Pixelated Microfluidics for Drug Screening on Tumour Spheroids and Ex Vivo Microdissected Tumour Explants

Author:

Dorrigiv Dina12ORCID,Goyette Pierre-Alexandre2ORCID,St-Georges-Robillard Amélie13ORCID,Mes-Masson Anne-Marie14ORCID,Gervais Thomas123ORCID

Affiliation:

1. Centre de Recherche du Centre Hospitalier de l’Université de Montréal (CRCHUM), Institut du Cancer de Montréal, Montreal, QC H2X 0A9, Canada

2. Institute of Biomedical Engineering, Polytechnique Montréal, Montreal, QC H3T 1J4, Canada

3. Department of Engineering Physics, Polytechnique Montréal, Montreal, QC H3T 1J4, Canada

4. Department of Medicine, Université de Montréal, Montreal, QC H3T 1J4, Canada

Abstract

Anticancer drugs have the lowest success rate of approval in drug development programs. Thus, preclinical assays that closely predict the clinical responses to drugs are of utmost importance in both clinical oncology and pharmaceutical research. 3D tumour models preserve the tumoral architecture and are cost- and time-efficient. However, the short-term longevity, limited throughput, and limitations of live imaging of these models have so far driven researchers towards less realistic tumour models such as monolayer cell cultures. Here, we present an open-space microfluidic drug screening platform that enables the formation, culture, and multiplexed delivery of several reagents to various 3D tumour models, namely cancer cell line spheroids and ex vivo primary tumour fragments. Our platform utilizes a microfluidic pixelated chemical display that creates isolated adjacent flow sub-units of reagents, which we refer to as fluidic ‘pixels’, over tumour models in a contact-free fashion. Up to nine different treatment conditions can be tested over 144 samples in a single experiment. We provide a proof-of-concept application by staining fixed and live tumour models with multiple cellular dyes. Furthermore, we demonstrate that the response of the tumour models to biological stimuli can be assessed using the platform. Upscaling the microfluidic platform to larger areas can lead to higher throughputs, and thus will have a significant impact on developing treatments for cancer.

Funder

National Science and Engineering Research Council of Canada

Fonds de Recherche du Québec—Nature et Technologies

CMC Microsystems

Publisher

MDPI AG

Subject

Cancer Research,Oncology

Reference77 articles.

1. Parsing clinical success rates;Mullard;Nat. Rev. Drug Discov.,2016

2. Clinical development success rates for investigational drugs;Hay;Nat. Biotechnol.,2014

3. Estimation of clinical trial success rates and related parameters;Wong;Biostatistics,2019

4. Preclinical models for precision oncology;Cervantes;Biochim. Et Biophys. Acta (BBA)-Rev. Cancer,2018

5. Ex vivo organotypic culture system of precision-cut slices of human pancreatic ductal adenocarcinoma;Misra;Sci. Rep.,2019

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