Establishment of a protocol for rapidly expanding Epstein-Barr-virus-specific cytotoxic T cells with enhanced cytotoxicity.

BACKGROUND: Lytic Epstein-Barr virus (EBV) infection plays a major role in the pathogenesis of nasopharyngeal carcinoma (NPC). For patients with recurrent or metastatic NPC and resistant to conventional therapies, adoptive cell therapy using EBV-specific cytotoxic T cells (EBV-CTLs) is a promising option. However, the long production period (around 3 to 4 weeks) and low EBV-CTL purity (approximately 40% of total CD8 T cells) in the cell product limits the application of EBV-CTLs in clinics. Thus, this study aimed to establish a protocol for the rapid production of EBV-CTLs. METHODS: By culturing peripheral blood mononuclear cells (PBMCs) from EBV-seropositive donors with EBV-specific peptides and interleukin (IL)-2, IL-15, and interferon α (IFN-α) for 9 days, we identified that IL-15 can enhance IL-2-mediated CTL activation and significantly increase the yield of CTLs. RESULTS: When IFN-α was used in IL-2/IL-15-mediated CTL production from days 0 to 6, the productivity of EBV-CTLs and EBV-specific cytotoxicity significantly were reinforced relative to EBV-CTLs from IL-2/IL-15 treatment. Additionally, IFN-α-induced production improvement of virus-specific CTLs was not only the case for EBV-CTLs but also for cytomegalovirus-specific CTLs. CONCLUSION: We established a novel protocol to rapidly expand highly pure EBV-CTLs from PBMCs, which can produce EBV-CTLs in 9 days and does not require feeder cells during cultivation.

Characterization of tumoricidal activities mediated by a novel immune cell regimen composing interferon-producing killer dendritic cells and tumor-specific cytotoxic T lymphocytes.

BACKGROUND: Although immune cell therapy has long been used for treating solid cancer, its efficacy remains limited. Interferon (IFN)-producing killer dendritic cells (IKDCs) exhibit cytotoxicity and present antigens to relevant cells; thus, they can selectively induce tumor-associated antigen (TAA)-specific CD8 T cells and may be useful in cancer treatment. Various protocols have been used to amplify human IKDCs from peripheral sources, but the complexity of the process has prevented their widespread clinical application. Additionally, the induction of TAA-specific CD8 T cells through the adoptive transfer of IKDCs to immunocompromised patients with cancer may be insufficient. Therefore, we developed a method for generating an immune cell-based regimen, Phyduxon-T, comprising a human IKDC counterpart (Phyduxon) and expanded TAA-specific CD8 T cells. METHODS: Peripheral blood mononuclear cells from ovarian cancer patients were cultured with human interleukin (hIL)-15, hIL-12, and hIL-18 to generate Phyduxon-T. Then, its phenotype, cytotoxicity, and antigen-presenting function were evaluated through flow cytometry using specific monoclonal antibodies. RESULTS: Phyduxon exhibited the characteristics of both natural killer and dendritic cells. This regimen also exhibited cytotoxicity against primary ovarian cancer cells and presented TAAs, thereby inducing TAA-specific CD8 T cells, as evidenced by the expression of 4-1BB and IFN-γ. Notably, the Phyduxon-T manufacturing protocol effectively expanded IFN-γ-producing 4-1BB+ TAA-specific CD8 T cells from peripheral sources; these cells exhibited cytotoxic activities against ovarian cancer cells. CONCLUSIONS: Phyduxon-T, which is a combination of natural killer cells, dendritic cells, and TAA-specific CD8 T cells, may enhance the efficacy of cancer immunotherapy.

May I see what you see? Predicting visual features from neuronal activity.

Understanding brain response to audiovisual stimuli is a key challenge in understanding neuronal processes. In this paper, we describe our effort aimed at reconstructing video frames from observed functional MRI images. We also demonstrate that our model can predict visual objects. Our method constructs an autoencoder model for a set of training video segments to code video streams into their corresponding latent representations. Next, we learn a mapping from the observed fMRI response to the corresponding latent video frame representation. Finally, we pass the latent vectors computed using the fMRI response through the decoder to reconstruct the predicted image. We show that the representations of video frames and those constructed from corresponding fMRI images are highly clustered, the latent representations can be used to predict objects in video frames using just the fMRI frames, and fMRI responses can be used to reconstruct the inputs to predict the presence of faces.