News archives


OCTOBER - DECEMBER 17

JULY - SEPTEMBER 17

APRIL - JUNE 17

JANUARY - MARCH 17

OCTOBER - DECEMBER 16

JULY - SEPTEMBER 16

APRIL - JUNE 16

JANUARY - MARCH 16

OCTOBER - DECEMBER 15

JULY - SEPTEMBER 15

APRIL - JUNE 15

JANUARY - MARCH 15

OCTOBER - DECEMBER 14

JULY - SEPTEMBER 14

APRIL - JUNE 14

JANUARY - MARCH 14

OCTOBER - DECEMBER 13

JULY - SEPTEMBER 13

APRIL - JUNE 13

JANUARY - MARCH 13

OCTOBER - DECEMBER 12

JULY - SEPTEMBER 12

APRIL - JUNE 12

JANUARY - MARCH 12

OCTOBER - DECEMBER 11

JULY - SEPTEMBER 11

APRIL - JUNE 11

JANUARY - MARCH 11

OCTOBER - DECEMBER 10

JULY - SEPTEMBER 10

APRIL - JUNE 10

JANUARY - MARCH 10

OCTOBER - DECEMBER 09

JULY - SEPTEMBER 09

APRIL - JUNE 09

JANUARY - MARCH 09

OCTOBER - DECEMBER 08

JULY - SEPTEMBER 08

APRIL - JUNE 08

JANUARY - MARCH 08

OCTOBER - DECEMBER 07

JULY - SEPTEMBER 07

APRIL - JUNE 07

JANUARY - MARCH 07

 
  current news   Press   selected story    
     
  27 June 2017  
 
A 3D microfluidic model for preclinical evaluation of TCR-engineered T cells against solid tumors
 
 




Authors
Andrea Pavesi1,2, Anthony T. Tan3, Sarene Koh4, Adeline Chia3, Marta Colombo5, Emanuele Antonecchia5, Carlo Miccolis5, Erica Ceccarello3, Giulia Adriani2, Manuela T. Raimondi5, Roger D. Kamm2,6 and Antonio Bertoletti3,4

Author Affiliations
1 Institute of Molecular and Cell Biology, Agency for Science, Technology, and Research, Singapore.
2 BioSystems and Micromechanics IRG, Singapore-MIT Alliance for Research and Technology, Singapore.
3 Emerging Infectious Disease Program, Duke-NUS Graduate Medical School, Singapore.
4 Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore.
5 Department of Chemistry, Materials and Chemical Engineering “Giulio Natta,” Politecnico di Milano,   Milan, Italy.
6 MechanoBiology Laboratory, Department of Biological Engineering, Massachusetts Institute of   Technology, Cambridge, Massachusetts, USA.
Authorship note: A. Pavesi and A.T. Tan contributed equally to this work

Published in JCI Insight on 15 June 2017. (doi:10.1172/jci.insight.89762)

Abstract

The tumor microenvironment imposes physical and functional constraints on the antitumor efficacy of adoptive T cell immunotherapy. Preclinical testing of different T cell preparations can help in the selection of efficient immune therapies, but in vivo models are expensive and cumbersome to develop, while classical in vitro 2D models cannot recapitulate the spatiotemporal dynamics experienced by T cells targeting cancer. Here, we describe an easily customizable 3D model, in which the tumor microenvironment conditions are modulated and the functionality of different T cell preparations is tested. We incorporate human cancer hepatocytes as a single cell or as tumor cell aggregates in a 3D collagen gel region of a microfluidic device. Human T cells engineered to express tumor-specific T cell receptors (TCR–T cells) are then added in adjacent channels. The TCR–T cells’ ability to migrate and kill the tumor target and the profile of soluble factors were investigated under conditions of varying oxygen levels and in the presence of inflammatory cytokines. We show that only the 3D model detects the effect that oxygen levels and the inflammatory environment impose on engineered TCR–T cell function, and we also used the 3D microdevice to analyze the TCR–T cell efficacy in an immunosuppressive scenario. Hence, we show that our microdevice platform enables us to decipher the factors that can alter T cell function in 3D and can serve as a preclinical assay to tailor the most efficient immunotherapy configuration for a specific therapeutic goal.

Figure

Figure Legend:

Evaluation of TCR-engineered T cell function using a 3D microfluidic device. Factors influencing the functionality of TCR-engineered T cells were assessed using the microdevice, and the information obtained will then be used to improve the in vivo efficiency of the engineered T cells. (A–C) The workflow of the presented work is explained. (D and E) 3D rendering of the devices in disperse cell configuration and aggregate configuration. (F) The predominantly gravity-driven migration of engineered T cells along the z axis, as occurs in a 2D well-based assay, compared with the directional chemotaxis in a 3D microdevice.


For more information on Andrea PAVESI's lab, please click here.