, this success has not yet been matched for solid tumours and a suitable dosing strategy to maximise efficacy remains uncertain [3][4][5][6][7][8]. Typical response curves (amount of CART-cell transgene observed in blood versus time) in patients with haematological disorders are marked by an initial cellular expansion (typically 100-1000-fold [9]), due to the large numbers of CART and target cells colocalising in readily accessible tissues. Expansion increases the effective cellular dose entering and proliferating within compartments with lower perfusion or less efficient access, which can drive the clearance of target cells required to achieve complete responses in these compartments.…”

Section: Introductionmentioning

confidence: 99%

Quantifying the Limits of Immunotherapies in Mice and Men

Brown

Gaffney

Ager

et al. 2019

Preprint

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CART (Chimeric Antigen Receptor T)-cells are approved for treatment of several leukaemia and lymphoma indications. However, this therapeutic modality has not delivered comparable clinical efficacy for solid tumour indications despite promising preclinical outcomes in mouse solid tumour models. Lower rates of effective CART-cell delivery to solid tumours in humans as compared to human haematological malignancies and/or solid tumours in mice might partially explain these divergent outcomes. As the initial delivery of CART-cells to tumour tissue is mediated by the circulatory system, we developed in silico models of the human, rat and mouse circulatory systems. Model structure and parameterisation were informed by an extensive body of published comparative anatomical and physiological studies and associated experimental data. Models were used to estimate the species-dependent upper limit and variation of delivery rates of blood borne immune cells, such as T-and NK cells, to tumour tissue across different organs and species. Large cross-species differences in absolute delivery rates to organs were identified. Estimated maximum delivery rates were up to 10,000-fold greater in mice than humans, yet reported administered CART-cell doses were typically only 10-100 times lower in mice. This suggests that higher human CART-doses may be needed to drive efficacy comparable to that observed in preclinical solid tumour mice models. Accordingly, we posit that a more quantitative analysis of species-and organ-specific immune cell delivery rates and how they may be pharmacologically optimised will be key to unlocking the potential of engineered T-cells for solid tumours.

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Tisagenlecleucel Model‐Based Cellular Kinetic Analysis of Chimeric Antigen Receptor–T Cells

Cited by 96 publications

References 22 publications

Mathematical deconvolution of CAR T-cell proliferation and exhaustion from real-time killing assay data

Mathematical deconvolution of CAR T-cell proliferation and exhaustion from real-time killing assay data

Three-Compartment Model of CAR T-cell Immunotherapy

Quantifying the Limits of Immunotherapies in Mice and Men

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