Chimeric antigen receptor (CAR) T-cell therapy has shown promise in the treatment of haematological cancers and is currently being investigated for solid tumours, including high-grade glioma brain tumours. There is a desperate need to quantitatively study the factors that contribute to the efficacy of CAR T-cell therapy in solid tumours. 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, proliferation, exhaustion, and persistence. We use patient-derived and engineered cancer cell lines with an in vitro real-time cell analyser to parametrize 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 when compared with higher doses. Furthermore, the exhaustion rate was observed to increase significantly with tumour 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 tumour characteristics including tumour growth rate and antigen level to maximize therapeutic benefit.

The ability to accurately and non-invasively distinguish high-grade glioma from low-grade glioma remains a challenge despite advances in molecular and magnetic resonance imaging. We investigated the ability of fluciclovine (18F) PET as a means to identify and distinguish these lesions in patients with known gliomas and to correlate uptake with Ki-67. Sixteen patients with a total of 18 newly diagnosed low-grade gliomas (n = 6) and high grade gliomas (n = 12) underwent fluciclovine PET imaging after histopathologic assessment. Fluciclovine PET analysis comprised tumor SUVmax and SUVmean, as well as metabolic tumor thresholds (1.3*, 1.6*, 1.9*) to normal brain background (TBmax, and TBmean). Comparison was additionally made to the proliferative status of the tumor as indicated by Ki-67 values. Fluciclovine uptake greater than normal brain parenchyma was found in all lesions studied. Time activity curves demonstrated statistically apparent flattening of the curves for both high-grade gliomas and low-grade gliomas starting 30 min after injection, suggesting an influx/efflux equilibrium. The best semiquantitative metric in discriminating HGG from LGG was obtained utilizing a metabolic 1 tumor threshold of 1.3* contralateral normal brain parenchyma uptake to create a tumor: background (TBmean1.3) cutoff of 2.15 with an overall sensitivity of 97.5% and specificity of 95.5%. Additionally, using a SUVmax > 4.3 cutoff gave a sensitivity of 90.9% and specificity of 97.5%. Tumor SUVmean and tumor SUVmax as a ratio to mean normal contralateral brain were both found to be less relevant predictors of tumor grade. Both SUVmax (R = 0.71, p = 0.0227) and TBmean (TBmean1.3: R = 0.81, p = 0.00081) had a high correlation with the tumor proliferative index Ki-67. Fluciclovine PET produces high-contrast images between both low-grade and high grade gliomas and normal brain by visual and semiquantitative analysis. Fluciclovine PET appears to discriminate between low-grade glioma and high-grade glioma, but must be validated with a larger sample size.

Targeted radionuclide therapy (TRT) has recently seen a surge in popularity with the use of radionuclides conjugated to small molecules and antibodies. Similarly, immunotherapy also has shown promising results, an example being chimeric antigen receptor T cell (CAR-T) therapy in hematologic malignancies. Moreover, TRT and CAR-T therapies possess unique features that require special consideration when determining how to dose as well as the timing and sequence of combination treatments including the distribution of the TRT dose in the body, the decay rate of the radionuclide, and the proliferation and persistence of the CAR-T cells. These characteristics complicate the additive or synergistic effects of combination therapies and warrant a mathematical treatment that includes these dynamics in relation to the proliferation and clearance rates of the target tumor cells. Here, we combine two previously published mathematical models to explore the effects of dose, timing, and sequencing of TRT and CAR-T cell-based therapies in a multiple myeloma setting. We find that, for a fixed TRT and CAR-T cell dose, the tumor proliferation rate is the most important parameter in determining the best timing of TRT and CAR-T therapies.

Introduction: Cancer combination treatments involving immunotherapies with targeted radiation therapy are at the forefront of treating cancers. However, dosing and scheduling of these therapies pose a challenge. Mathematical models provide a unique way of optimizing these therapies. Methods: Using a preclinical model of multiple myeloma as an example, we demonstrate the capability of a mathematical model to combine these therapies to achieve maximum response, defined as delay in tumor growth. Data from mice studies with targeted radionuclide therapy (TRT) and chimeric antigen receptor (CAR)-T cell monotherapies and combinations with different intervals between them was used to calibrate mathematical model parameters. The dependence of progression-free survival (PFS), overall survival (OS), and the time to minimum tumor burden on dosing and scheduling was evaluated. Different dosing and scheduling schemes were evaluated to maximize the PFS and optimize timings of TRT and CAR-T cell therapies. Results: Therapy intervals that were too close or too far apart are shown to be detrimental to the therapeutic efficacy, as TRT too close to CAR-T cell therapy results in radiation related CAR-T cell killing while the therapies being too far apart result in tumor regrowth, negatively impacting tumor control and survival. We show that splitting a dose of TRT or CAR-T cells when administered in combination is advantageous only if the first therapy delivered can produce a significant benefit as a monotherapy. Discussion: Mathematical models are crucial tools for optimizing the delivery of cancer combination therapy regimens with application along the lines of achieving cure, maximizing survival or minimizing toxicity.

High-risk relapsed or refractory (R/R) classical Hodgkin lymphoma (HL) is associated with poor outcomes after conventional salvage therapy and autologous hematopoietic cell transplantation (AHCT). Post-AHCT consolidation with brentuximab vedotin (BV) improves progression-free survival (PFS), but with increasing use of BV early in the treatment course, the utility of consolidation is unclear. CD25 is often expressed on Reed-Sternberg cells and in the tumor microenvironment in HL, and we hypothesized that the addition of 90Y-antiCD25 (aTac) to carmustine, etoposide, cytarabine, melphalan (BEAM) AHCT would be safe and result in a transplantation platform that is agnostic to prior HL-directed therapy. Twenty-five patients with high-risk R/R HL were enrolled in this phase 1 dose-escalation trial of aTac-BEAM. Following an imaging dose of 111In-antiCD25, 2 patients had altered biodistribution, and a third developed an unrelated catheter-associated bacteremia; therefore, 22 patients ultimately received therapeutic 90Y-aTac-BEAM AHCT. No dose-limiting toxicities were observed, and 0.6 mCi/kg was deemed the recommended phase 2 dose, the dose at which the heart wall would not receive >2500 cGy. Toxicities and time to engraftment were similar to those observed with standard AHCT, though 95% of patients developed stomatitis (all grade 1-2 per Bearman toxicity scale). Seven relapses (32%) were observed, most commonly in patients with ≥3 risk factors. The estimated 5-year PFS and overall survival probabilities among 22 evaluable patients were 68% and 95%, respectively, and non-relapse mortality was 0%. aTac-BEAM AHCT was tolerable in patients with high-risk R/R HL, and we are further evaluating the efficacy of this approach in a phase 2 trial. This trial was registered at www.clinicaltrials.gov as #NCT01476839.

Targeted radionuclide therapy (TRT) is based on injections of cancer-specific molecules conjugated with radioactive nuclides. Despite the specificity of this treatment, it is not devoid of side effects limiting its use and is especially harmful for rapidly proliferating organs well perfused by blood, like bone marrow. Optimization of radioconjugate administration accounting for toxicity constraints can increase treatment efficacy. Based on our experiments on a disseminated multiple myeloma mouse model treated by 225Ac-DOTA-daratumumab, we developed a mathematical model, investigation of which highlighted the following principles for optimization of TRT: (i) Nuclide-to-antibody ratio importance. The density of radioconjugates on cancer cells determines the density of radiation energy deposited in them. A low labeling ratio as well as accumulation of unlabeled antibodies and antibodies attached to decay products in the bloodstream can mitigate cancer radiation damage due to excessive occupation of specific receptors by antibodies devoid of radioactive nuclides. (ii) Cancer-binding capacity–based dosing. The total number of specific receptors on cancer cells is a critical factor for treatment optimization, and its estimation may allow increasing treatment efficacy close to its theoretical limit. Injection of doses significantly exceeding cancer-binding capacity should be avoided because radioconjugates remaining in the bloodstream have a negligible efficacy-to-toxicity ratio. (iii) Particle range–guided multi-dosing. The use of short-range particle emitters and high-affinity antibodies can allow for robust treatment optimization via initial saturation of cancer-binding capacity, enabling redistribution of further injected radioconjugates and deposited doses toward still viable cells that continue expressing specific receptors. Significance: Mathematical modeling yields general principles for optimization of TRT in mouse models of multiple myeloma that can be extrapolated to other cancer models and clinical settings.