CAR T cells for T-cell leukemias: Insights from mathematical models

Pérez-Garcı́a, Vı́ctor M.; León-Triana, Odelaisy; Rosa, María; Pérez‐Martínez, Antonio

doi:10.1016/j.cnsns.2020.105684

Cited by 22 publications

(15 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several studies have incorporated CAR T-cells in the form of a compartment that expands and acts on B cells and cancer cells [26,32,[34][35][36]. However, clinical evidence suggests that a better description of the dynamics can be achieved by considering two subpopulations [22][23][24].…”

Section: Car T-cell Compartmentmentioning

confidence: 99%

“…While there are some studies involving solid tumors [26,27], most focus on hematological malignancies, given the success obtained in this group of cancers. There are general models of leukemia and lymphoma [28][29][30][31] and more specific applications in B-cell lymphoma [32], B-cell chronic lymphoblastic leukemia [33], T-cell ALL [34], and B-cell ALL [35,36].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Mathematical Description of the Bone Marrow Dynamics during CAR T-Cell Therapy in B-Cell Childhood Acute Lymphoblastic Leukemia

Martínez-Rubio

Chulián

Goñi

et al. 2021

IJMS

Self Cite

View full text Add to dashboard Cite

Chimeric Antigen Receptor (CAR) T-cell therapy has demonstrated high rates of response in recurrent B-cell Acute Lymphoblastic Leukemia in children and young adults. Despite this success, a fraction of patients’ experience relapse after treatment. Relapse is often preceded by recovery of healthy B cells, which suggests loss or dysfunction of CAR T-cells in bone marrow. This site is harder to access, and thus is not monitored as frequently as peripheral blood. Understanding the interplay between B cells, leukemic cells, and CAR T-cells in bone marrow is paramount in ascertaining the causes of lack of response. In this paper, we put forward a mathematical model representing the interaction between constantly renewing B cells, CAR T-cells, and leukemic cells in the bone marrow. Our model accounts for the maturation dynamics of B cells and incorporates effector and memory CAR T-cells. The model provides a plausible description of the dynamics of the various cellular compartments in bone marrow after CAR T infusion. After exploration of the parameter space, we found that the dynamics of CAR T product and disease were independent of the dose injected, initial B-cell load, and leukemia burden. We also show theoretically the importance of CAR T product attributes in determining therapy outcome, and have studied a variety of possible response scenarios, including second dosage schemes. We conclude by setting out ideas for the refinement of the model.

show abstract

Section: Car T-cell Compartmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Mathematical Description of the Bone Marrow Dynamics during CAR T-Cell Therapy in B-Cell Childhood Acute Lymphoblastic Leukemia

Martínez-Rubio

Chulián

Goñi

et al. 2021

IJMS

Self Cite

View full text Add to dashboard Cite

show abstract

“…In the present paper, we focus on advantages, possibilities and obstacles of immunotherapy [59]. We consider immunotherapy in silico, i.e., chimeric antigen receptor (CAR) T-cell therapy [36,37,60]. The model shows how the progression of cancer and the effect of treatments inherently depend on the coupling and the levels of cancer and infection.…”

Section: Discussionmentioning

confidence: 99%

Potential of Immunotherapies in Treating Hematological Cancer-Infection Comorbidities—A Mathematical Modelling Approach

Ottesen

Andersen

2021

Cancers

View full text Add to dashboard Cite

The immune system protects the human body against threats such as emerging cancers or infections, e.g., COVID-19. Mutated malignant cells may in many cases be controlled by the immune system to be kept at unnoticed low amount. However, a severe infection may compromise the immune system in controlling such malignant clones leading to escape and fatal cancer progression. A novel mechanism based computational model coupling cancer and infection to the adaptive immune system is presented and analyzed. The model pin-points important physiological mechanisms responsible for cancer progression and explains numerous medical observations. The progression of a cancers and the effects of treatments depend on cancer burden, the level of infection and on the efficiency of the adaptive immune system. The model exhibits bi-stability, i.e., gravitate towards one of two stable steady states: a harmless dormant state or a full-blown cancer-infection disease state. A borderline exists and if infection exceeds this for a sufficiently long period of time the cancer escapes. Early treatment is vital for remission and may control the cancer back into the stable dormant state. CAR T-cell immunotherapy is investigated by help of the model. The therapy significantly improves its efficacy in combination with antibiotics or immunomodulation.

show abstract

“…These same approaches can be naturally extended to inform and predict both pre-clinical and clinical applications of immunotherapies [18][19][20][21]. Most recently, such efforts have been applied to model and predict CAR T-cell therapies for leukemia [22,23], glioblastoma organoids and solid brains tumors [11], and combination therapies with radiotherapy [24] and chemotherapy [25].…”

Section: Mathematical Modeling Of Car T-cells Has Demonstrated Value In Quantitativelymentioning

confidence: 99%

Dose-dependent thresholds of dexamethasone destabilize CAR T-cell treatment efficacy

Yang

et al. 2021

Preprint

View full text Add to dashboard Cite

Chimeric antigen receptor (CAR) T-cell therapy is potentially an effective targeted immunotherapy for glioblastoma, yet there is presently little known about the efficacy of CAR T-cell treatment when combined with the widely used anti-inflammatory and immunosuppressant glucocorticoid, Dexamethasone. Here we present a mathematical model-based analysis of three patient-derived glioblastoma cell lines treated in vitro with CAR T-cells and Dexamethasone. Advanced in vitro experimental cell killing assay technologies allow for highly resolved temporal dynamics of tumor cells treated with CAR T-cells and Dexamethone, making this a valuable model system for studying the rich dynamics of nonlinear biological processes with translational applications. We model the system as a non-autonomous, two-species predator-prey interaction of tumor cells and CAR T-cells, with explicit time-dependence in the clearance rate of Dexamethasone. Using time as a bifurcation parameter, we show that (1) the presence of Dexamethasone destabilizes coexistence equilibria between CAR T-cells and tumor cells and (2) as Dexamethasone is cleared from the system, a stable coexistence equilibrium returns in the form of a Hopf bifurcation. With the model fit to experimental data, we demonstrate that high concentrations of Dexamethasone antagonizes CAR T-cell efficacy by exhausting, or reducing the activity of CAR T-cells, and by promoting tumor cell growth. Finally, we identify a critical threshold in the ratio of CAR T-cell death to CAR T-cell proliferation rates that predicts eventual treatment success or failure that may be used to guide the dose and timing of CAR T-cell therapy in the presence of Dexamethasone in patients.

show abstract

CAR T cells for T-cell leukemias: Insights from mathematical models

Cited by 22 publications

References 27 publications

A Mathematical Description of the Bone Marrow Dynamics during CAR T-Cell Therapy in B-Cell Childhood Acute Lymphoblastic Leukemia

A Mathematical Description of the Bone Marrow Dynamics during CAR T-Cell Therapy in B-Cell Childhood Acute Lymphoblastic Leukemia

Potential of Immunotherapies in Treating Hematological Cancer-Infection Comorbidities—A Mathematical Modelling Approach

Dose-dependent thresholds of dexamethasone destabilize CAR T-cell treatment efficacy

Contact Info

Product

Resources

About