Microfluidic models for adoptive cell-mediated cancer immunotherapies

Current adoptive T cell therapies have shown promising results in clinical trials but need further development as an effective cancer treatment. Here, we discuss how 3D microfluidic tumour models mimicking the tumour microenvironment could help in testing T cell immunotherapies by assessing engineer...

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Main Authors: Adriani, Giulia, Pavesi, Andrea, Tan, Anthony T., Bertoletti, Antonio, Thiery, Jean Paul, Kamm, Roger Dale
Other Authors: Massachusetts Institute of Technology. Department of Biological Engineering
Format: Article
Published: Elsevier 2018
Online Access:http://hdl.handle.net/1721.1/119471
https://orcid.org/0000-0002-7232-304X
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author Adriani, Giulia
Pavesi, Andrea
Tan, Anthony T.
Bertoletti, Antonio
Thiery, Jean Paul
Kamm, Roger Dale
author2 Massachusetts Institute of Technology. Department of Biological Engineering
author_facet Massachusetts Institute of Technology. Department of Biological Engineering
Adriani, Giulia
Pavesi, Andrea
Tan, Anthony T.
Bertoletti, Antonio
Thiery, Jean Paul
Kamm, Roger Dale
author_sort Adriani, Giulia
collection MIT
description Current adoptive T cell therapies have shown promising results in clinical trials but need further development as an effective cancer treatment. Here, we discuss how 3D microfluidic tumour models mimicking the tumour microenvironment could help in testing T cell immunotherapies by assessing engineered T cells and identifying combinatorial therapy to improve therapeutic efficacy. We propose that 3D microfluidic systems can be used to screen different patient-specific treatments, thereby reducing the burden of in vivo testing and facilitating the rapid translation of successful T cell cancer immunotherapies to the clinic.
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spelling mit-1721.1/1194712022-09-28T14:30:56Z Microfluidic models for adoptive cell-mediated cancer immunotherapies Adriani, Giulia Pavesi, Andrea Tan, Anthony T. Bertoletti, Antonio Thiery, Jean Paul Kamm, Roger Dale Massachusetts Institute of Technology. Department of Biological Engineering Kamm, Roger Dale Current adoptive T cell therapies have shown promising results in clinical trials but need further development as an effective cancer treatment. Here, we discuss how 3D microfluidic tumour models mimicking the tumour microenvironment could help in testing T cell immunotherapies by assessing engineered T cells and identifying combinatorial therapy to improve therapeutic efficacy. We propose that 3D microfluidic systems can be used to screen different patient-specific treatments, thereby reducing the burden of in vivo testing and facilitating the rapid translation of successful T cell cancer immunotherapies to the clinic. National Cancer Institute (U.S.) (Grant 1-U01CA202177-01) 2018-12-07T18:14:51Z 2018-12-07T18:14:51Z 2016-05 2018-12-05T17:31:29Z Article http://purl.org/eprint/type/JournalArticle 1359-6446 http://hdl.handle.net/1721.1/119471 Adriani, Giulia et al. “Microfluidic Models for Adoptive Cell-Mediated Cancer Immunotherapies.” Drug Discovery Today 21, 9 (September 2016): 1472–1478 © 2016 Elsevier Ltd https://orcid.org/0000-0002-7232-304X http://dx.doi.org/10.1016/J.DRUDIS.2016.05.006 Drug Discovery Today Creative Commons Attribution-NonCommercial-NoDerivs License http://creativecommons.org/licenses/by-nc-nd/4.0/ application/pdf Elsevier PMC
spellingShingle Adriani, Giulia
Pavesi, Andrea
Tan, Anthony T.
Bertoletti, Antonio
Thiery, Jean Paul
Kamm, Roger Dale
Microfluidic models for adoptive cell-mediated cancer immunotherapies
title Microfluidic models for adoptive cell-mediated cancer immunotherapies
title_full Microfluidic models for adoptive cell-mediated cancer immunotherapies
title_fullStr Microfluidic models for adoptive cell-mediated cancer immunotherapies
title_full_unstemmed Microfluidic models for adoptive cell-mediated cancer immunotherapies
title_short Microfluidic models for adoptive cell-mediated cancer immunotherapies
title_sort microfluidic models for adoptive cell mediated cancer immunotherapies
url http://hdl.handle.net/1721.1/119471
https://orcid.org/0000-0002-7232-304X
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