Data driven model discovery and interpretation for CAR T-cell killing using sparse identification and latent variables

被引:15
作者
Brummer, Alexander B. [1 ,2 ]
Xella, Agata [3 ]
Woodall, Ryan [1 ]
Adhikarla, Vikram [1 ]
Cho, Heyrim [4 ]
Gutova, Margarita [5 ]
Brown, Christine E. [3 ]
Rockne, Russell C. [1 ]
机构
[1] City Hope Natl Med Ctr, Beckman Res Inst, Dept Computat & Quantitat Med, Div Math Oncol, Duarte, CA 91010 USA
[2] Coll Charleston, Dept Phys & Astron, Charleston, SC 29424 USA
[3] Beckman Res Inst, City Hope Natl Med Ctr, Dept Hemtaol & Hematopoiet Cell Translat & Immuno, Duarte, CA 91010 USA
[4] Univ Calif Riverside, Dept Math, Riverside, CA USA
[5] Beckman Res Inst, City Hope Natl Med Ctr, Dept Stem Cell Biol & Regenerat Med, Duarte, CA USA
基金
美国国家卫生研究院;
关键词
dynamical systems; latent variables; CAR T-cells; antigen binding; allee effect; SINDy; glioblastoma; cell therapy; KOOPMAN THEORY; OPTIMIZATION; REGRESSION; FRAMEWORK;
D O I
10.3389/fimmu.2023.1115536
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
In the development of cell-based cancer therapies, quantitative mathematical models of cellular interactions are instrumental in understanding treatment efficacy. Efforts to validate and interpret mathematical models of cancer cell growth and death hinge first on proposing a precise mathematical model, then analyzing experimental data in the context of the chosen model. In this work, we present the first application of the sparse identification of non-linear dynamics (SINDy) algorithm to a real biological system in order discover cell-cell interaction dynamics in in vitro experimental data, using chimeric antigen receptor (CAR) T-cells and patient-derived glioblastoma cells. By combining the techniques of latent variable analysis and SINDy, we infer key aspects of the interaction dynamics of CAR T-cell populations and cancer. Importantly, we show how the model terms can be interpreted biologically in relation to different CAR T-cell functional responses, single or double CAR T-cell-cancer cell binding models, and density-dependent growth dynamics in either of the CAR T-cell or cancer cell populations. We show how this data-driven model-discovery based approach provides unique insight into CAR T-cell dynamics when compared to an established model-first approach. These results demonstrate the potential for SINDy to improve the implementation and efficacy of CAR T-cell therapy in the clinic through an improved understanding of CAR T-cell dynamics.
引用
收藏
页数:18
相关论文
共 64 条
[1]   A Mathematical Modeling Approach for Targeted Radionuclide and Chimeric Antigen Receptor T Cell Combination Therapy [J].
Adhikarla, Vikram ;
Awuah, Dennis ;
Brummer, Alexander B. ;
Caserta, Enrico ;
Krishnan, Amrita ;
Pichiorri, Flavia ;
Minnix, Megan ;
Shively, John E. ;
Wong, Jeffrey Y. C. ;
Wang, Xiuli ;
Rockne, Russell C. .
CANCERS, 2021, 13 (20)
[2]   Forecasting the action of CAR-T cells against SARS-corona virus-II infection with branching process [J].
Al-Utaibi, Khaled A. ;
Nutini, Alessandro ;
Sohail, Ayesha ;
Arif, Robia ;
Tunc, Sumeyye ;
Sait, Sadiq M. .
MODELING EARTH SYSTEMS AND ENVIRONMENT, 2022, 8 (03) :3413-3421
[3]   Data-driven discovery of reduced plasma physics models from fully kinetic simulations [J].
Alves, E. P. ;
Fiuza, F. .
PHYSICAL REVIEW RESEARCH, 2022, 4 (03)
[4]  
Bakarji J., 2022, arXiv
[5]   Tumor cell-organized fibronectin maintenance of a dormant breast cancer population [J].
Barney, Lauren E. ;
Hall, Christopher L. ;
Schwartz, Alyssa D. ;
Parks, Akia N. ;
Sparages, Christopher ;
Galarza, Sualyneth ;
Platt, Manu O. ;
Mercurio, Arthur M. ;
Peyton, Shelly R. .
SCIENCE ADVANCES, 2020, 6 (11)
[6]   An Emerging Allee Effect Is Critical for Tumor Initiation and Persistence [J].
Boettger, Katrin ;
Hatzikirou, Haralambos ;
Voss-Boehme, Anja ;
Cavalcanti-Adam, Elisabetta Ada ;
Herrero, Miguel A. ;
Deutsch, Andreas .
PLOS COMPUTATIONAL BIOLOGY, 2015, 11 (09)
[7]   Optimization of IL13Rα2-Targeted Chimeric Antigen Receptor T Cells for Improved Anti-tumor Efficacy against Glioblastoma [J].
Brown, Christine E. ;
Aguilar, Brenda ;
Starr, Renate ;
Yang, Xin ;
Chang, Wen-Chung ;
Weng, Lihong ;
Chang, Brenda ;
Sarkissian, Aniee ;
Brito, Alfonso ;
Sanchez, James F. ;
Ostberg, Julie R. ;
D'Apuzzo, Massimo ;
Badie, Behnam ;
Barish, Michael E. ;
Forman, Stephen J. .
MOLECULAR THERAPY, 2018, 26 (01) :31-44
[8]   Regression of Glioblastoma after Chimeric Antigen Receptor T-Cell Therapy [J].
Brown, Christine E. ;
Alizadeh, Darya ;
Starr, Renate ;
Weng, Lihong ;
Wagner, Jamie R. ;
Naranjo, Araceli ;
Ostberg, Julie R. ;
Blanchard, M. Suzette ;
Kilpatrick, Julie ;
Simpson, Jennifer ;
Kurien, Anita ;
Priceman, Saul J. ;
Wang, Xiuli ;
Harshbarger, Todd L. ;
D'Apuzzo, Massimo ;
Ressler, Julie A. ;
Jensen, Michael C. ;
Barish, Michael E. ;
Chen, Mike ;
Portnow, Jana ;
Forman, Stephen J. ;
Badie, Behnam .
NEW ENGLAND JOURNAL OF MEDICINE, 2016, 375 (26) :2561-2569
[9]   Stem-like Tumor-Initiating Cells Isolated from IL13Rα2 Expressing Gliomas Are Targeted and Killed by IL13-Zetakine-Redirected T Cells [J].
Brown, Christine E. ;
Starr, Renate ;
Aguilar, Brenda ;
Shami, Andrew F. ;
Martinez, Catalina ;
D'Apuzzo, Massimo ;
Barish, Michael E. ;
Forman, Stephen J. ;
Jensen, Michael C. .
CLINICAL CANCER RESEARCH, 2012, 18 (08) :2199-2209
[10]   Dose-dependent thresholds of dexamethasone destabilize CAR T-cell treatment efficacy [J].
Brummer, Alexander B. ;
Yang, Xin ;
Ma, Eric ;
Gutova, Margarita ;
Brown, Christine E. ;
Rockne, Russell C. .
PLOS COMPUTATIONAL BIOLOGY, 2022, 18 (01)