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Issue 5, 2021

Cryopreservable arrays of paper-based 3D tumor models for high throughput drug screening

Author affiliations

Abstract

Three-dimensional (3D) tumor models have gained increased attention in life-science applications as they better represent physiological conditions of in vivo tumor microenvironments, and thus, possess big potential for guiding drug screening studies. Although various techniques proved effective in growing cancer cells in 3D, their procedures are typically complex, time consuming, and expensive. Here, we present a versatile, robust, and cost-effective method that utilizes a paper platform to create cryopreservable high throughput arrays of 3D tumor models. In the approach, we use custom 3D printed masks along with simple chemistry modifications to engineer highly localized hydrophilic ‘virtual microwells’, or microspots, on paper for 3D cell aggregation, surrounded by hydrophobic barriers that prevent inter-microspot mixing. The method supports the formation and cryopreservation of 3D tumor arrays for extended periods of storage time. Using MCF-7 and MDA-MB-231 breast cancer cell lines, we show that the cryopreservable arrays of paper-based 3D models are effective in studying tumor response to cisplatin drug treatment, while replicating key characteristics of the in vivo tumors that are absent in conventional 2D cultures. This technology offers a low cost, easy, and fast experimental procedure, and allows for 3D tumor arrays to be cryopreserved and thawed for on-demand use. This could potentially provide unparalleled advantages to the fields of tissue engineering and personalized medicine.

Graphical abstract: Cryopreservable arrays of paper-based 3D tumor models for high throughput drug screening

Supplementary files

Article information


Submitted
21 Dec 2020
Accepted
02 Feb 2021
First published
22 Feb 2021

This article is Open Access

Lab Chip, 2021,21, 844-854
Article type
Paper

Cryopreservable arrays of paper-based 3D tumor models for high throughput drug screening

B. Samara, M. Deliorman, P. Sukumar and M. A. Qasaimeh, Lab Chip, 2021, 21, 844 DOI: 10.1039/D0LC01300E

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