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Wang Z, Cho H, Choyke P, Levy D, Sato N. A Mathematical Model of TCR-T Cell Therapy for Cervical Cancer. Bull Math Biol 2024; 86:57. [PMID: 38625492 DOI: 10.1007/s11538-024-01261-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 01/11/2024] [Indexed: 04/17/2024]
Abstract
Engineered T cell receptor (TCR)-expressing T (TCR-T) cells are intended to drive strong anti-tumor responses upon recognition of the specific cancer antigen, resulting in rapid expansion in the number of TCR-T cells and enhanced cytotoxic functions, causing cancer cell death. However, although TCR-T cell therapy against cancers has shown promising results, it remains difficult to predict which patients will benefit from such therapy. We develop a mathematical model to identify mechanisms associated with an insufficient response in a mouse cancer model. We consider a dynamical system that follows the population of cancer cells, effector TCR-T cells, regulatory T cells (Tregs), and "non-cancer-killing" TCR-T cells. We demonstrate that the majority of TCR-T cells within the tumor are "non-cancer-killing" TCR-T cells, such as exhausted cells, which contribute little or no direct cytotoxicity in the tumor microenvironment (TME). We also establish two important factors influencing tumor regression: the reversal of the immunosuppressive TME following depletion of Tregs, and the increased number of effector TCR-T cells with antitumor activity. Using mathematical modeling, we show that certain parameters, such as increasing the cytotoxicity of effector TCR-T cells and modifying the number of TCR-T cells, play important roles in determining outcomes.
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Affiliation(s)
- Zuping Wang
- Department of Mathematics, University of Maryland, College Park, MD, 20742, USA
| | - Heyrim Cho
- School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ, 85281, USA
| | - Peter Choyke
- Molecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Doron Levy
- Department of Mathematics, University of Maryland, College Park, MD, 20742, USA.
| | - Noriko Sato
- Molecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
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Ottesen JT, Andersen M. Aging, Inflammation, and Comorbidity in Cancers-A General In Silico Study Exemplified by Myeloproliferative Malignancies. Cancers (Basel) 2023; 15:4806. [PMID: 37835500 PMCID: PMC10572046 DOI: 10.3390/cancers15194806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 09/23/2023] [Accepted: 09/27/2023] [Indexed: 10/15/2023] Open
Abstract
(1) Background: We consider dormant, pre-cancerous states prevented from developing into cancer by the immune system. Inflammatory morbidity may compromise the immune system and cause the pre-cancer to escape into an actual cancerous development. The immune deficiency described is general, but the results may vary across specific cancers due to different variances (2) Methods: We formulate a general conceptual model to perform rigorous in silico consequence analysis. Relevant existing data for myeloproliferative malignancies from the literature are used to calibrate the in silico computations. (3) Results and conclusions: The hypothesis suggests a common physiological origin for many clinical and epidemiological observations in relation to cancers in general. Examples are the observed age-dependent prevalence for hematopoietic cancers, a general mechanism-based explanation for why the risk of cancer increases with age, and how somatic mutations in general, and specifically seen in screenings of citizens, sometimes are non-increased or even decrease when followed over time. The conceptual model is used to characterize different groups of citizens and patients, describing different treatment responses and development scenarios.
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Affiliation(s)
- Johnny T. Ottesen
- Mathematical Modeling—Human Health and Disease, IMFUFA, Department of Science and Environment, Roskilde University, 4000 Roskilde, Denmark;
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Li J, Xiao Z, Wang D, Jia L, Nie S, Zeng X, Hu W. The screening, identification, design and clinical application of tumor-specific neoantigens for TCR-T cells. Mol Cancer 2023; 22:141. [PMID: 37649123 PMCID: PMC10466891 DOI: 10.1186/s12943-023-01844-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 08/16/2023] [Indexed: 09/01/2023] Open
Abstract
Recent advances in neoantigen research have accelerated the development of tumor immunotherapies, including adoptive cell therapies (ACTs), cancer vaccines and antibody-based therapies, particularly for solid tumors. With the development of next-generation sequencing and bioinformatics technology, the rapid identification and prediction of tumor-specific antigens (TSAs) has become possible. Compared with tumor-associated antigens (TAAs), highly immunogenic TSAs provide new targets for personalized tumor immunotherapy and can be used as prospective indicators for predicting tumor patient survival, prognosis, and immune checkpoint blockade response. Here, the identification and characterization of neoantigens and the clinical application of neoantigen-based TCR-T immunotherapy strategies are summarized, and the current status, inherent challenges, and clinical translational potential of these strategies are discussed.
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Affiliation(s)
- Jiangping Li
- Division of Thoracic Tumor Multimodality Treatment, Cancer Center, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China.
| | - Zhiwen Xiao
- Department of Otolaryngology Head and Neck Surgery, The Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510655, People's Republic of China
| | - Donghui Wang
- Department of Radiation Oncology, The Third Affiliated Hospital Sun Yat-Sen University, Guangzhou, 510630, People's Republic of China
| | - Lei Jia
- International Health Medicine Innovation Center, Shenzhen University, Shenzhen, 518060, People's Republic of China
| | - Shihong Nie
- Department of Radiation Oncology, West China Hospital, Sichuan University, Cancer Center, Chengdu, 610041, People's Republic of China
| | - Xingda Zeng
- Department of Parasitology of Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China
| | - Wei Hu
- Division of Vascular Surgery, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610072, People's Republic of China
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Yu L, Lanqing G, Huang Z, Xin X, Minglin L, Fa-hui L, Zou H, Min J. T cell immunotherapy for cervical cancer: challenges and opportunities. Front Immunol 2023; 14:1105265. [PMID: 37180106 PMCID: PMC10169584 DOI: 10.3389/fimmu.2023.1105265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 02/27/2023] [Indexed: 05/15/2023] Open
Abstract
Cancer cellular immunotherapy has made inspiring therapeutic effects in clinical practices, which brings new hope for the cure of cervical cancer. CD8+T cells are the effective cytotoxic effector cells against cancer in antitumor immunity, and T cells-based immunotherapy plays a crucial role in cellular immunotherapy. Tumor infiltrated Lymphocytes (TIL), the natural T cells, is approved for cervical cancer immunotherapy, and Engineered T cells therapy also has impressive progress. T cells with natural or engineered tumor antigen binding sites (CAR-T, TCR-T) are expanded in vitro, and re-infused back into the patients to eradicate tumor cells. This review summarizes the preclinical research and clinical applications of T cell-based immunotherapy for cervical cancer, and the challenges for cervical cancer immunotherapy.
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Affiliation(s)
- Lingfeng Yu
- School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China
| | - Gong Lanqing
- Department of Obstetrics and Gynecology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ziyu Huang
- School of Arts and Sciences, Brandeis University, Boston, MA, United States
| | - Xiaoyan Xin
- School of Arts and Sciences, Brandeis University, Boston, MA, United States
| | - Liang Minglin
- School of Arts and Sciences, Brandeis University, Boston, MA, United States
| | - Lv Fa-hui
- Department of Obstetrics and Gynecology, The Second People’s Hospital of Hefei, Hefei, Anhui, China
| | - Hongmei Zou
- Department of Obstetrics, Qianjiang Central Hospital, Qianjiang, Hubei, China
| | - Jie Min
- Department of Obstetrics and Gynecology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Li R, Sahoo P, Wang D, Wang Q, Brown CE, Rockne RC, Cho H. Modeling interaction of Glioma cells and CAR T-cells considering multiple CAR T-cells bindings. IMMUNOINFORMATICS (AMSTERDAM, NETHERLANDS) 2023; 9:100022. [PMID: 36875891 PMCID: PMC9983577 DOI: 10.1016/j.immuno.2023.100022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Chimeric antigen receptor (CAR) T-cell based immunotherapy has shown its potential in treating blood cancers, and its application to solid tumors is currently being extensively investigated. For glioma brain tumors, various CAR T-cell targets include IL13Rα2, EGFRvIII, HER2, EphA2, GD2, B7-H3, and chlorotoxin. In this work, we are interested in developing a mathematical model of IL13Rα2 targeting CAR T-cells for treating glioma. We focus on extending the work of Kuznetsov et al. (1994) by considering binding of multiple CAR T-cells to a single glioma cell, and the dynamics of these multi-cellular conjugates. Our model more accurately describes experimentally observed CAR T-cell killing assay data than the models which do not consider multi-cellular conjugates. Moreover, we derive conditions in the CAR T-cell expansion rate that determines treatment success or failure. Finally, we show that our model captures distinct CAR T-cell killing dynamics from low to high antigen receptor densities in patient-derived brain tumor cells.
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Affiliation(s)
- Runpeng Li
- Department of Mathematics, University of California Riverside, 900 University Ave., Riverside, 92521, CA, USA
| | - Prativa Sahoo
- Division of Mathematical Oncology, Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope National Medical Center, 1500 E Duarte Rd., Duarte, 91010, CA, USA
| | - Dongrui Wang
- Zhejiang University Medical Center, 866 Yuhangtang Rd, Hangzhou, 310058, PR China
| | - Qixuan Wang
- Department of Mathematics, University of California Riverside, 900 University Ave., Riverside, 92521, CA, USA.,Interdisciplinary Center for Quantitative Modeling in Biology, University of California Riverside, 900 University Ave., Riverside, 92521, CA, USA
| | - Christine E Brown
- Department of Hematology & Hematopoietic Cell Transplantation, Beckman Research Institute, City of Hope National Medical Center, 1500 E Duarte Rd., Duarte, 91010, CA, USA
| | - Russell C Rockne
- Division of Mathematical Oncology, Department of Computational and Quantitative Medicine, Beckman Research Institute, City of Hope National Medical Center, 1500 E Duarte Rd., Duarte, 91010, CA, USA
| | - Heyrim Cho
- Department of Mathematics, University of California Riverside, 900 University Ave., Riverside, 92521, CA, USA.,Interdisciplinary Center for Quantitative Modeling in Biology, University of California Riverside, 900 University Ave., Riverside, 92521, CA, USA
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