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Cappabianca D, Pham D, Forsberg MH, Bugel M, Tommasi A, Lauer A, Vidugiriene J, Hrdlicka B, McHale A, Sodji QH, Skala MC, Capitini CM, Saha K. Metabolic priming of GD2 TRAC-CAR T cells during manufacturing promotes memory phenotypes while enhancing persistence. Mol Ther Methods Clin Dev 2024; 32:101249. [PMID: 38699288 PMCID: PMC11063605 DOI: 10.1016/j.omtm.2024.101249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Accepted: 04/05/2024] [Indexed: 05/05/2024]
Abstract
Manufacturing chimeric antigen receptor (CAR) T cell therapies is complex, with limited understanding of how medium composition impacts T cell phenotypes. CRISPR-Cas9 ribonucleoproteins can precisely insert a CAR sequence while disrupting the endogenous T cell receptor alpha constant (TRAC) gene resulting in TRAC-CAR T cells with an enriched stem cell memory T cell population, a process that could be further optimized through modifications to the medium composition. In this study we generated anti-GD2 TRAC-CAR T cells using "metabolic priming" (MP), where the cells were activated in glucose/glutamine-low medium and then expanded in glucose/glutamine-high medium. T cell products were evaluated using spectral flow cytometry, metabolic assays, cytokine production, cytotoxicity assays in vitro, and potency against human GD2+ xenograft neuroblastoma models in vivo. Compared with standard TRAC-CAR T cells, MP TRAC-CAR T cells showed less glycolysis, higher CCR7/CD62L expression, more bound NAD(P)H activity, and reduced IFN-γ, IL-2, IP-10, IL-1β, IL-17, and TGF-β production at the end of manufacturing ex vivo, with increased central memory CAR T cells and better persistence observed in vivo. MP with medium during CAR T cell biomanufacturing can minimize glycolysis and enrich memory phenotypes ex vivo, which could lead to better responses against solid tumors in vivo.
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Affiliation(s)
- Dan Cappabianca
- Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI 53715, USA
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53715, USA
| | - Dan Pham
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53715, USA
- Morgridge Institute for Research, University of Wisconsin-Madison, Madison, WI 53715, USA
| | - Matthew H. Forsberg
- Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, WI 53705, USA
| | - Madison Bugel
- Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI 53715, USA
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53715, USA
| | - Anna Tommasi
- Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI 53715, USA
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53715, USA
| | | | | | - Brookelyn Hrdlicka
- Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI 53715, USA
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53715, USA
| | - Alexandria McHale
- Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI 53715, USA
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53715, USA
| | - Quaovi H. Sodji
- University of Wisconsin Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI 53705, USA
- Department of Human Oncology, University of Wisconsin School of Medicine and Public Health, Madison, WI 53705, USA
| | - Melissa C. Skala
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53715, USA
- Morgridge Institute for Research, University of Wisconsin-Madison, Madison, WI 53715, USA
- University of Wisconsin Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Christian M. Capitini
- Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, WI 53705, USA
- University of Wisconsin Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Krishanu Saha
- Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI 53715, USA
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53715, USA
- University of Wisconsin Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI 53705, USA
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Hou F, Guo Z, Ho MT, Hui Y, Zhao CX. Particle-Based Artificial Antigen-Presenting Cell Systems for T Cell Activation in Adoptive T Cell Therapy. ACS NANO 2024; 18:8571-8599. [PMID: 38483840 DOI: 10.1021/acsnano.3c10180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
T cell-based adoptive cell therapy (ACT) has emerged as a promising treatment for various diseases, particularly cancers. Unlike other immunotherapy modalities, ACT involves directly transferring engineered T cells into patients to eradicate diseased cells; hence, it necessitates methods for effectively activating and expanding T cells in vitro. Artificial antigen-presenting cells (aAPCs) have been widely developed based on biomaterials, particularly micro- and nanoparticles, and functionalized with T cell stimulatory antibodies to closely mimic the natural T cell-APC interactions. Due to their vast clinical utility, aAPCs have been employed as an off-the-shelf technology for T cell activation in FDA-approved ACTs, and the development of aAPCs is constantly advancing with the emergence of aAPCs with more sophisticated designs and additional functionalities. Here, we review the recent advancements in particle-based aAPCs for T cell activation in ACTs. Following a brief introduction, we first describe the manufacturing processes of ACT products. Next, the design and synthetic strategies for micro- and nanoparticle-based aAPCs are discussed separately to emphasize their features, advantages, and limitations. Then, the impact of design parameters of aAPCs, such as size, shape, ligand density/mobility, and stiffness, on their functionality and biomedical performance is explored to provide deeper insights into the design concepts and principles for more efficient and safer aAPCs. The review concludes by discussing current challenges and proposing future perspectives for the development of more advanced aAPCs.
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Affiliation(s)
- Fei Hou
- School of Chemical Engineering, Faculty of Sciences, Engineering and Technology, The University of Adelaide, Adelaide, South Australia 5005, Australia
| | - Zichao Guo
- School of Chemical Engineering, Faculty of Sciences, Engineering and Technology, The University of Adelaide, Adelaide, South Australia 5005, Australia
| | - Minh Trang Ho
- School of Chemical Engineering, Faculty of Sciences, Engineering and Technology, The University of Adelaide, Adelaide, South Australia 5005, Australia
| | - Yue Hui
- School of Chemical Engineering, Faculty of Sciences, Engineering and Technology, The University of Adelaide, Adelaide, South Australia 5005, Australia
| | - Chun-Xia Zhao
- School of Chemical Engineering, Faculty of Sciences, Engineering and Technology, The University of Adelaide, Adelaide, South Australia 5005, Australia
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Cappabianca D, Pham D, Forsberg MH, Bugel M, Tommasi A, Lauer A, Vidugiriene J, Hrdlicka B, McHale A, Sodji Q, Skala MC, Capitini CM, Saha K. Metabolic priming of GD2 TRAC -CAR T cells during manufacturing promotes memory phenotypes while enhancing persistence. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.31.575774. [PMID: 38562720 PMCID: PMC10983869 DOI: 10.1101/2024.01.31.575774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Manufacturing Chimeric Antigen Receptor (CAR) T cell therapies is complex, with limited understanding of how media composition impact T-cell phenotypes. CRISPR/Cas9 ribonucleoproteins can precisely insert a CAR sequence while disrupting the endogenous T cell receptor alpha constant ( TRAC ) gene resulting in TRAC -CAR T cells with an enriched stem cell memory T-cell population, a process that could be further optimized through modifications to the media composition. In this study we generated anti-GD2 TRAC -CAR T cells using "metabolic priming" (MP), where the cells were activated in glucose/glutamine low media and then expanded in glucose/glutamine high media. T cell products were evaluated using spectral flow cytometry, metabolic assays, cytokine production, cytotoxicity assays in vitro and potency against human GD2+ xenograft neuroblastoma models in vivo . Compared to standard TRAC -CAR T cells, MP TRAC -CAR T cells showed less glycolysis, higher CCR7/CD62L expression, more bound NAD(P)H activity and reduced IFN-γ, IL-2, IP-10, IL-1β, IL-17, and TGFβ production at the end of manufacturing ex vivo , with increased central memory CAR T cells and better persistence observed in vivo . Metabolic priming with media during CAR T cell biomanufacturing can minimize glycolysis and enrich memory phenotypes ex vivo , which could lead to better responses against solid tumors in vivo .
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Gillette AA, Pham DL, Skala MC. Touch-free optical technologies to streamline the production of T cell therapies. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2023; 25:100434. [PMID: 36642996 PMCID: PMC9837746 DOI: 10.1016/j.cobme.2022.100434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Currently approved adoptive T cell therapy relies on autologous (obtained from the same patient) T cells, which often suffer from poor quality that diminishes treatment efficacy. Due to the heterogeneous nature of T cell quality between and within patients, significant efforts are aimed at optimizing cell manipulation and growth conditions for potent T cell products. We believe that touch-free imaging and sensing technologies are critical to monitor single-cell features during T cell manufacturing to ensure consistent and optimally timed methods for cell manipulation and growth. Here, we discuss emerging label-free optical imaging and sensing methods, along with machine learning techniques that could enable in-line feedback to optimize T cell quality at multiple stages during manufacturing. These methods have the potential to streamline current workflow, accelerate the manufacture of safe high-quality T cell therapies, and improve our understanding of the dynamic, heterogeneous processes of T cell manufacturing.
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Affiliation(s)
| | - Dan L Pham
- Department of Biomedical Engineering, University of Wisconsin-Madison
| | - Melissa C Skala
- Morgridge Institute for Research, Madison, Wisconsin
- Department of Biomedical Engineering, University of Wisconsin-Madison
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Understanding and improving cellular immunotherapies against cancer: From cell-manufacturing to tumor-immune models. Adv Drug Deliv Rev 2021; 179:114003. [PMID: 34653533 DOI: 10.1016/j.addr.2021.114003] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 10/05/2021] [Accepted: 10/08/2021] [Indexed: 12/14/2022]
Abstract
The tumor microenvironment (TME) is shaped by dynamic metabolic and immune interactions between precancerous and cancerous tumor cells and stromal cells like epithelial cells, fibroblasts, endothelial cells, and hematopoietically-derived immune cells. The metabolic states of the TME, including the hypoxic and acidic niches, influence the immunosuppressive phenotypes of the stromal and immune cells, which confers resistance to both host-mediated tumor killing and therapeutics. Numerous in vitro TME platforms for studying immunotherapies, including cell therapies, are being developed. However, we do not yet understand which immune and stromal components are most critical and how much model complexity is needed to answer specific questions. In addition, scalable sourcing and quality-control of appropriate TME cells for reproducibly manufacturing these platforms remain challenging. In this regard, lessons from the manufacturing of immunomodulatory cell therapies could provide helpful guidance. Although immune cell therapies have shown unprecedented results in hematological cancers and hold promise in solid tumors, their manufacture poses significant scale, cost, and quality control challenges. This review first provides an overview of the in vivo TME, discussing the most influential cell populations in the tumor-immune landscape. Next, we summarize current approaches for cell therapies against cancers and the relevant manufacturing platforms. We then evaluate current immune-tumor models of the TME and immunotherapies, highlighting the complexity, architecture, function, and cell sources. Finally, we present the technical and fundamental knowledge gaps in both cell manufacturing systems and immune-TME models that must be addressed to elucidate the interactions between endogenous tumor immunity and exogenous engineered immunity.
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CAR-T cell therapy in India requires a paradigm shift in training, education and health care processes. Cytotherapy 2021; 24:101-109. [PMID: 34753677 DOI: 10.1016/j.jcyt.2021.09.007] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 09/10/2021] [Accepted: 09/13/2021] [Indexed: 11/21/2022]
Abstract
Chimeric antigen receptor (CAR)-T cell therapy has revolutionized the treatment of some kinds of cancers. Hundreds of companies and academic institutions are collaborating to develop gene-modified cell therapies using novel targets, different cell types, and manufacturing processes of autologous and allogenic cell therapies. The individualized, custom-made autologous CAR-T cell production platform remains a significant limiting factor for its large-scale clinical application. In this respect, the advances in standardization and automation of the process can have considerable impact on cost reduction. Development of off-the-shelf, ready-to-use universal killer cells can enable scaling up. Despite the wide use of this cell therapy in the United States, Europe and China, its development is limited in developing countries in Southeast Asia, Africa and Latin America. In this review, we focus on good manufacturing practices-compliant manufacturing requirements, operational logistics, and regulatory processes that need to be considered for high-quality gene-modified cell therapies from an Indian perspective. We also list the potential strategies to overcome challenges associated with translation to affordability and scalability.
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Jakobsen LH, Callréus T, Sessa M, Jerkeman M, Andersen M, El-Galaly TC. Detecting deviations from the efficacy and safety results of single-arm trials using real-world data: The case of a CAR-T cell therapy in B-cell lymphoma. Pharmacoepidemiol Drug Saf 2021; 30:514-519. [PMID: 33432654 DOI: 10.1002/pds.5195] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Accepted: 01/06/2021] [Indexed: 11/08/2022]
Abstract
PURPOSE Personalized therapies are leading to an increasing number of marketing authorizations based on single-arm trials, which increases the demand for better post-authorization monitoring strategies. The aim of the present study was to estimate the power over time as data accrue in population-based registries for detecting deviations from the expected efficacy/safety of chimeric antigen receptor T cell (CAR-T) therapy approved for relapsed/refractory large B-cell lymphoma (RR-LBCL). METHODS The number of real-world RR-LBCL patients was projected over time in a general population of 5, 15, and 25 million citizens using lymphoma registry data. For each scenario, we computed the power over time for detecting significant deviations in efficacy (1-year overall survival [1yOS]) when comparing to historical controls (SCHOLAR-1 study; 1yOS, 28%) and RR-LBCL patients treated with CAR-T cell therapy in a single-arm trial (ZUMA-1; 1yOS, 59%) as well as deviations in selected adverse events (grade ≥3 aphasia) from the ZUMA-1 trial. We assumed a 10% absolute deviation in 1yOS (efficacy) and a relative increase of 50% in grade ≥3 aphasia (safety). RESULTS Assuming a general population of 5, 15, and 25 million, the accrual time needed to achieve 80% power for detecting a significant increase over the 1yOS reported in SCHOLAR-1 was 9, 4, and 3 years, respectively, while 80% power for detecting a significant decrease in 1yOS compared to ZUMA-1 required 10.5, 4.5, and 3 years of data accrual, respectively. However, corresponding estimates for aphasia were >20, 8, and 5 years, respectively. CONCLUSIONS Projections of the statistical power for detecting important deviations in efficacy/safety from that reported in pivotal clinical trials(s) provide critical information about the expected performance of post-authorization monitoring programs.
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Affiliation(s)
- Lasse Hjort Jakobsen
- Department of Hematology, Clinical Cancer Research Center, Aalborg University Hospital, Denmark.,Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| | - Torbjörn Callréus
- Pharmacovigilance Research Center, Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
| | - Maurizio Sessa
- Pharmacovigilance Research Center, Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
| | - Mats Jerkeman
- Department of Oncology, Lund University, Lund, Sweden
| | - Morten Andersen
- Pharmacovigilance Research Center, Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
| | - Tarec Christoffer El-Galaly
- Department of Hematology, Clinical Cancer Research Center, Aalborg University Hospital, Denmark.,Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
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