Touch-free optical technologies to streamline the production of T cell therapies

Gillette, Amani A.; Pham, Dan; Skala, Melissa C.

doi:10.1016/j.cobme.2022.100434

Cited by 5 publications

(5 citation statements)

References 56 publications

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“…We have established robust correlations between OMI and gene transfer efficiency by retroviral vectors or EP-based CRISPR and validated OMI measurements with standard metabolic assays such as metabolite plate-based assays and extracellular flux analysis. These findings support the applications of OMI to address the current technology needs in CAR T manufacturing ( 54 ).…”

Section: Discussionsupporting

confidence: 80%

Label free metabolic imaging to enhance the efficacy of Chimeric Antigen Receptor T cell therapy

Pham,

Cappabianca,

Forsberg

et al. 2024

Preprint

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Chimeric antigen receptor (CAR) T cell therapy for solid tumors remains challenging due to the complex manufacturing process and the immunosuppressive tumor microenvironment. The manufacturing condition directly impacts CAR T cell yield, phenotype, and metabolism, which correlate within vivopotency and persistence. Optical metabolic imaging (OMI) is a non-invasive, label-free method to evaluate single cell metabolism based on autofluorescent metabolic coenzymes NAD(P)H and FAD. Using OMI, we identified the dominating impacts of media composition over the selection of antibody stimulation and/or cytokines on anti-GD2 CAR T cell metabolism, activation strength and kinetics, and phenotype. We demonstrated that OMI parameters were indicative of cell cycle stage and optimal gene transfer conditions for both viral transduction and electroporation-based CRISPR/Cas9. Notably, OMI accurately predicted oxidative metabolic phenotype of virus-free CRISPR-edited anti-GD2 CAR T cells that correlated to higherin vivopotency against neuroblastoma. Our data supports OMI’s potential as a robust, sensitive analytical tool that enables dynamic and optimal manufacturing conditions for increased CAR T cell yield and metabolic fitness.One sentence summaryAutofluorescence imaging informs manufacturing conditions that enhance yield and metabolic fitness of CAR T cells for neuroblastoma.

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Section: Discussionsupporting

confidence: 80%

Label free metabolic imaging to enhance the efficacy of Chimeric Antigen Receptor T cell therapy

Pham,

Cappabianca,

Forsberg

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…We have established robust correlations between OMI and gene transfer efficiency by retroviral vectors or electroporation-based CRISPR and validated OMI measurements with standard metabolic assays such as metabolite plate-based assays and extracellular flux analysis. These findings support the applications of OMI to address the current technology needs in CAR T manufacturing (66).…”

Section: Discussionsupporting

confidence: 76%

Label free metabolic imaging to enhance the efficacy of chimeric antigen receptor T cell therapy

Skala,

Pham,

Cappabianca

et al. 2024

Preprint

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Chimeric antigen receptor (CAR) T cell therapy for solid tumors is challenging not only because of the immunosuppressive tumor microenvironment, but also because of a complex manufacturing process that is difficult to monitor. Manufacturing directly impacts CAR T cell yield, phenotype, and metabolism, which correlate with in vivo potency and persistence. In particular, though metabolic fitness is a critical quality attribute, how T cell metabolic requirements vary throughout manufacturing remains unexplored. Here, we address this limitation with optical metabolic imaging (OMI), a non-invasive, label-free method to evaluate single-cell metabolism based on autofluorescent metabolic coenzymes NAD(P)H and FAD. Using OMI, we identified the dominating impacts of media composition over the selection of antibody stimulation and/or cytokines on anti-GD2 CAR T cell metabolism, activation strength and kinetics, and phenotype. We demonstrated that OMI parameters can indicate cell cycle stage and optimal gene transfer conditions for both viral transduction and electroporation-based CRISPR/Cas9. Notably, in a virus-free CRISPR-edited anti-GD2 CAR T cell model, OMI measurements allowed accurate prediction of an oxidative metabolic phenotype that yielded higher in vivo potency against neuroblastoma. Our data supports OMI’s potential as a robust, sensitive analytical tool to identify optimal manufacturing conditions and monitor cell metabolism throughout manufacturing for increased CAR T cell yield and metabolic fitness.

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“…171 Autologous therapy involves in vitro modification and expansion of T cells extracted from the patient, which is often challenging due to the damaged state of the patient's lymphocytes, leading to insufficient numbers of high-quality T cells and increased time and costs. 172,173 In contrast, allogeneic therapy retrieves high-quality T cells from healthy donors, but this requires immune modification to reduce the risk of host anti-graft rejection. While some clinical trials have positive outcomes, 174,175 concerns about safety persist for the widespread application of universal CAR-T therapies since they are allogeneic-derived T cells.…”

Section: Car-t Therapymentioning

confidence: 99%

“…However, the problem is that under autologous therapies, the autologously constructed PDTO model still cannot promptly respond to the actual situation in vivo; thus, researchers have proposed CAR‐T‐based allogeneic therapies 171 . Autologous therapy involves in vitro modification and expansion of T cells extracted from the patient, which is often challenging due to the damaged state of the patient's lymphocytes, leading to insufficient numbers of high‐quality T cells and increased time and costs 172,173 . In contrast, allogeneic therapy retrieves high‐quality T cells from healthy donors, but this requires immune modification to reduce the risk of host anti‐graft rejection.…”

Section: Pdtos In Immunotherapymentioning

confidence: 99%

Tumour organoids and assembloids: Patient‐derived cancer avatars for immunotherapy

Mei,

Liu,

Tian

et al. 2024

Clinical & Translational Med

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BackgroundOrganoid technology is an emerging and rapidly growing field that shows promise in studying organ development and screening therapeutic regimens. Although organoids have been proposed for a decade, concerns exist, including batch‐to‐batch variations, lack of the native microenvironment and clinical applicability.Main bodyThe concept of organoids has derived patient‐derived tumour organoids (PDTOs) for personalized drug screening and new drug discovery, mitigating the risks of medication misuse. The greater the similarity between the PDTOs and the primary tumours, the more influential the model will be. Recently, ‘tumour assembloids’ inspired by cell‐coculture technology have attracted attention to complement the current PDTO technology. High‐quality PDTOs must reassemble critical components, including multiple cell types, tumour matrix, paracrine factors, angiogenesis and microorganisms. This review begins with a brief overview of the history of organoids and PDTOs, followed by the current approaches for generating PDTOs and tumour assembloids. Personalized drug screening has been practised; however, it remains unclear whether PDTOs can predict immunotherapies, including immune drugs (e.g. immune checkpoint inhibitors) and immune cells (e.g. tumour‐infiltrating lymphocyte, T cell receptor‐engineered T cell and chimeric antigen receptor‐T cell). PDTOs, as cancer avatars of the patients, can be expanded and stored to form a biobank.ConclusionFundamental research and clinical trials are ongoing, and the intention is to use these models to replace animals. Pre‐clinical immunotherapy screening using PDTOs will be beneficial to cancer patients.Key Points The current PDTO models have not yet constructed key cellular and non‐cellular components. PDTOs should be expandable and editable. PDTOs are promising preclinical models for immunotherapy unless mature PDTOs can be established. PDTO biobanks with consensual standards are urgently needed.

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Touch-free optical technologies to streamline the production of T cell therapies

Cited by 5 publications

References 56 publications

Label free metabolic imaging to enhance the efficacy of Chimeric Antigen Receptor T cell therapy

Label free metabolic imaging to enhance the efficacy of Chimeric Antigen Receptor T cell therapy

Label free metabolic imaging to enhance the efficacy of chimeric antigen receptor T cell therapy

Tumour organoids and assembloids: Patient‐derived cancer avatars for immunotherapy

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