Literature DB >> 29625078

Automated generation of immature dendritic cells in a single-use system.

Andrew Kozbial1, Lekhana Bhandary1, Bradley B Collier1, Christopher S Eickhoff2, Daniel F Hoft3, Shashi K Murthy4.   

Abstract

Dendritic cells (DCs) are an indispensable part of studying human responses that are important for protective immunity against cancer and infectious diseases as well as prevention of autoimmunity and transplant rejection. These cells are also key elements of personalized vaccines for cancer and infectious diseases. Despite the vital role of DCs in both clinical and basic research contexts, methods for obtaining these cells from individuals remains a comparatively under-developed and inefficient process. DCs are present in very low concentrations (<1%) in blood, thus they must be generated from monocytes and the current methodology in DC generation involves a laborious process of static culture and stimulation with cytokines contained in culture medium. Herein, we describe an automated fluidic system, MicroDEN, that allows for differentiation of monocytes into immature-DCs (iDCs) utilizing continuous perfusion of differentiation media. Manual steps associated with current ex vivo monocyte differentiation are vastly reduced and an aseptic environment is ensured by the use of an enclosed cartridge and tubing network. Benchmark phenotyping was performed on the generated iDCs along with allogeneic T-cell proliferation and syngeneic antigen-specific functional assays. MicroDEN generated iDCs were phenotypically and functionally similar to well plate generated iDCs, thereby demonstrating the feasibility of utilizing MicroDEN in the broad range of applications requiring DCs.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Antigen-presenting cell; Cancer vaccinology; Dendritic cell; Monocyte; Personalized medicine; Vaccine

Mesh:

Year:  2018        PMID: 29625078      PMCID: PMC5946316          DOI: 10.1016/j.jim.2018.03.010

Source DB:  PubMed          Journal:  J Immunol Methods        ISSN: 0022-1759            Impact factor:   2.303


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