A Mathematical Modeling Approach for Targeted Radionuclide and Chimeric Antigen Receptor T Cell Combination Therapy.

CAR-T CS1 TRT actinium-225 alpha particle therapy combination therapy daratumumab immunotherapy mathematical model multiple myeloma targeted radionuclide therapy

Journal

Cancers
ISSN: 2072-6694
Titre abrégé: Cancers (Basel)
Pays: Switzerland
ID NLM: 101526829

Informations de publication

Date de publication:
15 Oct 2021
Historique:
received: 27 08 2021
revised: 30 09 2021
accepted: 07 10 2021
entrez: 23 10 2021
pubmed: 24 10 2021
medline: 24 10 2021
Statut: epublish

Résumé

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.

Identifiants

pubmed: 34680320
pii: cancers13205171
doi: 10.3390/cancers13205171
pmc: PMC8533817
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : NCI NIH HHS
ID : R01 CA238429
Pays : United States
Organisme : NCI NIH HHS
ID : R01CA238429, P30CA03357
Pays : United States

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Auteurs

Vikram Adhikarla (V)

Division of Mathematical Oncology, Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010, USA.

Dennis Awuah (D)

Department of Hematology & Hematopoietic Cell Transplantation, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010, USA.

Alexander B Brummer (AB)

Division of Mathematical Oncology, Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010, USA.

Enrico Caserta (E)

Department of Hematologic Malignancies Translational Science, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010, USA.

Amrita Krishnan (A)

Department of Hematology & Hematopoietic Cell Transplantation, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010, USA.

Flavia Pichiorri (F)

Department of Hematologic Malignancies Translational Science, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010, USA.

Megan Minnix (M)

Department of Molecular Imaging and Therapy, City of Hope National Medical Center, Duarte, CA 91010, USA.

John E Shively (JE)

Department of Molecular Imaging and Therapy, City of Hope National Medical Center, Duarte, CA 91010, USA.

Jeffrey Y C Wong (JYC)

Department of Radiation Oncology, City of Hope National Medical Center, Duarte, CA 91010, USA.

Xiuli Wang (X)

Department of Hematology & Hematopoietic Cell Transplantation, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010, USA.

Russell C Rockne (RC)

Division of Mathematical Oncology, Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010, USA.

Classifications MeSH